{"type": "FeatureCollection", "features": [{"id": "10.3390/su10020537", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-08-24T16:19:19Z", "type": "Journal Article", "created": "2018-02-20", "title": "The Short-Term Effects Of Rice Straw Biochar, Nitrogen And Phosphorus Fertilizer On Rice Yield And Soil Properties In A Cold Waterlogged Paddy Field", "description": "<p>Crop productivity in cold waterlogged paddy fields can be constrained by chronic flooding stress and low temperature. Farmers typically use chemical fertilizer to improve crop production, but this conventional fertilization is not very effective in a cold waterlogged paddy field. Biochar amendment has been proposed as a promising management approach to eliminating these obstacles. However, little is known about the performance of biochar when combined with N fertilizer and P fertilizer in cold waterlogged soils. The aim of this study was, therefore, to assess the main effects and interactive effects of rice straw biochar, N and P fertilizer on rice growth and soil properties in a cold waterlogged paddy field. The field treatments consisted of a factorial combination of two biochar levels (0 and 2.25 t ha\uffe2\uff88\uff921), two N fertilizer levels (120.0 and 180.0 kg ha\uffe2\uff88\uff921) and two P fertilizer levels (37.5 and 67.5 kg ha\uffe2\uff88\uff921) which were arranged in a randomized block design, with three replicates. Results confirmed that biochar application caused a significant increase in the soil pH due to its liming effect, while this application resulted in a significant decrease in soil exchangeable cations, such as exchangeable Ca, Mg, Al and base cations. The interactive effect of N fertilizer, P fertilizer and biochar was significant for soil total N. Moreover, a negative effect of biochar on the internal K use efficiency suggested that K uptake into rice may benefit from biochar application. According to the partial Eta squared values, the combined application of N fertilizer and biochar was as effective as pure P fertilization at increasing straw P uptake. The addition of biochar to farmers\uffe2\uff80\uff99 fertilization practice treatment (180.0 kg N ha\uffe2\uff88\uff921, 67.5 kg P2O5 ha\uffe2\uff88\uff921 and 67.5 kg K2O ha\uffe2\uff88\uff921) significantly increased rice yield, mainly owing to improvements in grains per panicle. However, notable effects of biochar on rice yield and biomass production were not detected. More studies are required to assess the long-term behavior of biochar in a cold waterlogged paddy field. This study may lay a theoretical foundation for blended application of biochar with fertilizer in a cold waterlogged paddy field.</p>", "keywords": ["2. Zero hunger", "biochar; fertilizer; cold waterlogged paddy; rice yield; soil properties", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "6. Clean water"]}, "links": [{"href": "http://www.mdpi.com/2071-1050/10/2/537/pdf"}, {"href": "https://doi.org/10.3390/su10020537"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Sustainability", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/su10020537", "name": "item", "description": "10.3390/su10020537", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/su10020537"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-02-17T00:00:00Z"}}, {"id": "10.3389/fmicb.2016.01207", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:19:03Z", "type": "Journal Article", "created": "2016-08-03", "title": "Wheat And Rice Growth Stages And Fertilization Regimes Alter Soil Bacterial Community Structure, But Not Diversity", "description": "Maintaining soil fertility and the microbial communities that determine fertility is critical to sustainable agricultural strategies, and the use of different organic fertilizer (OF) regimes represents an important practice in attempts to preserve soil quality. However, little is known about the dynamic response of bacterial communities to fertilization regimes across crop growth stages. In this study, we examined microbial community structure and diversity across eight representative growth stages of wheat-rice rotation under four different fertilization treatments: no nitrogen fertilizer (NNF), chemical fertilizer (CF), organic-inorganic mixed fertilizer (OIMF), and OF. Quantitative PCR (QPCR) and high-throughput sequencing of bacterial 16S rRNA gene fragments revealed that growth stage as the best predictor of bacterial community abundance and structure. Additionally, bacterial community compositions differed between wheat and rice rotations. Relative to soils under wheat rotation, soils under rice rotation contained higher relative abundances (RA) of anaerobic and mesophilic microbes and lower RA of aerophilic microbes. With respect to fertilization regime, NNF plots had a higher abundance of nitrogen-fixing Cyanobacteria. OIMF had a lower abundance of ammonia-oxidizing Thaumarchaeota compared with CF. Application of chemical fertilizers (CF and OIMF treatments) significantly increased the abundance of some generally oligotrophic bacteria such those belonging to the Acidobacteria, while more copiotrophic of the phylum Proteobacteria increased with OF application. A high correlation coefficient was found when comparing RA of Acidobacteria based upon QPCR vs. sequence analysis, yet poor correlations were found for the \u03b1- and \u03b2- Proteobacteria, highlighting the caution required when interpreting these molecular data. In total, crop, fertilization scheme and plant developmental stage all influenced soil microbial community structure, but not total levels of alpha diversity.", "keywords": ["2. Zero hunger", "Growth stage", "Fertilization regime", "04 agricultural and veterinary sciences", "15. Life on land", "bacterial community", "Microbiology", "Bacterial communities", "QR1-502", "growth stage", "fertilization regime", "wheat-rice rotation system", "0401 agriculture", " forestry", " and fisheries", "dynamic variation", "Wheat-rice rotation system", "Dynamic variation"]}, "links": [{"href": "https://doi.org/10.3389/fmicb.2016.01207"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Frontiers%20in%20Microbiology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3389/fmicb.2016.01207", "name": "item", "description": "10.3389/fmicb.2016.01207", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3389/fmicb.2016.01207"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2016-08-03T00:00:00Z"}}, {"id": "10.26882/histagrar.091e07f", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:18:59Z", "type": "Journal Article", "created": "2023-11-27", "title": "Changing rice geographies: a long-term perspective of Portuguese regional production (1860-2018)", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>From its origins in Asia, cultivation of Oryza sativa L. in Portugal has had to adapt to local agroecological conditions. Since the late eighteenth century, there has been significant human intervention in rice production, particularly through public policies aimed at increasing production to achieve national food self-sufficiency. Using national and regional statistics on rice production, this article analyses how public policies on rice cultivation over the last 160 years have impacted and interacted with territorial agroecological conditions and the genetic characteristics of the rice varieties being cultivated. We concluded that public policies led to increased production by favouring the geographical reorganisation of rice production based on the rice varieties used and changing territorial agroecological conditions.</p></article>", "keywords": ["2. Zero hunger", "0301 basic medicine", "03 medical and health sciences", "regional inequality", "rice", "historical geography", "05 social sciences", "0507 social and economic geography", "agricultural policy", "15. Life on land", "16. Peace & justice"]}, "links": [{"href": "https://doi.org/10.26882/histagrar.091e07f"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Historia%20Agraria%20Revista%20de%20agricultura%20e%20historia%20rural", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.26882/histagrar.091e07f", "name": "item", "description": "10.26882/histagrar.091e07f", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.26882/histagrar.091e07f"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-11-27T00:00:00Z"}}, {"id": "10.3389/fenvs.2018.00061", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:19:01Z", "type": "Journal Article", "created": "2018-07-10", "title": "Recognizing Patterns: Spatial Analysis of Observed Microbial Colonization on Root Surfaces", "description": "Root surfaces are major sites of interactions between plants and associated microorganisms. Here, plants and microbes communicate via signaling molecules, compete for nutrients, and release substrates that may have beneficial or harmful effects on each other. Whilst the body of knowledge on the abundance and diversity of microbial communities at root-soil interfaces is now substantial, information on their spatial distribution at the microscale is still scarce. In this study, a standardized method for recognizing and analyzing microbial cell distributions on root surfaces is presented. Fluorescence microscopy was combined with automated image analysis and spatial statistics to explore the distribution of bacterial colonization patterns on rhizoplanes of rice roots. To test and evaluate the presented approach, a gnotobiotic experiment was performed using a potential nitrogen-fixing bacterial strain in combination with roots of wetland rice. The automated analysis procedure resulted in reliable spatial data of bacterial cells colonizing the rhizoplane. Among all replicate roots, the analysis revealed an increasing density of bacterial cells from the root tip to the region of root cell maturation. Moreover, bacterial cells showed significant spatial clustering and tended to be located around plant root cell borders. The quantitative data suggest that the structure of the root surface plays a major role in bacterial colonization patterns. Possible adaptations of the presented approach for future studies are discussed along with potential pitfalls such as inaccurate imaging. Our results demonstrate that standardized recognition and statistical evaluation of microbial colonization on root surfaces holds the potential to increase our understanding of microbial associations with roots and of the underlying ecological interactions.", "keywords": ["[SDE] Environmental Sciences", "0301 basic medicine", "570", "bacterial colonization", "[SDV]Life Sciences [q-bio]", "CATALYZED REPORTER DEPOSITION", "microbial ecology;root surface;bacterial colonization;point process;spatial statistics;image analysis;pattern recognition;wetland rice", "ECOLOGY", "microbial ecology", "Image analysis", "spatial statistics", "Microbial ecology", "03 medical and health sciences", "image analysis", "Pattern recognition", "root surface", "GE1-350", "Point process", "Wetland rice", "point process", "2. Zero hunger", "106022 Mikrobiologie", "0303 health sciences", "Spatial statistics", "IDENTIFICATION", "pattern recognition", "IN-SITU HYBRIDIZATION", "15. Life on land", "Bacterial colonization", "[SDV] Life Sciences [q-bio]", "SOIL", "Environmental sciences", "wetland rice", "Root surface", "[SDE]Environmental Sciences", "BACTERIA", "106022 Microbiology", "POPULATIONS", "COMMUNITIES"]}, "links": [{"href": "https://doi.org/10.3389/fenvs.2018.00061"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Frontiers%20in%20Environmental%20Science", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3389/fenvs.2018.00061", "name": "item", "description": "10.3389/fenvs.2018.00061", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3389/fenvs.2018.00061"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-07-10T00:00:00Z"}}, {"id": "10.5061/dryad.6m11c", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:19:34Z", "type": "Dataset", "title": "Data from: Do microorganism stoichiometric alterations affect carbon sequestration in paddy soil subjected to phosphorus input?", "description": "unspecifiedData on Soil C-N-P-MS#  14-0189R1-EA-2014-08-10Properties of soil  chemistry on total orgnic carbon, nitrogen, and phosphorus in the  experimental paddy field after 7 years of phosphorus application, also  including soil labile carbon, soil available phosphorusData on Soil MBC-MBP-MS#  14-0189R1-EA-2014-08-10Properties of soil  chemistry on microbial biomass in the experimental paddy field after 7  years of phosphorus application, including the following microbial biomass  carbon (MBC) and microbial biomass phosphorus (MBP)Data on Soil C-P vis  MBC-MBP-MS# 14-0189R1-EA-2014-08-10Properties of soil  chemistry on C:P stoichiometry and microbial biomass, in the experimental  paddy field after 7 years of phosphorus applicationData on Soil  Eco-emzymatic activities-MS# 14-0189R1-EA-2014-08-10Properties of  Eco-emzymatic activities on C and P dynamics, in the experimental paddy  field after 7 years of phosphorus applicationData on Grain and  Yield-MS# 14-0189R1-EA-2014-08-10Ice grain yield and  yield components from the experimental paddy field in 2011 and  2012.Data on Soil C  Mineralization-MS# 14-0189R1-EA-2014-08-10Soil biochemical  propoiety on C Mineralization for samples collected from the experimental  paddy field after 7 years of phosphorus application.Data on Soil  microorganisms-MS# 14-0189R1-EA-2014-08-10Bacterial community in  soil for each P fertilized treatment and the relative number of sequences  of the detected bacteria that are involved in the carbon (C) cycle in  paddy field soil", "keywords": ["2. Zero hunger", "agricultural soil", "13. Climate action", "Rice", "15. Life on land", "6. Clean water", "Carbon"], "contacts": [{"organization": "Zhang, Zhi Jian, He, Qiang, Zhang, ZhiJian, Li, HongYi, Hu, Jiao, Li, Xia, Tian, GuangMing, Wang, Hang, Wang, ShunYao, Wang, Bei,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.6m11c"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.6m11c", "name": "item", "description": "10.5061/dryad.6m11c", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.6m11c"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2015-08-11T00:00:00Z"}}, {"id": "10.3390/agronomy11122439", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:19:07Z", "type": "Journal Article", "created": "2021-11-30", "title": "Grain Yield Estimation in Rice Breeding Using Phenological Data and Vegetation Indices Derived from UAV Images", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>The accurate estimation of grain yield in rice breeding is crucial for breeders to screen and select qualified cultivars. In this study, a low-cost unmanned aerial vehicle (UAV) platform mounted with an RGB camera was carried out to capture high-spatial resolution images of rice canopy in rice breeding. The random forest (RF) regression techniques were used to establish yield models by using (1) only color vegetation indices (VIs), (2) only phenological data, and (3) fusion of VIs and phenological data as inputs, respectively. Then, the performances of RF models were compared with the manual observation and CERES-Rice model. The results indicated that the RF model using VIs only performed poorly for estimating yield; the optimized RF model that combined the use of phenological data and color VIs performed much better, which demonstrated that the phenological data significantly improved the model performance. Furthermore, the yield estimation accuracy of 21 rice cultivars that were continuously planted over three years in the optimal RF model had no significant difference (p &gt; 0.05) with that of the CERES-Rice model. These findings demonstrate that the RF model, by combining phenological data and color Vis, is a potential and cost-effective way to estimate yield in rice breeding.</p></article>", "keywords": ["2. Zero hunger", "0106 biological sciences", "S", "UAV", "CERES-Rice", "Agriculture", "04 agricultural and veterinary sciences", "15. Life on land", "yield", "01 natural sciences", "rice breeding", "UAV; rice breeding; yield; CERES-Rice; RF; vegetation indices", "vegetation indices", "RF", "0401 agriculture", " forestry", " and fisheries"], "contacts": [{"organization": "Haixiao Ge, Fei Ma, Zhenwang Li, Changwen Du,", "roles": ["creator"]}]}, "links": [{"href": "http://www.mdpi.com/2073-4395/11/12/2439/pdf"}, {"href": "https://doi.org/10.3390/agronomy11122439"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agronomy", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/agronomy11122439", "name": "item", "description": "10.3390/agronomy11122439", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/agronomy11122439"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-11-29T00:00:00Z"}}, {"id": "10.3390/agronomy11122446", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:19:07Z", "type": "Journal Article", "created": "2021-12-01", "title": "Global Sensitivity Analysis for CERES-Rice Model under Different Cultivars and Specific-Stage Variations of Climate Parameters", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Global sensitivity analysis (SA) has become an efficient way to identify the most influential parameters on model results. However, the effects of cultivar variation and specific-stage variations of climate conditions on model outputs still remain unclear. In this study, 30 indica hybrid rice cultivars were simulated in the CERES-Rice model; then the Sobol\u2019 method was used to perform a global SA on 16 investigated parameters for three model outputs (anthesis day, maturity day, and yield). In addition, we also compared the differences in the sensitivity results under four specific-stage variations (vegetative phase, panicle-formation phase, ripening phase, and the whole growth season) of climate conditions. The results indicated that (1) parameter Tavg, G4, and P2O are the most influential parameters for all model outputs across cultivars during the whole growth season; (2) under the vegetative-phase variation of climate parameters; the variability of model outputs is mainly controlled by parameter P2O and Tavg; (3) under the panicle-formation-phase or ripening-phase variation of climate parameters, parameter P2O was the dominant variable for all model outputs; (4) parameter PORM had a considerable effect (the total sensitivity index, STi; STi&gt;0.05) on yield regardless of the various specific-stage variations of the climate parameters. Findings obtained from this study will contribute to understanding the comprehensive effects of crop parameters on model outputs under different cultivars and specific-stage variations of climate conditions.</p></article>", "keywords": ["2. Zero hunger", "sensitivity analysis", "S", "rice", "CERES-Rice", "CERES-Rice; rice; cultivars; Sobol\u2019 method; sensitivity analysis", "cultivars", "Sobol\u2019 method", "0401 agriculture", " forestry", " and fisheries", "Agriculture", "Sobol' method", "04 agricultural and veterinary sciences", "15. Life on land"], "contacts": [{"organization": "Haixiao Ge, Fei Ma, Zhenwang Li, Changwen Du,", "roles": ["creator"]}]}, "links": [{"href": "http://www.mdpi.com/2073-4395/11/12/2446/pdf"}, {"href": "https://doi.org/10.3390/agronomy11122446"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agronomy", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/agronomy11122446", "name": "item", "description": "10.3390/agronomy11122446", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/agronomy11122446"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-11-30T00:00:00Z"}}, {"id": "10.3390/agronomy13010261", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:19:07Z", "type": "Journal Article", "created": "2023-01-16", "title": "New Insights from Soil Microorganisms for Sustainable Double Rice-Cropping System with 37-Year Manure Fertilization", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Long-term intensive use of mineral fertilizers in double rice-cropping systems has led to soil acidification and soil degradation. Manure fertilization was suggested as an alternative strategy to mitigate soil degradation. However, the effects of long-term mineral and manure fertilization on rice grain yield, yield stability, soil organic carbon (SOC) content, soil total nitrogen (TN) content, and the underlying mechanisms are unclear. Based on a long-term experiment established in 1981 in southern China, we compared four treatments: no fertilizer application (Control); application of nitrogen\u2013phosphorus\u2013potassium (NPK); NPK plus green manure in early rice (M1); and M1 plus farmyard manure in late rice and rice straw return in winter (M2). Our results showed that 37 years of NPK, M1, and M2 significantly increased rice grain yield by 54%, 46%, and 72%, and yield stability by 22%, 17%, and 9%, respectively. M1 and M2 significantly increased SOC content by 39% and 23% compared to Control, respectively, whereas there was no difference between Control and NPK. Regarding soil TN content, it was significantly increased by 8%, 46%, and 20% by NPK, M1, and M2, respectively. In addition, M2 significantly increased bacterial OTU richness by 68%, Chao1 index by 79%, and altered the bacterial community composition. Changes in soil nutrient availability and bacterial Simpson index were positively correlated with the changes in grain yield, while shifts in bacterial community were closely related to yield stability. This study provides pioneer comprehensive assessments of the simultaneous responses of grain yield, yield stability, SOC and TN content, nutrient availability, and bacterial community composition to long-term mineral and manure fertilization in a double rice-cropping system. Altogether, this study spanning nearly four decades provides new perspectives for developing sustainable yet intensive rice cultivation to meet growing global demands.</p></article>", "keywords": ["2. Zero hunger", "[SDU.OCEAN]Sciences of the Universe [physics]/Ocean", "soil nutrient", "Atmosphere", "[SDU.OCEAN] Sciences of the Universe [physics]/Ocean", " Atmosphere", "S", "Agriculture", "04 agricultural and veterinary sciences", "15. Life on land", "double rice-cropping systems", "bacterial community", "630", "6. Clean water", "sustainable agriculture", "reddish paddy soil", "0401 agriculture", " forestry", " and fisheries", "organic amendment; double rice-cropping systems; bacterial community; reddish paddy soil; soil nutrient; sustainable agriculture", "organic amendment"]}, "links": [{"href": "http://www.mdpi.com/2073-4395/13/1/261/pdf"}, {"href": "https://doi.org/10.3390/agronomy13010261"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agronomy", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/agronomy13010261", "name": "item", "description": "10.3390/agronomy13010261", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/agronomy13010261"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-01-15T00:00:00Z"}}, {"id": "10.3390/atmos13010103", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:19:08Z", "type": "Journal Article", "created": "2022-01-10", "title": "Long-Term Dynamic of Cold Stress during Heading and Flowering Stage and Its Effects on Rice Growth in China", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Short episodes of low-temperature stress during reproductive stages can cause significant crop yield losses, but our understanding of the dynamics of extreme cold events and their impact on rice growth and yield in the past and present climate remains limited. In this study, by analyzing historical climate, phenology and yield component data, the spatial and temporal variability of cold stress during the rice heading and flowering stages and its impact on rice growth and yield in China was characterized. The results showed that cold stress was unevenly distributed throughout the study region, with the most severe events observed in the Yunnan Plateau with altitudes higher than 1800 m. With the increasing temperature, a significant decreasing trend in cold stress was observed across most of the three ecoregions after the 1970s. However, the phenological-shift effects with the prolonged growing period during the heading and flowering stages have slowed down the cold stress decreasing trend and led to an underestimation of the magnitude of cold stress events. Meanwhile, cold stress during heading and flowering will still be a potential threat to rice production. The cold stress-induced yield loss is related to both the intensification of extreme cold stress and the contribution of related components to yield in the three regions.</p></article>", "keywords": ["2. Zero hunger", "climate change; cold stress; yield variability; rice growth; food security", "rice growth", "food security", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "climate change", "13. Climate action", "Meteorology. Climatology", "cold stress", "0401 agriculture", " forestry", " and fisheries", "QC851-999", "yield variability", "0105 earth and related environmental sciences"], "contacts": [{"organization": "Zhenwang Li, Zhengchao Qiu, Haixiao Ge, Changwen Du,", "roles": ["creator"]}]}, "links": [{"href": "http://www.mdpi.com/2073-4433/13/1/103/pdf"}, {"href": "https://doi.org/10.3390/atmos13010103"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Atmosphere", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/atmos13010103", "name": "item", "description": "10.3390/atmos13010103", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/atmos13010103"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-01-10T00:00:00Z"}}, {"id": "10.3929/ethz-b-000648810", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:19:26Z", "type": "Journal Article", "title": "Transformation of jarosite and iron oxyhydroxides in acid sulfate paddy soils", "description": "Open AccessMinerals containing Fe are ubiquitous in soils. By providing an abundance of sites for the sorption and incorporation of major and trace elements, Fe minerals can govern the fate and behaviour of numerous pollutants and nutrients in soils. Furthermore, the reactivity of Fe in redox-dynamic soils produces a web of Fe mineral transformation processes with broad consequences for element cycling. The importance of Fe cycling is no exception in acid sulfate soils, although the high sulfur and low pH conditions produce unique Fe mineral transformation processes and compositions. In acid sulfate soils, jarosite, an Fe-K hydroxysulfate mineral, and ferrihydrite, a common short-range-ordered Fe oxyhydroxide mineral, play a central role in the pedological development of active and post-active acid sulfate soils. Soil pH and the dynamics of metals, such as aluminium, are key to understanding the toxicity of acid sulfate soils and can be directly influenced by jarosite and ferrihydrite transformation processes.   Although the transformation of Fe minerals is a key component of biogeochemical processes in redox-active soils, the variables that control the rates and pathways of Fe mineral transformations in soil remain uncertain. The uncertainty arises from the difficulty of tracing molecular processes within a matrix of diverse soil components. Iron minerals are regularly characterised in soils, but the processes that explain the Fe mineral composition of soils cannot be easily resolved. An alternative approach is to perform simplified experiments, such as mixed mineral suspension experiments, under controlled laboratory conditions, to test the effect of individual variables. These systems often use synthetic minerals, although relatively pure jarosite may also be isolated from soils and tested in mixed suspension experiments. While useful to derive mechanistic understanding, the measured outcomes of mixed suspension experiments may not represent the rates and products of transformations that occur in soils.  Therefore, the objective of this thesis was to gain new understanding of the stability and transformation of jarosite and ferrihydrite in acid sulfate soils by developing novel experimental techniques to follow the transformation of synthetic jarosite and ferrihydrite directly in soils. The central theme of the thesis is the comparison of jarosite and aluminium-substituted jarosite transformation in experimental media of increasing complexity. The experiments are performed under conditions that are relevant to rice paddy soils because of the importance of rice in global food production, and the unique management of rice paddies whereby regular flooding during the growing season produces distinct redox cycles. In Thailand, large areas of the Chao Phraya River delta are cultivated as rice paddies despite being acid sulfate soils, providing a suitable site to observe the effects of regular redox cycling on the biogeochemistry of Fe minerals in acid sulfate soils.  The thesis begins with characterisation of synthetic and natural jarosite mineral composition and reactivity. Spectroscopic techniques (Raman spectroscopy, M\u00f6ssbauer spectroscopy and Energy-dispersive X-ray spectrometry) and X-ray diffraction (XRD) were used to assess the element substitution of mineral samples from two jarosite-alunite synthetic solid solution series. The same characterisation techniques were then applied to a sample of jarosite from an acid sulfate soil in Thailand has a natural Al-for-Fe substitution. The mineral characterisation was followed by a transformation experiment in a mixed-suspension system, similar to experimental designs that have been previously used to study mineral transformation processes. The experiment followed the transformation of the natural jarosite sample from an acid sulfate soil in Thailand and three jarosite samples with variable amounts of Al substitution. The reaction solution mimicked the pH (circumneutral) and Fe(II) content (up to 1:1 ratio of Fe(II) in solution to Fe(III) in solids) of flooded acid sulfate soils. Furthermore, using a 57Fe tracer, the simultaneous transformation processes that explained the distribution of mineral products could be resolved from one another. The transformation experiment revealed the relative reactivity of the minerals in the presence of Fe(II), and created a baseline that could be used to compare traditional mixed-suspension experiments with transformations in complex media such as soil.   To advance mineral transformation experiments towards studies in which transformation processes may be followed within a soil matrix, several novel techniques were developed. In a first step, ferrihydrite was incubated for up to twelve weeks in microcosms, each containing 300 g of 5 mM CaCl2 solution and 250 g of one of five paddy soils. The ferrihydrite was buried in the soil within a mesh bag (polyethel terephthalate, 51 \u03bcm pores, 30 mm x 12 mm x 3 mm) that allowed free contact between the synthetic minerals and the pore water, but separated the minerals from direct contact with the soil matrix. The mineral products of the transformation were identified and quantified by Rietveld fitting of XRD patterns. Further, the spatial arrangements of the ferrihydrite and transformation products were measured after two weeks by Raman spectroscopy, which could be used to assess the effects of pore water chemistry and diffusion processes on mineral transformation in the mesh bags. The second step involved measuring jarosite and Al-substituted jarosite transformation in flooded topsoil and subsoils from a rice paddy located on the Bangkok Plain in Central Thailand using an adaptation of the mesh bag method. To test the effect of pore water on the transformation of jarosite in soil, mesh bags were filled with synthetic jarosite and aluminium-jarosite and incubated in topsoils and subsoils, both in laboratory mesocosms and directly in the field. Then, the effect of the soil matrix was tested by completing a parallel experiment using mesh bags containing soil that was pre-enriched with synthetic 57Fe-labelled jarosite and aluminium-substituted jarosite. To facilitate the deployment and collection of small mesh bags in large soil volumes, the mesh bags were inserted into soils using custom-designed 3D-printed sample holders. At three timepoints within twelve weeks, one set of mesh bags were removed from the soil. Transformation products were identified and quantified in the pure jarosite and aluminium-jarosite mesh bags using Rietveld fitting of XRD patterns, while the fate of the 57Fe in enriched soil mesh bags was traced using 57Fe M\u00f6ssbauer spectroscopy.   Performing experiments in increasingly complex media provides an insight into the effect of experimental design on the observation of Fe mineral transformations and provides new information regarding the transformation rates and pathways of jarosite and ferrihydrite within full complexity of soil media. Indeed, this thesis demonstrates that the complex chemistry, biological activity, and physical arrangement of components in the soil have strong effects on the rate and products of jarosite and ferrihydrite transformation processes. The transformation of jarosite and Al-substituted jarosite in mixed-suspension experiments presented in this thesis, in agreement with previous mixed-suspension experiments on both jarosite and ferrihydrite, occurred within a matter of hours. By contrast, the rate of ferrihydrite, jarosite and Al-jarosite transformation in soil pore and in direct contact with the soil matrix occurred over the course of several weeks or months. In the ferrihydrite mesh bags, slow ferrihydrite transformation kinetics on the outer rim of the mesh bag, and deep in the core of the mesh bag, indicated that the sorption of chemical components of soil pore water and diffusion limitations of Fe(II) in pore water could be reasons for the slower rates of transformation in soil. In addition, both Al-for-Fe substitution and Fe(II) concentration in solution were important factors that altered the rate of mineral transformation.  The different incubation conditions for jarosite and Al-jarosite also altered the products of the transformation. Whereas the hydrolysis of jarosite in the absence of Fe(II) resulted primarily in the formation of ferrihydrite, jarosite transformation in the presence of Fe(II) led to ferrihydrite, goethite and lepidocrocite formation. The Fe oxyhydroxide products were consistent with Fe(II)-catalysed transformation, and Fe(II)-catalysed recrystallisation of jarosite may have occurred concurrently. Aluminium-for-iron substitution hindered the formation of lepidocrocite formation in favour of ferrihydrite and goethite. Similar product phases occurred when jarosite and Al-jarosite were reacted with pore water from acid sulfate soils, indicating that similar transformation pathways may define the mineral products of jarosite transformations when the jarosite occurs as accumulations of pure mineral in soil. However, non- or poorly crystalline phases predominated in the transformation products when jarosite or Al-jarosite were incubated in direct contact with the soil matrix, indicating that the transformation of jarosite under these circumstances was governed by different pathways and processes.  The new insights into the transformation of ferrihydrite, jarosite and Al-jarosite in acid sulfate soils demonstrate that phases previously considered meta-stable may participate in the biogeochemistry of soil over period of several months. In the context of rice cultivation, the transformation processes may affect the biogeochemistry of the soils throughout the growing season. The formation of poorly crystalline minerals following the transformation in flooded soils may have positive consequences on the sequestration of other trace and major elements that were associated with the ferrihydrite, jarosite or Al-jarosite prior to the transformation. However, the stabilisation of reduced Fe in the soil matrix may have the opposite effect, promoting the mobility of other ions in solution. The methods used to incubate jarosite and ferrihydrite in soils are easily adaptable to new experimental questions involving the behaviour of Fe-bearing minerals in soil. Therefore, the findings open up a new class of experiments within environmental mineralogy and biogeochemistry, that can help to uncover the processes that occur in the environment and explain the natural variation in the composition of Fe phases in soil.", "keywords": ["jarosite", "iron biogeochemistry", "soil chemistry", "acid sulfate soil", "laboratory study", "ferrihydrite", "soil", "soil incubation", "redox chemistry", "goethite", "iron minerals", "2. Zero hunger", "soil biogeochemistry", "info:eu-repo/classification/ddc/550", "M\u00f6ssbauer spectroscopy", "rice paddy soil", "15. Life on land", "6. Clean water", "Earth sciences", "lepidocrocite", "field study", "13. Climate action", "Raman spectroscopy", "iron oxyhydroxide", "mineral transformation", "iron minerals; mineral transformation; soil; soil chemistry; soil mineralogy; soil biogeochemistry; redox chemistry; iron biogeochemistry; acid sulfate soil; rice paddy soil; jarosite; ferrihydrite; goethite; lepidocrocite; iron oxyhydroxide; M\u00f6ssbauer spectroscopy; Raman spectroscopy; field study; laboratory study; soil incubation", "soil mineralogy"], "contacts": [{"organization": "Grigg, Andrew R.C.", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.3929/ethz-b-000648810"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Thesis/Dissertation", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3929/ethz-b-000648810", "name": "item", "description": "10.3929/ethz-b-000648810", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3929/ethz-b-000648810"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-01-01T00:00:00Z"}}, {"id": "10.3390/f12101332", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-08-24T16:19:10Z", "type": "Journal Article", "created": "2021-09-29", "title": "The Value of Hybrid Aspen Coppice Investment under Different Discount Rate, Price and Management Scenarios: A Case Study of Estonia.", "description": "<p>Hybrid aspen is one of the most promising tree species for short-rotation forestry in Northern Europe. After the clearcutting of hybrid aspen plantation, the next generation arises from root and stump sprouts. The economic feasibility of different management strategies of hybrid aspen coppice stands has not yet been comprehensively evaluated in Northern Europe. We compared the land expectation values (LEVs) of hybrid aspen coppice stands managed according to four scenarios: three early thinning methods (corridor, cross-corridor and single-tree) followed by conventional management and intensive bioenergy production (repeated harvests in 5-year rotations) over a 25-year period in hemiboreal Estonia. We considered the historic price volatility of aspen wood assortments under various discount rates (1\uffe2\uff80\uff9320%). We found that the 25-year rotation with different early thinning methods was more profitable than short bioenergy cycles in the case of low discount rates (&lt;5%). The LEV of short coppice cycles for only bioenergy production became more profitable in comparison with those by thinning methods, when higher discount rates (&gt;10%) were applied. Hybrid aspen coppice stands can be managed profitably, but more risks are taken when the management strategy focuses only on bioenergy production.</p>", "keywords": ["Estonia", "coppice forestry", "forest thinning strategies", "04 agricultural and veterinary sciences", "15. Life on land", "7. Clean energy", "01 natural sciences", "wood price volatility", "investment in forestry", "land expectation value", "<i>Populus</i>", "0401 agriculture", " forestry", " and fisheries", "short-rotation forestry", "0105 earth and related environmental sciences"]}, "links": [{"href": "http://www.mdpi.com/1999-4907/12/10/1332/pdf"}, {"href": "https://www.mdpi.com/1999-4907/12/10/1332/pdf"}, {"href": "https://doi.org/10.3390/f12101332"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Forests", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/f12101332", "name": "item", "description": "10.3390/f12101332", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/f12101332"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-09-29T00:00:00Z"}}, {"id": "10.3390/rs12193228", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:19:17Z", "type": "Journal Article", "created": "2020-10-05", "title": "Qualifications of Rice Growth Indicators Optimized at Different Growth Stages Using Unmanned Aerial Vehicle Digital Imagery", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>The accurate estimation of the key growth indicators of rice is conducive to rice production, and the rapid monitoring of these indicators can be achieved through remote sensing using the commercial RGB cameras of unmanned aerial vehicles (UAVs). However, the method of using UAV RGB images lacks an optimized model to achieve accurate qualifications of rice growth indicators. In this study, we established a correlation between the multi-stage vegetation indices (VIs) extracted from UAV imagery and the leaf dry biomass, leaf area index, and leaf total nitrogen for each growth stage of rice. Then, we used the optimal VI (OVI) method and object-oriented segmentation (OS) method to remove the noncanopy area of the image to improve the estimation accuracy. We selected the OVI and the models with the best correlation for each growth stage to establish a simple estimation model database. The results showed that the OVI and OS methods to remove the noncanopy area can improve the correlation between the key growth indicators and VI of rice. At the tillering stage and early jointing stage, the correlations between leaf dry biomass (LDB) and the Green Leaf Index (GLI) and Red Green Ratio Index (RGRI) were 0.829 and 0.881, respectively; at the early jointing stage and late jointing stage, the coefficient of determination (R2) between the Leaf Area Index (LAI) and Modified Green Red Vegetation Index (MGRVI) was 0.803 and 0.875, respectively; at the early stage and the filling stage, the correlations between the leaf total nitrogen (LTN) and UAV vegetation index and the Excess Red Vegetation Index (ExR) were 0.861 and 0.931, respectively. By using the simple estimation model database established using the UAV-based VI and the measured indicators at different growth stages, the rice growth indicators can be estimated for each stage. The proposed estimation model database for monitoring rice at the different growth stages is helpful for improving the estimation accuracy of the key rice growth indicators and accurately managing rice production.</p></article>", "keywords": ["2. Zero hunger", "object-oriented segmentation method", "optimal index method", "rice", "Science", "Q", "rice; growth indicators; multi-stage vegetation index; unmanned aerial vehicle; optimal index method; object-oriented segmentation method; estimation accuracy", "0211 other engineering and technologies", "04 agricultural and veterinary sciences", "02 engineering and technology", "multi-stage vegetation index", "15. Life on land", "estimation accuracy", "growth indicators", "13. Climate action", "unmanned aerial vehicle", "0401 agriculture", " forestry", " and fisheries"], "contacts": [{"organization": "Zhengchao Qiu, Haitao Xiang, Fei Ma, Changwen Du,", "roles": ["creator"]}]}, "links": [{"href": "http://www.mdpi.com/2072-4292/12/19/3228/pdf"}, {"href": "https://www.mdpi.com/2072-4292/12/19/3228/pdf"}, {"href": "https://doi.org/10.3390/rs12193228"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Remote%20Sensing", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/rs12193228", "name": "item", "description": "10.3390/rs12193228", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/rs12193228"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-10-03T00:00:00Z"}}, {"id": "10.3390/polym11020200", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-08-24T16:19:16Z", "type": "Journal Article", "created": "2019-01-24", "title": "Mitigating the Impact of Cellulose Particles on the Performance of Biopolyester-Based Composites by Gas-Phase Esterification", "description": "<p>Materials that are both biodegradable and bio-sourced are becoming serious candidates for substituting traditional petro-sourced plastics that accumulate in natural systems. New biocomposites have been produced by melt extrusion, using bacterial polyester (poly(3-hydroxybutyrate-co-3-hydroxyvalerate)) as a matrix and cellulose particles as fillers. In this study, gas-phase esterified cellulose particles, with palmitoyl chloride, were used to improve filler-matrix compatibility and reduce moisture sensitivity. Structural analysis demonstrated that intrinsic properties of the polymer matrix (crystallinity, and molecular weight) were not more significantly affected by the incorporation of cellulose, either virgin or grafted. Only a little decrease in matrix thermal stability was noticed, this being limited by cellulose grafting. Gas-phase esterification of cellulose improved the filler\uffe2\uff80\uff99s dispersion state and filler/matrix interfacial adhesion, as shown by SEM cross-section observations, and limiting the degradation of tensile properties (stress and strain at break). Water vapor permeability, moisture, and liquid water uptake of biocomposites were increased compared to the neat matrix. The increase in thermodynamic parameters was limited in the case of grafted cellulose, principally ascribed to their increased hydrophobicity. However, no significant effect of grafting was noticed regarding diffusion parameters.</p>", "keywords": ["biocomposite", "660", "est\u00e9rification", "matrice polym\u00e9rique", "Ing\u00e9nierie des aliments", "poly(hydroxybutyrate-co-valerate) (PHBV)", "Gas-phase esterification", "02 engineering and technology", "[SDV.IDA] Life Sciences [q-bio]/Food engineering", "poly(hydroxybutyrate-co-valerate) (PHBV);Biocomposite;Gas-phase esterification;Water transfer", "7. Clean energy", "cellulose", "Article", "structure mol\u00e9culaire", "gas-phase esterification", "13. Climate action", "poly(hydroxybutyrate-<i>co</i>-valerate) (PHBV)", "[SDV.IDA]Life Sciences [q-bio]/Food engineering", "biomat\u00e9riau", "Water transfer", "Food engineering", "water transfer", "0210 nano-technology", "Biocomposite"]}, "links": [{"href": "http://www.mdpi.com/2073-4360/11/2/200/pdf"}, {"href": "https://hal.inrae.fr/hal-02625163/file/David-Polymers-2019-CC-BY_1.pdf"}, {"href": "https://doi.org/10.3390/polym11020200"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Polymers", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/polym11020200", "name": "item", "description": "10.3390/polym11020200", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/polym11020200"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-01-24T00:00:00Z"}}, {"id": "10.3390/rs13091769", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:19:17Z", "type": "Journal Article", "created": "2021-05-02", "title": "A Scalable Machine Learning Pipeline for Paddy Rice Classification Using Multi-Temporal Sentinel Data", "description": "<p>The demand for rice production in Asia is expected to increase by 70% in the next 30 years, which makes evident the need for a balanced productivity and effective food security management at a national and continental level. Consequently, the timely and accurate mapping of paddy rice extent and its productivity assessment is of utmost significance. In turn, this requires continuous area monitoring and large scale mapping, at the parcel level, through the processing of big satellite data of high spatial resolution. This work designs and implements a paddy rice mapping pipeline in South Korea that is based on a time-series of Sentinel-1 and Sentinel-2 data for the year of 2018. There are two challenges that we address; the first one is the ability of our model to manage big satellite data and scale for a nationwide application. The second one is the algorithm\uffe2\uff80\uff99s capacity to cope with scarce labeled data to train supervised machine learning algorithms. Specifically, we implement an approach that combines unsupervised and supervised learning. First, we generate pseudo-labels for rice classification from a single site (Seosan-Dangjin) by using a dynamic k-means clustering approach. The pseudo-labels are then used to train a Random Forest (RF) classifier that is fine-tuned to generalize in two other sites (Haenam and Cheorwon). The optimized model was then tested against 40 labeled plots, evenly distributed across the country. The paddy rice mapping pipeline is scalable as it has been deployed in a High Performance Data Analytics (HPDA) environment using distributed implementations for both k-means and RF classifiers. When tested across the country, our model provided an overall accuracy of 96.69% and a kappa coefficient 0.87. Even more, the accurate paddy rice area mapping was returned early in the year (late July), which is key for timely decision-making. Finally, the performance of the generalized paddy rice classification model, when applied in the sites of Haenam and Cheorwon, was compared to the performance of two equivalent models that were trained with locally sampled labels. The results were comparable and highlighted the success of the model\uffe2\uff80\uff99s generalization and its applicability to other regions.</p>", "keywords": ["semi-supervised learning", "2. Zero hunger", "Science", "Q", "0211 other engineering and technologies", "food security", "04 agricultural and veterinary sciences", "02 engineering and technology", "15. Life on land", "high performance computing", "pseudo-labeling", "0401 agriculture", " forestry", " and fisheries", "paddy rice mapping", "distributed learning", "pseudo-labeling; paddy rice mapping; distributed learning; semi-supervised learning; food security; high performance computing"]}, "links": [{"href": "http://www.mdpi.com/2072-4292/13/9/1769/pdf"}, {"href": "https://www.mdpi.com/2072-4292/13/9/1769/pdf"}, {"href": "https://doi.org/10.3390/rs13091769"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Remote%20Sensing", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/rs13091769", "name": "item", "description": "10.3390/rs13091769", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/rs13091769"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-05-01T00:00:00Z"}}, {"id": "10.3390/rs14061384", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:19:18Z", "type": "Journal Article", "created": "2022-03-14", "title": "Development of Prediction Models for Estimating Key Rice Growth Variables Using Visible and NIR Images from Unmanned Aerial Systems", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>The rapid and accurate acquisition of rice growth variables using unmanned aerial system (UAS) is useful for assessing rice growth and variable fertilization in precision agriculture. In this study, rice plant height (PH), leaf area index (LAI), aboveground biomass (AGB), and nitrogen nutrient index (NNI) were obtained for different growth periods in field experiments with different nitrogen (N) treatments from 2019\u20132020. Known spectral indices derived from the visible and NIR images and key rice growth variables measured in the field at different growth periods were used to build a prediction model using the random forest (RF) algorithm. The results showed that the different N fertilizer applications resulted in significant differences in rice growth variables; the correlation coefficients of PH and LAI with visible-near infrared (V-NIR) images at different growth periods were larger than those with visible (V) images while the reverse was true for AGB and NNI. RF models for estimating key rice growth variables were established using V-NIR images and V images, and the results were validated with an R2 value greater than 0.8 for all growth stages. The accuracy of the RF model established from V images was slightly higher than that established from V-NIR images. The RF models were further tested using V images from 2019: R2 values of 0.75, 0.75, 0.72, and 0.68 and RMSE values of 11.68, 1.58, 3.74, and 0.13 were achieved for PH, LAI, AGB, and NNI, respectively, demonstrating that RGB UAS achieved the same performance as multispectral UAS for monitoring rice growth.</p></article>", "keywords": ["2. Zero hunger", "digital imagery", "rice growth variables; unmanned aerial system; multispectral imagery; digital imagery; random forest model", "Science", "random forest model", "Q", "0401 agriculture", " forestry", " and fisheries", "rice growth variables", "04 agricultural and veterinary sciences", "15. Life on land", "multispectral imagery", "unmanned aerial system"], "contacts": [{"organization": "Zhengchao Qiu, Fei Ma, Zhenwang Li, Xuebin Xu, Changwen Du,", "roles": ["creator"]}]}, "links": [{"href": "http://www.mdpi.com/2072-4292/14/6/1384/pdf"}, {"href": "https://doi.org/10.3390/rs14061384"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Remote%20Sensing", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/rs14061384", "name": "item", "description": "10.3390/rs14061384", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/rs14061384"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-03-13T00:00:00Z"}}, {"id": "10.3390/su10051371", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:19:19Z", "type": "Journal Article", "created": "2018-04-27", "title": "Effect Of Biochar Amendment On Methane Emissions From Paddy Field Under Water-Saving Irrigation", "description": "<p>Biochar has been proposed as a new countermeasure to mitigate climate change because of its potential in inhibiting greenhouse gas emissions from farmlands. A field experiment was conducted in Taihu Lake region in China to assess the effects of rice-straw biochar amendment on methane (CH4) emissions from paddy fields under water-saving irrigation using three treatments, namely, control with no amendment (C0), 20 t ha\uffe2\uff88\uff921 (C20), and 40 t ha\uffe2\uff88\uff921 rice-straw biochar amendments (C40). Results showed that biochar application significantly decreased CH4 emissions by 29.7% and 15.6% at C20 and C40 biochar addition level, respectively. C20 significantly increased soil dissolved organic carbon, total nitrogen, and NH4+-N by 79.5, 24.5, and 47.7%, respectively, and decreased NO3\uffe2\uff88\uff92-N by 30.4% compared with C0. On the other hand, no significant difference was observed in soil pH and soil organic carbon in all treatments. C20 and C40 significantly increased and decreased soil oxidation-reduction potential, respectively. Compared with C0, rice yield and irrigation water productivity significantly increased by 24.0% and 33.4% and 36.3% and 42.5% for C20 and C40, respectively. Thus, rice-straw biochar amendment and water-saving irrigation technology can inhibit CH4 emissions while increasing rice yield and irrigation water productivity. The effects of increasing rice yield and irrigation water productivity were more remarkable for C40, but C20 was more effective in mitigating CH4 emission.</p>", "keywords": ["2. Zero hunger", "13. Climate action", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "biochar; water-saving irrigation; methane emission; rice yield", "7. Clean energy", "6. Clean water"]}, "links": [{"href": "http://www.mdpi.com/2071-1050/10/5/1371/pdf"}, {"href": "https://doi.org/10.3390/su10051371"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Sustainability", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/su10051371", "name": "item", "description": "10.3390/su10051371", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/su10051371"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-04-27T00:00:00Z"}}, {"id": "10.5061/dryad.rbnzs7hf0", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:19:39Z", "type": "Dataset", "title": "Biochar and nitrogen fertilizer promote rice yield by altering soil enzyme activity and microbial community structure", "description": "unspecifiedBiochar can significantly change soil properties and improve soil quality.  However, the effects of long-term combined application of biochar (B) and  nitrogen (N) fertilizer on relationships between soil enzyme activity,  microbial community structure and crop yield are still obscure. We  characterized these relationships in a long-term (8 years) field  experiment with rice, two biochar rates of 0 and 13.5 t ha-1 year-1 (B0  and B) and two N fertilizer rates of 0 and 300 kg N ha-1 year-1 (N0 and  N). The repeated, long-term combined applications of biochar and N  fertilizer significantly increased microbial biomass carbon and nitrogen  (MBC and MBN), but biochar decreased the abundance of total bacteria,  fungi, actinomycetes, Gram-positive and Gram-negative bacteria as well as  the amount of total phospholipid fatty acids. The activity of leucine  aminopeptidase (LAP) decreased significantly in the biochar-amended and N  fertilized treatment, but the LAP activity either remained unchanged or  increased with biochar amendment at N0. The relative abundance of  bacterial phylum Chloroflexi was increased in the combined biochar and N  fertilizer treatment. The changes in soil organic matter and the activity  of \u03b1-1,4-xylosidase were the major properties influencing soil bacterial  community composition, whereas the structure of fungal community was  governed by MBC, MBN and LAP activity. In addition, long-term biochar and  N fertilizer applied together significantly increased rice yield (more  than biochar and nitrogen fertilizer applied alone). Yield was  significantly positively correlated with LAP activity, but significantly  negatively correlated with the relative abundance of Chloroflexi. In  conclusion, long-term biochar and nitrogen fertilizer applications  increased rice yield, which was associated with altered soil microbial  community and enhanced activity of some enzymes.", "keywords": ["2. Zero hunger", "Microbial community", "FOS: Agricultural sciences", "biochar", "phospholipid fatty acids", "15. Life on land", "6. Clean water", "long-term experiment", "nitrogen fertilizer", "enzyme activity", "rice yield"], "contacts": [{"organization": "Zhang, Aiping", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.rbnzs7hf0"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.rbnzs7hf0", "name": "item", "description": "10.5061/dryad.rbnzs7hf0", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.rbnzs7hf0"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-09-01T00:00:00Z"}}, {"id": "10.5281/zenodo.3465229", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:20:50Z", "type": "Report", "created": "2019-10-23", "title": "3D geological model reconstruction for liquefaction hazard assessment in the Po Plain", "description": "Proceedings of the VII ICEGE 7th International Conference on Earthquake Geotechnical Engineering, Rome, Italy, 17-20 June 2019.", "keywords": ["dynamic", "550", "earthquake; site effects; topographic effect", "0211 other engineering and technologies", "600", "02 engineering and technology", "624", "laboratory tests", "name=General Earth and Planetary Sciences", "620", "site effects", " Central italy earthquake 2016", " Amatrice", "2-D numerical models", " GIS", "0201 civil engineering", "3D Geological model", " liquefaction hazard", " earthquake", " Po Plain.", "/dk/atira/pure/subjectarea/asjc/1900/1900", "name=General Environmental Science", "sandy", "/dk/atira/pure/subjectarea/asjc/2300/2300"], "contacts": [{"organization": "C. Meisina, R. Boni\u0300, M. Bordoni, C. Lai, A. Fama\u0300, F. Bozzoni, R. M. Cosentini, D. Castaldini, D. Fontana, S. Lugli, A. Ghinoi, L. Martelli, P. Severi,", "roles": ["creator"]}]}, "links": [{"href": "https://www.iris.unict.it/bitstream/20.500.11769/386431/2/ch385.pdf"}, {"href": "https://doi.org/10.5281/zenodo.3465229"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.3465229", "name": "item", "description": "10.5281/zenodo.3465229", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.3465229"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-10-22T00:00:00Z"}}, {"id": "10.5281/zenodo.4139735", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:20:52Z", "type": "Dataset", "title": "Dataset associated to Bioinspired electro-permeable glycans on carbon: Fouling control for sensing in complex matrices", "description": "This dataset is associated to the publication 'Bioinspired electro-permeable glycans on carbon: Fouling control for sensing in complex matrices' performed in Trinity College, Dublin, Ireland. The dataset contains raw data associated to the measures contained in the article: X ray photoelectron spectroscopy, Atomic force microscopy, cyclic voltammetries. This publication has emanated from research conducted with the financial support of Science Foundation Ireland (SFI) grant No. 13/CDA/2213. AM and JAB gratefully acknowledge support from the School of Chemistry and the Irish Research Council Grant No. GOIPG/2014/399, respectively. EW is grateful for support by the Undergraduate Research Bursary Program of the Royal Society of Chemistry and Nuffield Foundation. Use of the XPS of Prof. I. V. Shvets and C. McGuinness provided under SFI Equipment Infrastructure funds. This project has received funding from the European Union\u2019s Horizon 2020 research and innovation programme under the Marie Sk\u0142odowska-Curie grant agreement No. 799175 (HiBriCarbon). The results of this publication reflect only the authors\u2019 view and the Commission is not responsible for any use that may be made of the information it contains.", "keywords": ["Complex matrices", "Nanoscience & Materials", "Glycan adlayers"], "contacts": [{"organization": "Iannaci, Alessandro, Myles, Adam, Behan A., James, Whelan, \u00c9adaoin, Scanlan M., Eoin, Colavita E., Paula,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4139735"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4139735", "name": "item", "description": "10.5281/zenodo.4139735", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4139735"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-11-09T00:00:00Z"}}, {"id": "10.5281/zenodo.4748444", "type": "Feature", "geometry": null, "properties": {"license": "Embargo", "updated": "2026-08-24T16:20:54Z", "type": "Dataset", "title": "The extent of woody plant invasion in selected sites of the communally managed Molopo District, North West Province.", "description": "EmbargoWoody plant invasion (bush encroachment) is a problem in the semi arid communal areas of the North West Province which had been affecting the Molopo Area as early as 1960. It affects the livelihoods of the communal farmer because it reduces carrying capacity and is a form of veld degradation. The extent of woody plant encroachment was quantified at selected sites and reference sites in the Molopo District. There was a study site and reference site selected in a commercially managed area. Soil samples from these selected sites were also analysed for chemical and physical properties as well as nutrient content that could have an influence on the proliferation of the woody plants. Social surveys were also conducted to investigate the perceptions and influence of the affected communities towards woody plant invasion. The prominent species identified in the area included Acacia mellifera, Dichrostachys cenerea, Prosopis velutina and Terminalia sericea. All of the study sites, except the benchmark sites, had woody plant densities of more than 2 000 TE/ha that according to Moore &amp; Odendaal (1987), almost totally suppress grass growth. It was clear from the data that the nutrient status of soils of encroached areas was higher than the benchmark sites although some of the differences were statistically insignificant. Organic carbon was higher at most of the encroached sites (71 % of the sites) where 80 % of the enriched sites had significantly higher organic carbon than that of the benchmark sites. There is a need to develop small scale farming practices that are appropriate in terms of sustainable development in the local context.", "keywords": ["2. Zero hunger", "woody plants", "Molopo district", "Prosopis velutina", "Dichrostachys cenerea", "Masters", "15. Life on land", "Acacia mellifera", "North West Province", "Terminalia sericea", "Molopo Area"], "contacts": [{"organization": "Mogodi, Phemelo", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4748444"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4748444", "name": "item", "description": "10.5281/zenodo.4748444", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4748444"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2010-01-01T00:00:00Z"}}, {"id": "10.5281/zenodo.7657746", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:21:05Z", "type": "Journal Article", "created": "2023-02-16", "title": "Does population density influence fluctuating asymmetry of Sitophilus oryzae laboratory populations?", "description": "RestrictedThe rice weevil, Sitophilus oryzae, is one of the most pernicious pests of stored grain. It is a primary pest and causes a reduction in weight, quality, seed viability and commercial value of various cereals. For this study, we reared S. oryzae on wheat grains under two different adult densities, low and high, with an aim to assess the influence of population density on fluctuating asymmetry of the adult\u2019s ventral body. Fluctuating asymmetry represents slight and random deviations from bilateral symmetry normally distributed around a 0 mean, and its level is usually higher under a disturbed developmental process. Accordingly, we expected that environmental stress caused by higher density would increase its level. Opposite to our hypothesis, the study showed that population density did not influence fluctuating asymmetry of S. oryzae adults. Both experimental populations exhibited a similar, non-significant level of fluctuating asymmetry.", "keywords": ["2. Zero hunger", "0106 biological sciences", "0301 basic medicine", "abundance", "rice weevil", "03 medical and health sciences", "wheat", "fluctuating asymmetry", "Fluctuating asymmetry", "Abundance", " Rice weevil", " Wheat", "01 natural sciences"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.7657746"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Stored%20Products%20Research", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.7657746", "name": "item", "description": "10.5281/zenodo.7657746", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.7657746"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-03-01T00:00:00Z"}}, {"id": "10.5281/zenodo.8085976", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:21:08Z", "type": "Journal Article", "created": "2020-10-05", "title": "Qualifications of Rice Growth Indicators Optimized at Different Growth Stages Using Unmanned Aerial Vehicle Digital Imagery", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>The accurate estimation of the key growth indicators of rice is conducive to rice production, and the rapid monitoring of these indicators can be achieved through remote sensing using the commercial RGB cameras of unmanned aerial vehicles (UAVs). However, the method of using UAV RGB images lacks an optimized model to achieve accurate qualifications of rice growth indicators. In this study, we established a correlation between the multi-stage vegetation indices (VIs) extracted from UAV imagery and the leaf dry biomass, leaf area index, and leaf total nitrogen for each growth stage of rice. Then, we used the optimal VI (OVI) method and object-oriented segmentation (OS) method to remove the noncanopy area of the image to improve the estimation accuracy. We selected the OVI and the models with the best correlation for each growth stage to establish a simple estimation model database. The results showed that the OVI and OS methods to remove the noncanopy area can improve the correlation between the key growth indicators and VI of rice. At the tillering stage and early jointing stage, the correlations between leaf dry biomass (LDB) and the Green Leaf Index (GLI) and Red Green Ratio Index (RGRI) were 0.829 and 0.881, respectively; at the early jointing stage and late jointing stage, the coefficient of determination (R2) between the Leaf Area Index (LAI) and Modified Green Red Vegetation Index (MGRVI) was 0.803 and 0.875, respectively; at the early stage and the filling stage, the correlations between the leaf total nitrogen (LTN) and UAV vegetation index and the Excess Red Vegetation Index (ExR) were 0.861 and 0.931, respectively. By using the simple estimation model database established using the UAV-based VI and the measured indicators at different growth stages, the rice growth indicators can be estimated for each stage. The proposed estimation model database for monitoring rice at the different growth stages is helpful for improving the estimation accuracy of the key rice growth indicators and accurately managing rice production.</p></article>", "keywords": ["2. Zero hunger", "object-oriented segmentation method", "optimal index method", "rice", "Science", "Q", "rice; growth indicators; multi-stage vegetation index; unmanned aerial vehicle; optimal index method; object-oriented segmentation method; estimation accuracy", "0211 other engineering and technologies", "04 agricultural and veterinary sciences", "02 engineering and technology", "multi-stage vegetation index", "15. Life on land", "growth indicators", "13. Climate action", "unmanned aerial vehicle", "0401 agriculture", " forestry", " and fisheries"], "contacts": [{"organization": "Zhengchao Qiu, Haitao Xiang, Fei Ma, Changwen Du,", "roles": ["creator"]}]}, "links": [{"href": "http://www.mdpi.com/2072-4292/12/19/3228/pdf"}, {"href": "https://www.mdpi.com/2072-4292/12/19/3228/pdf"}, {"href": "https://doi.org/10.5281/zenodo.8085976"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Remote%20Sensing", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.8085976", "name": "item", "description": "10.5281/zenodo.8085976", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.8085976"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-10-03T00:00:00Z"}}, {"id": "10.5281/zenodo.8090784", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:21:08Z", "type": "Journal Article", "created": "2021-08-31", "title": "Estimation of nitrogen nutrition index in rice from UAV RGB images coupled with machine learning algorithms", "description": "Rapid and accurate estimation of rice Nitrogen Nutrition Index (NNI) is beneficial for management of nitrogen application in rice production. Traditional estimation methods required manual actual measurement data in the field, which was time-consuming and cost-expensive, and RGB images from unmanned aerial vehicle (UAV) provided an alternative option for nitrogen nutrition index (NNI) monitoring. In this study, RGB images from unmanned aerial vehicle (UAV) were obtained from each growth period of rice, and six machine learning (ML) algorithms, i.e., adaptive boosting (AB), artificial neural network (ANN), K-nearest neighbor (KNN), partial least squares (PLSR), random forest (RF) and support vector machine (SVM), were used to extract target information for estimating NNI as well as vegetation index (VI). Results showed that most UAV VIs were significantly correlated with rice NNI at the key growing periods; the estimation results of rice NNI using six ML algorithms showed that the RF algorithms performed the best at each growth period with the determination coefficient (R<sup>2</sup> ) ranged from 0.88 to 0.96 and room mean square error (RMSE) ranged from 0.03 to 0.07, in which the estimation of NNI was the best in filling period and the early jointing stage. Rice NNI at the early jointing stage was significantly correlated with soil available nitrogen (AN) with the R<sup>2 </sup>of 0.84 in Pukou and 0.72 in Luhe, respectively, and rice NNI was significantly correlated with the yield with the R2 of more than 0.7 in Pukou at the whole period and more than 0.7 in Luhe from late jointing to maturity stage. Therefore, the combination of RGB images from UAV and ML algorithms was a scalable, simple and inexpensive method for rapid qualification of rice NNI, which effectively improved nitrogen use efficiency and provided guidance for precision fertilization in rice production.", "keywords": ["2. Zero hunger", "Machine learning", "0211 other engineering and technologies", "0401 agriculture", " forestry", " and fisheries", "Precision fertilization", "Rice", "Nitrogen nutrition index", "Unmanned aerial vehicle", "04 agricultural and veterinary sciences", "02 engineering and technology", "6. Clean water"], "contacts": [{"organization": "Zhengchao Qiu, Ma, Fei, Zhenwang Li, Xuebin Xu, Haixiao Ge, Changwen Du,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.8090784"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Computers%20and%20Electronics%20in%20Agriculture", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.8090784", "name": "item", "description": "10.5281/zenodo.8090784", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.8090784"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-10-01T00:00:00Z"}}, {"id": "10.5281/zenodo.8091294", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:21:09Z", "type": "Journal Article", "created": "2021-11-30", "title": "Grain Yield Estimation in Rice Breeding Using Phenological Data and Vegetation Indices Derived from UAV Images", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>The accurate estimation of grain yield in rice breeding is crucial for breeders to screen and select qualified cultivars. In this study, a low-cost unmanned aerial vehicle (UAV) platform mounted with an RGB camera was carried out to capture high-spatial resolution images of rice canopy in rice breeding. The random forest (RF) regression techniques were used to establish yield models by using (1) only color vegetation indices (VIs), (2) only phenological data, and (3) fusion of VIs and phenological data as inputs, respectively. Then, the performances of RF models were compared with the manual observation and CERES-Rice model. The results indicated that the RF model using VIs only performed poorly for estimating yield; the optimized RF model that combined the use of phenological data and color VIs performed much better, which demonstrated that the phenological data significantly improved the model performance. Furthermore, the yield estimation accuracy of 21 rice cultivars that were continuously planted over three years in the optimal RF model had no significant difference (p &gt; 0.05) with that of the CERES-Rice model. These findings demonstrate that the RF model, by combining phenological data and color Vis, is a potential and cost-effective way to estimate yield in rice breeding.</p></article>", "keywords": ["0106 biological sciences", "2. Zero hunger", "S", "UAV", "CERES-Rice", "Agriculture", "04 agricultural and veterinary sciences", "15. Life on land", "yield", "01 natural sciences", "rice breeding", "UAV; rice breeding; yield; CERES-Rice; RF; vegetation indices", "vegetation indices", "RF", "0401 agriculture", " forestry", " and fisheries"], "contacts": [{"organization": "Haixiao Ge, Fei Ma, Zhenwang Li, Changwen Du,", "roles": ["creator"]}]}, "links": [{"href": "http://www.mdpi.com/2073-4395/11/12/2439/pdf"}, {"href": "https://doi.org/10.5281/zenodo.8091294"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agronomy", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.8091294", "name": "item", "description": "10.5281/zenodo.8091294", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.8091294"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-11-29T00:00:00Z"}}, {"id": "10.5281/zenodo.8091705", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:21:09Z", "type": "Journal Article", "created": "2021-11-30", "title": "Global Sensitivity Analysis for CERES-Rice Model under Different Cultivars and Specific-Stage Variations of Climate Parameters", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Global sensitivity analysis (SA) has become an efficient way to identify the most influential parameters on model results. However, the effects of cultivar variation and specific-stage variations of climate conditions on model outputs still remain unclear. In this study, 30 indica hybrid rice cultivars were simulated in the CERES-Rice model; then the Sobol\u2019 method was used to perform a global SA on 16 investigated parameters for three model outputs (anthesis day, maturity day, and yield). In addition, we also compared the differences in the sensitivity results under four specific-stage variations (vegetative phase, panicle-formation phase, ripening phase, and the whole growth season) of climate conditions. The results indicated that (1) parameter Tavg, G4, and P2O are the most influential parameters for all model outputs across cultivars during the whole growth season; (2) under the vegetative-phase variation of climate parameters; the variability of model outputs is mainly controlled by parameter P2O and Tavg; (3) under the panicle-formation-phase or ripening-phase variation of climate parameters, parameter P2O was the dominant variable for all model outputs; (4) parameter PORM had a considerable effect (the total sensitivity index, STi; STi&gt;0.05) on yield regardless of the various specific-stage variations of the climate parameters. Findings obtained from this study will contribute to understanding the comprehensive effects of crop parameters on model outputs under different cultivars and specific-stage variations of climate conditions.</p></article>", "keywords": ["2. Zero hunger", "sensitivity analysis", "S", "rice", "CERES-Rice", "CERES-Rice; rice; cultivars; Sobol\u2019 method; sensitivity analysis", "cultivars", "Sobol\u2019 method", "0401 agriculture", " forestry", " and fisheries", "Agriculture", "Sobol' method", "04 agricultural and veterinary sciences", "15. Life on land"], "contacts": [{"organization": "Haixiao Ge, Fei Ma, Zhenwang Li, Changwen Du,", "roles": ["creator"]}]}, "links": [{"href": "http://www.mdpi.com/2073-4395/11/12/2446/pdf"}, {"href": "https://doi.org/10.5281/zenodo.8091705"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agronomy", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.8091705", "name": "item", "description": "10.5281/zenodo.8091705", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.8091705"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-11-30T00:00:00Z"}}, {"id": "10.5281/zenodo.8092635", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:21:09Z", "type": "Journal Article", "created": "2022-01-10", "title": "Long-Term Dynamic of Cold Stress during Heading and Flowering Stage and Its Effects on Rice Growth in China", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Short episodes of low-temperature stress during reproductive stages can cause significant crop yield losses, but our understanding of the dynamics of extreme cold events and their impact on rice growth and yield in the past and present climate remains limited. In this study, by analyzing historical climate, phenology and yield component data, the spatial and temporal variability of cold stress during the rice heading and flowering stages and its impact on rice growth and yield in China was characterized. The results showed that cold stress was unevenly distributed throughout the study region, with the most severe events observed in the Yunnan Plateau with altitudes higher than 1800 m. With the increasing temperature, a significant decreasing trend in cold stress was observed across most of the three ecoregions after the 1970s. However, the phenological-shift effects with the prolonged growing period during the heading and flowering stages have slowed down the cold stress decreasing trend and led to an underestimation of the magnitude of cold stress events. Meanwhile, cold stress during heading and flowering will still be a potential threat to rice production. The cold stress-induced yield loss is related to both the intensification of extreme cold stress and the contribution of related components to yield in the three regions.</p></article>", "keywords": ["2. Zero hunger", "climate change; cold stress; yield variability; rice growth; food security", "rice growth", "food security", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "climate change", "13. Climate action", "Meteorology. Climatology", "cold stress", "0401 agriculture", " forestry", " and fisheries", "QC851-999", "yield variability", "0105 earth and related environmental sciences"], "contacts": [{"organization": "Zhenwang Li, Zhengchao Qiu, Haixiao Ge, Changwen Du,", "roles": ["creator"]}]}, "links": [{"href": "http://www.mdpi.com/2073-4433/13/1/103/pdf"}, {"href": "https://doi.org/10.5281/zenodo.8092635"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Atmosphere", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.8092635", "name": "item", "description": "10.5281/zenodo.8092635", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.8092635"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-01-10T00:00:00Z"}}, {"id": "10.5281/zenodo.8092713", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:21:09Z", "type": "Journal Article", "created": "2022-03-13", "title": "Development of Prediction Models for Estimating Key Rice Growth Variables Using Visible and NIR Images from Unmanned Aerial Systems", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>The rapid and accurate acquisition of rice growth variables using unmanned aerial system (UAS) is useful for assessing rice growth and variable fertilization in precision agriculture. In this study, rice plant height (PH), leaf area index (LAI), aboveground biomass (AGB), and nitrogen nutrient index (NNI) were obtained for different growth periods in field experiments with different nitrogen (N) treatments from 2019\u20132020. Known spectral indices derived from the visible and NIR images and key rice growth variables measured in the field at different growth periods were used to build a prediction model using the random forest (RF) algorithm. The results showed that the different N fertilizer applications resulted in significant differences in rice growth variables; the correlation coefficients of PH and LAI with visible-near infrared (V-NIR) images at different growth periods were larger than those with visible (V) images while the reverse was true for AGB and NNI. RF models for estimating key rice growth variables were established using V-NIR images and V images, and the results were validated with an R2 value greater than 0.8 for all growth stages. The accuracy of the RF model established from V images was slightly higher than that established from V-NIR images. The RF models were further tested using V images from 2019: R2 values of 0.75, 0.75, 0.72, and 0.68 and RMSE values of 11.68, 1.58, 3.74, and 0.13 were achieved for PH, LAI, AGB, and NNI, respectively, demonstrating that RGB UAS achieved the same performance as multispectral UAS for monitoring rice growth.</p></article>", "keywords": ["2. Zero hunger", "digital imagery", "rice growth variables; unmanned aerial system; multispectral imagery; digital imagery; random forest model", "Science", "random forest model", "Q", "0401 agriculture", " forestry", " and fisheries", "rice growth variables", "04 agricultural and veterinary sciences", "15. Life on land", "multispectral imagery", "unmanned aerial system"], "contacts": [{"organization": "Zhengchao Qiu, Fei Ma, Zhenwang Li, Xuebin Xu, Changwen Du,", "roles": ["creator"]}]}, "links": [{"href": "http://www.mdpi.com/2072-4292/14/6/1384/pdf"}, {"href": "https://doi.org/10.5281/zenodo.8092713"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Remote%20Sensing", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.8092713", "name": "item", "description": "10.5281/zenodo.8092713", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.8092713"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-03-13T00:00:00Z"}}, {"id": "10261/220255", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:21:47Z", "type": "Journal Article", "created": "2020-01-09", "title": "SHui, an EU-Chinese cooperative project to optimize soil and water management in agricultural areas in the XXI century", "description": "Open AccessThis work has been supported by Project SHui which is co-funded by the European Union Project GA 773903 and the Chinese MOST. This work has been supported by P12-AGR-0931 (Andalusian Government), RTA2014-00063- C04-03 (Spanish government), SHui (European Commission Grant Agreement number: 773903) and EU\u2012FEDER funds", "keywords": ["Yield", "550", "EROSION", "FLOW", "Cropping", "SIMULATE YIELD RESPONSE", "Soil Science", "Environmental Sciences & Ecology", "RICE YIELDS", "01 natural sciences", "630", "12. Responsible consumption", "4104 Environmental management", "4105 Pollution and contamination", "DRYING IRRIGATION", "11. Sustainability", "FAO CROP MODEL", "0105 earth and related environmental sciences", "2. Zero hunger", "Science & Technology", "1. No poverty", "Agriculture", "04 agricultural and veterinary sciences", "15. Life on land", "Engineering (General). Civil engineering (General)", "6. Clean water", "4106 Soil sciences", "Cooperation", "Sustainability", "13. Climate action", "Physical Sciences", "Water Resources", "0401 agriculture", " forestry", " and fisheries", "TA1-2040", "Life Sciences & Biomedicine", "Environmental Sciences"]}, "links": [{"href": "https://doi.org/10261/220255"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/International%20Soil%20and%20Water%20Conservation%20Research", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10261/220255", "name": "item", "description": "10261/220255", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10261/220255"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-03-01T00:00:00Z"}}, {"id": "10.7910/DVN/23785", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:21:40Z", "type": "Dataset", "created": "2012-01-01", "title": "Modelling the role of algae in rice crop nutrition and soil organic carbon maintenance", "description": "Closed AccessSubject: null Type: CESD Notes: ;", "keywords": ["Algae", "Cropping systems", "APSIM", "Rice", "Biological nitrogen fixation", "ORYZA2000"], "contacts": [{"organization": "Gaydon, D.S., Probert, M.E., Buresh, R.J., Meinke, H., Timsina, J.,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.7910/DVN/23785"}, {"rel": "self", "type": "application/geo+json", "title": "10.7910/DVN/23785", "name": "item", "description": "10.7910/DVN/23785", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.7910/DVN/23785"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2012-01-01T00:00:00Z"}}, {"id": "10.7910/DVN/2XHKHB", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:21:40Z", "type": "Dataset", "created": "2009-01-01", "title": "Performance of diverse upland rice cultivars in low and high soil fertility conditions in West Africa", "description": "Traditional tropical japonica (Oryza sativa) and Oryzaglaberrimacultivars are typically grown in lowinput, subsistence production systems in the uplands of West Africa by resource-poor farmers. In these systems, low soil fertility (LF), which is generally associated with lower organic carbon content, and N and P availability, is one of the major constraints to rice productivity. Thus, cultivars adapted to LF are needed for the food security of farmers, who would otherwise be solely reliant on nutrient inputs to increase productivity. This study evaluated the performance of six diverse cultivars grown in LF and high soil fertility (HF) conditions with supplemental irrigation over two seasons. Average grain yield across all cultivars in LF was 54% of that in HF (156 vs. 340 g m_2). Three improved indicarice cultivars and CG 14 (O. glaberrima) out-yielded Morobe\u00b4 re\u00b4kan (traditional tropical japonica) and WAB450-IBP-38-HB (progeny from interspecific hybridization of tropical japonica and O. glaberrima) in LF (181 vs. 105 g m_2 on average). The high grain yield in LF was the result of large spikelet number m_2 due to superior tillering ability and high harvest index rather than biomass production. The high-yielding cultivars in LF consistently had lower leaf chlorophyll content and higher specific leaf area during the period from the early vegetative stage through the reproductive stage. Among them, two indicacultivars (B6144F-MR-6-0-0 and IR 55423-01) were also high yielding in HF. The use of improved indicacultivars adapted to LF, but also with input-responsiveness, appears to offer an attractive and economical approach to improving upland rice productivity and widening genetic diversity in this region.", "keywords": ["Specific leaf area", "West Africa", "Indica", "Upland rice", "Low soil fertility", "Chlorophyll content", "Oryzaglaberrima"], "contacts": [{"organization": "Saito, Kazuki, Futakuchi, Koichi,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.7910/DVN/2XHKHB"}, {"rel": "self", "type": "application/geo+json", "title": "10.7910/DVN/2XHKHB", "name": "item", "description": "10.7910/DVN/2XHKHB", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.7910/DVN/2XHKHB"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2012-01-01T00:00:00Z"}}, {"id": "10.7910/DVN/9SPT9N", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:21:40Z", "type": "Dataset", "title": "Raw data for the Crop Health (Project 4) of ICON: Introducing non-flooded crops in rice-dominated landscapes: Impact on CarbOn, Nitrogen and water budgets", "description": "Open AccessClimate data for modelling data past 2012 can be obtained from the IRRI Climate Group <h1>ICON</h1>  <h2>Introducing non-flooded crops in rice-dominated landscapes: Impact on CarbOn, Nitrogen and water budgets</h2>    Above ground foliar, stem and panicle injury observation and root nematode observation data collected for the ICON project.    The relevant excerpt from the proposal, also included in .doc format, follows.    <h2>Project 4 (Disease epidemics in rice-based systems affected by changes in water management;</h2>  <p>IRRI, Savary \u2013 no funding requested) will monitor disease progress - in particular  sheath blight - in relation to the physical environment of the soil and of the canopy (microclimate), in both the rice and the maize crops (Project 3). The shift from flooded to non-flooded cropping systems directly affects the physical environment and occurrence of natural enemies of the soil-borne pathogens and this, indirectly, affects the physical environment of the canopy, where non soil-borne pathogens may develop (H.1). Rhizoctonia species are soil-borne fungi causing sheath blight in rice, a major disease in rice production, and there is indication that some of the R. solani sub-species can infect maize as well. In this project emphasis will be given to identify the responses of Rhizoctonia as well as other pathogens to (i) crop rotation and (ii) water management regime in order to develop functional relationships between cropping system and crop management and disease progress (H.3).</p>    <p>Change in water management is a prerequisite for adaptation of rice-based agroecosystems in a context of climate change. While water-saving technologies, including supply of agricultural water (the largest user of water in tropical Asia), but also tillage and crop establishment is necessary, singignificant, and possibly considerable changes are to be expected with respect to the entire guild of yield-reducing organisms of rice, including pathogens (bacteria, fungi, and viruses), as well as insects (Savary et al., 2005).</p>    <p>It is worth noting here that this work is congruent with large scale work IRRI has engaged in South Asia, under the umbrella of the Cereal System Initiative for South Asia. This project, among a series of objectives, aims at improving the performances of environmentally constrained \u2013 especially, water constrained \u2013 intensive cereal systems that must develop to feed South Asia for the decades to come; and this includes a series of heavily instrumented platforms where work similar to what is described below will be conducted.</p>    <p>Over the years, IRRI has developed a set of methodologies \u2013 coupled standardized acquisition methods of injuries (IP) due to diseases and insects, as well as weeds; characterization of production situations (PS), including the physiological status of the crop; statistical multivariate, non-parametric methods to link IPs and PSs; and simulation modeling methods to analyze the effects of individual yield reducing organism of the guild within a community. A recent publication summarizes these methods and their applications (Savary et al, 2006).</p>    <p>Project 4 of ICON will look at a series of attributes that will be changed with evolving water supply to rice crops:  <ul>  <li>meso-climate (which will be monitored in the overall experiment);</li>  <li>micro-climate, and I particular, leaf temperature and leaf wetness duration.</li>  </ul>  </p>  <p>We intend to implement the above methodology at successive development stages, including at least:  <ul>  <li>Maximum tillering</li>  <li>Booting</li>  <li>Early dough</li>  </ul>    where the levels of  <ol>  <li>  leaf diseases (esp., bacterial blight, sheath blight, blast, brown spot, narrow brown spot, bacterial leaf streak)</li>  <li>tiller diseases (esp. sheath blight, sheath rot, stem rot)</li>  <li>panicle diseases (esp. grain discoloration, false smut, bakanae)</li>  <li>whole-plant diseases (esp. rice tungro)</li>  <li>insect leaf injuries (esp. leaf folders, whorl maggots)</li>  <li>insect tiller injuries (esp. stem borers \u2013 \u201cdead hearts\u201d)</li>  <li>insect panicle injuries (esp. stem borers \u2013 \u201cwhite heads\u201d)</li>  <li>sucking insect populations (brown plant hopper, white-back planthopper, and green leaf hopper)</li>  </ol>  will be monitored.</p>    <p>Groups a and e \u2013 leaf injury; b and f \u2013 tiller injury; c and g \u2013 panicle injury; d \u2013 systemic injury; and h \u2013 sucking injury represent the framework of the \u201csub-guilds\u201d developed in the above approach to characterize yield-reducing yields. These also are the basis of RICEPEST (Willocquet et al., a generic, mechanistic, crop physiology-based simulation model which enables to explore the individual impact of specific yield-reducer, and their combined effects on systems\u2019 performances. RIRCEPEST has been parameterized, tested, and validated in China, India, and the Philippines during several cropping seasons.</p>    <p>IRRI\u2019s inputs in Project 4 should thus be seen twofold.    <ol>  <li>Quantification of the effects of varying levels of water management on the entire guild of yield-reducing organisms<br />    This component will make use of field data acquisition procedure that have been heavily tested and validated in China, India, Vietnam, and the Philippines, as well as in Laos and Cambodia. The main approach to analyze the data will be  <ul>  <li>conventional-parametric statistics: relating macro-, micro-climate, and water with individual levels of injuries;</li>  <li>non-parametric, including Bayesian, multivariate methods, to address the guild of yield-reducers in a given production situation as a whole.</li>  <li>The purpose of this component would primarily be descriptive, hypothesis-forwarding, and analytical.</li>  </ul>  </li>    <li>Modeling yield losses due to the guild of yield reducers at different levels of water management</li>    <p>This component would involve RICEPEST, and therefore simulation modeling based on crop cuts at a series of development stages during the cropping season (a minimum of 4 crop cuts, especially at harvest, is necessary; however, 7-8 crop cuts would be desirable). These crop cuts would enable to (1) re-parameterize the model for different water regimes \u2013 keeping the flooded regime as a control (year 1), (2) test the model (year 2), and (3) conduct scenario and sensitivity analyses (year 3).  The purpose of this second component would enable generating an outlook of the consequences of water regime scenarios on yield-reduction due to diseases and insects, as well as to identify which of the yield-reducing components of the guild are the most import in what context. </p>  <p>This second component would also enable linking Project 4 with other components of ICON in assessing the performances of water-constrained rice-based ecosystems in a holistic manner.</p>    <p>Savary, S., Castilla, N.P., Elazegui, F.A. & Teng, P.S., 2005. Multiple effects of two drivers of agricultural change, labour shortage and water scarcity, on rice pest profiles in tropical Asia. Field Crops Research 91/2-3: 263-271.</p>    <p>Savary, S., Teng, P.S., Willocquet, L. & Nutter, F.W., Jr., 2006. Quantification and modeling of crop losses: a review of purposes. Annual Review of Phytopathology 44: 89-112.</p>    <p>Willocquet, L., Elazegui, F. A., Castilla, N., Fernandez, L., Fischer, K. S., Peng, S., Teng, P. S., Srivastava, R. K., Singh, H. M., Zhu, D., and Savary, S., 2004. Research priorities for rice disease and pest management in tropical Asia: a simulation analysis of yield losses and management efficiencies. Phytopathology 94(7):672-682.</p>", "keywords": ["Agricultural Sciences", "Climate Change", "Weed Science", "Rice", "Alternate Wetting and Drying", "Plant Pathology", "Entomology", "Nematology", "Irrigation"], "contacts": [{"organization": "Sparks, Adam", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.7910/DVN/9SPT9N"}, {"rel": "self", "type": "application/geo+json", "title": "10.7910/DVN/9SPT9N", "name": "item", "description": "10.7910/DVN/9SPT9N", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.7910/DVN/9SPT9N"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2015-01-01T00:00:00Z"}}, {"id": "10.7910/DVN/KPTWFS", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:21:41Z", "type": "Dataset", "title": "Replication Data for: PERFORMANCE EVALUATION OF INTEGRATED RICE FISH FARMING USING KEBBI AND EBONYI STATE AND THEIR ADJOINING INSTITUTIONAL BASED PLATFORMS AS CASE STUDIES", "description": "Options for farm diversification through integrated aquaculture-agriculture (IAA) are being gradually embraced as a competitive alternative to traditional agriculture because of resource use efficiency and overall productivity. Despite the numerous benefits, the practice of IAA especially integrated rice-fish (IRF) farming in African countries such as Nigeria is limited, therefore, there is a need for proper documentation and demonstration to further encourage IRF adoption. This study was carried out on the MSU/USAID/FAO IRF plot (22m by 15m) for 16 weeks in two states which are Ebonyi and Kebbi and their adjoining institutional-based platforms which are the University of Ibadan (UI) and Usmanu Dan Fodiyo university (UDU) to evaluate the production efficiency and to access the water productivity of combining rice-fish. After transplanting rice seedlings and stocking fish seeds, data were collected on the growth and yield performance of fish such as average body weight(g) and length(cm), survival rate (%) and on rice such as number and length of tiller(cm) number and length of panicles(cm), paddy, grain yield(ton/ha). Water and soil quality parameters such as pH, alkalinity, nitrite, nitrate, ammonia, organic carbon and nitrogen were collected biweekly and monthly. Water use efficiency(kg/ha/cm) was also calculated. Statistical analysis was carried out through analysis of variance (ANOVA) and Ducan multiple range test to find the difference at 5% (p &lt; 0.05) levels. Water quality parameters result showed that alkalinity(mg/l) ranged from 17.8\u00b19.6(Kebbi) to 106.8\u00b14.5(UI), pH ranged from 6.0\u00b11.2(UI) to 8.5\u00b12.1(UDU), nitrate(mg/l) ranged from 0.0\u00b10.0(UI) to 0.3\u00b10.1(Kebbi), nitrite(mg/l) ranged from 0.0\u00b10.0(UI) to 0.5\u00b10.1(Kebbi), ammonia(mg/l) ranged from 0.0\u00b10.1(UI) to 0.5\u00b10.2(UI), hardness(mg/l) ranged from 34.4\u00b118.5(UDU) to 178.6\u00b110.0(UI) and dissolved oxygen(mg/l) ranged from 4.8\u00b10.5(UI) to 13.8\u00b12.8(UDU). For the soil quality parameters result, pH ranged from 5.8\u00b11.1(UI) to 8.0\u00b10.0(UI), nitrogen(g/kg) ranged from 0.6\u00b10.1(UI) to 2.3\u00b10.2(Ebonyi), phosphorus(mg/kg) ranged from 1.2\u00b10.0(Ebonyi) to 13.0\u00b10.0(UI), dissolved oxygen(mg/l) ranged from 4.2\u00b10.4(UI) to 5.6\u00b10.9(UI), organic carbon(g/kg) ranged from 5.0\u00b10.1(UI) to 24.3\u00b16.6(Ebonyi) and potassium(cmol/kg) ranged from 0.1\u00b10.0(Ebonyi) to 1.0\u00b10.3(Kebbi). The number (cell/litre) and abundance(cell/litre) of plankton ranged from 13.0\u00b11.1(Ebonyi) to 230\u00b15.9(UI) and 12.0\u00b11.2(UDUS) to 239\u00b175(UI) respectively. The most dominant species of plankton recorded were rotifera spp, euglena spp, Ulothrix spp and spiruna spp. The highest (73.3) and least (21.5) survival rates (%) were recorded in UI and Ebonyi respectively. The highest (8.3) and the least (1.6) fish yield (ton/ha) were recorded in UI and Kebbi respectively. The highest (5.1) and the least (1.9) rice yield(ton/ha) were recorded in UI and Ebonyi respectively. Consumptive water used(m3) ranged from 197.4\u00b120.5(UI) to 1000.7\u00b160.5(Kebbi), water use efficiency(kg/ha/cm) ranged from 0.5\u00b10.0(Ebonyi) to 1.5\u00b12.2(UI) and water productivity(kg/m3) ranged from 425\u00b140.2(UDU) to 1680\u00b178(Kebbi). There were no significant differences between the mean of water quality parameters in the adaptative plots except for the dissolved oxygen in UDU and Kebbi which were significantly different from UI and Ebonyi. The result revealed that integrated rice fish farming could increase the yield of rice and fish compare to monoculture system of either rice and fish. Therefore, more research should be done and documented on integrated rice fish farming system to ascertain importance of this system for a wider adoption.", "keywords": ["Agricultural Sciences", "Integrated Rice and Fish Farming"], "contacts": [{"organization": "Halwart Mathias, K., Ajani Emmanuel, N. Bart, Amrit, Ajayi, Oluwafemi, Bamidele Omitoyin, Oyebola, Taiwo, Stankus, Austin, Burtle, Gary, E. Fonsah, Greg, Kazeem O. Kareem, Oduntan O., B., Yahaya Abubakar, Ikwuemesi Johnpaul,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.7910/DVN/KPTWFS"}, {"rel": "self", "type": "application/geo+json", "title": "10.7910/DVN/KPTWFS", "name": "item", "description": "10.7910/DVN/KPTWFS", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.7910/DVN/KPTWFS"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-01-01T00:00:00Z"}}, {"id": "11577/3392826", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:22:11Z", "type": "Journal Article", "created": "2021-05-18", "title": "Innovation, conservation, and repurposing of gene function in root cell type development", "description": "Plant species have evolved myriads of solutions, including complex cell type development and regulation, to adapt to dynamic environments. To understand this cellular diversity, we profiled tomato root cell type translatomes. Using xylem differentiation in tomato, examples of functional innovation, repurposing, and conservation of transcription factors are described, relative to the model plant Arabidopsis. Repurposing and innovation of genes are further observed within an exodermis regulatory network and illustrate its function. Comparative translatome analyses of rice, tomato, and Arabidopsis cell populations suggest increased expression conservation of root meristems compared with other homologous populations. In addition, the functions of constitutively expressed genes are more conserved than those of cell type/tissue-enriched genes. These observations suggest that higher order properties of cell type and pan-cell type regulation are evolutionarily conserved between plants and animals.", "keywords": ["root development", "translatomes", "General Biochemistry", "Genetics and Molecular Biology", "Green Fluorescent Proteins", "Meristem", "Arabidopsis", "cell types; evolution; exodermis; gene regulation; rice; root development; tomato; translatomes; xylem", "tomato", "xylem", "Genes", " Plant", "Plant Roots", "Inventions", "Solanum lycopersicum", "Species Specificity", "Gene Expression Regulation", " Plant", "Xylem", "evolution", "Gene Regulatory Networks", "Promoter Regions", " Genetic", "Plant Proteins", "2. Zero hunger", "exodermis", "rice", "15. Life on land", "Protein Biosynthesis", "cell types", "gene regulation", "Transcription Factors"]}, "links": [{"href": "https://www.research.unipd.it/bitstream/11577/3392826/2/PIIS0092867421005043.pdf"}, {"href": "https://doi.org/11577/3392826"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Cell", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "11577/3392826", "name": "item", "description": "11577/3392826", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/11577/3392826"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-06-01T00:00:00Z"}}, {"id": "10316/110910", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-08-24T16:21:55Z", "type": "Journal Article", "created": "2023-11-27", "title": "Changing rice geographies: a long-term perspective of Portuguese regional production (1860-2018)", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>From its origins in Asia, cultivation of Oryza sativa L. in Portugal has had to adapt to local agroecological conditions. Since the late eighteenth century, there has been significant human intervention in rice production, particularly through public policies aimed at increasing production to achieve national food self-sufficiency. Using national and regional statistics on rice production, this article analyses how public policies on rice cultivation over the last 160 years have impacted and interacted with territorial agroecological conditions and the genetic characteristics of the rice varieties being cultivated. We concluded that public policies led to increased production by favouring the geographical reorganisation of rice production based on the rice varieties used and changing territorial agroecological conditions.</p></article>", "keywords": ["0301 basic medicine", "2. Zero hunger", "03 medical and health sciences", "regional inequality", "rice", "historical geography", "05 social sciences", "0507 social and economic geography", "agricultural policy", "15. Life on land", "16. Peace & justice"]}, "links": [{"href": "https://doi.org/10316/110910"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Historia%20Agraria%20Revista%20de%20agricultura%20e%20historia%20rural", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10316/110910", "name": "item", "description": "10316/110910", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10316/110910"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-11-27T00:00:00Z"}}, {"id": "105af8c8-2b94-4945-a71a-4907c56db709", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[2.27, 7.25], [2.27, 7.25], [2.27, 7.25], [2.27, 7.25], [2.27, 7.25]]]}, "properties": {"license": "CC BY", "rights": "Restrictions applied to assure the protection of privacy or intellectual property, and any special restrictions or limitations or warnings on using the resource or metadata. Reports, articles, papers, scientific and non - scientific works of any form, including tables, maps, or any other kind of output, in printed or electronic form, based in whole or in part on the data supplied, must contain an acknowledgement of the form: \"Data reused from the BonaRes Data Centre www.bonares.de. This data were created as part of the ZALF Datenerfassung's research activities.\" Although every care has been taken in preparing and testing the data, the ZALF Datenerfassung and the BonaRes Data Centre cannot guarantee that the data are correct; neither does the ZALF Datenerfassung and the BonaRes Data Centre accept any liability whatsoever for any error, missing data or omission in the data, or for any loss or damage arising from its use. The ZALF Datenerfassung and BonaRes Data Centre will not be responsible for any direct or indirect use which might be made of the data.", "updated": "2024-06-17", "type": "Service", "created": "2024-04-03", "language": "eng", "title": "Web Map Service of the dataset 'Improving the water use efficiency of irrigated rice cultivation in Benin, West Africa'", "description": "This Web Map Service includes spatial information used by datasets 'Improving the water use efficiency of irrigated rice cultivation in Benin, West Africa'", "keywords": ["infoMapAccessService", "Soil", "nitrogen", "evapotranspiration", "rice", "Soil", "nitrogen", "evapotranspiration", "rice"], "contacts": [{"name": "Leibniz Centre for Agricultural Landscape Research", "organization": "ZALF", "position": "Research Platform 'Data Analysis & Simulation' - Workgroup Research Data Management", "roles": ["publisher"], "phones": [{"value": "+49 33432 82 300"}], "emails": [{"value": "dataservice@zalf.de"}], "addresses": [{"deliveryPoint": ["Eberswalder Strasse 84"], "city": "M\u00fcncheberg", "administrativeArea": "Brandenburg", "postalCode": "15374", "country": "Germany"}], "links": [{"href": {"url": null, "protocol": null, "protocol_url": "", "name": "https://ror.org/01ygyzs83", "name_url": "", "description": "ROR", "description_url": "", "applicationprofile": null, "applicationprofile_url": "", "function": null}}]}, {"name": "Geoffroy Sossa", "organization": "Leibniz Center for Agricultural Landscape Research (ZALF), West African Science Service Centre on Climate Change and Adapted Land Use (USTTB), Laboratory of Hydraulic and Water Control (Benin)", "position": null, "roles": ["author"], "phones": [{"value": null}], "emails": [{"value": "sogeof1992@gmail.com"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": null}]}, {"name": "Mathias Hoffmann", "organization": "Leibniz Centre for Agricultural Landscape Research", "position": null, "roles": ["author"], "phones": [{"value": null}], "emails": [{"value": "mathias.hoffmann@zalf.de"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": {"url": null, "protocol": null, "protocol_url": "", "name": "0000-0002-2776-1403", "name_url": "", "description": "ORCID", "description_url": "", "applicationprofile": null, "applicationprofile_url": "", "function": null}}]}, {"name": "Jesse Naab", "organization": "West African Science Service Centre on Climate Change and Adapted Land Use (WASCAL)", "position": null, "roles": ["author"], "phones": [{"value": null}], "emails": [{"value": "jessenaab@gmail.com"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": null}]}, {"name": "Souleymane Sanogo", "organization": "West African Science Service Centre on Climate Change and Adapted Land Use-GRP Climate Change and Agriculture, Universit\u00e9 des Sciences, des Techniques et des Technologies de Bamako (USTTB)", "position": null, "roles": ["author"], "phones": [{"value": null}], "emails": [{"value": "soulysanogo@gmail.com"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": null}]}, {"name": "Michael Asante", "organization": "West African Science Service Centre on Climate Change and Adapted Land Use, University of Sciences, Techniques and Technologies of Bamako (USTTB), Council for Scientific and Industrial Research-Savannah Agricultural Research Institute (CSIR-SARI)", "position": null, "roles": ["author"], "phones": [{"value": null}], "emails": [{"value": "mkasante08@yahoo.co.uk"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": null}]}, {"name": "Yvonne Ayaribil", "organization": "Leibniz Centre for Agricultural Landscape Research", "position": null, "roles": ["author"], "phones": [{"value": null}], "emails": [{"value": "Yvonne.Ayaribil@zalf.de"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": {"url": null, "protocol": null, "protocol_url": "", "name": "0009-0000-7985-7725", "name_url": "", "description": "ORCID", "description_url": "", "applicationprofile": null, "applicationprofile_url": "", "function": null}}]}, {"name": "Luc Sintondji", "organization": "Laboratory of Hydraulic and Water Control (LHME), National Water Institute, University of Abomey-Calavi", "position": null, "roles": ["author"], "phones": [{"value": null}], "emails": [{"value": "o_sintondji@yahoo.fr"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": null}]}, {"name": "J\u00fcrgen Augustin", "organization": "Leibniz Centre for Agricultural Landscape Research", "position": null, "roles": ["author"], "phones": [{"value": null}], "emails": [{"value": "jaug@zalf.de"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": null}]}, {"name": "Marren Dubbert", "organization": "Leibniz Centre for Agricultural Landscape Research", "position": null, "roles": ["author"], "phones": [{"value": null}], "emails": [{"value": "Maren.Dubbert@zalf.de"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": {"url": null, "protocol": null, "protocol_url": "", "name": "0000-0002-2352-8516", "name_url": "", "description": "ORCID", "description_url": "", "applicationprofile": null, "applicationprofile_url": "", "function": null}}]}, {"name": "Mathias Hoffmann", "organization": "Leibniz Centre for Agricultural Landscape Research", "position": 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Change and Adapted Land Use (USTTB), Laboratory of Hydraulic and Water Control (Benin);West African Science Service Centre on Climate Change and Adapted Land Use-GRP Climate Change and Agriculture, Universit\u00e9 des Sciences, des Techniques et des Technologies de Bamako (USTTB);West African Science Service Centre on Climate Change and Adapted Land Use, University of Sciences, Techniques and Technologies of Bamako (USTTB), Council for Scientific and Industrial Research-Savannah Agricultural Research Institute (CSIR-SARI);West African Science Service Centre on Climate Change and Adapted Land Use (WASCAL);Laboratory of Hydraulic and Water Control (LHME), National Water Institute, University of Abomey-Calavi", "roles": ["contributor"]}], "themes": [{"concepts": [{"id": "infoMapAccessService"}], "scheme": "GEMET - INSPIRE themes, version 1.0"}, {"concepts": [{"id": "Soil"}, {"id": "nitrogen"}, {"id": "evapotranspiration"}, {"id": "rice"}], "scheme": "AGROVOC Multilingual agricultural thesaurus"}, {"concepts": [{"id": "Soil"}, {"id": "nitrogen"}, {"id": "evapotranspiration"}, {"id": "rice"}], "scheme": "AGROVOC Multilingual agricultural thesaurus"}]}, "links": [{"href": "https://maps.bonares.de/mapapps/resources/apps/bonares/index.html?lang=en&mid=105af8c8-2b94-4945-a71a-4907c56db709", "rel": "information"}, {"href": "https://maps.bonares.de/wss/service/ags-relay/ags/guest/arcgis/rest/services/Zalf/ID_5281_site_location/MapServer/WMSServer?request=GetCapabilities&service=WMS"}, {"rel": "self", "type": "application/geo+json", "title": "105af8c8-2b94-4945-a71a-4907c56db709", "name": "item", "description": "105af8c8-2b94-4945-a71a-4907c56db709", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/105af8c8-2b94-4945-a71a-4907c56db709"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-06-17T00:00:00Z"}}, {"id": "11353/10.1033200", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:22:07Z", "type": "Journal Article", "created": "2018-07-10", "title": "Recognizing Patterns: Spatial Analysis of Observed Microbial Colonization on Root Surfaces", "description": "Root surfaces are major sites of interactions between plants and associated microorganisms. Here, plants and microbes communicate via signaling molecules, compete for nutrients, and release substrates that may have beneficial or harmful effects on each other. Whilst the body of knowledge on the abundance and diversity of microbial communities at root-soil interfaces is now substantial, information on their spatial distribution at the microscale is still scarce. In this study, a standardized method for recognizing and analyzing microbial cell distributions on root surfaces is presented. Fluorescence microscopy was combined with automated image analysis and spatial statistics to explore the distribution of bacterial colonization patterns on rhizoplanes of rice roots. To test and evaluate the presented approach, a gnotobiotic experiment was performed using a potential nitrogen-fixing bacterial strain in combination with roots of wetland rice. The automated analysis procedure resulted in reliable spatial data of bacterial cells colonizing the rhizoplane. Among all replicate roots, the analysis revealed an increasing density of bacterial cells from the root tip to the region of root cell maturation. Moreover, bacterial cells showed significant spatial clustering and tended to be located around plant root cell borders. The quantitative data suggest that the structure of the root surface plays a major role in bacterial colonization patterns. Possible adaptations of the presented approach for future studies are discussed along with potential pitfalls such as inaccurate imaging. Our results demonstrate that standardized recognition and statistical evaluation of microbial colonization on root surfaces holds the potential to increase our understanding of microbial associations with roots and of the underlying ecological interactions.", "keywords": ["[SDE] Environmental Sciences", "0301 basic medicine", "570", "bacterial colonization", "[SDV]Life Sciences [q-bio]", "CATALYZED REPORTER DEPOSITION", "microbial ecology;root surface;bacterial colonization;point process;spatial statistics;image analysis;pattern recognition;wetland rice", "ECOLOGY", "microbial ecology", "Image analysis", "spatial statistics", "Microbial ecology", "03 medical and health sciences", "image analysis", "Pattern recognition", "root surface", "GE1-350", "Point process", "Wetland rice", "point process", "2. Zero hunger", "106022 Mikrobiologie", "0303 health sciences", "Spatial statistics", "IDENTIFICATION", "pattern recognition", "IN-SITU HYBRIDIZATION", "15. Life on land", "Bacterial colonization", "[SDV] Life Sciences [q-bio]", "SOIL", "Environmental sciences", "wetland rice", "Root surface", "[SDE]Environmental Sciences", "BACTERIA", "106022 Microbiology", "POPULATIONS", "COMMUNITIES"]}, "links": [{"href": "https://doi.org/11353/10.1033200"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Frontiers%20in%20Environmental%20Science", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "11353/10.1033200", "name": "item", "description": "11353/10.1033200", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/11353/10.1033200"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-07-10T00:00:00Z"}}, {"id": "11390/1246806", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:22:09Z", "type": "Journal Article", "created": "2023-01-11", "title": "Responses of key root traits in the genusOryzato soil flooding mimicked by stagnant, deoxygenated nutrient solution", "description": "Abstract<p>Excess water can induce flooding stress resulting in yield loss, even in wetland crops such as rice (Oryza). However, traits from species of wild Oryza have already been used to improve tolerance to abiotic stress in cultivated rice. This study aimed to establish root responses to sudden soil flooding among eight wild relatives of rice with different habitat preferences benchmarked against three genotypes of O. sativa. Plants were raised hydroponically, mimicking drained or flooded soils, to assess the plasticity of adventitious roots. Traits included were apparent permeance (PA) to O2 of the outer part of the roots, radial water loss, tissue porosity, apoplastic barriers in the exodermis, and root anatomical traits. These were analysed using a plasticity index and hierarchical clustering based on principal component analysis. For example, O. brachyantha, a wetland species, possessed very low tissue porosity compared with other wetland species, whereas dryland species O. latifolia and O. granulata exhibited significantly lower plasticity compared with wetland species and clustered in their own group. Most species clustered according to growing conditions based on PA, radial water loss, root porosity, and key anatomical traits, indicating strong anatomical and physiological responses to sudden soil flooding.</p", "keywords": ["2. Zero hunger", "Oxygen", "0301 basic medicine", "Soil", "03 medical and health sciences", "Water", "Oryza", "Nutrients", "15. Life on land", "Research Papers", "Plant Roots", "6. Clean water", "Aerenchyma; barrier to radial oxygen loss; phenotypic plasticity; radial oxygen loss; radial water loss; rice; root porosity; root respiration; waterlogging"]}, "links": [{"href": "https://air.uniud.it/bitstream/11390/1246806/2/Tong_Responses%20of%20key%20root%20traits_2023.pdf"}, {"href": "https://academic.oup.com/jxb/article-pdf/74/6/2112/49702123/erad014.pdf"}, {"href": "https://doi.org/11390/1246806"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Experimental%20Botany", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "11390/1246806", "name": "item", "description": "11390/1246806", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/11390/1246806"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-01-11T00:00:00Z"}}, {"id": "20.500.11850/648810", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:22:36Z", "type": "Journal Article", "title": "Transformation of jarosite and iron oxyhydroxides in acid sulfate paddy soils", "description": "Open AccessMinerals containing Fe are ubiquitous in soils. By providing an abundance of sites for the sorption and incorporation of major and trace elements, Fe minerals can govern the fate and behaviour of numerous pollutants and nutrients in soils. Furthermore, the reactivity of Fe in redox-dynamic soils produces a web of Fe mineral transformation processes with broad consequences for element cycling. The importance of Fe cycling is no exception in acid sulfate soils, although the high sulfur and low pH conditions produce unique Fe mineral transformation processes and compositions. In acid sulfate soils, jarosite, an Fe-K hydroxysulfate mineral, and ferrihydrite, a common short-range-ordered Fe oxyhydroxide mineral, play a central role in the pedological development of active and post-active acid sulfate soils. Soil pH and the dynamics of metals, such as aluminium, are key to understanding the toxicity of acid sulfate soils and can be directly influenced by jarosite and ferrihydrite transformation processes.   Although the transformation of Fe minerals is a key component of biogeochemical processes in redox-active soils, the variables that control the rates and pathways of Fe mineral transformations in soil remain uncertain. The uncertainty arises from the difficulty of tracing molecular processes within a matrix of diverse soil components. Iron minerals are regularly characterised in soils, but the processes that explain the Fe mineral composition of soils cannot be easily resolved. An alternative approach is to perform simplified experiments, such as mixed mineral suspension experiments, under controlled laboratory conditions, to test the effect of individual variables. These systems often use synthetic minerals, although relatively pure jarosite may also be isolated from soils and tested in mixed suspension experiments. While useful to derive mechanistic understanding, the measured outcomes of mixed suspension experiments may not represent the rates and products of transformations that occur in soils.  Therefore, the objective of this thesis was to gain new understanding of the stability and transformation of jarosite and ferrihydrite in acid sulfate soils by developing novel experimental techniques to follow the transformation of synthetic jarosite and ferrihydrite directly in soils. The central theme of the thesis is the comparison of jarosite and aluminium-substituted jarosite transformation in experimental media of increasing complexity. The experiments are performed under conditions that are relevant to rice paddy soils because of the importance of rice in global food production, and the unique management of rice paddies whereby regular flooding during the growing season produces distinct redox cycles. In Thailand, large areas of the Chao Phraya River delta are cultivated as rice paddies despite being acid sulfate soils, providing a suitable site to observe the effects of regular redox cycling on the biogeochemistry of Fe minerals in acid sulfate soils.  The thesis begins with characterisation of synthetic and natural jarosite mineral composition and reactivity. Spectroscopic techniques (Raman spectroscopy, M\u00f6ssbauer spectroscopy and Energy-dispersive X-ray spectrometry) and X-ray diffraction (XRD) were used to assess the element substitution of mineral samples from two jarosite-alunite synthetic solid solution series. The same characterisation techniques were then applied to a sample of jarosite from an acid sulfate soil in Thailand has a natural Al-for-Fe substitution. The mineral characterisation was followed by a transformation experiment in a mixed-suspension system, similar to experimental designs that have been previously used to study mineral transformation processes. The experiment followed the transformation of the natural jarosite sample from an acid sulfate soil in Thailand and three jarosite samples with variable amounts of Al substitution. The reaction solution mimicked the pH (circumneutral) and Fe(II) content (up to 1:1 ratio of Fe(II) in solution to Fe(III) in solids) of flooded acid sulfate soils. Furthermore, using a 57Fe tracer, the simultaneous transformation processes that explained the distribution of mineral products could be resolved from one another. The transformation experiment revealed the relative reactivity of the minerals in the presence of Fe(II), and created a baseline that could be used to compare traditional mixed-suspension experiments with transformations in complex media such as soil.   To advance mineral transformation experiments towards studies in which transformation processes may be followed within a soil matrix, several novel techniques were developed. In a first step, ferrihydrite was incubated for up to twelve weeks in microcosms, each containing 300 g of 5 mM CaCl2 solution and 250 g of one of five paddy soils. The ferrihydrite was buried in the soil within a mesh bag (polyethel terephthalate, 51 \u03bcm pores, 30 mm x 12 mm x 3 mm) that allowed free contact between the synthetic minerals and the pore water, but separated the minerals from direct contact with the soil matrix. The mineral products of the transformation were identified and quantified by Rietveld fitting of XRD patterns. Further, the spatial arrangements of the ferrihydrite and transformation products were measured after two weeks by Raman spectroscopy, which could be used to assess the effects of pore water chemistry and diffusion processes on mineral transformation in the mesh bags. The second step involved measuring jarosite and Al-substituted jarosite transformation in flooded topsoil and subsoils from a rice paddy located on the Bangkok Plain in Central Thailand using an adaptation of the mesh bag method. To test the effect of pore water on the transformation of jarosite in soil, mesh bags were filled with synthetic jarosite and aluminium-jarosite and incubated in topsoils and subsoils, both in laboratory mesocosms and directly in the field. Then, the effect of the soil matrix was tested by completing a parallel experiment using mesh bags containing soil that was pre-enriched with synthetic 57Fe-labelled jarosite and aluminium-substituted jarosite. To facilitate the deployment and collection of small mesh bags in large soil volumes, the mesh bags were inserted into soils using custom-designed 3D-printed sample holders. At three timepoints within twelve weeks, one set of mesh bags were removed from the soil. Transformation products were identified and quantified in the pure jarosite and aluminium-jarosite mesh bags using Rietveld fitting of XRD patterns, while the fate of the 57Fe in enriched soil mesh bags was traced using 57Fe M\u00f6ssbauer spectroscopy.   Performing experiments in increasingly complex media provides an insight into the effect of experimental design on the observation of Fe mineral transformations and provides new information regarding the transformation rates and pathways of jarosite and ferrihydrite within full complexity of soil media. Indeed, this thesis demonstrates that the complex chemistry, biological activity, and physical arrangement of components in the soil have strong effects on the rate and products of jarosite and ferrihydrite transformation processes. The transformation of jarosite and Al-substituted jarosite in mixed-suspension experiments presented in this thesis, in agreement with previous mixed-suspension experiments on both jarosite and ferrihydrite, occurred within a matter of hours. By contrast, the rate of ferrihydrite, jarosite and Al-jarosite transformation in soil pore and in direct contact with the soil matrix occurred over the course of several weeks or months. In the ferrihydrite mesh bags, slow ferrihydrite transformation kinetics on the outer rim of the mesh bag, and deep in the core of the mesh bag, indicated that the sorption of chemical components of soil pore water and diffusion limitations of Fe(II) in pore water could be reasons for the slower rates of transformation in soil. In addition, both Al-for-Fe substitution and Fe(II) concentration in solution were important factors that altered the rate of mineral transformation.  The different incubation conditions for jarosite and Al-jarosite also altered the products of the transformation. Whereas the hydrolysis of jarosite in the absence of Fe(II) resulted primarily in the formation of ferrihydrite, jarosite transformation in the presence of Fe(II) led to ferrihydrite, goethite and lepidocrocite formation. The Fe oxyhydroxide products were consistent with Fe(II)-catalysed transformation, and Fe(II)-catalysed recrystallisation of jarosite may have occurred concurrently. Aluminium-for-iron substitution hindered the formation of lepidocrocite formation in favour of ferrihydrite and goethite. Similar product phases occurred when jarosite and Al-jarosite were reacted with pore water from acid sulfate soils, indicating that similar transformation pathways may define the mineral products of jarosite transformations when the jarosite occurs as accumulations of pure mineral in soil. However, non- or poorly crystalline phases predominated in the transformation products when jarosite or Al-jarosite were incubated in direct contact with the soil matrix, indicating that the transformation of jarosite under these circumstances was governed by different pathways and processes.  The new insights into the transformation of ferrihydrite, jarosite and Al-jarosite in acid sulfate soils demonstrate that phases previously considered meta-stable may participate in the biogeochemistry of soil over period of several months. In the context of rice cultivation, the transformation processes may affect the biogeochemistry of the soils throughout the growing season. The formation of poorly crystalline minerals following the transformation in flooded soils may have positive consequences on the sequestration of other trace and major elements that were associated with the ferrihydrite, jarosite or Al-jarosite prior to the transformation. However, the stabilisation of reduced Fe in the soil matrix may have the opposite effect, promoting the mobility of other ions in solution. The methods used to incubate jarosite and ferrihydrite in soils are easily adaptable to new experimental questions involving the behaviour of Fe-bearing minerals in soil. Therefore, the findings open up a new class of experiments within environmental mineralogy and biogeochemistry, that can help to uncover the processes that occur in the environment and explain the natural variation in the composition of Fe phases in soil.", "keywords": ["jarosite", "iron biogeochemistry", "soil chemistry", "acid sulfate soil", "laboratory study", "ferrihydrite", "soil", "soil incubation", "redox chemistry", "goethite", "iron minerals", "2. Zero hunger", "soil biogeochemistry", "info:eu-repo/classification/ddc/550", "M\u00f6ssbauer spectroscopy", "rice paddy soil", "15. Life on land", "6. Clean water", "Earth sciences", "lepidocrocite", "field study", "13. Climate action", "Raman spectroscopy", "iron oxyhydroxide", "mineral transformation", "iron minerals; mineral transformation; soil; soil chemistry; soil mineralogy; soil biogeochemistry; redox chemistry; iron biogeochemistry; acid sulfate soil; rice paddy soil; jarosite; ferrihydrite; goethite; lepidocrocite; iron oxyhydroxide; M\u00f6ssbauer spectroscopy; Raman spectroscopy; field study; laboratory study; soil incubation", "soil mineralogy"], "contacts": [{"organization": "Grigg, Andrew R.C.", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/20.500.11850/648810"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Thesis/Dissertation", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "20.500.11850/648810", "name": "item", "description": "20.500.11850/648810", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/20.500.11850/648810"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-01-01T00:00:00Z"}}, {"id": "20.500.11850/693515", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:22:37Z", "type": "Journal Article", "created": "2024-07-27", "title": "Stability and transformation of jarosite and Al-substituted jarosite in an acid sulfate paddy soil under laboratory and field conditions", "description": "Open AccessGeochimica et Cosmochimica Acta, 382", "keywords": ["Redox", "2. Zero hunger", "Soil incubation", "Mossbauer spectroscopy", "Iron minerals; Mossbauer spectroscopy; Redox; Rice paddy; Soil incubation", "Rice paddy", "15. Life on land", "Iron minerals", "6. Clean water"]}, "links": [{"href": "https://doi.org/20.500.11850/693515"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geochimica%20et%20Cosmochimica%20Acta", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "20.500.11850/693515", "name": "item", "description": "20.500.11850/693515", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/20.500.11850/693515"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-01T00:00:00Z"}}, {"id": "2262/92874", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:22:50Z", "type": "Journal Article", "created": "2019-11-09", "title": "Bioinspired electro-permeable glycans on carbon: Fouling control for sensing in complex matrices", "description": "Abstract   The effect of glycan adlayers on the electrochemical response of glassy carbon electrodes was studied using standard redox probes and complex aqueous matrices. Aryldiazonium cations of aryl-lactoside precursors were used to modify glassy carbon via spontaneous and electrochemically assisted covalent grafting. Contact angle and fluorescence binding using Peanut Agglutinin (PNA) as a diagnostic lectin indicate that electrografting results in adlayers with greater glycan surface density than those obtained via spontaneous reaction. X-ray photoelectron spectroscopy with a fluorinated analog confirmed that electrografting results in multilayers of cross-linked aryl-lactosides. Adsorption studies with Bovine Serum Albumin (BSA) show that aryl-lactoside adlayers minimize unspecific protein adsorption. However, no significant differences were detected between spontaneous and electrografted layers in their ability to resist protein fouling despite their differences in coverage. Voltammetry studies show that spontaneous grafting has minimal effects on the response of standard redox probes in solution, whereas electrografting results in additional charge transfer impedance arising from increased electrode passivation. Bare and lactoside-modified carbon electrodes were tested for the detection of caffeine before and after prolonged exposure to coffee solutions. Spontaneous grafting was found to result in optimal properties by imparting antifouling performance in these complex matrices while preserving fast interfacial charge transfer.", "keywords": ["Nanoscience & Materials", "GLASSY-CARBON", "GLASSY-CARBON ELECTRODES", "02 engineering and technology", "540", "01 natural sciences", "Bovine Serum Albumin (BSA)", "0104 chemical sciences", "Aqueous matrices", "CARBON", "Glassy carbon", "Coffee solutions", "Glycan adlayers", "0210 nano-technology", "Peanut Agglutinin (PNA)"]}, "links": [{"href": "https://doi.org/2262/92874"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Carbon", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2262/92874", "name": "item", "description": "2262/92874", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2262/92874"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-03-01T00:00:00Z"}}, {"id": "2262/93882", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:22:50Z", "type": "Dataset", "title": "Dataset associated to Bioinspired electro-permeable glycans on carbon: Fouling control for sensing in complex matrices", "description": "This dataset is associated to the publication 'Bioinspired electro-permeable glycans on carbon: Fouling control for sensing in complex matrices' performed in Trinity College, Dublin, Ireland. The dataset contains raw data associated to the measures contained in the article: X ray photoelectron spectroscopy, Atomic force microscopy, cyclic voltammetries. This publication has emanated from research conducted with the financial support of Science Foundation Ireland (SFI) grant No. 13/CDA/2213. AM and JAB gratefully acknowledge support from the School of Chemistry and the Irish Research Council Grant No. GOIPG/2014/399, respectively. EW is grateful for support by the Undergraduate Research Bursary Program of the Royal Society of Chemistry and Nuffield Foundation. Use of the XPS of Prof. I. V. Shvets and C. McGuinness provided under SFI Equipment Infrastructure funds. This project has received funding from the European Union\u2019s Horizon 2020 research and innovation programme under the Marie Sk\u0142odowska-Curie grant agreement No. 799175 (HiBriCarbon). The results of this publication reflect only the authors\u2019 view and the Commission is not responsible for any use that may be made of the information it contains.", "keywords": ["Complex matrices", "Nanoscience & Materials", "Glycan adlayers"], "contacts": [{"organization": "Iannaci, Alessandro, Myles, Adam, Behan A., James, Whelan, \u00c9adaoin, Scanlan M., Eoin, Colavita E., Paula,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/2262/93882"}, {"rel": "self", "type": "application/geo+json", "title": "2262/93882", "name": "item", "description": "2262/93882", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2262/93882"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-11-09T00:00:00Z"}}, {"id": "2318/1963515", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:22:52Z", "type": "Journal Article", "created": "2024-02-23", "title": "Organic carbon stabilization in temperate paddy fields and adjacent semi-natural forests along a soil age gradient", "description": "Rice paddy soils have high organic carbon (OC) storage potential, but predicting OC stocks in these soils is difficult due to the complex OC stabilization mechanisms under fluctuating redox conditions. Especially in temperate climates, these mechanisms remain understudied and comparisons to OC stocks under natural vegetation are scarce. Semi-natural forests could have similar or higher OC inputs than rice paddies, but in the latter mineralization under anoxic conditions and interactions between OC and redox-sensitive minerals (in particular Fe oxyhydroxides, hereafter referred to as Fe oxides) could promote OC stabilization. Moreover, management-induced soil redox cycling in rice paddies can interact with pre-existing pedogenetic differences of soils having different degrees of evolution. To disentangle these drivers of soil OC stocks, we focused on a soil age gradient in Northern Italy with a long (30\u00a0+\u00a0years) history of rice cultivation and remnant semi-natural forests. Irrespective of soil age, soils under semi-natural forest and paddy land-use showed comparable OC stocks. While, in topsoil, stocks of crystalline Fe and short-ranged Fe and Al oxides did not differ between land-uses, under paddy management more OC was found in the mineral-associated fraction. This hints to a stronger redox-driven OC stabilization in the paddy topsoil compared to semi-natural forest soils that might compensate for the presumed lower OC inputs under rice cropping. Despite the higher clay contents over the whole profile and more crystalline pedogenetic Fe stocks in the topsoil in older soils, OC stocks were higher in the younger soils, in particular in the 50\u201370\u00a0cm layer, where short-range ordered pedogenetic oxides were also more abundant. These patterns might be explained by differences in hydrological flows responsible for the translocation of Fe and dissolved OC to the subsoil, preferentially in the younger, coarse-textured soils. Taken together, these results indicate the importance of the complex interplay between redox-cycling affected by paddy-management and soil-age related hydrological properties.", "keywords": ["2. Zero hunger", "Science", "Q", "Soil Science", "Soil carbon storage", "04 agricultural and veterinary sciences", "15. Life on land", "Markvetenskap", "01 natural sciences", "Particulate organic carbon", "Fe oxyhydroxides", "0401 agriculture", " forestry", " and fisheries", "Rice paddy soil", "Mineral associated organic carbon", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://iris.unito.it/bitstream/2318/1963515/1/Geoderma_443_116825.pdf"}, {"href": "https://doi.org/2318/1963515"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoderma", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2318/1963515", "name": "item", "description": "2318/1963515", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2318/1963515"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-03-01T00:00:00Z"}}, {"id": "3000130041", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:23:15Z", "type": "Journal Article", "created": "2020-01-10", "title": "SHui, an EU-Chinese cooperative project to optimize soil and water management in agricultural areas in the XXI century", "description": "Open AccessThis work has been supported by Project SHui which is co-funded by the European Union Project GA 773903 and the Chinese MOST. This work has been supported by P12-AGR-0931 (Andalusian Government), RTA2014-00063- C04-03 (Spanish government), SHui (European Commission Grant Agreement number: 773903) and EU\u2012FEDER funds", "keywords": ["Yield", "550", "EROSION", "FLOW", "Cropping", "SIMULATE YIELD RESPONSE", "Soil Science", "Environmental Sciences & Ecology", "RICE YIELDS", "01 natural sciences", "630", "12. Responsible consumption", "4104 Environmental management", "4105 Pollution and contamination", "DRYING IRRIGATION", "11. Sustainability", "FAO CROP MODEL", "0105 earth and related environmental sciences", "2. Zero hunger", "Science & Technology", "1. No poverty", "Agriculture", "04 agricultural and veterinary sciences", "15. Life on land", "Engineering (General). Civil engineering (General)", "6. Clean water", "4106 Soil sciences", "Cooperation", "Sustainability", "13. Climate action", "Physical Sciences", "Water Resources", "0401 agriculture", " forestry", " and fisheries", "TA1-2040", "Life Sciences & Biomedicine", "Environmental Sciences"]}, "links": [{"href": "https://doi.org/3000130041"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/International%20Soil%20and%20Water%20Conservation%20Research", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "3000130041", "name": "item", "description": "3000130041", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3000130041"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-03-01T00:00:00Z"}}, {"id": "3092600768", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-08-24T16:23:19Z", "type": "Journal Article", "created": "2020-10-05", "title": "Qualifications of Rice Growth Indicators Optimized at Different Growth Stages Using Unmanned Aerial Vehicle Digital Imagery", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>The accurate estimation of the key growth indicators of rice is conducive to rice production, and the rapid monitoring of these indicators can be achieved through remote sensing using the commercial RGB cameras of unmanned aerial vehicles (UAVs). However, the method of using UAV RGB images lacks an optimized model to achieve accurate qualifications of rice growth indicators. In this study, we established a correlation between the multi-stage vegetation indices (VIs) extracted from UAV imagery and the leaf dry biomass, leaf area index, and leaf total nitrogen for each growth stage of rice. Then, we used the optimal VI (OVI) method and object-oriented segmentation (OS) method to remove the noncanopy area of the image to improve the estimation accuracy. We selected the OVI and the models with the best correlation for each growth stage to establish a simple estimation model database. The results showed that the OVI and OS methods to remove the noncanopy area can improve the correlation between the key growth indicators and VI of rice. At the tillering stage and early jointing stage, the correlations between leaf dry biomass (LDB) and the Green Leaf Index (GLI) and Red Green Ratio Index (RGRI) were 0.829 and 0.881, respectively; at the early jointing stage and late jointing stage, the coefficient of determination (R2) between the Leaf Area Index (LAI) and Modified Green Red Vegetation Index (MGRVI) was 0.803 and 0.875, respectively; at the early stage and the filling stage, the correlations between the leaf total nitrogen (LTN) and UAV vegetation index and the Excess Red Vegetation Index (ExR) were 0.861 and 0.931, respectively. By using the simple estimation model database established using the UAV-based VI and the measured indicators at different growth stages, the rice growth indicators can be estimated for each stage. The proposed estimation model database for monitoring rice at the different growth stages is helpful for improving the estimation accuracy of the key rice growth indicators and accurately managing rice production.</p></article>", "keywords": ["2. Zero hunger", "object-oriented segmentation method", "optimal index method", "rice", "Science", "Q", "rice; growth indicators; multi-stage vegetation index; unmanned aerial vehicle; optimal index method; object-oriented segmentation method; estimation accuracy", "0211 other engineering and technologies", "04 agricultural and veterinary sciences", "02 engineering and technology", "multi-stage vegetation index", "15. Life on land", "estimation accuracy", "growth indicators", "13. Climate action", "unmanned aerial vehicle", "0401 agriculture", " forestry", " and fisheries"], "contacts": [{"organization": "Zhengchao Qiu, Haitao Xiang, Fei Ma, Changwen Du,", "roles": ["creator"]}]}, "links": [{"href": "http://www.mdpi.com/2072-4292/12/19/3228/pdf"}, {"href": "https://www.mdpi.com/2072-4292/12/19/3228/pdf"}, {"href": "https://doi.org/3092600768"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Remote%20Sensing", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "3092600768", "name": "item", "description": "3092600768", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3092600768"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-10-03T00:00:00Z"}}, {"id": "3215526408", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:23:30Z", "type": "Journal Article", "created": "2021-11-30", "title": "Grain Yield Estimation in Rice Breeding Using Phenological Data and Vegetation Indices Derived from UAV Images", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>The accurate estimation of grain yield in rice breeding is crucial for breeders to screen and select qualified cultivars. In this study, a low-cost unmanned aerial vehicle (UAV) platform mounted with an RGB camera was carried out to capture high-spatial resolution images of rice canopy in rice breeding. The random forest (RF) regression techniques were used to establish yield models by using (1) only color vegetation indices (VIs), (2) only phenological data, and (3) fusion of VIs and phenological data as inputs, respectively. Then, the performances of RF models were compared with the manual observation and CERES-Rice model. The results indicated that the RF model using VIs only performed poorly for estimating yield; the optimized RF model that combined the use of phenological data and color VIs performed much better, which demonstrated that the phenological data significantly improved the model performance. Furthermore, the yield estimation accuracy of 21 rice cultivars that were continuously planted over three years in the optimal RF model had no significant difference (p &gt; 0.05) with that of the CERES-Rice model. These findings demonstrate that the RF model, by combining phenological data and color Vis, is a potential and cost-effective way to estimate yield in rice breeding.</p></article>", "keywords": ["2. Zero hunger", "0106 biological sciences", "S", "UAV", "CERES-Rice", "Agriculture", "04 agricultural and veterinary sciences", "15. Life on land", "yield", "01 natural sciences", "rice breeding", "UAV; rice breeding; yield; CERES-Rice; RF; vegetation indices", "vegetation indices", "RF", "0401 agriculture", " forestry", " and fisheries"], "contacts": [{"organization": "Haixiao Ge, Fei Ma, Zhenwang Li, Changwen Du,", "roles": ["creator"]}]}, "links": [{"href": "http://www.mdpi.com/2073-4395/11/12/2439/pdf"}, {"href": "https://doi.org/3215526408"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agronomy", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "3215526408", "name": "item", "description": "3215526408", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3215526408"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-11-29T00:00:00Z"}}, {"id": "3198159648", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:23:28Z", "type": "Journal Article", "created": "2021-08-31", "title": "Estimation of nitrogen nutrition index in rice from UAV RGB images coupled with machine learning algorithms", "description": "Rapid and accurate estimation of rice Nitrogen Nutrition Index (NNI) is beneficial for management of nitrogen application in rice production. Traditional estimation methods required manual actual measurement data in the field, which was time-consuming and cost-expensive, and RGB images from unmanned aerial vehicle (UAV) provided an alternative option for nitrogen nutrition index (NNI) monitoring. In this study, RGB images from unmanned aerial vehicle (UAV) were obtained from each growth period of rice, and six machine learning (ML) algorithms, i.e., adaptive boosting (AB), artificial neural network (ANN), K-nearest neighbor (KNN), partial least squares (PLSR), random forest (RF) and support vector machine (SVM), were used to extract target information for estimating NNI as well as vegetation index (VI). Results showed that most UAV VIs were significantly correlated with rice NNI at the key growing periods; the estimation results of rice NNI using six ML algorithms showed that the RF algorithms performed the best at each growth period with the determination coefficient (R<sup>2</sup> ) ranged from 0.88 to 0.96 and room mean square error (RMSE) ranged from 0.03 to 0.07, in which the estimation of NNI was the best in filling period and the early jointing stage. Rice NNI at the early jointing stage was significantly correlated with soil available nitrogen (AN) with the R<sup>2 </sup>of 0.84 in Pukou and 0.72 in Luhe, respectively, and rice NNI was significantly correlated with the yield with the R2 of more than 0.7 in Pukou at the whole period and more than 0.7 in Luhe from late jointing to maturity stage. Therefore, the combination of RGB images from UAV and ML algorithms was a scalable, simple and inexpensive method for rapid qualification of rice NNI, which effectively improved nitrogen use efficiency and provided guidance for precision fertilization in rice production.", "keywords": ["2. Zero hunger", "Machine learning", "0211 other engineering and technologies", "0401 agriculture", " forestry", " and fisheries", "Precision fertilization", "Rice", "Nitrogen nutrition index", "Unmanned aerial vehicle", "04 agricultural and veterinary sciences", "02 engineering and technology", "6. Clean water"], "contacts": [{"organization": "Zhengchao Qiu, Ma, Fei, Zhenwang Li, Xuebin Xu, Haixiao Ge, Changwen Du,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/3198159648"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Computers%20and%20Electronics%20in%20Agriculture", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "3198159648", "name": "item", "description": "3198159648", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3198159648"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-10-01T00:00:00Z"}}, {"id": "3215193907", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:23:30Z", "type": "Journal Article", "created": "2021-12-01", "title": "Global Sensitivity Analysis for CERES-Rice Model under Different Cultivars and Specific-Stage Variations of Climate Parameters", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Global sensitivity analysis (SA) has become an efficient way to identify the most influential parameters on model results. However, the effects of cultivar variation and specific-stage variations of climate conditions on model outputs still remain unclear. In this study, 30 indica hybrid rice cultivars were simulated in the CERES-Rice model; then the Sobol\u2019 method was used to perform a global SA on 16 investigated parameters for three model outputs (anthesis day, maturity day, and yield). In addition, we also compared the differences in the sensitivity results under four specific-stage variations (vegetative phase, panicle-formation phase, ripening phase, and the whole growth season) of climate conditions. The results indicated that (1) parameter Tavg, G4, and P2O are the most influential parameters for all model outputs across cultivars during the whole growth season; (2) under the vegetative-phase variation of climate parameters; the variability of model outputs is mainly controlled by parameter P2O and Tavg; (3) under the panicle-formation-phase or ripening-phase variation of climate parameters, parameter P2O was the dominant variable for all model outputs; (4) parameter PORM had a considerable effect (the total sensitivity index, STi; STi&gt;0.05) on yield regardless of the various specific-stage variations of the climate parameters. Findings obtained from this study will contribute to understanding the comprehensive effects of crop parameters on model outputs under different cultivars and specific-stage variations of climate conditions.</p></article>", "keywords": ["2. 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