{"type": "FeatureCollection", "features": [{"id": "10.1016/j.agee.2020.107082", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:15:33Z", "type": "Journal Article", "created": "2020-07-23", "title": "Crop type and within-field location as sources of intraspecific variations in the phenology and the production of floral and fruit resources by weeds", "description": "Abstract   In arable farming, weeds provide important floral and seed resources that have the potential to support the provision of ecosystem services such as pollination or pest control. Estimating the production of these weed resources in the landscape is however not trivial as large-scale surveys of weed communities are usually conducted once in the season with a timing that may not coincide with the flowering and fruiting stages of all weed species. More, intraspecific variation in the mortality and phenology of individual weed species may arise from differences in the quality of the growing environment of each plant. In this study, we monitored the phenology of 30 common weed species in the field core and the field edge of 64 commercial fields grown with 6 crop types. Our hypothesis was that the production of resources by an individual plant would be modulated by its within-field location and by the crop type where it grows. We quantified floral (proportion, starting date and duration of flowering, dry biomass at flowering as a proxy for the amount of flowers) and seed resource production (proportion and starting date of fruiting). For most species, flowering and fruiting success were higher in field edges than in field cores and were lower in cereal crops than in other crops. Weeds flowered and fruited earlier and the flowering period was longer in field edges, except those of cereal crops. Dry biomass at flowering varied with field location either way, depending on the weed species, but tended to be lower in cereal crops than in other crops. This important intraspecific phenological variability in the production of seed and/or flower or resources should be considered when evaluating the contribution of weed communities to ecosystem services. It also suggests that within an agricultural landscape, the amount, timing and duration of provision of services by weeds could be enhanced by maintaining sufficient lengths of field edges and by growing a diversity of crop types.", "keywords": ["580", "[SDE] Environmental Sciences", "0106 biological sciences", "2. Zero hunger", "pollination", "farming management", "edge", "04 agricultural and veterinary sciences", "15. Life on land", "field", "phenology", "01 natural sciences", "630", "flowering success", "[SDE]Environmental Sciences", "0401 agriculture", " forestry", " and fisheries", "pest control"]}, "links": [{"href": "https://doi.org/10.1016/j.agee.2020.107082"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agriculture%2C%20Ecosystems%20%26amp%3B%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.agee.2020.107082", "name": "item", "description": "10.1016/j.agee.2020.107082", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.agee.2020.107082"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-10-01T00:00:00Z"}}, {"id": "10.1007/s11104-005-8770-z", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:14:59Z", "type": "Journal Article", "created": "2005-11-29", "title": "Does The Gradualness Of Leaf Shedding Govern Nutrient Resorption From Senescing Leaves In Mediterranean Woody Plants?", "description": "Open AccessPeer reviewed", "keywords": ["2. Zero hunger", "0106 biological sciences", "Resorption proficiency", "Nutrient retranslocation", "Resorption efficiency", "Potassium", "Leaf shedding phenology", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "Nutrient status", "01 natural sciences"]}, "links": [{"href": "https://doi.org/10.1007/s11104-005-8770-z"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Plant%20and%20Soil", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s11104-005-8770-z", "name": "item", "description": "10.1007/s11104-005-8770-z", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s11104-005-8770-z"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2005-12-01T00:00:00Z"}}, {"id": "10.1007/s11104-024-06756-x", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:15:10Z", "type": "Journal Article", "created": "2024-06-01", "title": "CH4 transport in wetland plants under controlled environmental conditions \u2013 separating the impacts of phenology from environmental variables", "description": "Abstract                        Background and Aims             <p>Methane (CH4) fluxes at peatland plant surfaces are net results of transport of soil-produced CH4 and within-plant CH4 production and consumption, yet factors and processes controlling these fluxes remain unclear. We aimed to assess the effects of seasonality, environmental variables, and CH4 cycling microbes on CH4 fluxes from characteristic fen species.</p>                                   Methods             <p>Four species (Carex rostrata, Menyanthes trifoliata, Betula nana, Salix lapponum) were selected, and their CH4 fluxes determined in climate-controlled environments with three mesocosms per growing season per species. Microbial genes for CH4 cycling were analysed to check the potential for within-plant CH4 production and oxidation. Two extra experiments were conducted: removal of C. rostrata leaves to identify how leaves constrain CH4 transport, and a labelling experiment with S. lapponum to distinguish between plant-produced and soil-produced CH4 in the plant flux.</p>                                   Results             <p>All species showed seasonal variability in CH4 fluxes. Higher porewater CH4 concentration increased fluxes from C. rostrata and M. trifoliata, decreased fluxes from S. lapponum, and did not affect fluxes from B. nana. Air temperature only and negatively affected CH4 flux from C. rostrata. Light level did not impact CH4 fluxes. Both methanogens and methanotrophs were detected in shoots of S. lapponum and M. trifoliata, methanotrophs in B. nana, and neither in C. rostrata.</p>                                   Conclusion             <p>Our study demonstrates that the seasonal phase of the plants regulates the CH4 fluxes they mediate across species. The detection of methanogens and methanotrophs in herbs and shrubs suggests that microbial processes may contribute to their CH4 fluxes.</p>", "keywords": ["0301 basic medicine", "570", "0303 health sciences", "metanotrofit", "varvut", "Herbs", "11831 Plant biology", "metaani", "Environmental sciences", "Controlled environments", "Microbes", "03 medical and health sciences", "Phenology", "suot", "Plant-mediated CH fluxes", "suokasvillisuus", "Shrubs", "metanogeenit", "sarat"]}, "links": [{"href": "https://doi.org/10.1007/s11104-024-06756-x"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Plant%20and%20Soil", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s11104-024-06756-x", "name": "item", "description": "10.1007/s11104-024-06756-x", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s11104-024-06756-x"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-06-01T00:00:00Z"}}, {"id": "10.1016/j.agrformet.2020.108031", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:15:36Z", "type": "Journal Article", "created": "2020-05-29", "title": "Inter-individual variability in spring phenology of temperate deciduous trees depends on species, tree size and previous year autumn phenology", "description": "We explored the inter-individual variability in bud-burst and its potential drivers, in homogeneous mature stands of temperate deciduous trees. Phenological observations of leaves and wood formation were performed weekly from summer 2017 to summer 2018 for pedunculate oak, European beech and silver birch in Belgium. The variability of bud-burst was correlated to previous' year autumn phenology (i.e. the onset of leaf senescence and the cessation of wood formation) and tree size but with important differences among species. In fact, variability of bud-burst was primarily related to onset of leaf senescence, cessation of wood formation and tree height for oak, beech and birch, respectively. The inter-individual variability of onset of leaf senescence was not related to the tree characteristics considered and was much larger than the inter-individual variability in bud-burst. Multi-species multivariate models could explain up to 66% of the bud-burst variability. These findings represent an important advance in our fundamental understanding and modelling of phenology and tree functioning of deciduous tree species.", "keywords": ["Agriculture and Food Sciences", "0106 biological sciences", "Atmospheric Science", "polno olistanje", "Broadleaved forest", "Silver birch", "Edellauvskog", "coloration", "01 natural sciences", "fenologija", "navadna bukev", "Pedunculate oak", "FAGUS-SYLVATICA", "PHLOEM", "Global and Planetary Change", "LEAF PHENOLOGY", "CLIMATE-CHANGE", "VDP::\u00d8kologi: 488", "Physics", "Forestry", "VDP::Ecology: 488", "04 agricultural and veterinary sciences", "dob", "navadna breza", "Chemistry", "Phenology", "info:eu-repo/classification/udc/630*811", "rumenenje listov", "XYLEM", "MODELS", "Article", "leaf unfolding", "Fenologi", "Coloration", "nastanek lesa", "Biology", "Wood formation", "kambij", "Leaf unfolding", "RADIAL GROWTH", "15. Life on land", "listavci", "European beech", "[SDE.BE] Environmental Sciences/Biodiversity and Ecology", "SENESCENCE", "13. Climate action", "wood formation", "0401 agriculture", " forestry", " and fisheries", "[SDE.BE]Environmental Sciences/Biodiversity and Ecology", "Agronomy and Crop Science"]}, "links": [{"href": "https://doi.org/10.1016/j.agrformet.2020.108031"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agricultural%20and%20Forest%20Meteorology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.agrformet.2020.108031", "name": "item", "description": "10.1016/j.agrformet.2020.108031", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.agrformet.2020.108031"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-08-01T00:00:00Z"}}, {"id": "10.1016/j.eja.2022.126723", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:16:03Z", "type": "Journal Article", "created": "2022-09-07", "title": "Field Evaluation of Selected Autochthonous Herbaceous Species for Cover Crops in Mediterranean Woody Crops", "description": "Open AccessPeer reviewed", "keywords": ["0106 biological sciences", "2. Zero hunger", "Phenology", "Ground cover", "Aerial biomass", "0401 agriculture", " forestry", " and fisheries", "Key plant traits", "04 agricultural and veterinary sciences", "Fine root", "15. Life on land", "Cover crop mixtures", "01 natural sciences"], "contacts": [{"organization": "Soriano, Mar\u00eda-Auxiliadora, Cabezas, Jos\u00e9 Manuel, G\u00f3mez, Jos\u00e9 Alfonso,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1016/j.eja.2022.126723"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/SSRN%20Electronic%20Journal", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.eja.2022.126723", "name": "item", "description": "10.1016/j.eja.2022.126723", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.eja.2022.126723"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-01-01T00:00:00Z"}}, {"id": "10.1016/j.scitotenv.2021.152880", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:16:53Z", "type": "Journal Article", "created": "2022-01-06", "title": "Exploring the potential role of environmental and multi-source satellite data in crop yield prediction across Northeast China", "description": "Open AccessLe d\u00e9veloppement d'un syst\u00e8me pr\u00e9cis de pr\u00e9diction du rendement des cultures \u00e0 grande \u00e9chelle est d'une importance primordiale pour la gestion des ressources agricoles et la s\u00e9curit\u00e9 alimentaire mondiale. L'observation de la Terre fournit une source unique d'informations pour surveiller les cultures \u00e0 partir d'une diversit\u00e9 de gammes spectrales. Cependant, l'utilisation int\u00e9gr\u00e9e de ces donn\u00e9es et de leurs valeurs dans la pr\u00e9diction du rendement des cultures est encore peu \u00e9tudi\u00e9e. Ici, nous avons propos\u00e9 la combinaison de donn\u00e9es environnementales (climat, sol, g\u00e9ographie et topographie) avec de multiples donn\u00e9es satellitaires (indices de v\u00e9g\u00e9tation optiques, fluorescence induite par le soleil (SIF), temp\u00e9rature de surface du sol (LST) et profondeur optique de la v\u00e9g\u00e9tation micro-ondes (VOD)) dans le cadre pour estimer le rendement des cultures de ma\u00efs, de riz et de soja dans le nord-est de la Chine, et leur valeur unique et leur influence relative sur la pr\u00e9diction du rendement ont \u00e9t\u00e9 \u00e9valu\u00e9es. Deux m\u00e9thodes de r\u00e9gression lin\u00e9aire, trois m\u00e9thodes d'apprentissage automatique (ML) et un mod\u00e8le d'ensemble ML ont \u00e9t\u00e9 adopt\u00e9s pour construire des mod\u00e8les de pr\u00e9diction de rendement. Les r\u00e9sultats ont montr\u00e9 que les m\u00e9thodes individuelles de ML surpassaient les m\u00e9thodes de r\u00e9gression lin\u00e9aire, le mod\u00e8le d'ensemble de ML a encore am\u00e9lior\u00e9 les mod\u00e8les de ML uniques. De plus, les mod\u00e8les avec plus d'intrants ont obtenu de meilleures performances, la combinaison de donn\u00e9es satellitaires avec des donn\u00e9es environnementales, qui expliquaient respectivement 72\u00a0%, 69\u00a0% et 57\u00a0% de la variabilit\u00e9 du rendement du ma\u00efs, du riz et du soja, a d\u00e9montr\u00e9 des performances de pr\u00e9diction du rendement sup\u00e9rieures \u00e0 celles des intrants individuels. Alors que les donn\u00e9es satellitaires ont contribu\u00e9 \u00e0 la pr\u00e9diction du rendement des cultures principalement au d\u00e9but de la pointe de la saison de croissance, les donn\u00e9es climatiques ont fourni des informations suppl\u00e9mentaires principalement \u00e0 la pointe de la fin de la saison. Nous avons \u00e9galement constat\u00e9 que l'utilisation combin\u00e9e de l'IVE, du LST et du SIF a am\u00e9lior\u00e9 la pr\u00e9cision du mod\u00e8le par rapport au mod\u00e8le d'IVE de r\u00e9f\u00e9rence. Cependant, les indices de v\u00e9g\u00e9tation bas\u00e9s sur l'optique partageaient des informations similaires et ne fournissaient pas beaucoup d'informations suppl\u00e9mentaires au-del\u00e0 de l'IVE. Les pr\u00e9visions de rendement en cours de saison ont montr\u00e9 que les rendements des cultures peuvent \u00eatre pr\u00e9vus de mani\u00e8re satisfaisante deux \u00e0 trois mois avant la r\u00e9colte. La g\u00e9ographie, la topographie, la VOD, l'IVE, les param\u00e8tres hydrauliques du sol et les param\u00e8tres nutritifs sont plus importants pour la pr\u00e9diction du rendement des cultures.", "keywords": ["Atmospheric sciences", "Climate", "Multi-source satellite data", "Normalized Difference Vegetation Index", "Engineering", "Pathology", "Climate change", "Urban Heat Islands and Mitigation Strategies", "Linear regression", "2. Zero hunger", "Global and Planetary Change", "Vegetation Monitoring", "Ecology", "Geography", "Statistics", "Agriculture", "Geology", "Remote Sensing in Vegetation Monitoring and Phenology", "04 agricultural and veterinary sciences", "Remote sensing", "Aerospace engineering", "Archaeology", "Physical Sciences", "Metallurgy", "Medicine", "Seasons", "Global Vegetation Models", "Biomass Estimation", "Regression analysis", "Vegetation (pathology)", "Crops", " Agricultural", "Environmental Engineering", "Environmental data", "Yield (engineering)", "Zea mays", "Environmental science", "Machine learning", "FOS: Mathematics", "Crop yield", "Biology", "Global Forest Drought Response and Climate Change", "FOS: Environmental engineering", "Predictive modelling", "Food security", "FOS: Earth and related environmental sciences", "15. Life on land", "Agronomy", "Materials science", "Yield prediction", "Satellite", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Growing season", "0401 agriculture", " forestry", " and fisheries", "Mathematics"], "contacts": [{"organization": "Zhenwang Li, Lei Ding, Donghui Xu,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1016/j.scitotenv.2021.152880"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Science%20of%20The%20Total%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.scitotenv.2021.152880", "name": "item", "description": "10.1016/j.scitotenv.2021.152880", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.scitotenv.2021.152880"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-04-01T00:00:00Z"}}, {"id": "10.1038/s41598-019-55251-2", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:17:52Z", "type": "Journal Article", "created": "2019-12-16", "title": "Assessing the impact of global climate changes on irrigated wheat yields and water requirements in a semi-arid environment of Morocco", "description": "Abstract<p>The present work aims to quantify the impact of climate change (CC) on the grain yields of irrigated cereals and their water requirements in the Tensift region of Morocco. The Med-CORDEX (MEDiterranean COordinated Regional Climate Downscaling EXperiment) ensemble runs under scenarios RCP4.5 (Representative Concentration Pathway) and RCP8.5 are first evaluated and disaggregated using the quantile-quantile approach. The impact of CC on the duration of the main wheat phenological stages based on the degree-day approach is then analyzed. The results show that the rise in air temperature causes a shortening of the development cycle of up to 50 days. The impacts of rising temperature and changes in precipitation on wheat yields are next evaluated, based on the AquaCrop model, both with and without taking into account the fertilizing effect of CO2. As expected, optimal wheat yields will decrease on the order of 7 to 30% if CO2 concentration rise is not considered. The fertilizing effect of CO2 can counterbalance yield losses, since optimal yields could increase by 7% and 13% respectively at mid-century for the RCP4.5 and RCP8.5 scenarios. Finally, water requirements are expected to decrease by 13 to 42%, mainly in response to the shortening of the cycle. This decrease is associated with a change in temporal patterns, with the requirement peak coming two months earlier than under current conditions.</p>", "keywords": ["Water resources", "Atmospheric sciences", "Agricultural Irrigation", "environment/Bioclimatology", "550", "Representative Concentration Pathways", "Adaptation to Climate Change in Agriculture", "Arid", "Rain", "[SDV.SA.AGRO]Life Sciences [q-bio]/Agricultural sciences/Agronomy", "Climate Change and Variability Research", "Plant Science", "Precipitation", "02 engineering and technology", "01 natural sciences", "Agricultural and Biological Sciences", "Downscaling", "Climate change", "Quantile", "Triticum", "Climatology", "2. Zero hunger", "Global and Planetary Change", "Ecology", "Geography", "Temperature", "Life Sciences", "Geology", "Morocco", "Phenology", "[SDV.EE.BIO]Life Sciences [q-bio]/Ecology", "Seeds", "Physical Sciences", "Metallurgy", "Desert Climate", "Impacts of Elevated CO2 and Ozone on Plant Physiology", "Climate Change", "0207 environmental engineering", "Yield (engineering)", "Climate model", "Article", "Environmental science", "FOS: Economics and business", "Meteorology", "FOS: Mathematics", "Econometrics", "[SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology", "Biology", "Ecology", " Evolution", " Behavior and Systematics", "0105 earth and related environmental sciences", "[SDV.SA.AGRO] Life Sciences [q-bio]/Agricultural sciences/Agronomy", "Water", "FOS: Earth and related environmental sciences", "Carbon Dioxide", "15. Life on land", "Agronomy", "Materials science", "[SDV.EE.BIO] Life Sciences [q-bio]/Ecology", " environment/Bioclimatology", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "[SDU.STU.HY] Sciences of the Universe [physics]/Earth Sciences/Hydrology", "Crop Yield", "Mediterranean climate", "Mathematics", "Climate Modeling"]}, "links": [{"href": "https://www.nature.com/articles/s41598-019-55251-2.pdf"}, {"href": "https://doi.org/10.1038/s41598-019-55251-2"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Scientific%20Reports", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1038/s41598-019-55251-2", "name": "item", "description": "10.1038/s41598-019-55251-2", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1038/s41598-019-55251-2"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-12-16T00:00:00Z"}}, {"id": "10.1111/gcb.13151", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:18:49Z", "type": "Journal Article", "created": "2015-11-07", "title": "Canopy leaf area of a mature evergreen Eucalyptus woodland does not respond to elevated atmospheric [CO 2 ] but tracks water availability", "description": "Abstract<p>Canopy leaf area, quantified by the leaf area index (L), is a crucial driver of forest productivity, water use and energy balance. Because L responds to environmental drivers, it can represent an important feedback to climate change, but its responses to rising atmospheric [CO2] and water availability of forests have been poorly quantified. We studied canopy leaf area dynamics for 28\uffc2\uffa0months in a native evergreen Eucalyptus woodland exposed to free\uffe2\uff80\uff90air CO2 enrichment (the EucFACE experiment), in a subtropical climate where water limitation is common. We hypothesized that, because of expected stimulation of productivity and water\uffe2\uff80\uff90use efficiency, L should increase with elevated [CO2]. We estimated L from diffuse canopy transmittance, and measured monthly leaf litter production. Contrary to expectation, L did not respond to elevated [CO2]. We found that L varied between 1.10 and 2.20 across the study period. The dynamics of L showed a quick increase after heavy rainfall and a steady decrease during periods of low rainfall. Leaf litter production was correlated to changes in L, both during periods of decreasing L (when no leaf growth occurred) and during periods of increasing L (active shedding of old foliage when new leaf growth occurred). Leaf lifespan, estimated from mean L and total annual litter production, was up to 2\uffc2\uffa0months longer under elevated [CO2] (1.18 vs. 1.01\uffc2\uffa0years; P\uffc2\uffa0=\uffc2\uffa00.05). Our main finding that L was not responsive to elevated CO2 is consistent with other forest FACE studies, but contrasts with the positive response of L commonly predicted by many ecosystem models.</p>", "keywords": ["[SDE] Environmental Sciences", "0106 biological sciences", "Eucalyptus", "leaf area index", "Atmosphere", "Water", "drought", "Carbon Dioxide", "Forests", "15. Life on land", "phenology", "01 natural sciences", "free-air CO2 enrichment", "6. Clean water", "[SDV] Life Sciences [q-bio]", "Plant Leaves", "13. Climate action", "atmospheric carbon dioxide", "XXXXXX - Unknown", "leaves", "New South Wales", "litter production"]}, "links": [{"href": "https://onlinelibrary.wiley.com/doi/pdf/10.1111/gcb.13151"}, {"href": "https://doi.org/10.1111/gcb.13151"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Global%20Change%20Biology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1111/gcb.13151", "name": "item", "description": "10.1111/gcb.13151", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1111/gcb.13151"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2016-02-09T00:00:00Z"}}, {"id": "10.1093/treephys/tpaa058", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:18:31Z", "type": "Journal Article", "created": "2020-04-24", "title": "Timeline of autumn phenology in temperate deciduous trees", "description": "Abstract                <p>Cessation of xylem formation or wood growth (CWG) and onset of foliar senescence (OFS) are key autumn phenological events in temperate deciduous trees. Their timing is fundamental for the development and survival of trees, ecosystem nutrient cycling and the seasonal exchange of matter and energy between the biosphere and atmosphere, and affects the impact and feedback of forests to global change. A large-scale experimental effort and improved observational methods have allowed us to compare the timing of CWG and OFS for different deciduous tree species in Western Europe, particularly in silver birch, a pioneer species, and European beech, a late-succession species, at stands of different latitudes, of different levels of site fertility, for 2 years with contrasting meteorological and drought conditions, i.e., the low moderately dry 2017 and the extremely dry 2018. Specifically, we tested whether foliar senescence started before, after or concurrently with CWG. Onset of foliar senescence and CWG occurred generally between late September and early November, with larger differences across species and sites for OFS. Foliar senescence started concurrently with CWG in most cases, except for the drier 2018 and, for beech, at the coldest site, where OFS occurred significantly later than CWG. The behavior of beech in Spain, the southern edge of its European distribution, was unclear, with no CWG, but very low wood growth at the time of OFS. Our study suggests that OFS is generally triggered by the same drivers of CWG or when wood growth decreases in late summer, indicating an overarching mechanism of sink limitation as a possible regulator of the timing of foliar senescence.</p>", "keywords": ["0106 biological sciences", "listna senescenca", "nastajanje lesa", "cambium", "info:eu-repo/classification/udc/630*18:630*8", "autumn phenology", " xylem formation", " foliar senescence", " cambium", " chlorophyll", " radial growth", " wood", " decidiuous trees", " common aspen", " common beech", " pedunculate oak", " silver birch", "01 natural sciences", "jesenska fenologija", " nastajanje lesa", " listna senescenca", " kambij", " klorofil", " debelinska rast", " les", " listavci", " trepetlika", " navadna bukev", " dob", " navadna breza", "trepetlika", "Trees", "navadna bukev", "klorofil", "les", "chlorophyll", "pedunculate oak", "Biology", "info:eu-repo/classification/udc/630*1", "Ecosystem", "xylem formation", "kambij", "silver birch", "Temperature", "sink limitation", "04 agricultural and veterinary sciences", "dob", "navadna breza", "15. Life on land", "debelinska rast", "common beech", "listavci", "[SDE.BE] Environmental Sciences/Biodiversity and Ecology", "Europe", "Plant Leaves", "radial growth", "jesenska fenologija", "common aspen", "Spain", "13. Climate action", "foliar senescence", "wood growth", "0401 agriculture", " forestry", " and fisheries", "Seasons", "[SDE.BE]Environmental Sciences/Biodiversity and Ecology", "autumn phenology", "decidiuous trees", "wood"]}, "links": [{"href": "https://doi.org/10.1093/treephys/tpaa058"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Tree%20Physiology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1093/treephys/tpaa058", "name": "item", "description": "10.1093/treephys/tpaa058", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1093/treephys/tpaa058"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-04-27T00:00:00Z"}}, {"id": "10.1111/gcb.15596", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:18:51Z", "type": "Journal Article", "created": "2021-03-12", "title": "Phenological stage of tundra vegetation controls bidirectional exchange of BVOCs in a climate change experiment on a subarctic heath", "description": "Abstract<p>Traditionally, biogenic volatile organic compound (BVOC) emissions are often considered a unidirectional flux, from the ecosystem to the atmosphere, but recent studies clearly show the potential for bidirectional exchange. Here we aimed to investigate how warming and leaf litter addition affect the bidirectional exchange (flux) of BVOCs in a long\uffe2\uff80\uff90term field experiment in the Subarctic. We also assessed changes in net BVOC fluxes in relation to the time of day and the influence of different plant phenological stages. The study was conducted in a full factorial experiment with open top chamber warming and annual litter addition treatments in a tundra heath in Abisko, Northern Sweden. After 18\uffc2\uffa0years of treatments, ecosystem\uffe2\uff80\uff90level net BVOC fluxes were measured in the experimental plots using proton\uffe2\uff80\uff90transfer\uffe2\uff80\uff90reaction time\uffe2\uff80\uff90of\uffe2\uff80\uff90flight mass spectrometry (PTR\uffe2\uff80\uff93ToF\uffe2\uff80\uff93MS). The warming treatment increased monoterpene and isoprene emissions by \uffe2\uff89\uff8850%. Increasing temperature, due to diurnal variations, can both increase BVOC emission and simultaneously, increase ecosystem uptake. For any given treatment, monoterpene, isoprene, and acetone emissions also increased with increasing ambient air temperatures caused by diurnal variability. Acetaldehyde, methanol, and sesquiterpenes decreased likely due to a deposition flux. For litter addition, only a significant indirect effect on isoprene and monoterpene fluxes (decrease by ~50%\uffe2\uff80\uff9375%) was observed. Litter addition may change soil moisture conditions, leading to changes in plant species composition and biomass, which could subsequently result in changes to BVOC emission compositions. Phenological stages significantly affected fluxes of methanol, isoprene and monoterpenes. We suggest that plant phenological stages differ in impacts on BVOC net emissions, but ambient air temperature and photosynthetically active radiation (PAR) also interact and influence BVOC net emissions differently. Our results may also suggest that BVOC fluxes are not only a response to changes in temperature and light intensity, as the circadian clock also affects emission rates.</p>", "keywords": ["BVOC", "Sweden", "Take urgent action to combat climate change and its impacts", "Volatile Organic Compounds", "tundra", "Methanol", "Terpenoids", "Climate Change", "plant volatiles", "15. Life on land", "Primary Research Articles", "phenology", "01 natural sciences", "Arctic", "climate change", "Phenology", "terpenoids", "13. Climate action", "11. Sustainability", "Plant volatiles", "Tundra", "Ecosystem", "methanol", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://onlinelibrary.wiley.com/doi/pdf/10.1111/gcb.15596"}, {"href": "https://doi.org/10.1111/gcb.15596"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Global%20Change%20Biology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1111/gcb.15596", "name": "item", "description": "10.1111/gcb.15596", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1111/gcb.15596"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-04-04T00:00:00Z"}}, {"id": "10.1111/j.1365-2486.2011.02424.x", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:19:02Z", "type": "Journal Article", "created": "2011-03-21", "title": "Impacts Of Multiple Extreme Winter Warming Events On Sub-Arctic Heathland: Phenology, Reproduction, Growth, And Co2 Flux Responses", "description": "Abstract<p>Extreme weather events can have strong negative impacts on species survival and community structure when surpassing lethal thresholds. Extreme, short\uffe2\uff80\uff90lived, winter warming events in the Arctic rapidly melt snow and expose ecosystems to unseasonably warm air (for instance, 2\uffe2\uff80\uff9310\uffe2\uff80\uff83\uffc2\uffb0C for 2\uffe2\uff80\uff9314 days) but upon return to normal winter climate exposes the ecosystem to much colder temperatures due to the loss of insulating snow. Single events have been shown to reduce plant reproduction and increase shoot mortality, but impacts of multiple events are little understood as are the broader impacts on community structure, growth, carbon balance, and nutrient cycling. To address these issues, we simulated week\uffe2\uff80\uff90long extreme winter warming events \uffe2\uff80\uff93 using infrared heating lamps and soil warming cables \uffe2\uff80\uff93 for 3 consecutive years in a sub\uffe2\uff80\uff90Arctic heathland dominated by the dwarf shrubsEmpetrum hermaphroditum, Vaccinium vitis\uffe2\uff80\uff90idaea(both evergreen) andVaccinium myrtillus(deciduous). During the growing seasons after the second and third winter event, spring bud burst was delayed by up to a week forE. hermaphroditumandV. myrtillus, and berry production reduced by 11\uffe2\uff80\uff9375% and 52\uffe2\uff80\uff9395% forE. hermaphroditumandV. myrtillus, respectively. Greater shoot mortality occurred inE. hermaphroditum(up to 52%),V. vitis\uffe2\uff80\uff90idaea(51%), andV. myrtillus(80%). Root growth was reduced by more than 25% but soil nutrient availability remained unaffected. Gross primary productivity was reduced by more than 50% in the summer following the third simulation. Overall, the extent of damage was considerable, and critically plant responses were opposite in direction to the increased growth seen in long\uffe2\uff80\uff90term summer warming simulations and the \uffe2\uff80\uff98greening\uffe2\uff80\uff99 seen for some arctic regions. Given the Arctic is warming more in winter than summer, and extreme events are predicted to become more frequent, this generates large uncertainty in our current understanding of arctic ecosystem responses to climate change.</p>", "keywords": ["flowering phenology", "0106 biological sciences", "extreme events", "climate change", "13. Climate action", "arctic", "winter warming", "nutrient cycling", "GPP", "15. Life on land", "dwarf shrub", "01 natural sciences", "SDG 15 - Life on Land"]}, "links": [{"href": "https://doi.org/10.1111/j.1365-2486.2011.02424.x"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Global%20Change%20Biology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1111/j.1365-2486.2011.02424.x", "name": "item", "description": "10.1111/j.1365-2486.2011.02424.x", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1111/j.1365-2486.2011.02424.x"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2011-04-13T00:00:00Z"}}, {"id": "10.3390/rs12244018", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:21:16Z", "type": "Journal Article", "created": "2020-12-08", "title": "Linkages between Rainfed Cereal Production and Agricultural Drought through Remote Sensing Indices and a Land Data Assimilation System: A Case Study in Morocco", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>In Morocco, cereal production shows high interannual variability due to uncertain rainfall and recurrent drought periods. Considering the socioeconomic importance of cereal for the country, there is a serious need to characterize the impact of drought on cereal yields. In this study, drought is assessed through (1) indices derived from remote sensing data (the vegetation condition index (VCI), temperature condition index (TCI), vegetation health ind ex (VHI), soil moisture condition index (SMCI) and soil water index for different soil layers (SWI)) and (2) key land surface variables (Land Area Index (LAI), soil moisture (SM) at different depths, soil evaporation and plant transpiration) from a Land Data Assimilation System (LDAS) over 2000\u20132017. A lagged correlation analysis was conducted to assess the relationships between the drought indices and cereal yield at monthly time scales. The VCI and LAI around the heading stage (March-April) are highly linked to yield for all provinces (R = 0.94 for the Khemisset province), while a high link for TCI occurs during the development stage in January-February (R = 0.83 for the Beni Mellal province). Interestingly, indices related to soil moisture in the superficial soil layer are correlated with yield earlier in the season around the emergence stage (December). The results demonstrate the clear added value of using an LDAS compared with using a remote sensing product alone, particularly concerning the soil moisture in the root-zone, considered a key variable for yield production, that is not directly observable from space. The time scale of integration is also discussed. By integrating the indices on the main phenological stages of wheat using a dynamic threshold approach instead of the monthly time scale, the correlation between indices and yield increased by up to 14%. In addition, the contributions of VCI and TCI to VHI were optimized by using yield anomalies as proxies for drought. This study opens perspectives for the development of drought early warning systems in Morocco and over North Africa, as well as for seasonal crop yield forecasting.</p></article>", "keywords": ["[SDE] Environmental Sciences", "550", "Science", "0207 environmental engineering", "Agricultural drought", "02 engineering and technology", "01 natural sciences", "630", "Environmental science", "remote sensing", "Land data assimilation systems", "Pathology", "assimilation systems", "Biology", "land data assimilation systems", "0105 earth and related environmental sciences", "2. Zero hunger", "Global and Planetary Change", "Vegetation Monitoring", "Water content", "Ecology", "Drought", "Global Forest Drought Response and Climate Change", "Q", "Hydrology (agriculture)", "Geology", "cereal yield", "Remote Sensing in Vegetation Monitoring and Phenology", "FOS: Earth and related environmental sciences", "Remote sensing", "semiarid region", "15. Life on land", "agricultural drought", "Agronomy", "6. Clean water", "Cereal yield", "Geotechnical engineering", "13. Climate action", "FOS: Biological sciences", "[SDE]Environmental Sciences", "Global Drought Monitoring and Assessment", "Environmental Science", "Physical Sciences", "Leaf area index", "Medicine", "Semiarid region", "land data", "Vegetation (pathology)"]}, "links": [{"href": "http://www.mdpi.com/2072-4292/12/24/4018/pdf"}, {"href": "https://www.mdpi.com/2072-4292/12/24/4018/pdf"}, {"href": "https://doi.org/10.3390/rs12244018"}, {"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/rs12244018", "name": "item", "description": "10.3390/rs12244018", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/rs12244018"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-12-08T00:00:00Z"}}, {"id": "10.3389/fpls.2021.698640", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:20:57Z", "type": "Journal Article", "created": "2021-08-06", "title": "High-Resolution X-Ray Computed Tomography: A New Workflow for the Analysis of Xylogenesis and Intra-Seasonal Wood Biomass Production", "description": "<p>Understanding tree growth and carbon sequestration are of crucial interest to forecast the feedback of forests to climate change. To have a global understanding of the wood formation, it is necessary to develop new methodologies for xylogenesis measurements, valid across diverse wood structures and applicable to both angiosperms and gymnosperms. In this study, the authors present a new workflow to study xylogenesis using high-resolution X-ray computed tomography (HRXCT), which is generic and offers high potential for automatization. The HXRCT-based approach was benchmarked with the current classical approach (microtomy) on three tree species with contrasted wood anatomy (Pinus nigra, Fagus sylvatica, and Quercus robur). HRXCT proved to estimate the relevant xylogenesis parameters (timing, duration, and growth rates) across species with high accuracy. HRXCT showed to be an efficient avenue to investigate tree xylogenesis for a wide range of wood anatomies, structures, and species. HRXCT also showed its potential to provide quantification of intra-annual dynamics of biomass production through high-resolution 3D mapping of wood biomass within the forming growth ring.</p>", "keywords": ["0106 biological sciences", "[SDV.BID.SPT]Life Sciences [q-bio]/Biodiversity/Systematics", "XYLEM", "tree growth", "secondary growth phenology", "Plant Science", "01 natural sciences", "7. Clean energy", "[SDV.BV.BOT] Life Sciences [q-bio]/Vegetal Biology/Botanics", "SB1-1110", "Tree growth", "Secondary growth phenology", "microtomy", "PHENOLOGY", "[SDV.BID.SPT] Life Sciences [q-bio]/Biodiversity/Systematics", " Phylogenetics and taxonomy", "FAGUS-SYLVATICA", "[SDV.EE.ECO] Life Sciences [q-bio]/Ecology", " environment/Ecosystems", "Biology", "TREE", "Xylogenesis", "580", "xylogenesis", "high-resolution X-ray computed tomography", "Biology and Life Sciences", "Plant culture", "Phylogenetics and taxonomy", "Microtomy", "[SDV.BV.BOT]Life Sciences [q-bio]/Vegetal Biology/Botanics", "15. Life on land", "BEECH", "[SDE.BE] Environmental Sciences/Biodiversity and Ecology", "13. Climate action", "[SDV.EE.ECO]Life Sciences [q-bio]/Ecology", "PLANT STRUCTURE", "[SDE.BE]Environmental Sciences/Biodiversity and Ecology", "environment/Ecosystems", "Engineering sciences. Technology"]}, "links": [{"href": "https://doi.org/10.3389/fpls.2021.698640"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Frontiers%20in%20Plant%20Science", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3389/fpls.2021.698640", "name": "item", "description": "10.3389/fpls.2021.698640", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3389/fpls.2021.698640"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-08-06T00:00:00Z"}}, {"id": "10.2139/ssrn.4210928", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:20:33Z", "type": "Journal Article", "created": "2022-09-07", "title": "Field Evaluation of Selected Autochthonous Herbaceous Species for Cover Crops in Mediterranean Woody Crops", "description": "Open AccessPeer reviewed", "keywords": ["0106 biological sciences", "2. Zero hunger", "Phenology", "Ground cover", "Aerial biomass", "0401 agriculture", " forestry", " and fisheries", "Key plant traits", "04 agricultural and veterinary sciences", "Fine root", "15. Life on land", "Cover crop mixtures", "01 natural sciences"], "contacts": [{"organization": "Soriano, Mar\u00eda-Auxiliadora, Cabezas, Jos\u00e9 Manuel, G\u00f3mez, Jos\u00e9 Alfonso,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.2139/ssrn.4210928"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/SSRN%20Electronic%20Journal", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.2139/ssrn.4210928", "name": "item", "description": "10.2139/ssrn.4210928", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.2139/ssrn.4210928"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-01-01T00:00:00Z"}}, {"id": "10.3390/agriculture13081637", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-05-29T16:20:59Z", "type": "Journal Article", "created": "2023-08-21", "title": "Puccinia Spore Concentrations in Relation to Weather Factors and Phenological Development of a Wheat Crop in Northwestern Spain", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Rust is one of the main diseases affecting wheat crops in Spain, causing significant yield and quality losses. Research on its identification and quantification in the air is a worldwide priority due to the importance of this crop as a source of food and feed. The objective of this study is to determine the temporal variation of airborne spores of Puccinia and their relationship with meteorological variables and the phenological development of a wheat crop in Northwestern Spain during two growing seasons. The study was conducted in A Limia, Ourense, located in Northwestern Spain, during the wheat growing seasons of 2021 and 2022. The Lanzoni VPPS 2010 spore trap was used to collect airborne spores, which were identified using optical microscopy. The wheat growing season was less than 95 days during both years, and wheat rust spores were detected during all phenological stages of the crop. Concentrations were higher than 100 spores/m3 from the booting stage to senescence, mainly in 2021. Statistical analyses showed that temperature was the meteorological variable that most influenced Puccinia concentrations in the air in both years. The modification of a prediction model proposed by other authors for wheat rust, which takes into account mean temperature (10\u201325 \u00b0C), dew point temperature (&lt;5 \u00b0C), and nighttime temperature (10\u201320 \u00b0C), allowed us to tentatively predict the increase in Puccinia concentrations in the year 2022 when these conditions occurred for four or five consecutive days. This research is the first in Spain to report the presence of rust-causing Puccinia spores in the air during all phenological stages of the wheat crop and provides useful information for designing management strategies, considering temperature values.</p></article>", "keywords": ["2. Zero hunger", "aerobiology", "13. Climate action", "aerobiology; airborne spores; wheat; phenology; meteorology", "wheat", "Agriculture (General)", "airborne spores", "3103.04 Protecci\u00f3n de Los Cultivos", "15. Life on land", "meteorology", "phenology", "S1-972"]}, "links": [{"href": "http://www.mdpi.com/2077-0472/13/8/1637/pdf"}, {"href": "https://doi.org/10.3390/agriculture13081637"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agriculture", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/agriculture13081637", "name": "item", "description": "10.3390/agriculture13081637", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/agriculture13081637"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-08-19T00:00:00Z"}}, {"id": "10.3390/rs13142678", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:21:17Z", "type": "Journal Article", "created": "2021-07-07", "title": "Improved Accuracy of Phenological Detection in Rice Breeding by Using Ensemble Models of Machine Learning Based on UAV-RGB Imagery", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Accurate and timely detection of phenology at plot scale in rice breeding trails is crucial for understanding the heterogeneity of varieties and guiding field management. Traditionally, remote sensing studies of phenology detection have heavily relied on the time-series vegetation index (VI) data. However, the methodology based on time-series VI data was often limited by the temporal resolution. In this study, three types of ensemble models including hard voting (majority voting), soft voting (weighted majority voting) and model stacking, were proposed to identify the principal phenological stages of rice based on unmanned aerial vehicle (UAV) RGB imagery. These ensemble models combined RGB-VIs, color space (e.g., RGB and HSV) and textures derived from UAV-RGB imagery, and five machine learning algorithms (random forest; k-nearest neighbors; Gaussian na\u00efve Bayes; support vector machine and logistic regression) as base models to estimate phenological stages in rice breeding. The phenological estimation models were trained on the dataset of late-maturity cultivars and tested independently on the dataset of early-medium-maturity cultivars. The results indicated that all ensemble models outperform individual machine learning models in all datasets. The soft voting strategy provided the best performance for identifying phenology with the overall accuracy of 90% and 93%, and the mean F1-scores of 0.79 and 0.81, respectively, in calibration and validation datasets, which meant that the overall accuracy and mean F1-scores improved by 5% and 7%, respectively, in comparison with those of the best individual model (GNB), tested in this study. Therefore, the ensemble models demonstrated great potential in improving the accuracy of phenology detection in rice breeding.</p></article>", "keywords": ["2. Zero hunger", "machine learning", "Science", "UAV", "breeding", "Q", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "ensemble models", "phenology"]}, "links": [{"href": "http://www.mdpi.com/2072-4292/13/14/2678/pdf"}, {"href": "https://doi.org/10.3390/rs13142678"}, {"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/rs13142678", "name": "item", "description": "10.3390/rs13142678", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/rs13142678"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-07-07T00:00:00Z"}}, {"id": "10.3390/rs14246331", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:21:18Z", "type": "Journal Article", "created": "2022-12-15", "title": "Remote Sensing of Poplar Phenophase and Leaf Miner Attack in Urban Forests", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Remote sensing of phenology is adopted as the practice in greenery monitoring. Now research is turned towards the fusion of data from various sensors to fill in the gap in time series and allow monitoring of pests and disturbances. Poplar species were monitored for the determination of the best approach for detecting phenology and disturbances. With the adjustments that include a choice of indices, wavelengths, and a setup, a multispectral camera may be used to calibrate satellite images. The image processing pipeline included different denoising and interpolation methods. The correlation of the changes in a signal of top and lateral imaging proved that the contribution of the whole canopy is reflected in satellite images. Normalized difference vegetation index (NDVI) and normalized difference red edge index (NDRE) successfully distinguished among phenophases and detected leaf miner presence, unlike enhanced vegetation index (EVI). Changes in the indices were registered before, during, and after the development of the disease. NDRE is the most sensitive as it distinguished among the different intensities of damage caused by pests but it was not able to forecast its occurrence. An efficient and accurate system for detection and monitoring of phenology enables the improvement of the phenological models\u2019 quality and creates the basis for a forecast that allows planning in various disciplines.</p></article>", "keywords": ["data fusion", "<i>Populus</i> sp.", "Science", "Q", "multispectral imaging", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "Sentinel-2", "<i>Fenusella hortulana</i> (Klug\uff1b1818)", "15. Life on land", "phenology", "01 natural sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://www.mdpi.com/2072-4292/14/24/6331/pdf"}, {"href": "https://doi.org/10.3390/rs14246331"}, {"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/rs14246331", "name": "item", "description": "10.3390/rs14246331", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/rs14246331"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-12-14T00:00:00Z"}}, {"id": "10.4141/a03-034", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:21:31Z", "type": "Journal Article", "created": "2011-04-24", "title": "Methane Emissions By Charolais Cows Grazing A Monospecific Pasture Of Timothy At Four Stages Of Maturity", "description": "<p> In order to examine the relationship between herbage maturity and methane (CH4) emission under conditions which minimized opportunities for selective grazing, six 8-yr-old, dry and early-pregnant Charolais cows [712 \uffc2\uffb1 22.7 kg liveweight (LW)] were grazed on a mono-specific pasture of timothy at four stages of maturity: early vegetative, heading, flowering, and senescence. Daily CH4 production was measured during 7 d using the sulfur hexafluoride (SF6) tracer-gas technique. Organic matter intake (OMI) was determined from fecal output estimated by Yb2O3 dosing and feed digestibility (OMD) estimated using a fecal N index. The OMD (%) decreased (P &lt; 0.05) from 77.6 at early vegetative to 56.2 at senescence, but no cow effect upon OMD was observed. The OMI (14.8 g kg-1 LW) and CH4 production (273 g d-1) were higher (P &lt; 0.05) at heading than at the other stages of maturity. The proportion of gross energy intake (GEI) lost in CH4 did not differ with maturity (mean 6.4% of GEI). Cow effects upon OMI and CH4 emission were significant (P &lt; 0.05). CH4 production (g d-1) was not related to diet chemical composition or OMD, but was correlated with digestible neutral detergent fiber (NDF) intake (kg d-1) (r = 0.61, P &lt; 0.01). Across all stages of maturity between-cow variation explained 54 to 70% of the total variation in CH4 production. Key words: Methane, cattle, animal variation, timothy, phenology, selective grazing </p>", "keywords": ["2. Zero hunger", "bovin", "timothy", "animal variation", "[SDV]Life Sciences [q-bio]", "0402 animal and dairy science", "variabilit\u00e9 animale", "04 agricultural and veterinary sciences", "[INFO] Computer Science [cs]", "phenology", "fl\u00e9ole", "630", "ph\u00e9nologie", "[SDV] Life Sciences [q-bio]", "cattle", "p\u00e2turage s\u00e9lectif", "[INFO]Computer Science [cs]", "m\u00e9thane", "selective grazing"], "contacts": [{"organization": "Pinares-Pati\u00f1o, C.S., Baumont, Ren\u00e9, Martin, C\u00e9cile,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.4141/a03-034"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Canadian%20Journal%20of%20Animal%20Science", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.4141/a03-034", "name": "item", "description": "10.4141/a03-034", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.4141/a03-034"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2003-12-01T00:00:00Z"}}, {"id": "10.5194/essd-13-3707-2021", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:22:00Z", "type": "Journal Article", "created": "2021-01-07", "title": "C-band radar data and in situ measurements for the monitoring of wheat crops in a semi-arid area (center of Morocco)", "description": "<p>Abstract. A better understanding of the hydrological functioning of irrigated crops using remote sensing observations is of prime importance in the semi-arid areas where the water resources are limited. Radar observations, available at high resolution and revisit time since the launch of Sentinel-1 in 2014, have shown great potential for the monitoring of the water content of the upper soil and of the canopy. In this paper, a complete set of data for radar signal analysis is shared to the scientific community for the first time to our knowledge. The data set is composed of Sentinel-1 products and in situ measurements of soil and vegetation variables collected during three agricultural seasons over drip-irrigated winter wheat in the Haouz plain in Morocco. The in situ data gathers soil measurements (time series of half-hourly surface soil moisture, surface roughness and agricultural practices) and vegetation measurements collected every week/two weeks including above-ground fresh and dry biomasses, vegetation water content based on destructive measurements, cover fraction, leaf area index and plant height. Radar data are the backscattering coefficient and the interferometric coherence derived from Sentinel-1 GRDH (Ground Range Detected High resolution) and SLC (Single Look Complex) products, respectively. The normalized difference vegetation index derived from Sentinel-2 data based on Level-2A (surface reflectance and cloud mask) atmospheric effects-corrected products is also provided. This database, which is the first of its kind made available in open access, is described here comprehensively in order to help the scientific community to evaluate and to develop new or existing remote sensing algorithms for monitoring wheat canopy under semi-arid conditions. The data set is particularly relevant for the development of radar applications including surface soil moisture and vegetation parameters retrieval using either physically based or empirical approaches such as machine and deep learning algorithms. The database is archived in the DataSuds repository and is freely-accessible via the DOI:  https://doi.org/10.23708/8D6WQC  (Ouaadi et al., 2020a).                         </p>", "keywords": ["550", "Arid", "Soil Moisture", "0211 other engineering and technologies", "FOS: Mechanical engineering", "02 engineering and technology", "Digital Soil Mapping Techniques", "Normalized Difference Vegetation Index", "630", "Agricultural and Biological Sciences", "Engineering", "Pathology", "GE1-350", "2. Zero hunger", "QE1-996.5", "Vegetation Monitoring", "Water content", "Ecology", "Geography", "Statistics", "Life Sciences", "Hydrology (agriculture)", "Geology", "Remote Sensing in Vegetation Monitoring and Phenology", "04 agricultural and veterinary sciences", "Remote sensing", "Soil Erosion and Agricultural Sustainability", "6. Clean water", "Satellite Observations", "Archaeology", "Physical Sciences", "Leaf area index", "Telecommunications", "Medicine", "Vegetation (pathology)", "Environmental Engineering", "Data set", "[SDU.STU]Sciences of the Universe [physics]/Earth Sciences", "Aerospace Engineering", "Soil Science", "Environmental science", "Digital Soil Mapping", "[SDU] Sciences of the Universe [physics]", "Global Soil Information", "FOS: Mathematics", "Biology", "Radar", "Synthetic Aperture Radar Interferometry", "Canopy", "FOS: Environmental engineering", "Soil Properties", "Paleontology", "FOS: Earth and related environmental sciences", "15. Life on land", "Remote Sensing of Soil Moisture", "Surface Deformation Monitoring", "Computer science", "Agronomy", "Environmental sciences", "Geotechnical engineering", "[SDU]Sciences of the Universe [physics]", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "[SDU.STU] Sciences of the Universe [physics]/Earth Sciences", "0401 agriculture", " forestry", " and fisheries", "Mathematics"]}, "links": [{"href": "https://essd.copernicus.org/articles/13/3707/2021/essd-13-3707-2021.pdf"}, {"href": "https://doi.org/10.5194/essd-13-3707-2021"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Earth%20System%20Science%20Data", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/essd-13-3707-2021", "name": "item", "description": "10.5194/essd-13-3707-2021", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/essd-13-3707-2021"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-01-07T00:00:00Z"}}, {"id": "10261/309220", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:24:50Z", "type": "Journal Article", "created": "2022-09-07", "title": "Field Evaluation of Selected Autochthonous Herbaceous Species for Cover Crops in Mediterranean Woody Crops", "description": "Open AccessPeer reviewed", "keywords": ["2. Zero hunger", "0106 biological sciences", "Phenology", "Ground cover", "Aerial biomass", "0401 agriculture", " forestry", " and fisheries", "Key plant traits", "04 agricultural and veterinary sciences", "Fine root", "15. Life on land", "Cover crop mixtures", "01 natural sciences"]}, "links": [{"href": "https://doi.org/10261/309220"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/SSRN%20Electronic%20Journal", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10261/309220", "name": "item", "description": "10261/309220", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10261/309220"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-01-01T00:00:00Z"}}, {"id": "10.5281/zenodo.17475742", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:23:24Z", "type": "Dataset", "title": "In-situ and UAV dataset with crop and soil parameters obtained from winter wheat fields", "description": "unspecifiedThe study area was located in the Danubian Plain, Bulgaria, near the town of Knezha (43.495\u00b0N, 24.081\u00b0E). Five field campaigns (November, March, April, May, and June) were conducted during the 2016-2017 agricultural season and two (November and April) during the 2017-2018 agricultural season. Each campaign took four-five days to complete. A hierarchical sampling strategy, consisting of three levels, was adopted: Unit (a single commercial agricultural field), Elementary Sampling Unit (ESU; a 20 \u00d7 20 m plot), and Elementary Sub-Sampling Unit (ESSU; a particular location in the ESU where measurement is taken). Six Units were selected for sampling during each agricultural season. Different number of ESUs were sampled in each Unit depending of its size and diversity of soils. The location of the ESUs was kept unchanged during the season except in case relocation was needed due to waterlogging. The geographic coordinates were measured each time an ESU was visited, irrespective of whether it was relocated or not and a unique ID assigned to the ESU. Thus, data from each visit are presented as a separate independent record (row) in the dataset. In each ESU there were 3 ESSUs, one at the center and two at opposite corners of the ESU. The biological yield was measured only in the central ESSU. The dataset contains only data averaged at ESU level. Two unique identifiers, Unit_ID and ESU_ID, were used across the dataset's tables, helping identify data records and connect tables. The Unit_ID consists of the season and the Unit number, for instance \u201cS16-17_U1\u201d, where \u201cS16-17\u201d is the agricultural season 2016-2017, and \u201cU1\u201d is Unit 1. The ESU_ID consists of the month and year of the field campaign, the Unit number, and the ESU number, for instance \u201capr2017_1_2\u201d, where \u201capr2017\u201d is the April 2017 field campaign, \u201c1\u201d is the Unit number, and \u201c2\u201d is the ESU number.   The LAI, fIPAR, FAPAR, and fCover were measured using AccuPAR LP-80 ceptometer. The CC was measured using CCM-300. The AGB and plant nitrogen samples were collected from a 1 m x 1 m plot at the central ESSU and 50 cm x 50 cm plots in the other two ESSUs. The nitrogen (N) content of the above-ground organs was determined by the Kjeldahl method and expressed as per-cent of the dry weight. N uptake (g m-2) was determined as the product of N content and the dry AGB. Soil moisture content (W) was measured gravimetrically at the surface (0-5 cm) and, in some ESUs, at three additional depths (0-30 cm, 30-60 cm, and 60-100 cm) in 10 cm increments. The data were expressed in percent by mass. Reflectance data was collected using ASD FieldSpec 4 HiRes Field Spectrometer (ASD HH FS4 HiRes). Crop phenology was reported after Zadoks et al. (1974). The damages and weeds status were assessed using five-point rating scales.   The data from the four soil profiles included morphological description of soil horizons, texture (the particle-size distribution was determined by sieving and the pipette method in accordance with ISO 11277-2020), concentration of organic carbon, pH, bulk density, water retention at suctions from 0.25 kPa (pF 0.4) to 33 kPa (pF 2.7), total porosity. Soil water retention curves (pF curves) were obtained during the drainage of the samples by using the suction plate method, pressure membrane apparatus, and desiccators methods, as described in (Rousseva et al., 2017). The field capacity (FC) was estimated by the water content retained at a suction of 10 kPa (pF = 2.0). The wilting point was estimated at a suction 1500 kPa (pF = 4.2). The water retention experimental data at different suctions were approximated with the van Genuchten equation (Van Genuchten, 1980).  The crop calendar and management data included information for the studied winter wheat fields, including soil type, predecessor, pre-sowing preparation, variety, sowing date and norm, dates and type of fertilization, plant protection measures, dates of the main development stages of winter wheat, harvesting date and yield. \u00a0\u00a0  Multispectral image mosaics of the studied fields were generated using the fixed-wing drone eBee Ag furnished with Sequoia camera. The camera has Multi-channel sensor with green (550 nm), red (660 nm), red edge (735 nm), and NIR (790 nm) bands.  Meteorological data were collected by an automatic telemetric agro-meteorological station ADCON addVantage Pro6.5 installed in the vicinity of the town of Knezha. The station operated between 30.11.2016 and 22.03.2017 on its initial location (Location 1: 43.521917\u00b0N, 24.098848\u00b0E) and was later moved to another location, 1.3 km southwards (Location 2: 43.511391\u00b0N, 24.092252\u00b0E), where it collected data between 26.04.2017 and 3.12.2018. The station was equipped with sensors for air temperature, relative humidity, solar radiation, wind speed, wind direction, rain, PAR, soil moisture and temperature (12 depths between 5 cm and 115 cm at 10 cm intervals). Data from all sensors were recorded at 30 min intervals.  References:  Zadoks, J.C., T.T. Chang, C.F. Konzak. 1974. A decimal code of the growth stages of cereals. Weed Research, 14, 415-421.  Rousseva, S., Kercheva, M., Shishkov, T., Lair, G.J., Nikolaidis, N.P., Moraetis, D., Kr\u00e1m, P., Bernasconi, S.M., Blum, W.E.H., Menon, M., et al. 2017. Soil Water Characteristics of European SoilTrEC Critical Zone Observatories. In Advances in Agronomy; Academic Press: Cambridge, MA, USA, Volume 142, pp. 29\u201372.  van Genuchten, M. T., 1980. A closed-form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Sci. Soc. Am. J. 44, 892\u2013898.", "keywords": ["Winter wheat", "Chlorophyll", "Phenology", "UAV", "Yield (agricultural)", "Soil profile", "Biomass", "Remote sensing", "Spectroscopy", "LAI"], "contacts": [{"organization": "Dimitrov, Petar, Roumenina, Eugenia, Jelev, Georgi, Filchev, Lachezar, Gikov, Alexander, Kamenova, Ilina, Ilieva, Iliana, Ganeva, Dessislava, Kercheva, Milena, Banov, Martin, Krasteva, Veneta, Kolchakov, Viktor, Dimitrov, Emil, Miteva, Nevena,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.17475742"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.17475742", "name": "item", "description": "10.5281/zenodo.17475742", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.17475742"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-10-31T00:00:00Z"}}, {"id": "10.5281/zenodo.8091449", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:23:55Z", "type": "Journal Article", "created": "2021-07-07", "title": "Improved Accuracy of Phenological Detection in Rice Breeding by Using Ensemble Models of Machine Learning Based on UAV-RGB Imagery", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Accurate and timely detection of phenology at plot scale in rice breeding trails is crucial for understanding the heterogeneity of varieties and guiding field management. Traditionally, remote sensing studies of phenology detection have heavily relied on the time-series vegetation index (VI) data. However, the methodology based on time-series VI data was often limited by the temporal resolution. In this study, three types of ensemble models including hard voting (majority voting), soft voting (weighted majority voting) and model stacking, were proposed to identify the principal phenological stages of rice based on unmanned aerial vehicle (UAV) RGB imagery. These ensemble models combined RGB-VIs, color space (e.g., RGB and HSV) and textures derived from UAV-RGB imagery, and five machine learning algorithms (random forest; k-nearest neighbors; Gaussian na\u00efve Bayes; support vector machine and logistic regression) as base models to estimate phenological stages in rice breeding. The phenological estimation models were trained on the dataset of late-maturity cultivars and tested independently on the dataset of early-medium-maturity cultivars. The results indicated that all ensemble models outperform individual machine learning models in all datasets. The soft voting strategy provided the best performance for identifying phenology with the overall accuracy of 90% and 93%, and the mean F1-scores of 0.79 and 0.81, respectively, in calibration and validation datasets, which meant that the overall accuracy and mean F1-scores improved by 5% and 7%, respectively, in comparison with those of the best individual model (GNB), tested in this study. Therefore, the ensemble models demonstrated great potential in improving the accuracy of phenology detection in rice breeding.</p></article>", "keywords": ["2. Zero hunger", "machine learning", "Science", "UAV", "breeding", "Q", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "ensemble models", "phenology"]}, "links": [{"href": "http://www.mdpi.com/2072-4292/13/14/2678/pdf"}, {"href": "https://doi.org/10.5281/zenodo.8091449"}, {"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.8091449", "name": "item", "description": "10.5281/zenodo.8091449", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.8091449"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-07-07T00:00:00Z"}}, {"id": "10.60692/7hann-x9205", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:24:25Z", "type": "Journal Article", "created": "2020-12-08", "title": "Linkages between Rainfed Cereal Production and Agricultural Drought through Remote Sensing Indices and a Land Data Assimilation System: A Case Study in Morocco", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>In Morocco, cereal production shows high interannual variability due to uncertain rainfall and recurrent drought periods. Considering the socioeconomic importance of cereal for the country, there is a serious need to characterize the impact of drought on cereal yields. In this study, drought is assessed through (1) indices derived from remote sensing data (the vegetation condition index (VCI), temperature condition index (TCI), vegetation health ind ex (VHI), soil moisture condition index (SMCI) and soil water index for different soil layers (SWI)) and (2) key land surface variables (Land Area Index (LAI), soil moisture (SM) at different depths, soil evaporation and plant transpiration) from a Land Data Assimilation System (LDAS) over 2000\u20132017. A lagged correlation analysis was conducted to assess the relationships between the drought indices and cereal yield at monthly time scales. The VCI and LAI around the heading stage (March-April) are highly linked to yield for all provinces (R = 0.94 for the Khemisset province), while a high link for TCI occurs during the development stage in January-February (R = 0.83 for the Beni Mellal province). Interestingly, indices related to soil moisture in the superficial soil layer are correlated with yield earlier in the season around the emergence stage (December). The results demonstrate the clear added value of using an LDAS compared with using a remote sensing product alone, particularly concerning the soil moisture in the root-zone, considered a key variable for yield production, that is not directly observable from space. The time scale of integration is also discussed. By integrating the indices on the main phenological stages of wheat using a dynamic threshold approach instead of the monthly time scale, the correlation between indices and yield increased by up to 14%. In addition, the contributions of VCI and TCI to VHI were optimized by using yield anomalies as proxies for drought. This study opens perspectives for the development of drought early warning systems in Morocco and over North Africa, as well as for seasonal crop yield forecasting.</p></article>", "keywords": ["[SDE] Environmental Sciences", "550", "Science", "0207 environmental engineering", "Agricultural drought", "02 engineering and technology", "01 natural sciences", "630", "Environmental science", "remote sensing", "Land data assimilation systems", "Pathology", "assimilation systems", "Biology", "land data assimilation systems", "0105 earth and related environmental sciences", "2. Zero hunger", "Global and Planetary Change", "Vegetation Monitoring", "Water content", "Ecology", "Drought", "Global Forest Drought Response and Climate Change", "Q", "Hydrology (agriculture)", "Geology", "cereal yield", "Remote Sensing in Vegetation Monitoring and Phenology", "FOS: Earth and related environmental sciences", "Remote sensing", "semiarid region", "15. Life on land", "agricultural drought", "Agronomy", "6. Clean water", "Cereal yield", "Geotechnical engineering", "13. Climate action", "FOS: Biological sciences", "[SDE]Environmental Sciences", "Global Drought Monitoring and Assessment", "Environmental Science", "Physical Sciences", "Leaf area index", "Medicine", "Semiarid region", "land data", "Vegetation (pathology)"]}, "links": [{"href": "http://www.mdpi.com/2072-4292/12/24/4018/pdf"}, {"href": "https://www.mdpi.com/2072-4292/12/24/4018/pdf"}, {"href": "https://doi.org/10.60692/7hann-x9205"}, {"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": "10.60692/7hann-x9205", "name": "item", "description": "10.60692/7hann-x9205", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.60692/7hann-x9205"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-12-08T00:00:00Z"}}, {"id": "10138/577327", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:24:44Z", "type": "Journal Article", "created": "2024-06-01", "title": "CH4 transport in wetland plants under controlled environmental conditions \u2013 separating the impacts of phenology from environmental variables", "description": "Abstract                        Background and Aims             <p>Methane (CH4) fluxes at peatland plant surfaces are net results of transport of soil-produced CH4 and within-plant CH4 production and consumption, yet factors and processes controlling these fluxes remain unclear. We aimed to assess the effects of seasonality, environmental variables, and CH4 cycling microbes on CH4 fluxes from characteristic fen species.</p>                                   Methods             <p>Four species (Carex rostrata, Menyanthes trifoliata, Betula nana, Salix lapponum) were selected, and their CH4 fluxes determined in climate-controlled environments with three mesocosms per growing season per species. Microbial genes for CH4 cycling were analysed to check the potential for within-plant CH4 production and oxidation. Two extra experiments were conducted: removal of C. rostrata leaves to identify how leaves constrain CH4 transport, and a labelling experiment with S. lapponum to distinguish between plant-produced and soil-produced CH4 in the plant flux.</p>                                   Results             <p>All species showed seasonal variability in CH4 fluxes. Higher porewater CH4 concentration increased fluxes from C. rostrata and M. trifoliata, decreased fluxes from S. lapponum, and did not affect fluxes from B. nana. Air temperature only and negatively affected CH4 flux from C. rostrata. Light level did not impact CH4 fluxes. Both methanogens and methanotrophs were detected in shoots of S. lapponum and M. trifoliata, methanotrophs in B. nana, and neither in C. rostrata.</p>                                   Conclusion             <p>Our study demonstrates that the seasonal phase of the plants regulates the CH4 fluxes they mediate across species. The detection of methanogens and methanotrophs in herbs and shrubs suggests that microbial processes may contribute to their CH4 fluxes.</p>", "keywords": ["0301 basic medicine", "570", "0303 health sciences", "metanotrofit", "varvut", "Herbs", "11831 Plant biology", "metaani", "Environmental sciences", "Controlled environments", "Microbes", "03 medical and health sciences", "Phenology", "suot", "Plant-mediated CH fluxes", "suokasvillisuus", "Shrubs", "metanogeenit", "sarat"]}, "links": [{"href": "https://doi.org/10138/577327"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Plant%20and%20Soil", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10138/577327", "name": "item", "description": "10138/577327", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10138/577327"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-06-01T00:00:00Z"}}, {"id": "11093/5192", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:25:08Z", "type": "Journal Article", "created": "2023-08-21", "title": "Puccinia Spore Concentrations in Relation to Weather Factors and Phenological Development of a Wheat Crop in Northwestern Spain", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Rust is one of the main diseases affecting wheat crops in Spain, causing significant yield and quality losses. Research on its identification and quantification in the air is a worldwide priority due to the importance of this crop as a source of food and feed. The objective of this study is to determine the temporal variation of airborne spores of Puccinia and their relationship with meteorological variables and the phenological development of a wheat crop in Northwestern Spain during two growing seasons. The study was conducted in A Limia, Ourense, located in Northwestern Spain, during the wheat growing seasons of 2021 and 2022. The Lanzoni VPPS 2010 spore trap was used to collect airborne spores, which were identified using optical microscopy. The wheat growing season was less than 95 days during both years, and wheat rust spores were detected during all phenological stages of the crop. Concentrations were higher than 100 spores/m3 from the booting stage to senescence, mainly in 2021. Statistical analyses showed that temperature was the meteorological variable that most influenced Puccinia concentrations in the air in both years. The modification of a prediction model proposed by other authors for wheat rust, which takes into account mean temperature (10\u201325 \u00b0C), dew point temperature (&lt;5 \u00b0C), and nighttime temperature (10\u201320 \u00b0C), allowed us to tentatively predict the increase in Puccinia concentrations in the year 2022 when these conditions occurred for four or five consecutive days. This research is the first in Spain to report the presence of rust-causing Puccinia spores in the air during all phenological stages of the wheat crop and provides useful information for designing management strategies, considering temperature values.</p></article>", "keywords": ["2. Zero hunger", "aerobiology", "13. Climate action", "aerobiology; airborne spores; wheat; phenology; meteorology", "wheat", "Agriculture (General)", "airborne spores", "3103.04 Protecci\u00f3n de Los Cultivos", "15. Life on land", "meteorology", "phenology", "S1-972"]}, "links": [{"href": "http://www.mdpi.com/2077-0472/13/8/1637/pdf"}, {"href": "https://doi.org/11093/5192"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agriculture", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "11093/5192", "name": "item", "description": "11093/5192", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/11093/5192"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-08-19T00:00:00Z"}}, {"id": "3092828027", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:26:27Z", "type": "Journal Article", "created": "2020-10-16", "title": "Gypsum-exclusive plants accumulate more leaf S than non-exclusive species both in and off gypsum", "description": "Abstract   Gypsum-exclusive species (gypsophiles), are restricted to gypseous soils in natural environments. However, it is unclear why gypsophiles display greater affinity to gyspeous soils than other soils. These plants are edaphic endemics, growing in alkaline soils with high Ca and S. Gypsophiles tend to show higher foliar Ca and S, lower K and, sometimes, higher Mg than non-exclusive gypsum species, named gypsovags. Our aim was to test if the unique leaf elemental signature of gypsophiles could be the result of special nutritional requirements linked to their specificity to gypseous soils. These nutritional requirements could hamper the completion of their life cycle and growth in other soil types. To test this hypothesis, we cultivated five gypsophiles and five gypsovags dominant in Spanish gypsum outcrops on gypseous and calcareous (non-gypseous) field soil for 29 months. We regularly measured growth and phenology, and differences in leaf traits, final biomass, individual seed mass, seed viability, photosynthetic assimilation and leaf elemental composition. We found all the gypsophiles studied were able to complete their life cycle in non-gypseous soil, producing viable seeds, attaining greater biomass and displaying higher photosynthetic assimilation rates than in gypseous soil. The leaf elemental composition of some species (both gypsophiles and gypsovags) shifted depending on soil, although none of them showed leaf deficiency symptoms. Regardless of soil type, gypsophiles had higher leaf S, Mg, Fe, Al, Na, Mn, Cr and lower K than gypsovags. Consequently, gypsophiles have a unique leaf chemical signature compared to gypsovags of the same family, particularly due to their high leaf S regardless of soil conditions. However, these nutrient requirements are not sufficient to explain why gypsophiles are restricted to gypsum soil in natural conditions.", "keywords": ["Edaphism", "0106 biological sciences", "2. Zero hunger", "04 agricultural and veterinary sciences", "Gypsum", "15. Life on land", "01 natural sciences", "Thiophores", "Phenology", "0401 agriculture", " forestry", " and fisheries", "Leaf chemical signature", "Gypsophile", "Semiarid", "Nutrient"]}, "links": [{"href": "https://doi.org/3092828027"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20and%20Experimental%20Botany", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "3092828027", "name": "item", "description": "3092828027", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3092828027"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-02-01T00:00:00Z"}}, {"id": "3113036323", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:26:30Z", "type": "Journal Article", "created": "2020-12-08", "title": "Linkages between Rainfed Cereal Production and Agricultural Drought through Remote Sensing Indices and a Land Data Assimilation System: A Case Study in Morocco", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>In Morocco, cereal production shows high interannual variability due to uncertain rainfall and recurrent drought periods. Considering the socioeconomic importance of cereal for the country, there is a serious need to characterize the impact of drought on cereal yields. In this study, drought is assessed through (1) indices derived from remote sensing data (the vegetation condition index (VCI), temperature condition index (TCI), vegetation health ind ex (VHI), soil moisture condition index (SMCI) and soil water index for different soil layers (SWI)) and (2) key land surface variables (Land Area Index (LAI), soil moisture (SM) at different depths, soil evaporation and plant transpiration) from a Land Data Assimilation System (LDAS) over 2000\u20132017. A lagged correlation analysis was conducted to assess the relationships between the drought indices and cereal yield at monthly time scales. The VCI and LAI around the heading stage (March-April) are highly linked to yield for all provinces (R = 0.94 for the Khemisset province), while a high link for TCI occurs during the development stage in January-February (R = 0.83 for the Beni Mellal province). Interestingly, indices related to soil moisture in the superficial soil layer are correlated with yield earlier in the season around the emergence stage (December). The results demonstrate the clear added value of using an LDAS compared with using a remote sensing product alone, particularly concerning the soil moisture in the root-zone, considered a key variable for yield production, that is not directly observable from space. The time scale of integration is also discussed. By integrating the indices on the main phenological stages of wheat using a dynamic threshold approach instead of the monthly time scale, the correlation between indices and yield increased by up to 14%. In addition, the contributions of VCI and TCI to VHI were optimized by using yield anomalies as proxies for drought. This study opens perspectives for the development of drought early warning systems in Morocco and over North Africa, as well as for seasonal crop yield forecasting.</p></article>", "keywords": ["[SDE] Environmental Sciences", "550", "Science", "0207 environmental engineering", "Agricultural drought", "02 engineering and technology", "01 natural sciences", "630", "Environmental science", "remote sensing", "Land data assimilation systems", "Pathology", "assimilation systems", "Biology", "land data assimilation systems", "0105 earth and related environmental sciences", "2. Zero hunger", "Global and Planetary Change", "Vegetation Monitoring", "Water content", "Ecology", "Drought", "Global Forest Drought Response and Climate Change", "Q", "Hydrology (agriculture)", "Geology", "cereal yield", "Remote Sensing in Vegetation Monitoring and Phenology", "FOS: Earth and related environmental sciences", "Remote sensing", "semiarid region", "15. Life on land", "agricultural drought", "Agronomy", "6. Clean water", "Cereal yield", "Geotechnical engineering", "13. Climate action", "FOS: Biological sciences", "[SDE]Environmental Sciences", "Global Drought Monitoring and Assessment", "Environmental Science", "Physical Sciences", "Leaf area index", "Medicine", "Semiarid region", "land data", "Vegetation (pathology)"]}, "links": [{"href": "http://www.mdpi.com/2072-4292/12/24/4018/pdf"}, {"href": "https://www.mdpi.com/2072-4292/12/24/4018/pdf"}, {"href": "https://doi.org/3113036323"}, {"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": "3113036323", "name": "item", "description": "3113036323", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3113036323"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-12-08T00:00:00Z"}}, {"id": "3181125785", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:26:35Z", "type": "Journal Article", "created": "2021-07-07", "title": "Improved Accuracy of Phenological Detection in Rice Breeding by Using Ensemble Models of Machine Learning Based on UAV-RGB Imagery", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Accurate and timely detection of phenology at plot scale in rice breeding trails is crucial for understanding the heterogeneity of varieties and guiding field management. Traditionally, remote sensing studies of phenology detection have heavily relied on the time-series vegetation index (VI) data. However, the methodology based on time-series VI data was often limited by the temporal resolution. In this study, three types of ensemble models including hard voting (majority voting), soft voting (weighted majority voting) and model stacking, were proposed to identify the principal phenological stages of rice based on unmanned aerial vehicle (UAV) RGB imagery. These ensemble models combined RGB-VIs, color space (e.g., RGB and HSV) and textures derived from UAV-RGB imagery, and five machine learning algorithms (random forest; k-nearest neighbors; Gaussian na\u00efve Bayes; support vector machine and logistic regression) as base models to estimate phenological stages in rice breeding. The phenological estimation models were trained on the dataset of late-maturity cultivars and tested independently on the dataset of early-medium-maturity cultivars. The results indicated that all ensemble models outperform individual machine learning models in all datasets. The soft voting strategy provided the best performance for identifying phenology with the overall accuracy of 90% and 93%, and the mean F1-scores of 0.79 and 0.81, respectively, in calibration and validation datasets, which meant that the overall accuracy and mean F1-scores improved by 5% and 7%, respectively, in comparison with those of the best individual model (GNB), tested in this study. Therefore, the ensemble models demonstrated great potential in improving the accuracy of phenology detection in rice breeding.</p></article>", "keywords": ["2. Zero hunger", "machine learning", "Science", "UAV", "breeding", "Q", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "ensemble models", "phenology"]}, "links": [{"href": "http://www.mdpi.com/2072-4292/13/14/2678/pdf"}, {"href": "https://doi.org/3181125785"}, {"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": "3181125785", "name": "item", "description": "3181125785", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3181125785"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-07-07T00:00:00Z"}}, {"id": "34998760", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:26:46Z", "type": "Journal Article", "created": "2022-01-06", "title": "Exploring the potential role of environmental and multi-source satellite data in crop yield prediction across Northeast China", "description": "Open AccessLe d\u00e9veloppement d'un syst\u00e8me pr\u00e9cis de pr\u00e9diction du rendement des cultures \u00e0 grande \u00e9chelle est d'une importance primordiale pour la gestion des ressources agricoles et la s\u00e9curit\u00e9 alimentaire mondiale. L'observation de la Terre fournit une source unique d'informations pour surveiller les cultures \u00e0 partir d'une diversit\u00e9 de gammes spectrales. Cependant, l'utilisation int\u00e9gr\u00e9e de ces donn\u00e9es et de leurs valeurs dans la pr\u00e9diction du rendement des cultures est encore peu \u00e9tudi\u00e9e. Ici, nous avons propos\u00e9 la combinaison de donn\u00e9es environnementales (climat, sol, g\u00e9ographie et topographie) avec de multiples donn\u00e9es satellitaires (indices de v\u00e9g\u00e9tation optiques, fluorescence induite par le soleil (SIF), temp\u00e9rature de surface du sol (LST) et profondeur optique de la v\u00e9g\u00e9tation micro-ondes (VOD)) dans le cadre pour estimer le rendement des cultures de ma\u00efs, de riz et de soja dans le nord-est de la Chine, et leur valeur unique et leur influence relative sur la pr\u00e9diction du rendement ont \u00e9t\u00e9 \u00e9valu\u00e9es. Deux m\u00e9thodes de r\u00e9gression lin\u00e9aire, trois m\u00e9thodes d'apprentissage automatique (ML) et un mod\u00e8le d'ensemble ML ont \u00e9t\u00e9 adopt\u00e9s pour construire des mod\u00e8les de pr\u00e9diction de rendement. Les r\u00e9sultats ont montr\u00e9 que les m\u00e9thodes individuelles de ML surpassaient les m\u00e9thodes de r\u00e9gression lin\u00e9aire, le mod\u00e8le d'ensemble de ML a encore am\u00e9lior\u00e9 les mod\u00e8les de ML uniques. De plus, les mod\u00e8les avec plus d'intrants ont obtenu de meilleures performances, la combinaison de donn\u00e9es satellitaires avec des donn\u00e9es environnementales, qui expliquaient respectivement 72\u00a0%, 69\u00a0% et 57\u00a0% de la variabilit\u00e9 du rendement du ma\u00efs, du riz et du soja, a d\u00e9montr\u00e9 des performances de pr\u00e9diction du rendement sup\u00e9rieures \u00e0 celles des intrants individuels. Alors que les donn\u00e9es satellitaires ont contribu\u00e9 \u00e0 la pr\u00e9diction du rendement des cultures principalement au d\u00e9but de la pointe de la saison de croissance, les donn\u00e9es climatiques ont fourni des informations suppl\u00e9mentaires principalement \u00e0 la pointe de la fin de la saison. Nous avons \u00e9galement constat\u00e9 que l'utilisation combin\u00e9e de l'IVE, du LST et du SIF a am\u00e9lior\u00e9 la pr\u00e9cision du mod\u00e8le par rapport au mod\u00e8le d'IVE de r\u00e9f\u00e9rence. Cependant, les indices de v\u00e9g\u00e9tation bas\u00e9s sur l'optique partageaient des informations similaires et ne fournissaient pas beaucoup d'informations suppl\u00e9mentaires au-del\u00e0 de l'IVE. Les pr\u00e9visions de rendement en cours de saison ont montr\u00e9 que les rendements des cultures peuvent \u00eatre pr\u00e9vus de mani\u00e8re satisfaisante deux \u00e0 trois mois avant la r\u00e9colte. La g\u00e9ographie, la topographie, la VOD, l'IVE, les param\u00e8tres hydrauliques du sol et les param\u00e8tres nutritifs sont plus importants pour la pr\u00e9diction du rendement des cultures.", "keywords": ["Atmospheric sciences", "Climate", "Multi-source satellite data", "Normalized Difference Vegetation Index", "Engineering", "Pathology", "Climate change", "Urban Heat Islands and Mitigation Strategies", "Linear regression", "2. Zero hunger", "Global and Planetary Change", "Vegetation Monitoring", "Ecology", "Geography", "Statistics", "Agriculture", "Geology", "Remote Sensing in Vegetation Monitoring and Phenology", "04 agricultural and veterinary sciences", "Remote sensing", "Aerospace engineering", "Archaeology", "Physical Sciences", "Metallurgy", "Medicine", "Seasons", "Global Vegetation Models", "Biomass Estimation", "Regression analysis", "Vegetation (pathology)", "Crops", " Agricultural", "Environmental Engineering", "Environmental data", "Yield (engineering)", "Zea mays", "Environmental science", "Machine learning", "FOS: Mathematics", "Crop yield", "Biology", "Global Forest Drought Response and Climate Change", "FOS: Environmental engineering", "Predictive modelling", "Food security", "FOS: Earth and related environmental sciences", "15. Life on land", "Agronomy", "Materials science", "Yield prediction", "Satellite", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Growing season", "0401 agriculture", " forestry", " and fisheries", "Mathematics"], "contacts": [{"organization": "Zhenwang Li, Lei Ding, Donghui Xu,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/34998760"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Science%20of%20The%20Total%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "34998760", "name": "item", "description": "34998760", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/34998760"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-04-01T00:00:00Z"}}, {"id": "aa436b63-21de-4df1-a8c7-e39c7890c596", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[5.81, 47.26], [5.81, 54.76], [15.77, 54.76], [15.77, 47.26], [5.81, 47.26]]]}, "properties": {"themes": [{"concepts": [{"id": "farming"}], "scheme": "https://standards.iso.org/iso/19139/resources/gmxCodelists.xml#MD_TopicCategoryCode"}, {"concepts": [{"id": "Soil"}, {"id": "field experimentation"}, {"id": "research data"}, {"id": "mixed cropping"}, {"id": "wheat"}, {"id": "coriander"}, {"id": "intercropping"}, {"id": "crop performance"}, {"id": "crop yield"}], "scheme": "AGROVOC Multilingual agricultural thesaurus"}, {"concepts": [{"id": "opendata"}, {"id": "crop phenology"}, {"id": "field experiments"}, {"id": "deeprooting crops"}, {"id": "carbon sequestration"}, {"id": "pollinators"}, {"id": "drought stress"}], "scheme": "Individual"}, {"concepts": [{"id": "Boden"}], "scheme": "GEMET - INSPIRE themes, version 1.0"}, {"concepts": [{"id": "Germany"}, {"id": "Hesse"}, {"id": "Focus Area Central Hessian arable cropping areas"}, {"id": "East Hessian Low Mountain Ranges"}, {"id": "Frankenhausen"}, {"id": "University of Kassel"}], "scheme": "individual"}], "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": "2025-04-11", "type": "Dataset", "created": "2025-02-04", "language": "eng", "title": "TRIO - Pre-experiments", "description": "This table contains the pre-experiments of the TRIO experiment.\nGeneral description see mother table: (https://doi.org/10.4228/zalf-zca6-5y36); Related datasets are listed in the metadata element 'Related Identifier'. Dataset version 1.0", "formats": [{"name": "CSV"}], "keywords": ["Soil", "field experimentation", "research data", "mixed cropping", "wheat", "coriander", "intercropping", "crop performance", "crop yield", "opendata", "crop phenology", "field experiments", "deeprooting crops", "carbon sequestration", "pollinators", "drought stress", "Boden", "Germany", "Hesse", "Focus Area Central Hessian arable cropping areas", "East Hessian Low Mountain Ranges", "Frankenhausen", "University of Kassel"], "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": 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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 research activities of the DFG funded project 'Data-Meta Analysis to assess the productivity development of cultivated plants'\"(Grant number: Stu 127/19-3) at the Institute of Horticultural Production Systems of the Faculty of Natural Sciences at the Leibniz Universit\u00e4t Hanover (LUH). Although every care has been taken in preparing and testing the data, the above mentioned project and the BonaRes Data Centre cannot guarantee that the data are correct; neither does the above mentioned project 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. 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"3b08f0fc-f209-425f-86e1-f106f29f4ee6", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[5.81, 47.26], [5.81, 54.76], [15.77, 54.76], [15.77, 47.26], [5.81, 47.26]]]}, "properties": {"themes": [{"concepts": [{"id": "farming"}], "scheme": "https://standards.iso.org/iso/19139/resources/gmxCodelists.xml#MD_TopicCategoryCode"}, {"concepts": [{"id": "climate"}], "scheme": "AGROVOC Multilingual agricultural thesaurus"}, {"concepts": [{"id": "Winter wheat"}, {"id": "yield development"}, {"id": "nitrogen fertilization experiments"}, {"id": "climate change"}, {"id": "climate effects"}, {"id": "phenology"}, {"id": "meta-analysis"}, {"id": "mixed-effect analysis"}, {"id": "soil types"}, {"id": "soil quality rating"}, {"id": "opendata"}], "scheme": "Individual"}, {"concepts": [{"id": "Climate change impact"}, {"id": "climatic change"}, {"id": "environmental impact"}, {"id": "environmental statistics"}, {"id": "data analysis"}, {"id": "statistical analysis"}, {"id": "field experiment"}, {"id": "soil"}, {"id": "heat stress"}, {"id": "water stress"}, {"id": "Land use"}], "scheme": "GEMET - INSPIRE themes, version 1.0"}, {"concepts": [{"id": "Boden"}], "scheme": "GEMET - INSPIRE themes, version 1.0"}], "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 research activities of the DFG funded project 'Data-Meta Analysis to assess the productivity development of cultivated plants'\"(Grant number: Stu 127/19-3) at the Institute of Horticultural Production Systems of the Faculty of Natural Sciences at the Leibniz Universit\u00e4t Hanover (LUH). Although every care has been taken in preparing and testing the data, the above mentioned project and the BonaRes Data Centre cannot guarantee that the data are correct; neither does the above mentioned project 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 above mentioned project and BonaRes Data Centre will not be responsible for any direct or indirect use which might be made of the data.", "updated": "2023-12-12", "type": "Dataset", "created": "2020-01-28", "language": "eng", "title": "Dataset of winter wheat yields in Germany between 1958 and 2015 from N-fertilization experiments - TRIAL_SITES", "description": "This data set (TRIAL_SITES) is the starting point of a larger data set that contains data and information used in the study \u201cYield development of German winter wheat between 1958 and 2015\u201d in the Project \u201cData-Meta Analysis to assess the productivity development of cultivated plants\u201d funded by the DFG. This starting table contains geographical and environmental information about the experimental sites at which the N-fertilisation experiments were conducted. Amon other topics, this data set can be mainly  used to analyse the impact of climatic changes on the development of winter wheat in Germany.\n\nThe data set comprises following data:\n- Winter wheat (Triticum aestivum) yields and nitrogen application amounts from nitrogen fertilization experiments of variable duration (1-6 years) carried out at 43 locations across Germany, between 1958 and 2015, and found in 34 different sources in the literature.\n- The derived maximum yields (Ymax) and optimal nitrogen amounts (Nopt) from the nitrogen experiments, function coefficients, and statistics.\n- Geographical information (latitude, longitude, altitude) and other site specific information of the experimental sites (soil type, soil yield potential, mean annual temperature, mean annual precipitation, mean annual climatic water balance, soil climate region, cultivation region).\n- Processed phenological and climatic data for each experimental site.", "formats": [{"name": "CSV"}], "keywords": ["climate", "Winter wheat", "yield development", "nitrogen fertilization experiments", "climate change", "climate effects", "phenology", "meta-analysis", "mixed-effect analysis", "soil types", "soil quality rating", "opendata", "Climate change impact", "climatic change", "environmental impact", "environmental statistics", "data analysis", "statistical analysis", "field experiment", "soil", "heat stress", "water stress", "Land use", "Boden"], "contacts": [{"name": "BonaRes Data Centre", "organization": "Leibniz Centre for Agricultural Landscape Research (ZALF)", "position": "Research Platform 'Data' - WG Geodata", "roles": ["publisher"], "phones": [{"value": "+49 33432 82 171"}], "emails": [{"value": "bonares-datenzentrum@zalf.de"}], "addresses": [{"deliveryPoint": ["Eberswalder Strasse 84"], "city": "M\u00fcncheberg", "administrativeArea": "Brandenburg", "postalCode": "15374", "country": "Germany"}], "links": [{"href": null}]}, {"name": "Eric B\u00f6necke", "organization": "Leibniz University Hanover", "position": "Scientist", "roles": ["author"], "phones": [{"value": "+49 511 762-19269"}], "emails": [{"value": "boenecke@igzev.de, boenecke@gem.uni-hannover.de"}], "addresses": [{"deliveryPoint": ["Herrenh\u00e4user Strasse 2"], "city": "Hanover", "administrativeArea": "Lower Saxony", "postalCode": "30419", "country": "Germany"}], "links": [{"href": null}]}, {"name": "Laura Breitsameter", "organization": "Leibniz University Hanover", "position": null, "roles": ["author"], "phones": [{"value": "+49 511 762-19269"}], "emails": [{"value": "breitsameter@igzev.de, boenecke@gem.uni-hannover.de"}], "addresses": [{"deliveryPoint": ["Herrenh\u00e4user Strasse 2"], "city": "Hanover", "administrativeArea": "Lower Saxony", "postalCode": "30419", "country": "Germany"}], "links": [{"href": null}]}, {"name": "Nicolas Br\u00fcggeman", "organization": "Research Centre Julich", "position": "Professor", "roles": ["author"], "phones": [{"value": "+49 246 161 8643"}], "emails": [{"value": "n.brueggemann@fz-juelich.de"}], "addresses": [{"deliveryPoint": ["Wilhelm-Johnen-Stra\u00dfe"], "city": "Julich", "administrativeArea": "North Rhine-Westphalia", "postalCode": "52428", "country": "Germany"}], "links": [{"href": null}]}, {"name": "Till Feike", "organization": "Julius Kuehn-Institute", "position": "Scientist", "roles": ["author"], "phones": [{"value": "+49 332 034 8312"}], "emails": [{"value": "til.feike@julius-kuehn.de"}], "addresses": [{"deliveryPoint": ["Stahnsdorfer Damm 81"], "city": "Kleinmachnow", "administrativeArea": "Brandenburg", "postalCode": "14532", "country": "Germany"}], "links": [{"href": null}]}, {"name": "Henning Kage", "organization": "Christian-Albrechts-University Kiel", "position": "Professor", "roles": ["author"], "phones": [{"value": "+49 431 880 3472"}], "emails": [{"value": "kage@pflanzenbau.uni-kiel.de"}], "addresses": [{"deliveryPoint": ["Hermann-Rodewald-Str. 9"], "city": "Kiel", "administrativeArea": "Schleswig-Holstein", "postalCode": "24118", "country": "Germany"}], "links": [{"href": null}]}, {"name": "Kurt-Christian Kersebaum", "organization": "Leibniz Centre for Agricultural Landscape Research", "position": "Scienctist", "roles": ["author"], "phones": [{"value": "+49 334 328 2394"}], "emails": [{"value": "ckersebaum@zalf.de"}], "addresses": [{"deliveryPoint": ["Eberswalder Stra\u00dfe 84"], "city": "Muencheberg", "administrativeArea": "Brandenburg", "postalCode": "15374", "country": "Germany"}], "links": [{"href": null}]}, {"name": "Hartmut St\u00fctzel", "organization": "Leibniz University Hanover", "position": "Professor", "roles": ["projectLeader"], "phones": [{"value": "+49 511 762 2635"}], "emails": [{"value": "st\u00fctzel@gem.uni-hannover.de"}], "addresses": [{"deliveryPoint": ["Herrenh\u00e4user Strasse 2"], "city": "Hanover", "administrativeArea": "Lower-Saxony", "postalCode": "30419", "country": "Germany"}], "links": [{"href": null}]}, {"name": "Hartmut St\u00fctzel", "organization": "Leibniz University Hanover", "position": "Professor", "roles": ["author"], "phones": [{"value": "+49 511 762 2635"}], "emails": [{"value": "st\u00fctzel@gem.uni-hannover.de"}], "addresses": [{"deliveryPoint": ["Herrenh\u00e4user Strasse 2"], "city": "Hanover", "administrativeArea": "Lower-Saxony", "postalCode": "30419", "country": "Germany"}], "links": [{"href": null}]}, {"organization": "Julius Kuehn-Institute;Leibniz University Hanover;Leibniz Centre for Agricultural Landscape Research;Research Centre Julich;Christian-Albrechts-University Kiel", "roles": ["contributor"]}]}, "links": [{"href": "https://maps.bonares.de/mapapps/resources/apps/bonares/index.html?lang=en&mid=3b08f0fc-f209-425f-86e1-f106f29f4ee6", "rel": "download"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3b08f0fc-f209-425f-86e1-f106f29f4ee6", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": 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"multiple regression analysis"}, {"id": "plant developmental stages"}, {"id": "phenology"}], "scheme": "AGROVOC Multilingual agricultural thesaurus"}, {"concepts": [{"id": "opendata"}], "scheme": "Individual"}, {"concepts": [{"id": "Boden"}, {"id": "agricultural management"}, {"id": "crop rotation"}, {"id": "environmental monitoring"}, {"id": "interpolation"}, {"id": "seasonal variation"}, {"id": "biological development"}], "scheme": "GEMET - Concepts, version 2.4"}, {"concepts": [{"id": "elevation"}, {"id": "land use"}, {"id": "meteorological geographical features"}, {"id": "geographical grid systems"}], "scheme": "INSPIRE"}, {"concepts": [{"id": "Germany"}], "scheme": "individual"}], "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 Repository www.bonares.de. This data were created as part of the JKI's research activities.\" Although every care has been taken in preparing and testing the data, the JKI and the BonaRes Data Centre cannot guarantee that the data are correct; neither does the JKI and the BonaRes Repository 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 Other and BonaRes Repository will not be responsible for any direct or indirect use which might be made of the data.", "updated": "2023-12-13", "type": "Dataset", "created": "2022-09-30", "language": "eng", "title": "Germany-wide time series of interpolated phenological observations for main crop types between 1993 and 2021", "description": "<p>The data set documents a Germany-wide and spatio-temporally consistent 1 \u00d7 1 km\u00b2 analysis-ready time series (ARD-TS) of interpolated DOYs (days of the year) covering 56 beginning phenological development stages (phases) of 9 main crop types for the period between 1993 and 2021. The derivation is based on Germany-wide observations of the German Weather Service (DWD), which were statistically filtered and interpolated. </p> \n<p>The German Weather Service operates a phenological observation network. About 1200 observers monitor 160 phenological phases of wild and cultivated plants. The PHASE model was developed to interpolate the phenological observations for the entire territory of Germany (Gerstmann et al. (2016) Rel.Identifer TAB 8). The model combines the concept of growing degree days (GDD) with a geostatistical interpolation procedure. The PHASE model was applied to create a Germany-wide and spatio-temporally consistent 1 \u00d7 1 km\u00b2 analysis-ready time series (ARD-TS) of interpolated DOYs (days of the year) covering 56 beginning phenological development stages (phases) of 9 main crop types for the period between 1993 and 2021. The dataset includes the following information: </p>\n<p>\n\u2022\tGermany-wide interpolated temperature data from the German Weather Service (DWD), <br/> \n\u2022\traster datasets of interpolated crop-specific and Germany-wide incipient phenological development stages for the period between 1993 and 2020. The value in each pixel of these rasters represents the Day Of the Year (DOY) of the respective beginning phenological plant development stage, \n<br/>\n\u2022\taccuracy metrics (RMSE, MSE, MAE, and R\u00b2) for each Germany-wide interpolation result. </p>\n<p>The code of the phase model is documented in a software repository (Rel.Identifer TAB 9 and 10). The temporally static model input data are also stored there. </p>\n<p><b>Research question </b> <br/> \nThe dataset allows the spatio-temporal definition of phenological windows for any available year and user-defined region (M\u00f6ller et al. (2020) Rel.Identifer TAB 1). Such information is important for various agricultural issues such as the derivation of weather or biodiversity indices, crop classification, soil erosion or crop yield modeling (Bucheli et al. (2022) Rel.Identifer TAB 5; Gerstmann et al. (2018) ; Rel.Identifer TAB 3; M\u00f6ller et al. (2017, 2018) ; Rel.Identifer TAB 2 and 4; Riedsel et al. (2022) ; Rel.Identifer TAB 6).  </p> \nAll relvant papers are listed under RelatedIdentifier. <br/>\nA form for creating an individual WCS can be found here:<br/>\n<a href=\"https://sf.julius-kuehn.de/openapi/phase/\">https://sf.julius-kuehn.de/openapi/phase/</a>", "formats": [{"name": "CSV"}], "keywords": ["Soil", "agricultural practices", "crop rotation", "environmental monitoring", "multiple regression analysis", "plant developmental stages", "phenology", "opendata", "Boden", "agricultural management", "crop rotation", "environmental monitoring", "interpolation", "seasonal variation", "biological development", "elevation", "land use", "meteorological geographical features", "geographical grid systems", "Germany"], "contacts": [{"name": "Markus M\u00f6ller", "organization": "Julius K\u00fchn Institute (JKI) \u2013 Federal Research Centre for Cultivated Plants, Institute for Crop and Soil Science, Bundesallee 69, D-38116 Braunschweig, Germany", "position": null, "roles": ["author"], "phones": [{"value": null}], "emails": [{"value": "markus.moeller@julius-kuehn.de"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": {"url": "https://orcid.org", "protocol": null, "protocol_url": "", "name": "0000-0002-1918-7747", "name_url": "", "description": "ORCID", "description_url": "", "applicationprofile": null, "applicationprofile_url": "", "function": null}}]}, {"name": "Markus M\u00f6ller", "organization": "Julius K\u00fchn Institute (JKI) \u2013 Federal Research Centre for Cultivated Plants, Institute for Crop and Soil Science, Bundesallee 58, 38116 Braunschweig, Germany", "position": null, "roles": ["projectLeader"], "phones": [{"value": null}], "emails": [{"value": "markus.moeller@julius-kuehn.de"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": {"url": "https://orcid.org", "protocol": null, "protocol_url": "", "name": "0000-0002-1918-7747", "name_url": "", "description": "ORCID", "description_url": "", "applicationprofile": null, "applicationprofile_url": "", "function": null}}]}, {"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": null}]}, {"name": "Henning, Gerstmann", "organization": "Federal Agency for Nature Conservation (BfN), Alte Messe 6, 04103 Leipzig", "position": null, "roles": ["researcher"], "phones": [{"value": null}], "emails": [{"value": "henning.gerstmann@bfn.de"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": null}]}, {"name": "Peter, Horney", "organization": "Julius K\u00fchn Institute (JKI) \u2013 Federal Research Centre for Cultivated Plants, Institute for for Strategies and Technology Assessment, Stahnsdorfer Damm 81, 14532 Kleinmachnow, Germany", "position": null, "roles": ["dataCurator"], "phones": [{"value": null}], "emails": [{"value": "peter.horney@julius-kuehn.de"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": null}]}, {"organization": "Julius K\u00fchn Institute (JKI) \u2013 Federal Research Centre for Cultivated Plants, Institute for Crop and Soil Science, Bundesallee 69, D-38116 Braunschweig, Germany", "roles": ["contributor"]}]}, "links": [{"href": "https://maps.bonares.de/mapapps/resources/apps/bonares/index.html?lang=en&mid=33aa2643-5018-4e31-8b88-c2eb0a7a56f8", "rel": "information"}, {"href": "https://metadata.bonares.de:443/smartEditor/preview/DOYs_interpolated.png", "name": "preview", "description": "Web image thumbnail (URL)", "protocol": "WWW:LINK-1.0-http--image-thumbnail", "rel": "preview"}, {"rel": "self", "type": "application/geo+json", "title": "33aa2643-5018-4e31-8b88-c2eb0a7a56f8", "name": "item", "description": "33aa2643-5018-4e31-8b88-c2eb0a7a56f8", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/33aa2643-5018-4e31-8b88-c2eb0a7a56f8"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-12-13T00:00:00Z"}}, {"id": "f99120bb-9a47-46c2-ab72-448fee17d2c8", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[7.39, 51.82], [7.39, 53.22], [14.43, 53.22], [14.43, 51.82], [7.39, 51.82]]]}, "properties": {"themes": [{"concepts": [{"id": "farming"}], "scheme": "https://standards.iso.org/iso/19139/resources/gmxCodelists.xml#MD_TopicCategoryCode"}, {"concepts": [{"id": "maize"}, {"id": "phenology"}, {"id": "normalized difference vegetation index"}], "scheme": "AGROVOC Multilingual agricultural thesaurus"}, {"concepts": [{"id": "opendata"}, {"id": "Satellite time series"}, {"id": "Vegetation indices"}, {"id": "Sentinel-2"}, {"id": "PlanetScope"}, {"id": "LSP \u2013 Land Surface Phenology"}, {"id": "Phenometrics"}, {"id": "Start-"}, {"id": "Peak-"}, {"id": "End-of-Season (SOS"}, {"id": "POS"}, {"id": "EOS)"}], "scheme": "Individual"}, {"concepts": [{"id": "Boden"}], "scheme": "GEMET - 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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": "2025-10-08", "type": "Dataset", "created": "2025-10-01", "language": "eng", "title": "Maize Phenometrics", "description": "Dataset include Land Surface Phenology metrics for maize, with Start-of-Season (SOS) related to maize emergence and shooting phenological stages, Peak-of-Season (POS) related to tip of tassel emergence, and End-of-Season (EOS) related to dough ripening and harvest. Using multiple vegetation indices (Normalized Difference Vegetation Index, Normalized Difference Phenology Index, Normalized Difference Red Edge, Modified Soil-Adjusted Vegetation Index) and retrieval methods (First-of-Slope, Median, Relative-Amplitude, and Seasonal-Amplitude), three maize phenometrics (SOS, POS, EOS) were derived from Sentinel-2 (S2) and Fused datasets (fusion of Sentinel-2 and PlanetScope data) for years 2021 and 2022. The pixel values refer to Day-of-Year (DOI) per phenological stage, clipped by fields and structured per test site and year. \nNote: This dataset consists of many rasterdata within a zipfile. Please start the download as csv and our server will compile a zip package.", "formats": [{"name": "CSV"}], "keywords": ["maize", "phenology", "normalized difference vegetation index", "opendata", "Satellite time series", "Vegetation indices", "Sentinel-2", "PlanetScope", "LSP \u2013 Land Surface Phenology", "Phenometrics", "Start-", "Peak-", "End-of-Season (SOS", "POS", "EOS)", "Boden", "Germany", "Northern Germany", "Brandenburg", "Lower Saxony"], "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, 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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. 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Under the stress conditions of climate change, this is characterized by increased water and nutrient uptake from previously underutilized soil areas, more complete use of irradiation, higher storage of atmospheric carbon in the soil, more diverse, more resilient microbiomes in soil, roots and crops, greater attractiveness for flower-visiting insects and higher crop yields and quality. The increase in production and quality through the intensification of ecological processes, which is modeled here as an example for Hesse, is aimed at the health of soil, plants, animals, people and the planet and thus follows the \u201cOne Health\u201d approach.\nUsing an experimental platform developed across contrasting locations, TRIO is quantifying and monetarily evaluating the ecosystem services of new combinations of resource-complementary crops. 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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 research activities of the DFG funded project 'Data-Meta Analysis to assess the productivity development of cultivated plants'\"(Grant number: Stu 127/19-3) at the Institute of Horticultural Production Systems of the Faculty of Natural Sciences at the Leibniz Universit\u00e4t Hanover (LUH). Although every care has been taken in preparing and testing the data, the above mentioned project and the BonaRes Data Centre cannot guarantee that the data are correct; neither does the above mentioned project 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 above mentioned project and BonaRes Data Centre will not be responsible for any direct or indirect use which might be made of the data.", "updated": "2023-12-12", "created": "2020-01-28", "language": "eng", "title": "Agro-climatic phases", "description": "This table (Agroclimatic phases) is part of a larger file dataset that contains processed data and information used in the meta-analysis \u201cYield development of German winter wheat between 1958 and 2015\u201d of the Project \u201cData-Meta Analysis to assess the productivity development of cultivated plants\u201d funded by the DFG. This table holds information about the agroclimatic phases important of crop growth and used in this project and can be used together with the entire dataset, which comprises the following data:\n- Winter wheat (Triticum aestivum) yields and nitrogen application amounts from nitrogen fertilization experiments of variable duration (1-6 years) carried out at 43 locations across Germany and between 1958 and 2015 found in 34 different sources in the literature.\n- The derived maximum yields (Ymax) and optimal nitrogen amounts (Nopt) from the nitrogen experiments, function coefficients, and statistics.\n- Geographical information (latitude, longitude, altitude) and other site specific information of the experimental sites (soil type, soil yield potential, mean annual temperature, mean annual precipitation, mean annual climatic water balance, soil climate region, cultivation region).\n- Processed phenological and climatic data for each experimental site.", "formats": [{"name": "CSV"}], 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