{"type": "FeatureCollection", "features": [{"id": "10.1007/s11104-010-0626-5", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:14:48Z", "type": "Journal Article", "created": "2010-11-11", "title": "Does the combined application of organic and mineral nutrient sources influence maize productivity? A meta-analysis", "description": "The combined application of organic resources (ORs) and mineral fertilizers is increasingly gaining recognition as a viable approach to address soil fertility decline in sub-Saharan Africa (SSA). We conducted a meta-analysis to provide a comprehensive and quantitative synthesis of conditions under which ORs, N fertilizers, and combined ORs with N fertilizers positively or negatively influence Zea mays (maize) yields, agronomic N use efficiency and soil organic C (SOC) in SSA. Four OR quality classes were assessed; classes I (high quality) and II (intermediate quality) had >2.5% N while classes III (intermediate quality) and IV (low quality) had <2.5% N and classes I and III had <4% polyphenol and <15% lignin. On the average, yield responses over the control were 60%, 84% and 114% following the addition of ORs, N fertilizers and ORs + N fertilizers, respectively. There was a general increase in yield responses with increasing OR quality and OR-N quantity, both when ORs were added alone or with N fertilizers. Surprisingly, greater OR residual effects were observed with high quality ORs and declined with decreasing OR quality. The greater yield responses with ORs + N fertilizers than either resource alone were mostly due to extra N added and not improved N utilization efficiency because negative interactive effects were, most often, observed when combining ORs with N fertilizers. Additionally, their agronomic N use efficiency was not different from sole added ORs but lower than N fertilizers added alone. Nevertheless, positive interactive effects were observed in sandy soils with low quality ORs whereas agronomic use efficiency was greater when smaller quantities of N were added in all soils. Compared to sole added ORs, yield responses for the combined treatment increased with decreasing OR quality and greater yield increases were observed in sandy (68%) than clayey soils (25%). While ORs and ORs + N fertilizer additions increased SOC by at least 12% compared to the control, N fertilizer additions were not different from control suggesting that ORs are needed to increase SOC. Thus, the addition of ORs will likely improve nutrient storage while crop yields are increased and more so for high quality ORs. Furthermore, interactive effects are seldom occurring, but agronomic N use efficiency of ORs + N fertilizers were greater with low quantities of N added, offering potential for increasing crop productivity.", "keywords": ["Soil nutrients", "0106 biological sciences", "Soil management", "Soil Science", "Plant Science", "fertilidad del suelo", "maize", "Soil fertility", "Soil degradation", "Agronomic n use efficiency", "01 natural sciences", "Soil quality", "ma\u00edz", "Soil", "abonos npk", "npk fertilizers", "Field Scale", "2. Zero hunger", "Soil organic matter", "Sub-Saharan Africa", "soil fertility", "04 agricultural and veterinary sciences", "Interactive effects", "15. Life on land", "Organic resource quality", "Yield response", "Integrated soil fertility management", "Meta-analysis", "Zea maize", "Soil conservation", "Fertilization", "0401 agriculture", " forestry", " and fisheries"]}, "links": [{"href": "https://doi.org/10.1007/s11104-010-0626-5"}, {"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/s11104-010-0626-5", "name": "item", "description": "10.1007/s11104-010-0626-5", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s11104-010-0626-5"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2010-11-12T00:00:00Z"}}, {"id": "10.1016/j.iswcr.2020.01.001", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:16:22Z", "type": "Journal Article", "created": "2020-01-09", "title": "SHui, an EU-Chinese cooperative project to optimize soil and water management in agricultural areas in the XXI century", "description": "This article outlines the major scientific objectives of the SHui project that seeks to optimize soil and water use in agricultural systems in the EU and China, by considering major current scientific challenges in this area. SHui (for Soil Hydrology research platform underpinning innovation to manage water scarcity in European and Chinese cropping systems) is large cooperative project that aims to provide significant advances through transdisciplinary research at multiple scales (plot, field, catchment and region). This paper explains our research platform of long-term experiments established at plot scale, approaches taken to integrate crop and hydrological models at field scale; coupled crop models and satellite-based observations at regional scales; decision support systems for specific farming situations; and the integration of these technologies to provide policy recommendations through socio-economic analysis of the impact of soil and water saving technologies. It also outlines the training of stakeholders to develop a basic common curriculum despite the subject being distributed across different disciplines and professions. As such, this article provides a review of major challenges for improving soil and water use in EU and China as well as information about the potential to access information made available by SHui, and to allow others to engage with the project. This work has been supported by Project SHui which is co-funded by the European Union Project GA 773903 and the Chinese MOST. This work has been supported by P12-AGR-0931 (Andalusian Government), RTA2014-00063- C04-03 (Spanish government), SHui (European Commission Grant Agreement number: 773903) and EU\u2012FEDER funds Peer reviewed", "keywords": ["Yield", "550", "EROSION", "FLOW", "Cropping", "SIMULATE YIELD RESPONSE", "Soil Science", "Environmental Sciences & Ecology", "RICE YIELDS", "01 natural sciences", "630", "12. Responsible consumption", "4104 Environmental management", "4105 Pollution and contamination", "DRYING IRRIGATION", "11. Sustainability", "FAO CROP MODEL", "0105 earth and related environmental sciences", "2. Zero hunger", "Science & Technology", "1. No poverty", "Agriculture", "04 agricultural and veterinary sciences", "15. Life on land", "Engineering (General). Civil engineering (General)", "6. Clean water", "4106 Soil sciences", "Cooperation", "Sustainability", "13. Climate action", "Physical Sciences", "Water Resources", "0401 agriculture", " forestry", " and fisheries", "TA1-2040", "Life Sciences & Biomedicine", "Environmental Sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.iswcr.2020.01.001"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/International%20Soil%20and%20Water%20Conservation%20Research", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.iswcr.2020.01.001", "name": "item", "description": "10.1016/j.iswcr.2020.01.001", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.iswcr.2020.01.001"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-03-01T00:00:00Z"}}, {"id": "10.1016/j.agwat.2016.01.023", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:15:23Z", "type": "Journal Article", "created": "2016-02-24", "title": "Grain Yield And Water Use Efficiency Of Maize As Influenced By Different Irrigation Regimes Through Sprinkler Irrigation Under Temperate Climate", "description": "In Vojvodina region, water deficit during the growing season is a major factor limiting maize production. Therefore, to achieve the ideal soil water content in this region, it is of crucial importance to optimize irrigation. The effects of different irrigation levels with sprinkler irrigation system on crop yield, yield components, water use, water (WUE) and irrigation water use (IWUE) efficiency of maize (Zea mays L.) were investigated in Vojvodina (northern Serbia), on a Calcaric Chernozem soil in temperate environment for 3 consecutive years (2006\u20132008). Maize was subjected to four irrigation regimes, as follows: non-limited irrigation (I100), 75% of non-limited irrigation (I75), 50% of non-limited irrigation (I50), and rainfed (non-irrigated) as the control (I0). The irrigation treatments were arranged in a complete randomized block design with 4 replicates. Results showed that maize grown in rainfed conditions had high annual variability, mainly due to amount of rainfall and its distribution during the crop-growing seasons. A significant irrigation effect was found for yield, yield components and others investigated parameters under study. Water stress had significant impact on yield response: as an average of the three years, a grain yield increase of 47.8, 32.8, and 22.9% was observed in I100, I75 and I50 treatments compared to rainfed (I0) treatment, respectively. Yield increased linearly with seasonal crop evapotranspiration and irrigation amount. Furthermore, WUE is maximized with a moderate water deficit (I50), while IWUE is the highest in I100 treatment. The deficit irrigation stress index, DISI, decreased with increasing irrigation rate. The results revealed that irrigation is necessary for maize cultivation because rainfall is insufficient to meet the crop water needs in Vojvodina. In addition, the study indicated that the irrigation regime of 25% water saving (I75) could ensure satisfactory grain yield of maize and increment of WUE.", "keywords": ["0106 biological sciences", "2. Zero hunger", "Yield response factor", "Yield components", "IWUE", "13. Climate action", "15. Life on land", "Deficit irrigation", "Zea mays", "01 natural sciences", "6. Clean water"]}, "links": [{"href": "https://doi.org/10.1016/j.agwat.2016.01.023"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agricultural%20Water%20Management", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.agwat.2016.01.023", "name": "item", "description": "10.1016/j.agwat.2016.01.023", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.agwat.2016.01.023"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2016-05-01T00:00:00Z"}}, {"id": "10.1016/j.rse.2023.113621", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:16:38Z", "type": "Journal Article", "created": "2023-05-13", "title": "Optimisation of AquaCrop backscatter simulations using Sentinel-1 observations", "description": "In preparation for active microwave-based data assimilation into a crop modeling system, the mapping of daily 1-km AquaCrop model (v6.1) biomass and surface soil moisture to backscatter was optimised, using two forward operators, i.e. the Water Cloud Model (WCM) and the Support Vector Regression (SVR). Both forward operators were calibrated (2014\u20132018) with 1-km Sentinel-1 backscatter ( ) observations in VV and VH polarisation, for three different study domains in Europe. For the validation period (2019\u20132021), the simulations showed reasonable performances around Czech Republic and the Iberian Peninsula, to good performances over Belgium, but with strong variations within each domain. The domain-averaged root mean square difference between the model and Sentinel-1 remained below 2 dB for both forward operators and all three study domains, and the mean bias for VV remained close to 0 dB, and close 0.5 dB for the VH polarisation. The WCM and SVR performed better in VV than VH and overall the SVR performed slightly better in mapping the AquaCrop soil moisture and vegetation to backscatter than the WCM. Additionally, the assumed linear relationship in the WCM between soil moisture and soil holds better for VV than for VH. The remaining differences between WCM or SVR simulations and Sentinel-1 observations are mainly caused by AquaCrop model errors.", "keywords": ["Agriculture and Food Sciences", "Crop biomass", "YIELD RESPONSE", "ASSIMILATION", "Backscatter modeling", "LEAF-AREA INDEX", "RADAR BACKSCATTER", "BIOMASS", "SAR BACKSCATTER", "AquaCrop optimisation", "13. Climate action", "SURFACE SOIL-MOISTURE", "Earth and Environmental Sciences", "SUPPORT", "Sentinel-1", "WATER", "Soil moisture", "FAO CROP MODEL"]}, "links": [{"href": "https://doi.org/10.1016/j.rse.2023.113621"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Remote%20Sensing%20of%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.rse.2023.113621", "name": "item", "description": "10.1016/j.rse.2023.113621", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.rse.2023.113621"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-08-01T00:00:00Z"}}, {"id": "10.1029/2024jg008231", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:17:33Z", "type": "Journal Article", "created": "2024-10-17", "title": "Assimilation of Sentinel\u20101 Backscatter to Update AquaCrop Estimates of Soil Moisture and Crop Biomass", "description": "Abstract

This study assesses the potential of regional microwave backscatter data assimilation (DA) in AquaCrop for the first time, using NASA's Land Information System. The objective is to assess whether the assimilation setup can improve surface soil moisture (SSM) and crop biomass estimates. SSM and crop biomass simulations from AquaCrop were updated using Sentinel\uffe2\uff80\uff901 synthetic aperture radar observations, over three regions in Europe in two separate DA experiments. The first experiment concerned updating SSM using VV\uffe2\uff80\uff90polarized backscatter and the corrections were propagated via the model to the biomass. In the second experiment, the DA setup was extended by also updating the biomass with VH\uffe2\uff80\uff90polarized backscatter. SSM was evaluated with local in situ data and with downscaled Soil Moisture Active Passive (SMAP) retrievals for all cropland grid cells, whereas crop biomass was compared to SMAP vegetation optical depth and the Copernicus dry matter productivity. The assimilation showed mixed results for root mean square error and Pearson's correlation, with slight overall improvements in the (anomaly) correlations of updated SSM relative to independent in situ and satellite data. By contrast, the biomass estimates obtained with backscatter DA did not agree better with reference data sets. Overall, the SSM evaluation showed that there is potential in using Sentinel\uffe2\uff80\uff901 backscatter for assimilation in AquaCrop, but the present setup was not able to improve crop biomass estimates. Our study reveals how the complex interaction between SSM, crop biomass and backscatter affect the impact and performance of DA, offering insight into ways to optimize DA for crop growth estimation.

The challenges of the global food supply and environment conservation require ongoing scientific observations of soil-to-plant and plant-to-environment interactions with the aim of improving agriculture resource management. This study included observations of winter wheat yield and biomass of four varieties over three consecutive growing seasons and four site-year cases to assess the effects of nitrogen (N) fertilization rate and time of application on grain yield and biomass. For different wheat varieties, the full factorial design was performed, where factorial combinations of year, location, fall and spring N applications were laid out in a randomized complete block design. The N rate significantly influenced grain yield and biomass production efficiency. The time of N application had a highly significant effect on grain yield, biomass and NUE traits. The N rate of 120 kg ha\u22121 was recognized as a breakpoint over which the grain yield and biomass showed a downtrend. N application in the fall had a significantly higher impact on grain yield and biomass compared to spring N application. The major contribution of wheat variability production belongs to seasonal climate circumstances (<85%) and consequential intrinsic soil properties. The average difference of grain yield between varieties was 15.75%, and 12% of biomass, respectively.

", "keywords": ["2. Zero hunger", "0106 biological sciences", "NUE", "S", "design of experiment (DoE)", "yield response", "0401 agriculture", " forestry", " and fisheries", "Agriculture", "nitrogen fertilization", "nitrogen fertilization; yield response; design of experiment (DoE); NUE", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences"]}, "links": [{"href": "http://www.mdpi.com/2073-4395/11/7/1413/pdf"}, {"href": "https://www.mdpi.com/2073-4395/11/7/1413/pdf"}, {"href": "https://doi.org/10.3390/agronomy11071413"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agronomy", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/agronomy11071413", "name": "item", "description": "10.3390/agronomy11071413", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/agronomy11071413"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-07-14T00:00:00Z"}}, {"id": "10.3923/pjbs.2008.517.524", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:21:13Z", "type": "Journal Article", "created": "2009-03-17", "description": "The objective of this study was to compare the responses of maize (Zea mays L.) to deficit irrigation. A field experiment was conducted during the 1999 and 2000 growing seasons in western Turkey. Irrigation treatments were tested with 100, 70, 50, 30 and 0% replenishment of water depleted at 120 cm soil profile from 100% replenishment treatment at ten days intervals. The irrigation amount ranged between 0 and 323.20 mm in the first year and 0-466.61 mm in the second year of the experiment. Seasonal crop water use values were between 142.19 and 481.91 mm in 1999 and 136.25-599.45 mm in 2000. Average maximum and minimum yields were 10639-10383 kg ha(-1) for full irrigated treatment (I100) and 3750-2136 kg ha(-1) for non-irrigated treatment (I0) in 1999 and 2000, respectively. Water deficit significantly affected maize yield. In both years, yield increased linearly with irrigation applied but the relationship varied from one year to the other. Water Use Efficiency (WUE) ranged from 1.49 to 2.71 kg m(-3), while Irrigation Water Use Efficiency (IWUE) varied from 1.44 to 2.55 kg m(-3) in both years. The yield response factor (ky) relating relative yield decrease to relative evapotranspiration deficit was found to be 0.99 for the data of the two experiments combined. Also, dry matter yields (DM) and leaf area index (LAI) were markedly affected by the irrigation treatments. The finding of this work showed that well-irrigated treatment should be used for maize grown in semi arid regions under no water scarcity.", "keywords": ["Crops", " Agricultural", "2. Zero hunger", "0106 biological sciences", "Turkey", "Water", "Agriculture", "15. Life on land", "Zea mays", "01 natural sciences", "6. Clean water", "Maize", "Yield response factor", "Biomass", "Seasons", "Grain yield", "Desert Climate", "Deficit irrigation"], "contacts": [{"organization": "Meng\u00fc G.P., \u00d6zg\u00fcrel M.,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.3923/pjbs.2008.517.524"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Pakistan%20Journal%20of%20Biological%20Sciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3923/pjbs.2008.517.524", "name": "item", "description": "10.3923/pjbs.2008.517.524", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3923/pjbs.2008.517.524"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2008-02-01T00:00:00Z"}}, {"id": "10.5194/gmd-2021-98", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:21:48Z", "type": "Journal Article", "created": "2021-11-30", "title": "Performance analysis of regional AquaCrop (v6.1) biomass and surface soil moisture simulations using satellite and in situ observations", "description": "

Abstract. The current intensive use of agricultural land is affecting the land quality and contributes to climate change. Feeding the world's growing population under changing climatic conditions demands a global transition to more sustainable agricultural systems. This requires efficient models and data to monitor land cultivation practices at the field to global scale. This study outlines a spatially distributed version of the field-scale crop model AquaCrop version 6.1 to simulate agricultural biomass production and soil moisture variability over Europe at a relatively fine resolution of 30\u2009arcsec (\u223c1\u2009km). A highly efficient parallel processing system is implemented to run the model regionally with global meteorological input data from the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2), soil textural information from the Harmonized World Soil Database version 1.2 (HWSDv1.2), and generic crop information. The setup with a generic crop is chosen as a baseline for a future satellite-based data assimilation system. The relative temporal variability in daily crop biomass production is evaluated with the Copernicus Global Land Service dry matter productivity (CGLS-DMP) data. Surface soil moisture is compared against NASA Soil Moisture Active\u2013Passive surface soil moisture (SMAP-SSM) retrievals, the Copernicus Global Land Service surface soil moisture (CGLS-SSM) product derived from Sentinel-1, and in situ data from the International Soil Moisture Network (ISMN). Over central Europe, the regional AquaCrop model is able to capture the temporal variability in both biomass production and soil moisture, with a spatial mean temporal correlation of 0.8 (CGLS-DMP), 0.74 (SMAP-SSM), and 0.52 (CGLS-SSM). The higher performance when evaluating with SMAP-SSM compared to Sentinel-1 CGLS-SSM is largely due to the lower quality of CGLS-SSM satellite retrievals under growing vegetation. The regional model further captures the short-term and inter-annual variability, with a mean anomaly correlation of 0.46 for daily biomass and mean anomaly correlations of 0.65 (SMAP-SSM) and 0.50 (CGLS-SSM) for soil moisture. It is shown that soil textural characteristics and irrigated areas influence the model performance. Overall, the regional AquaCrop model adequately simulates crop production and soil moisture and provides a suitable setup for subsequent satellite-based data assimilation.

", "keywords": ["YIELD RESPONSE", "2. Zero hunger", "LAND", "QE1-996.5", "Science & Technology", "PRODUCTIVITY", "04 Earth Sciences", "0207 environmental engineering", "UNCERTAINTY", "Geology", "02 engineering and technology", "15. Life on land", "7. Clean energy", "01 natural sciences", "WHEAT YIELD", "37 Earth sciences", "DATA ASSIMILATION", "13. Climate action", "ASSESSMENTS", "Physical Sciences", "IMPLEMENTATION", "FAO CROP MODEL", "Geosciences", " Multidisciplinary", "HIGH-RESOLUTION", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://gmd.copernicus.org/articles/14/7309/2021/gmd-14-7309-2021.pdf"}, {"href": "https://doi.org/10.5194/gmd-2021-98"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoscientific%20Model%20Development", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/gmd-2021-98", "name": "item", "description": "10.5194/gmd-2021-98", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/gmd-2021-98"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-05-17T00:00:00Z"}}, {"id": "1854/LU-01JM1T576ZX50W7293M9RBH0RG", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:25:01Z", "type": "Journal Article", "created": "2024-10-17", "title": "Assimilation of Sentinel\u20101 Backscatter to Update AquaCrop Estimates of Soil Moisture and Crop Biomass", "description": "Abstract

This study assesses the potential of regional microwave backscatter data assimilation (DA) in AquaCrop for the first time, using NASA's Land Information System. The objective is to assess whether the assimilation setup can improve surface soil moisture (SSM) and crop biomass estimates. SSM and crop biomass simulations from AquaCrop were updated using Sentinel\uffe2\uff80\uff901 synthetic aperture radar observations, over three regions in Europe in two separate DA experiments. The first experiment concerned updating SSM using VV\uffe2\uff80\uff90polarized backscatter and the corrections were propagated via the model to the biomass. In the second experiment, the DA setup was extended by also updating the biomass with VH\uffe2\uff80\uff90polarized backscatter. SSM was evaluated with local in situ data and with downscaled Soil Moisture Active Passive (SMAP) retrievals for all cropland grid cells, whereas crop biomass was compared to SMAP vegetation optical depth and the Copernicus dry matter productivity. The assimilation showed mixed results for root mean square error and Pearson's correlation, with slight overall improvements in the (anomaly) correlations of updated SSM relative to independent in situ and satellite data. By contrast, the biomass estimates obtained with backscatter DA did not agree better with reference data sets. Overall, the SSM evaluation showed that there is potential in using Sentinel\uffe2\uff80\uff901 backscatter for assimilation in AquaCrop, but the present setup was not able to improve crop biomass estimates. Our study reveals how the complex interaction between SSM, crop biomass and backscatter affect the impact and performance of DA, offering insight into ways to optimize DA for crop growth estimation.

Abstract. Global soil water availability is challenged by the effects of climate change and a growing population. On average, 70\u2009% of freshwater extraction is attributed to agriculture, and the demand is increasing. In this study, the effects of climate change on the evolution of the irrigation water requirement to sustain current crop productivity are assessed by using the Food and Agriculture Organization (FAO) crop growth model AquaCrop version 6.1. The model is run at 0.5\u2218lat\u00d70.5\u2218long resolution over the European mainland, assuming a general C3-type of crop, and forced by climate input data from the Inter-Sectoral Impact Model Intercomparison Project phase three (ISIMIP3). First, the AquaCrop surface soil moisture (SSM) forced with two types of ISIMIP3 historical meteorological datasets is evaluated with satellite-based SSM estimates in two ways. When driven by ISIMIP3a reanalysis meteorology, daily simulated SSM values have an unbiased root mean square difference of 0.08 and 0.06\u2009m3\u2009m\u22123, with SSM retrievals from the Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) missions, respectively, for the years 2015\u20132016 (2016 is the end year of the reanalysis data). When forced with ISIMIP3b meteorology from five global climate models (GCMs) for the years 2015\u20132020, the historical simulated SSM climatology closely agrees with the satellite-based SSM climatologies. Second, the evaluated AquaCrop model is run to quantify the future irrigation requirement, for an ensemble of five GCMs and three different emission scenarios. The simulated net irrigation requirement (Inet) of the three summer months for a near and far future climate period (2031\u20132060 and 2071\u20132100) is compared to the baseline period of 1985\u20132014 to assess changes in the mean and interannual variability of the irrigation demand. Averaged over the continent and the model ensemble, the far future Inet is expected to increase by 22\u2009mm per month (+30\u2009%) under a high-emission scenario Shared Socioeconomic Pathway (SSP) 3\u20137.0. Central and southern Europe are the most impacted, with larger Inet increases. The interannual variability in Inet is likely to increase in northern and central Europe, whereas the variability is expected to decrease in southern regions. Under a high mitigation scenario (SSP1\u20132.6), the increase in Inet will stabilize at around 13\u2009mm per month towards the end of the century, and interannual variability will still increase but to a smaller extent. The results emphasize a large uncertainty in the Inet projected by various GCMs.

", "keywords": ["IMPACTS", "LAND", "Technology", "Environmental Engineering", "AGRICULTURE", "DEFICIT IRRIGATION", "SIMULATE YIELD RESPONSE", "0207 environmental engineering", "UNCERTAINTY", "02 engineering and technology", "CROP WATER PRODUCTIVITY", "Environmental technology. Sanitary engineering", "01 natural sciences", "0905 Civil Engineering", "G", "DATA ASSIMILATION", "Geography. Anthropology. Recreation", "GE1-350", "Geosciences", " Multidisciplinary", "TD1-1066", "0105 earth and related environmental sciences", "2. Zero hunger", "Science & Technology", "3707 Hydrology", "T", "Geology", "15. Life on land", "TRENDS", "6. Clean water", "MODEL", "Environmental sciences", "0907 Environmental Engineering", "13. Climate action", "Physical Sciences", "Water Resources", "4013 Geomatic engineering", "0406 Physical Geography and Environmental Geoscience", "3709 Physical geography and environmental geoscience"]}, "links": [{"href": "https://biblio.vub.ac.be/vubirfiles/86261359/Busschaert_etal_2022_HESS.pdf"}, {"href": "https://hess.copernicus.org/articles/26/3731/2022/hess-26-3731-2022.pdf"}, {"href": "https://doi.org/10261/277923"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Hydrology%20and%20Earth%20System%20Sciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10261/277923", "name": "item", "description": "10261/277923", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10261/277923"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-01-12T00:00:00Z"}}, {"id": "10.5281/zenodo.6379480", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:23:20Z", "type": "Journal Article", "created": "2021-07-14", "title": "The Effect of N Fertilizer Application Timing on Wheat Yield on Chernozem Soil", "description": "

The challenges of the global food supply and environment conservation require ongoing scientific observations of soil-to-plant and plant-to-environment interactions with the aim of improving agriculture resource management. This study included observations of winter wheat yield and biomass of four varieties over three consecutive growing seasons and four site-year cases to assess the effects of nitrogen (N) fertilization rate and time of application on grain yield and biomass. For different wheat varieties, the full factorial design was performed, where factorial combinations of year, location, fall and spring N applications were laid out in a randomized complete block design. The N rate significantly influenced grain yield and biomass production efficiency. The time of N application had a highly significant effect on grain yield, biomass and NUE traits. The N rate of 120 kg ha\u22121 was recognized as a breakpoint over which the grain yield and biomass showed a downtrend. N application in the fall had a significantly higher impact on grain yield and biomass compared to spring N application. The major contribution of wheat variability production belongs to seasonal climate circumstances (<85%) and consequential intrinsic soil properties. The average difference of grain yield between varieties was 15.75%, and 12% of biomass, respectively.

", "keywords": ["2. Zero hunger", "0106 biological sciences", "NUE", "S", "design of experiment (DoE)", "yield response", "0401 agriculture", " forestry", " and fisheries", "Agriculture", "nitrogen fertilization", "nitrogen fertilization; yield response; design of experiment (DoE); NUE", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences"]}, "links": [{"href": "http://www.mdpi.com/2073-4395/11/7/1413/pdf"}, {"href": "https://www.mdpi.com/2073-4395/11/7/1413/pdf"}, {"href": "https://doi.org/10.5281/zenodo.6379480"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agronomy", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.6379480", "name": "item", "description": "10.5281/zenodo.6379480", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.6379480"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-07-14T00:00:00Z"}}, {"id": "10261/220255", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:24:29Z", "type": "Journal Article", "created": "2020-01-09", "title": "SHui, an EU-Chinese cooperative project to optimize soil and water management in agricultural areas in the XXI century", "description": "Open AccessThis work has been supported by Project SHui which is co-funded by the European Union Project GA 773903 and the Chinese MOST. This work has been supported by P12-AGR-0931 (Andalusian Government), RTA2014-00063- C04-03 (Spanish government), SHui (European Commission Grant Agreement number: 773903) and EU\u2012FEDER funds", "keywords": ["Yield", "550", "EROSION", "FLOW", "Cropping", "SIMULATE YIELD RESPONSE", "Soil Science", "Environmental Sciences & Ecology", "RICE YIELDS", "01 natural sciences", "630", "12. Responsible consumption", "4104 Environmental management", "4105 Pollution and contamination", "DRYING IRRIGATION", "11. Sustainability", "FAO CROP MODEL", "0105 earth and related environmental sciences", "2. Zero hunger", "Science & Technology", "1. No poverty", "Agriculture", "04 agricultural and veterinary sciences", "15. Life on land", "Engineering (General). Civil engineering (General)", "6. Clean water", "4106 Soil sciences", "Cooperation", "Sustainability", "13. Climate action", "Physical Sciences", "Water Resources", "0401 agriculture", " forestry", " and fisheries", "TA1-2040", "Life Sciences & Biomedicine", "Environmental Sciences"]}, "links": [{"href": "https://doi.org/10261/220255"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/International%20Soil%20and%20Water%20Conservation%20Research", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10261/220255", "name": "item", "description": "10261/220255", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10261/220255"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-03-01T00:00:00Z"}}, {"id": "20.500.14017/81a6df94-d40c-4db1-86dc-539a3cb8aaf8", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:25:18Z", "type": "Journal Article", "created": "2022-07-18", "title": "Net irrigation requirement under different climate scenarios using AquaCrop over Europe", "description": "

Abstract. Global soil water availability is challenged by the effects of climate change and a growing population. On average, 70\u2009% of freshwater extraction is attributed to agriculture, and the demand is increasing. In this study, the effects of climate change on the evolution of the irrigation water requirement to sustain current crop productivity are assessed by using the Food and Agriculture Organization (FAO) crop growth model AquaCrop version 6.1. The model is run at 0.5\u2218lat\u00d70.5\u2218long resolution over the European mainland, assuming a general C3-type of crop, and forced by climate input data from the Inter-Sectoral Impact Model Intercomparison Project phase three (ISIMIP3). First, the AquaCrop surface soil moisture (SSM) forced with two types of ISIMIP3 historical meteorological datasets is evaluated with satellite-based SSM estimates in two ways. When driven by ISIMIP3a reanalysis meteorology, daily simulated SSM values have an unbiased root mean square difference of 0.08 and 0.06\u2009m3\u2009m\u22123, with SSM retrievals from the Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) missions, respectively, for the years 2015\u20132016 (2016 is the end year of the reanalysis data). When forced with ISIMIP3b meteorology from five global climate models (GCMs) for the years 2015\u20132020, the historical simulated SSM climatology closely agrees with the satellite-based SSM climatologies. Second, the evaluated AquaCrop model is run to quantify the future irrigation requirement, for an ensemble of five GCMs and three different emission scenarios. The simulated net irrigation requirement (Inet) of the three summer months for a near and far future climate period (2031\u20132060 and 2071\u20132100) is compared to the baseline period of 1985\u20132014 to assess changes in the mean and interannual variability of the irrigation demand. Averaged over the continent and the model ensemble, the far future Inet is expected to increase by 22\u2009mm per month (+30\u2009%) under a high-emission scenario Shared Socioeconomic Pathway (SSP) 3\u20137.0. Central and southern Europe are the most impacted, with larger Inet increases. The interannual variability in Inet is likely to increase in northern and central Europe, whereas the variability is expected to decrease in southern regions. Under a high mitigation scenario (SSP1\u20132.6), the increase in Inet will stabilize at around 13\u2009mm per month towards the end of the century, and interannual variability will still increase but to a smaller extent. The results emphasize a large uncertainty in the Inet projected by various GCMs.

", "keywords": ["IMPACTS", "LAND", "Technology", "Environmental Engineering", "AGRICULTURE", "DEFICIT IRRIGATION", "SIMULATE YIELD RESPONSE", "0207 environmental engineering", "UNCERTAINTY", "02 engineering and technology", "CROP WATER PRODUCTIVITY", "Environmental technology. Sanitary engineering", "01 natural sciences", "0905 Civil Engineering", "G", "DATA ASSIMILATION", "Geography. Anthropology. Recreation", "GE1-350", "Geosciences", " Multidisciplinary", "TD1-1066", "0105 earth and related environmental sciences", "2. Zero hunger", "Science & Technology", "3707 Hydrology", "T", "Geology", "15. Life on land", "TRENDS", "6. Clean water", "MODEL", "Environmental sciences", "0907 Environmental Engineering", "13. Climate action", "Physical Sciences", "Water Resources", "4013 Geomatic engineering", "0406 Physical Geography and Environmental Geoscience", "3709 Physical geography and environmental geoscience"]}, "links": [{"href": "https://hess.copernicus.org/articles/26/3731/2022/hess-26-3731-2022.pdf"}, {"href": "https://doi.org/20.500.14017/81a6df94-d40c-4db1-86dc-539a3cb8aaf8"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Hydrology%20and%20Earth%20System%20Sciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "20.500.14017/81a6df94-d40c-4db1-86dc-539a3cb8aaf8", "name": "item", "description": "20.500.14017/81a6df94-d40c-4db1-86dc-539a3cb8aaf8", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/20.500.14017/81a6df94-d40c-4db1-86dc-539a3cb8aaf8"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-01-12T00:00:00Z"}}, {"id": "20.500.14017/cddeded8-2ef5-4f98-a327-9b94e00ba846", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:25:18Z", "type": "Journal Article", "created": "2021-11-30", "title": "Performance analysis of regional AquaCrop (v6.1) biomass and surface soil moisture simulations using satellite and in situ observations", "description": "

Abstract. The current intensive use of agricultural land is affecting the land quality and contributes to climate change. Feeding the world's growing population under changing climatic conditions demands a global transition to more sustainable agricultural systems. This requires efficient models and data to monitor land cultivation practices at the field to global scale. This study outlines a spatially distributed version of the field-scale crop model AquaCrop version 6.1 to simulate agricultural biomass production and soil moisture variability over Europe at a relatively fine resolution of 30\u2009arcsec (\u223c1\u2009km). A highly efficient parallel processing system is implemented to run the model regionally with global meteorological input data from the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2), soil textural information from the Harmonized World Soil Database version 1.2 (HWSDv1.2), and generic crop information. The setup with a generic crop is chosen as a baseline for a future satellite-based data assimilation system. The relative temporal variability in daily crop biomass production is evaluated with the Copernicus Global Land Service dry matter productivity (CGLS-DMP) data. Surface soil moisture is compared against NASA Soil Moisture Active\u2013Passive surface soil moisture (SMAP-SSM) retrievals, the Copernicus Global Land Service surface soil moisture (CGLS-SSM) product derived from Sentinel-1, and in situ data from the International Soil Moisture Network (ISMN). Over central Europe, the regional AquaCrop model is able to capture the temporal variability in both biomass production and soil moisture, with a spatial mean temporal correlation of 0.8 (CGLS-DMP), 0.74 (SMAP-SSM), and 0.52 (CGLS-SSM). The higher performance when evaluating with SMAP-SSM compared to Sentinel-1 CGLS-SSM is largely due to the lower quality of CGLS-SSM satellite retrievals under growing vegetation. The regional model further captures the short-term and inter-annual variability, with a mean anomaly correlation of 0.46 for daily biomass and mean anomaly correlations of 0.65 (SMAP-SSM) and 0.50 (CGLS-SSM) for soil moisture. It is shown that soil textural characteristics and irrigated areas influence the model performance. Overall, the regional AquaCrop model adequately simulates crop production and soil moisture and provides a suitable setup for subsequent satellite-based data assimilation.

", "keywords": ["YIELD RESPONSE", "2. Zero hunger", "LAND", "QE1-996.5", "Science & Technology", "PRODUCTIVITY", "04 Earth Sciences", "0207 environmental engineering", "UNCERTAINTY", "Geology", "02 engineering and technology", "15. Life on land", "7. Clean energy", "01 natural sciences", "WHEAT YIELD", "37 Earth sciences", "DATA ASSIMILATION", "13. Climate action", "ASSESSMENTS", "Physical Sciences", "IMPLEMENTATION", "FAO CROP MODEL", "Geosciences", " Multidisciplinary", "HIGH-RESOLUTION", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://gmd.copernicus.org/articles/14/7309/2021/gmd-14-7309-2021.pdf"}, {"href": "https://doi.org/20.500.14017/cddeded8-2ef5-4f98-a327-9b94e00ba846"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoscientific%20Model%20Development", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "20.500.14017/cddeded8-2ef5-4f98-a327-9b94e00ba846", "name": "item", "description": "20.500.14017/cddeded8-2ef5-4f98-a327-9b94e00ba846", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/20.500.14017/cddeded8-2ef5-4f98-a327-9b94e00ba846"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-05-17T00:00:00Z"}}, {"id": "1854/LU-01JKX1Z1QJK1BHR9JV20HBZ5Z4", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:25:01Z", "type": "Journal Article", "created": "2023-05-13", "title": "Optimisation of AquaCrop backscatter simulations using Sentinel-1 observations", "description": "Open AccessIn preparation for active microwave-based data assimilation into a crop modeling system, the mapping of daily 1-km AquaCrop model (v6.1) biomass and surface soil moisture to backscatter was optimised, using two forward operators, i.e. the Water Cloud Model (WCM) and the Support Vector Regression (SVR). Both forward operators were calibrated (2014\u20132018) with 1-km Sentinel-1 backscatter (\u03d2\u00b0) observations in VV and VH polarisation, for three different study domains in Europe. For the validation period (2019\u20132021), the \u03d2\u00b0 simulations showed reasonable performances around Czech Republic and the Iberian Peninsula, to good performances over Belgium, but with strong variations within each domain. The domain-averaged root mean square difference between the model and Sentinel-1 \u03d2\u00b0 remained below 2 dB for both forward operators and all three study domains, and the mean bias for VV remained close to 0 dB, and close 0.5 dB for the VH polarisation. The WCM and SVR performed better in VV than VH and overall the SVR performed slightly better in mapping the AquaCrop soil moisture and vegetation to backscatter than the WCM. Additionally, the assumed linear relationship in the WCM between soil moisture and soil \u03d2\u00b0 holds better for VV than for VH. The remaining differences between WCM or SVR simulations and Sentinel-1 observations are mainly caused by AquaCrop model errors.", "keywords": ["Agriculture and Food Sciences", "Technology", "ASSIMILATION", "Sentine;-1", "Environmental Sciences & Ecology", "Geological & Geomatics Engineering", "BIOMASS", "Remote Sensing", "SAR BACKSCATTER", "SURFACE SOIL-MOISTURE", "SUPPORT", "0909 Geomatic Engineering", "WATER", "FAO CROP MODEL", "Imaging Science & Photographic Technology", "crop biomass", "Crop biomass", "YIELD RESPONSE", "Science & Technology", "backscatter modelling", "Backscatter modeling", "LEAF-AREA INDEX", "RADAR BACKSCATTER", "37 Earth sciences", "AquaCrop optimisation", "13. Climate action", "Earth and Environmental Sciences", "Sentinel-1", "Soil moisture", "0406 Physical Geography and Environmental Geoscience", "Life Sciences & Biomedicine", "Environmental Sciences"]}, "links": [{"href": "https://biblio.vub.ac.be/vubirfiles/112110259/108189295.pdf"}, {"href": "https://doi.org/1854/LU-01JKX1Z1QJK1BHR9JV20HBZ5Z4"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Remote%20Sensing%20of%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "1854/LU-01JKX1Z1QJK1BHR9JV20HBZ5Z4", "name": "item", "description": "1854/LU-01JKX1Z1QJK1BHR9JV20HBZ5Z4", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1854/LU-01JKX1Z1QJK1BHR9JV20HBZ5Z4"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-08-01T00:00:00Z"}}, {"id": "3000130041", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:25:51Z", "type": "Journal Article", "created": "2020-01-10", "title": "SHui, an EU-Chinese cooperative project to optimize soil and water management in agricultural areas in the XXI century", "description": "Open AccessThis work has been supported by Project SHui which is co-funded by the European Union Project GA 773903 and the Chinese MOST. This work has been supported by P12-AGR-0931 (Andalusian Government), RTA2014-00063- C04-03 (Spanish government), SHui (European Commission Grant Agreement number: 773903) and EU\u2012FEDER funds", "keywords": ["Yield", "550", "EROSION", "FLOW", "Cropping", "SIMULATE YIELD RESPONSE", "Soil Science", "Environmental Sciences & Ecology", "RICE YIELDS", "01 natural sciences", "630", "12. Responsible consumption", "4104 Environmental management", "4105 Pollution and contamination", "DRYING IRRIGATION", "11. Sustainability", "FAO CROP MODEL", "0105 earth and related environmental sciences", "2. Zero hunger", "Science & Technology", "1. No poverty", "Agriculture", "04 agricultural and veterinary sciences", "15. Life on land", "Engineering (General). Civil engineering (General)", "6. Clean water", "4106 Soil sciences", "Cooperation", "Sustainability", "13. Climate action", "Physical Sciences", "Water Resources", "0401 agriculture", " forestry", " and fisheries", "TA1-2040", "Life Sciences & Biomedicine", "Environmental Sciences"]}, "links": [{"href": "https://doi.org/3000130041"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/International%20Soil%20and%20Water%20Conservation%20Research", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "3000130041", "name": "item", "description": "3000130041", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3000130041"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-03-01T00:00:00Z"}}, {"id": "3181088246", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:26:03Z", "type": "Journal Article", "created": "2021-07-14", "title": "The Effect of N Fertilizer Application Timing on Wheat Yield on Chernozem Soil", "description": "

The challenges of the global food supply and environment conservation require ongoing scientific observations of soil-to-plant and plant-to-environment interactions with the aim of improving agriculture resource management. This study included observations of winter wheat yield and biomass of four varieties over three consecutive growing seasons and four site-year cases to assess the effects of nitrogen (N) fertilization rate and time of application on grain yield and biomass. For different wheat varieties, the full factorial design was performed, where factorial combinations of year, location, fall and spring N applications were laid out in a randomized complete block design. The N rate significantly influenced grain yield and biomass production efficiency. The time of N application had a highly significant effect on grain yield, biomass and NUE traits. The N rate of 120 kg ha\u22121 was recognized as a breakpoint over which the grain yield and biomass showed a downtrend. N application in the fall had a significantly higher impact on grain yield and biomass compared to spring N application. The major contribution of wheat variability production belongs to seasonal climate circumstances (<85%) and consequential intrinsic soil properties. The average difference of grain yield between varieties was 15.75%, and 12% of biomass, respectively.

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