European Journal of Agronomy最新文献

{"title":"Unraveling the regional dynamics of straw mulching and incorporation on crop yields in Northeast China","authors":"Ying Song ,&nbsp;Zhijie Li ,&nbsp;Xiaoling He ,&nbsp;Jiaqiong Zhang ,&nbsp;Jinxia Fu ,&nbsp;Fenli Zheng ,&nbsp;Zhi Li","doi":"10.1016/j.eja.2025.127943","DOIUrl":"10.1016/j.eja.2025.127943","url":null,"abstract":"<div><div>Selecting an appropriate straw return method is crucial for enhancing crop productivity and promoting sustainable agriculture in the black soil region of Northeast China. However, few studies have evaluated the effectiveness of different straw return methods on crop yield, and their regional applicability has not yet been established. This study integrates machine learning approaches and meta-analysis to assess the impact of straw mulch (SM) and straw incorporation (SI) on crop yields under varying climate, soils, and agricultural management conditions in Northeast China’s drylands. Straw return overall increases crop yield by ∼5 %, among which SM and SI have similar mean contributions to yield improvements (5 % vs 4 %). The effects of two straw return methods vary with environmental conditions; specifically, SM outperforms SI under low temperatures (mean annual temperature MAT &lt;6 ℃), drought (mean annual precipitation MAP &lt;600 mm), and moderate erosion (mean annual soil erosion ASE 0.5–2 t/ha), but SI has better effects with high temperatures (MAT &gt;6 ℃), high precipitation (MAP &gt;600 mm), and severe erosion (ASE &gt;2 t/ha). SM achieves the highest yield benefit (8 %) under moderate straw return amounts (6000–10,000 kg/ha), whereas SI performs the best (6 %) at low straw return amounts (&lt; 6000 kg/ha). Furthermore, the yield-enhancing effects of both methods intensifies with increasing experimental duration, with SI's effect gradually and consistently surpassing that of SM. Spatial prediction results reveal that the overall extent of yield increase for SI is 9 %, with higher increasing yield potential observed in the southwest and southeast regions, while the extent of yield increase for SM is lower, at only 3 %. This study elucidates the differentiated yield-enhancing effects of different straw return methods in the black soil region, providing a scientific basis for precision agricultural management and sustainable utilization of black soil in Northeast China and other similar regions.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":"174 ","pages":"Article 127943"},"PeriodicalIF":5.5,"publicationDate":"2025-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145609504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Long-term fertilization reshapes stoichiometric networks driving shifts in microbial life history strategies across China’s croplands","authors":"Xiaodong Sun ,&nbsp;Andong Cai ,&nbsp;Chengjie Ren ,&nbsp;Shuohong Zhang ,&nbsp;Qiang Li ,&nbsp;Shutang Liu ,&nbsp;Shuiqing Zhang ,&nbsp;Huimin Zhang ,&nbsp;Yu Li ,&nbsp;Kailou Liu ,&nbsp;Minggang Xu","doi":"10.1016/j.eja.2025.127928","DOIUrl":"10.1016/j.eja.2025.127928","url":null,"abstract":"<div><div>The balance of carbon (C), nitrogen (N), and phosphorus (P) stoichiometry fundamentally regulates nutrient cycling and microbial metabolism in terrestrial ecosystems. However, the mechanisms through which long-term fertilization and climate jointly shape multidimensional stoichiometric networks and microbial life history strategies remain unclear. In this study, six long-term (27–44 years) fertilization experiments across a 17° latitudinal gradient in China were examined under three treatments: no fertilizer (CK), mineral fertilizer (CF), and mineral plus manure fertilizer (CFM). By integrating ecological stoichiometry with metagenomic approaches, this study assessed how fertilization and climate affect soil, resource, microbial, and enzyme stoichiometry, and how these stoichiometric shifts influence microbial life history strategies. Results showed that long-term fertilization altered stoichiometric patterns, strengthening network connectivity among soil, resource, microbial, and enzymatic stoichiometry. CFM reduced soil and microbial C:P and N:P ratios by 35–70 % and decreased DOC:Olsen-P and DON:Olsen-P by up to 95 %. These shifts restructured microbial life history strategies, promoting a transition from resource acquisition (A) to growth yield (Y) strategies, with Y strategists increasing to 45–56 % under fertilization. Moreover, available resource and microbial stoichiometry, particularly DOC:Olsen-P and DON:Olsen-P ratios, were the primary predictors of microbial strategies, linking stoichiometric balance to microbial energetic allocation. Fertilization and climate jointly regulated microbial life history strategies by alleviating C:P and N:P imbalances and promoting stoichiometric homeostasis. Overall, these findings establish a mechanistic framework connecting nutrient supply, stoichiometric regulation, and microbial adaptation, thereby providing theoretical guidance for optimizing fertilization practices and maintaining soil nutrient sustainability across climatic regions.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":"174 ","pages":"Article 127928"},"PeriodicalIF":5.5,"publicationDate":"2025-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145583818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of regional agricultural drought in the North China Plain and its attribution factors","authors":"Shaofeng Huang,&nbsp;Qi Zhang,&nbsp;Siyuan Dai","doi":"10.1016/j.eja.2025.127930","DOIUrl":"10.1016/j.eja.2025.127930","url":null,"abstract":"<div><div>Regional agricultural drought (RAD) can cause great losses and is a complex phenomenon with multiple attribution factors. Previous studies have rarely examined agricultural droughts from the perspective of regional events, overlooking the temporal and spatial synchronicity in their development processes. In this study, we enhanced the conventional three-dimensional (3D, latitude × longitude × time) connectivity approach by modifying the spatial connectivity criteria and objectively establishing two critical minimum area thresholds to identify RADs. The remote sensing-based Crop Water Stress Index (CWSI) was employed to characterize agricultural drought in the North China Plain (NCP). A total of 114 RADs were detected across the NCP from 2000 to 2023, and their occurrence characteristics and attribution factors were analyzed. The results suggested that setting the minimum area threshold for spatially contiguous agricultural drought clusters at 2.0 % of the total study area yielded more stable identification outcomes. The average duration of the 114 RADs was 52.24 days, with 23.68 % of the events lasting longer than three months and 31.58 % covering more than 90 % of the study area. In the NCP, spring and autumn were periods characterized by frequent and severe agricultural droughts, with spring droughts more intense than autumn droughts. From 2000, the severity and intensity of RADs exhibited a slight decreasing trend. RADs occurred much more frequently in the northwestern region, and the southwestward-moving events were the most common. Using the Geodetector method, precipitation, relative humidity, and evaporation were detected as the top three meteorological factors attributed the spatial distribution of RADs in the NCP. Potential evaporation and precipitation were the predominant meteorological factors influencing the interannual fluctuation of RADs. The Atlantic Multidecadal Oscillation and Western Pacific Subtropical High were identified as the primary teleconnection attributors of interannual variability of RADs. These findings provide novel insight into the characteristics and drivers of RADs, and can offer valuable references for agricultural planning and management from a regional perspective.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":"174 ","pages":"Article 127930"},"PeriodicalIF":5.5,"publicationDate":"2025-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145567790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Film-mulched drip irrigation in the main potato production areas of Northern China: Assessing future yield, greenhouse gas emissions and drivers under climate change","authors":"Qiaoling Liu ,&nbsp;Jianyu Zhao ,&nbsp;Fengxin Wang ,&nbsp;Kaijing Yang ,&nbsp;Jialu Dai ,&nbsp;Bin Yang","doi":"10.1016/j.eja.2025.127924","DOIUrl":"10.1016/j.eja.2025.127924","url":null,"abstract":"<div><div>Climate change threatens global agriculture through extreme weather and shifting growing conditions. Potatoes, a critical staple crop, face challenges like heat stress and water scarcity. Optimising agronomic practices, such as drip irrigation and film mulching, is critical to achieving climate-smart potato production and ensuring food security. During 2021–2100, the DeNitrification-DeComposition (DNDC) model and the Multiscale Geographically Weighted Regression (MGWR) model were comprehensively used to assess the effects of drip irrigation with and without film mulching on potato yield and global warming potential (GWP) under different future climate scenarios in the main potato producing areas of northern China. The results indicated that the DNDC model could effectively predict potato growth and emissions of nitrous oxide and methane (adjusted R² &gt; 0.81, normalized root mean square error &lt; 0.20). Compared to without film mulching (NM), the aboveground biomass and tuber yield were increased under drip irrigation with film mulch (TM), with the mean annual tuber yield of potatoes being 6.2 %-7.4 % higher under multiple emission scenarios. The GWP of TM increased by 1.1–1.4 times, and the net GWP offset decreased by 9.4 %-16.3 %. The MGWR analysis showed that precipitation had a significant positive effect on tuber yield in Inner Mongolia, Gansu and Ningxia, while temperature was the main negative influence on yield in Shaanxi. The main drivers of GWP were temperature and precipitation, with significant differences between regions. The findings provide a scientific basis for developing management strategies to adapt to and mitigate the effects of climate change on potato production, emphasizing the need to strike a balance between increasing yields and reducing greenhouse gas emissions.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":"174 ","pages":"Article 127924"},"PeriodicalIF":5.5,"publicationDate":"2025-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145567428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"TrSC2Y: A transfer-learning-based model from UAV hyper-spectra imagery for field-scale canola yield prediction by integrating DSSAT with PROSAIL","authors":"Ruiqi Du ,&nbsp;Wenbo Shi ,&nbsp;Xianghui Lu ,&nbsp;Youzhen Xiang ,&nbsp;Yue Zhang ,&nbsp;Xiaoying Feng ,&nbsp;Yu Ma","doi":"10.1016/j.eja.2025.127926","DOIUrl":"10.1016/j.eja.2025.127926","url":null,"abstract":"<div><div>Rapid and accurate acquisition of field crop yield is of great significance for agriculture management optimization, food security and crop productivity. By the non-destructive and high-throughput data acquisition, the unmanned aerial vehicle (UAV) remote sensing has become a key tool for crop growth monitoring. However, the scarcity of in-situ samples poses technical barriers and efficiency challenges to yield model training. This study has developed a new yield estimation framework that integrates process models, optical remote sensing, and transfer learning to improve the stability and accuracy of crop yield estimation under small sample conditions. The DSSAT was calibrated with hyperspectral UAV derived crop growth variables, to describe the spatial-temporal variation of small-scale field winter canola leaf nitrogen content during growing season. Firstly, a process-interpretative crop yield estimation framework, TrSC2Y, was pre-trained using the PROSAIL radiative transfer model and the DSSAT crop growth model. Secondly, TrSC2Y was fine-tuned using field observations and UAV hyper-spectra images from three-years canola experiment. Finally, the actual performance and application potential of fine-tuned TrSC2Y in canola yield estimation were evaluated with machine learning as a benchmark test. The results show that: (1) Pre-trained by the crop spectra dataset (from PROSAIL) and yield dataset (from DSSAT), TrSC2Y can accurately extract crop phenotype parameters from theoretical canopy spectra. The joint use of phenotype parameters from multiple growth stages can achieve the best yield estimation (R²= 0.98;RMSE= 33.07 kg/ha;MAE= 1.26 %);(2) Fine-tuned TrSC2Y can be transferred to the field winter canola yield estimation task and shows stable performance (R²= 0.86;RMSE=224.42 kg/ha;MAE=6.5 %). Compared with the machine learning benchmark test, the demand of modeling samples for TrSC2Y is reduced by 50 %; (3) TrSC2Y supports the visualization of field-scale winter canola yield and captures the spatial variability of winter canola yield caused by irrigation-fertilizer treatments.The above results provide a lightweight, cost-effective, and innovative method for field crop yield estimation, promoting the development of precision agriculture management and intelligent applications.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":"174 ","pages":"Article 127926"},"PeriodicalIF":5.5,"publicationDate":"2025-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145567431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identifying optimum sowing dates for rainfed soybeans in Brazil’s new agricultural frontier","authors":"José Wanderson Silva dos Santos ,&nbsp;George do Nascimento Araújo Junior ,&nbsp;Francisco Edson Paulo Ferreira ,&nbsp;Iêdo Peroba de Oliveira Teodoro ,&nbsp;Elvis Felipe Elli ,&nbsp;Wemerson Saulo da Silva Barbosa ,&nbsp;Ricardo Araújo Ferreira Junior ,&nbsp;Guilherme Bastos Lyra ,&nbsp;Iedo Teodoro ,&nbsp;Ivomberg Dourados Magalhães ,&nbsp;Adolpho Emanuel Quintela Rocha ,&nbsp;Alexsandro Claudio dos Santos Almeida","doi":"10.1016/j.eja.2025.127927","DOIUrl":"10.1016/j.eja.2025.127927","url":null,"abstract":"<div><div>Expanding soybean production into new, challenging environments will require advancing knowledge of agriculture management technologies to close yield gaps and enhance system’s sustainability. Crop modeling can be a powerful tool to accurately simulate crop growth and productivity under various cultivation conditions. In this study, the FAO AquaCrop model was calibrated and validated to simulate canopy cover (CC), biomass (B), grain yield (Y), soil water content (SWC), and crop evapotranspiration (ETc) for five soybean cultivars with maturity groups ranging from 6 to 9 under rainfed conditions in the Coastal Tablelands region of Alagoas, Brazil. Model performance was evaluated by modeling efficiency (EF), mean error (E), root mean square error (RMSE), normalized root mean square error (NRMSE), Willmott's index (d), and Pearson’s correlation coefficient (r). The model’s performance for CC ranged from acceptable to good, with the best results for cultivars BRS9383 and M6410. Cultivars AS3730, BMX-POTÊNCIA, and BRS9383 showed the best fit for B (20 % &gt; NRMSE &lt; 30 %; RMSE &lt; 1.30 tons ha⁻¹; EF above 0.8). The model overestimated SWC (E = 16.6 %) but demonstrated low error in predicting ETc for the cultivars (-18–19 mm). After calibration, the model was applied in long-term simulations to evaluate the impacts of alternative sowing dates on crop productivity. For this purpose, a 49-year series of meteorological data was used. The period from the second half of April to the second half of June is recommended for sowing soybean cultivars in the region. During this period, the average soybean productivity can reach 2.72 (±0.38) tons ha⁻¹. Cultivars M6410 (maturity group 6.4) and BMX-POTÊNCIA (maturity group 6.7) were the most suitable for cultivation in the region. AquaCrop model is powerful to optimize rainfed soybean management for cultivation in Brazil’s new agricultural frontier.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":"174 ","pages":"Article 127927"},"PeriodicalIF":5.5,"publicationDate":"2025-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145567794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Precision detection and geolocation of missed pre-tassels in hybrid maize seed production using UAV-based deep learning","authors":"Chenchen Ding ,&nbsp;Ruirui Zhang ,&nbsp;Jiangtao Qi ,&nbsp;Yuxin Xie ,&nbsp;Tongchuan Yi ,&nbsp;Longlong Li ,&nbsp;Mingqi Wu ,&nbsp;Weirong Zhang ,&nbsp;Zhiyuan Bao","doi":"10.1016/j.eja.2025.127923","DOIUrl":"10.1016/j.eja.2025.127923","url":null,"abstract":"<div><div>Hybrid maize seed production relies on detasseling, a critical process to ensure genetic purity by removing male pre-tassels from female plants. However, missed pre-tassels, which are immature tassels partially enclosed by leaves and similar in color to maize foliage, remain difficult to detect and typically require labor-intensive manual inspection. This study proposes an improved UAV-based detection framework, YOLO for Missed Pre-Tassel (YOLO-MPT), built upon YOLOv7 for precise identification and geolocation of missed pre-tassels in hybrid maize fields. YOLO-MPT integrates deformable convolutions (DCNv2) for adaptive feature extraction, the S²-MLPv2 attention mechanism for enhanced spatial representation, and an additional small-object detection head to increase sensitivity to tiny or occluded targets. A comprehensive UAV-derived pre-tassel dataset was constructed under diverse agronomic and lighting conditions to support model training and validation. The impact of input image size on detection performance was systematically analyzed to identify the optimal training resolution. Experimental results show that YOLO-MPT achieved an average precision (AP) of 93.8 %, precision (P) of 93.3 %, recall (R) of 90.2 %, and an F1-score of 91.7 %, outperforming baseline models. Furthermore, a geographic coordinate extraction method was developed and integrated into a standalone “Missed Pre-Tassel Detection and Localization Software,” enabling automatic conversion of pixel detections into precise geospatial locations. Field experiments verified the workflow’s robustness and positioning accuracy, demonstrating the system’s potential to improve post-detasseling efficiency and quality assurance in hybrid maize seed production.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":"173 ","pages":"Article 127923"},"PeriodicalIF":5.5,"publicationDate":"2025-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145553996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deciphering low nitrogen tolerance of wheat in mega-environments using integrated multivariate approaches","authors":"Gopalareddy Krishnappa ,&nbsp;Hanif Khan ,&nbsp;Amaresh ,&nbsp;Vinayaka ,&nbsp;T. Lakshmi Pathy ,&nbsp;Arun Gupta ,&nbsp;Anju Mahendru-Singh ,&nbsp;Arvind Kumar Ahlawat ,&nbsp;Jasavantlal Manilal Patel ,&nbsp;Suma S. Biradar ,&nbsp;Harohalli Masthigowda Mamrutha ,&nbsp;Rinki Khobra ,&nbsp;Vanita Pandey ,&nbsp;Gyanendra Pratap Singh ,&nbsp;Ratan Tiwari","doi":"10.1016/j.eja.2025.127919","DOIUrl":"10.1016/j.eja.2025.127919","url":null,"abstract":"<div><div>Enhancing low nitrogen (LN) tolerance is crucial for maintaining wheat productivity, particularly in the era of climate change and increasing input costs. This study aimed to identify high-yielding, LN-tolerant, and stable wheat genotypes using integrated multivariate approaches. Fifty diverse genotypes, including globally sourced germplasm and landmark Indian cultivars, were evaluated across three agro-climatic zones under two nitrogen regimes for two consecutive years. Pooled ANOVA revealed significant effects of genotype, nitrogen level, and genotype × environment interaction. Hierarchical clustering identified four clusters, with cluster I comprising high-yielding, nitrogen-efficient genotypes. For grain yield under nitrogen stress, NARBADA 4 was the only genotype with a BLUP based Z-score above + 2, indicating exceptional stability and yield potential. Based on the GGE’s Mean vs. Stability plot for grain yield, KRL 1–4 exhibited the highest mean performance coupled with stability. A novel metric, Gain<em>_d</em> (decadal gain index) was introduced to assess genetic gains for LN tolerance across decades. Decadal trend analysis showed non-linear gains in low-N tolerance, peaking in the 1970s and 2000s but declining in the 2010s. Comprehensive multivariate index analysis based on pooling the index ranks highlighted MACS 6222, NARBADA 4, MACS 2496, K 307, and HI 1544 as the most promising genotypes. These genotypes are promising for LN-specific breeding and genetic improvement programs, offering potential for both commercial cultivation and the mapping of nitrogen use efficiency traits. The findings pave the way for developing widely adapted LN-tolerant wheat cultivars.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":"173 ","pages":"Article 127919"},"PeriodicalIF":5.5,"publicationDate":"2025-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145579798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Potato growth, yield, and quality in response to phosphorus application rates across a range of soil test P concentrations","authors":"J. Rutan,&nbsp;K. Steinke","doi":"10.1016/j.eja.2025.127917","DOIUrl":"10.1016/j.eja.2025.127917","url":null,"abstract":"<div><div>Increased concern for both Great Lakes water quality and potato (<em>Solanum tuberosum</em> L.) phosphorus (P) requirements emphasize reviewing guidelines with regard to P fertilizer rates and potato response. Eleven field studies were conducted over a two-year period across multiple potato varieties and soil test phosphorus (STP) concentrations (64–210 mg kg⁻¹ Bray-P1) on predominantly coarse-textured soils. Six P fertilizer rates 0, 45, 90, 135, 179, and 224 kg P₂O₅ ha⁻¹ were twin banded in-furrow at planting with ammonium polyphosphate 5 cm beside and 5 cm above seed pieces. Potato yield response to added P fertilizer occurred 50, 75, and 33 % of time when STP values were deficient (i.e. &lt;75 mg kg⁻¹ Bray-P1), optimal (i.e. 75–150), or sufficient (i.e. &gt;150), respectively. Fertilizer P application to optimum testing soils protected again yield loss, but potato response to P was reduced as STP increased. In harmony with current literature, regression analysis indicated growers may apply up to 45 kg P₂O₅ ha⁻¹ as banded starter at planting regardless of STP. Mean tuber P₂O₅ removal values were reduced 13.3 % from the current reported value (1.30 kg P₂O₅ tonne⁻¹). Results highlight the continuous need for evaluating new varieties under field conditions. Soil testing remains an important tool and best management practice for judicious P management.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":"173 ","pages":"Article 127917"},"PeriodicalIF":5.5,"publicationDate":"2025-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145535816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring optimal N management based on the simulation of spring maize yield and N loss at a county scale","authors":"Fanchao Meng ,&nbsp;Lingchun Zhang ,&nbsp;Ming Li ,&nbsp;Xingai Gao ,&nbsp;Xiufei Wang ,&nbsp;Tong Yu ,&nbsp;William D. Betcholer ,&nbsp;Qiang Gao ,&nbsp;Kelin Hu ,&nbsp;Zhonghe Li","doi":"10.1016/j.eja.2025.127922","DOIUrl":"10.1016/j.eja.2025.127922","url":null,"abstract":"<div><div>Excessive nitrogen (N) fertilization has led to serious environmental problems in the black soil region of northeastern China. Understanding the spatial and temporal distribution of maize yield and N loss, as well as their driving factors, is critical for developing sustainable N management strategies. Lishu County was selected as the case study area for this research. Field experiment data from 2005 to 2013 along with related literature on N loss in the county were used to calibrate and validate the WHCNS (Water, Heat, Carbon, and Nitrogen Simulator) model. The model was then employed to simulate the spatial distribution of crop yield and N loss in Lishu County from 1991 to 2020. We further explored the potential of nitrification inhibitors (DMPP) and conservation tillage (strip tillage) to enhance yield and reduce N loss, ultimately identifying zonal N management strategies. Results demonstrated the model performed well in simulation of regional maize yield and N loss. The multi-year average maize yield in Lishu County ranged from 8861 to 12,508 kg·ha⁻¹ , with the central black soil sub-region achieving the highest yield (10,664 kg·ha⁻¹) and the western aeolian sandy soil sub-region having the lowest yield (8981 kg·ha⁻¹). Total N loss ranged from 25 to 78 kg·ha⁻¹ , with losses ranked as follows: western aeolian sandy soil area &gt; southern brown soil area &gt; central black soil area. Yield was significantly influenced by rainfall, solar radiation, and soil clay content, while N loss correlated strongly with rainfall, temperature, soil pH, and bulk density. Compared to conventional practices, DMPP application increased yields by 9.5–12.2 % and reduced N loss by 17.6–25.0 % across three sub-regions. Combining DMPP with strip tillage further enhanced yield by 4.4–6.4 % and reduced N loss by 29.4–35.0 %.Thus, integrating DMPP with strip tillage effectively balances yield improvement and N loss mitigation, offering a recommended strategy for local farmers. These findings provide a scientific basis for optimizing water and N management to minimize N loss while maintaining yield on large scale.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":"173 ","pages":"Article 127922"},"PeriodicalIF":5.5,"publicationDate":"2025-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145520622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}