Optimizing cropping systems and irrigation regimes to mitigate NH3 emissions and enhance crop productivity in the Huang-Huai-Hai Plain

Field Crops Research, Год журнала: 2025, Номер 322, С. 109763 - 109763

Опубликована: Янв. 24, 2025

Язык: Английский

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Subsurface Irrigation With Ceramic Emitters Improved the Water Productivity and Nitrogen Use Efficiency of Greenhouse Melons.

Irrigation and Drainage, Год журнала: 2025, Номер unknown

Опубликована: Янв. 28, 2025

ABSTRACT Increasing nitrogen use efficiency in agricultural fields is crucial for sustainable development. In a 2‐year greenhouse study, we compared two methods, subsurface irrigation with ceramic emitters (SICE) and drip (SDI), to evaluate their effects on soil moisture distribution, photosynthetic plant stoichiometry. The results showed that SICE can reduce the nitrate content by approximately 20% while maintaining at 70%–80%, improving melon yield. Under optimal yield treatment (applying 60.67 kg of fertilizer per hectare), SDI, increased 8%, water productivity 13%, absorption 4% 3%. addition, analysing stoichiometric characteristics different application rates growth stages under found main reason increase was coupled effect need plants maintain internal balance.

Язык: Английский

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Machine learning-driven analysis of greenhouse gas emissions from rice production in major Chinese provinces: Identifying key factors and developing reduction strategies

European Journal of Agronomy, Год журнала: 2025, Номер 164, С. 127536 - 127536

Опубликована: Фев. 6, 2025

Язык: Английский

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Optimizing irrigation and mulching strategies to improve root–water relations, water use efficiency, and yield in apple–soybean alley cropping systems on the Loess Plateau, China

European Journal of Agronomy, Год журнала: 2025, Номер 168, С. 127586 - 127586

Опубликована: Март 10, 2025

Язык: Английский

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Development of a Drought Monitoring System for Winter Wheat in the Huang-Huai-Hai Region, China, Utilizing a Machine Learning–Physical Process Hybrid Model

Agronomy, Год журнала: 2025, Номер 15(3), С. 696 - 696

Опубликована: Март 13, 2025

Droughts, intensified by climate change and human activities, pose a significant threat to winter wheat cultivation in the Huang-Huai-Hai (HHH) region. Soil moisture drought indices are crucial for monitoring agricultural droughts, while challenges such as data accessibility soil heterogeneous necessitate use of numerical simulations their effective regional-scale applications. The existing simulation methods like physical process models machine learning (ML) algorithms have limitations: struggle with parameter acquisition at regional scales, ML face difficulties settings due presence crops. As more advanced complex branch ML, deep even greater limitations related crop growth management. To address these challenges, this study proposed novel hybrid system that merged model. Initially, we employed Random Forest (RF) regression model integrated multi-source environmental factors estimate prior sowing wheat, achieving an average coefficient determination (R2) 0.8618, root mean square error (RMSE) 0.0182 m3 m−3, absolute (MAE) 0.0148 m−3 across eight depths. RF provided vital parameters operation Water Balance Winter Wheat (WBWW) scale, enabling assessments combined Moisture Anomaly Percentage Index (SMAPI). Subsequent comparative analyses between system-generated results actual disaster records during two events highlighted its efficacy. Finally, utilized examine spatiotemporal variations patterns HHH region over past decades. findings revealed overall intensification conditions decline SMAPI rate −0.021% per year. Concurrently, there has been shift patterns, characterized increase both frequency extremity events, duration intensity individual decreased majority Additionally, identified northeastern, western, southern areas requiring concentrated attention targeted intervention strategies. These efforts signify notable application fusion techniques integration within big context, thereby facilitating prevention, management, mitigation

Язык: Английский

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Post-anthesis water use and biomass accumulation in winter wheat under subsoiling and microsprinkler irrigation

Soil and Tillage Research, Год журнала: 2024, Номер 246, С. 106343 - 106343

Опубликована: Окт. 30, 2024

Язык: Английский

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