Explore the evolution of winter wheat production and its response to climate change under varying precipitation years in the Loess Plateau of China

Agricultural Water Management, Journal Year: 2025, Volume and Issue: 309, P. 109335 - 109335

Published: Feb. 4, 2025

Language: Английский

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Research trends and gaps in climate change impacts and adaptation potentials in major crops

Current Opinion in Environmental Sustainability, Journal Year: 2023, Volume and Issue: 60, P. 101249 - 101249

Published: Jan. 7, 2023

Language: Английский

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Grain legume response to future climate and adaptation strategies in Europe: A review of simulation studies

European Journal of Agronomy, Journal Year: 2023, Volume and Issue: 153, P. 127056 - 127056

Published: Dec. 12, 2023

Language: Английский

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Simulation of climate-adaptation responses to rainfall variability on rainfed yield anomalies

Environmental and Sustainability Indicators, Journal Year: 2024, Volume and Issue: 22, P. 100411 - 100411

Published: May 14, 2024

Climate adaptation offers promising approaches to cope with the detrimental impacts of climate change on rainfed agriculture, intending mitigate yield losses and safeguard food security worldwide. This is especially critical in semi-arid tropics, characterized by highly variable often intensified rainfall regimes. The current study explored potential contribution measures, specifically sowing windows supplemental irrigation (SI), offset variability crop Thondamuthur block, India. Under proposed this analyzed relationship between historical (1951–2019) rice, maize, sorghum anomalies. A seamlessly integrated framework was developed link analysis response simulations using AquaCrop model. Rainfall classification indicated an increase availability during Kharif season a decrease Rabi Period III compared baseline. late-sown early-sown crops demonstrated effective adaptation, 27th 38th SMWs identified as optimal climate-adapted weeks, respectively. Significant decreases 10% 12% SI requirements were observed maize sorghum, results showed that substituting rice led reductions 90% 75% seasonal requirements, contributed 88% relative increases, respectively, normal-sown. highlights effectiveness measures enabling farmers withstand climate-induced

Language: Английский

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Transdisciplinary coordination is essential for advancing agricultural modeling with machine learning

One Earth, Journal Year: 2025, Volume and Issue: 8(4), P. 101233 - 101233

Published: April 1, 2025

Language: Английский

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Are Supervised Learning Methods Suitable for Estimating Crop Water Consumption under Optimal and Deficit Irrigation?

Agronomy, Journal Year: 2024, Volume and Issue: 14(3), P. 532 - 532

Published: March 4, 2024

This study examined the performance of random forest (RF), support vector machine (SVM) and adaptive boosting (AB) learning models used to estimate daily potato crop evapotranspiration adjusted (ETc-adj) under full irrigation (I100), 50% supply (I50) rainfed cultivation (I0). Five scenarios weather, soil data availability were considered: (S1) reference precipitation, (S2) S1 coefficient, (S3) S2, fraction total available water root depth, (S4) S2 water, (S5) S3 water. The was compared with standard FAO56 calculation procedure. most accurate ETc-adj estimates observed AB4 for I100, RF3 I50 AB5 I0 coefficients determination (R2) 0.992, 0.816 0.922, slopes 1.004, 0.999 0.972, modelling efficiencies (EF) 0.815 0.917, mean absolute errors (MAE) 0.125, 0.405 0.241 mm day−1, square (RMSE) 0.171, 0.579 0.359 day−1 squared (MSE) 0.029, 0.335 0.129 respectively. AB model is suggested prediction I100 conditions, while RF recommended condition.

Language: Английский

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Cropping Systems and Application of Models

Published: Jan. 1, 2024

Deterioration of land due to intensive agriculture is creating trouble for food security. Hence, appropriate measures should be taken prevent from destruction. This includes adoption sustainable cropping systems under changing climate through the aid process-based models. Cropping and application models are closely intertwined in modern agriculture. Crop models, often referred as agricultural or crop simulation mathematical computational tools used simulate predict growth behavior crops various environmental management conditions. These valuable optimizing systems, enhancing productivity, addressing sustainability challenges. In this chapter, we elaborate how can assist designing by simulating performance different rotations specific climatic, soil, conditions that helps farmers planners choose most patterns achieve their goals, whether it maximizing yields, minimizing risk, promoting sustainability, e.g., regenerative Similarly, help select suitable varieties species region climate. Furthermore, they effects rotation on soil health, pest disease management, overall system sustainability. Farmers use these plan enhance fertility, reduce risk pests diseases, improve long-term productivity. optimize sowing harvest timing maximize yields quality consider factors such climate, conditions, stages recommend best planting harvesting. resource use, including water, nutrients, pesticides make informed decisions about irrigation scheduling, nutrient rates, control measures, reducing waste impact. With change, critical adapting They will perform altered scenarios guide selection climate-resilient practices. provide yield predictions based current future allowing estimate expected harvest. information essential insurance, marketing, financial planning. Researchers test new practices, varieties, technologies a virtual environment. accelerates development testing innovative approaches systems. Policymakers extension services design promote policies align with security goals. Finally, educating professionals principles management. practical way understand complex interactions

Language: Английский

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Predicted yield and soil organic carbon changes in grassland, arable, woodland, and agroforestry systems under climate change in a cool temperate Atlantic climate

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: July 12, 2024

This study predicts the effects of climate change on crop yields, timber volumes and soil organic carbon in grassland, arable, ash woodland, poplar plantation, silvopastoral silvoarable systems Northern Ireland. We modified a version biophysical Yield-SAFE agroforestry model that includes RothC module also effect atmospheric CO₂ fertilisation. The was calibrated using existing field measurements weather data from 1989 to 2021. two future scenarios were modelled, based representative concentration pathways (RCP 4.5 RCP 8.5) for 2020–2060 2060–2100. revealed impact grass arable tree growth positive with fertilisation more than offsetting generally negative increased temperatures drought stress yields. predicted land equivalent ratio (LER) remained relatively constant between baseline system (1.08 1.11). corresponding values 0.87–0.92 yields alone, or 1.11–1.17 if included. In system, but not suggested would benefit relative understorey crop. Greater losses under barley-only (1.02–1.18 t C ha^{− 1} yr^{− 1}) grassland (0.48–0.55 1), small differences scenarios. However, analysis indicated these could be mitigated by planting trees, this immediate as matter continue decline first 10 years until trees well-established. used examine different densities trade-offs volume

Language: Английский

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Adaptation of Tourism Transformation in Rural Areas under the Background of Regime Shift: A Social–Ecological Systems Framework

Systems, Journal Year: 2024, Volume and Issue: 12(8), P. 289 - 289

Published: Aug. 8, 2024

The rural transformation driven by regime shift is obvious around the world, and there still insufficient research exploring related effective analytical frameworks ideas. Transformation adaptation widely used in field of disaster as a concept dynamic systems’ evolutionary development, emphasizing fundamental changes structure or function systems promoting equity justice for communities social–ecological systems. This paper critically reviews synthesizes literature on to construct an evaluation framework transformative applied analysis adaptive process, capacity, outcomes tourism different cases Shaanxi Province, China. results were follows: (1) state process has diversified, while with active better capacity outcomes; (2) strong community foundation benefit-sharing development model can promote system; (3) social relationship networks, farmers’ collective interests discourse power, economic material conditions are key factors affecting transformation. study provides practical tools opportunities improving at global level.

Language: Английский

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Editorial overview: Navigating climate challenges for the future of food systems

Current Opinion in Environmental Sustainability, Journal Year: 2024, Volume and Issue: 69, P. 101450 - 101450

Published: June 18, 2024

Language: Английский

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