Multi-Objective Optimization of Staple Crop Production for Yield, Carbon Sequestration, and Greenhouse Gas Mitigation

Topic Information

Dear Colleagues,

As climate change and environmental sustainability pose increasingly critical challenges, improving agricultural practices to enhance both productivity and environmental performance is essential. Key strategies include optimizing crop yield while promoting carbon sequestration and mitigating greenhouse gas emissions. Innovative farming practices such as integrated systems, including rice–crayfish co-culture, offer ecosystem-based solutions that enhance productivity and reduce environmental impacts. Water-saving irrigation technologies and soil quality management are also crucial in improving crop physiology and minimizing the environmental footprint of farming. Additionally, precision agriculture techniques, such as spatial modeling and nitrogen management, enable the more efficient use of resources and help mitigate greenhouse gas emissions. These combined approaches provide a holistic strategy for sustainable crop production systems that balance agricultural productivity with environmental stewardship.

This Topic aims to showcase the latest interdisciplinary research on the optimization of multi-objective management strategies in agricultural systems, focusing on major staple crops such as rice, wheat, maize, and other key food crops. The goal is to improve crop yields while simultaneously enhancing carbon sequestration and mitigating greenhouse gas emissions, crucial for sustainable agricultural intensification.

We invite submissions to this Topic that explore strategies, technologies, and methodologies for optimizing crop production systems. Topics of particular interest include, but are not limited to, the following:

• Innovative strategies for water, nitrogen, and organic material management in multi-crop systems to enhance yield, carbon sequestration, and mitigate greenhouse gas emissions;
• Integration of crop cultivation and animal farming systems to promote a biodiverse food supply while minimizing environmental costs;
• Water-efficient agricultural practices and advanced irrigation technologies for sustainable crop growth;
• Crop physiology and management techniques designed to reduce environmental impact while boosting productivity;
• Assessment and reduction in greenhouse gas emissions and carbon footprint in crop production systems;
• Integrated approaches to carbon sequestration and ecosystem services within agricultural systems;
• Spatial modeling and analytical techniques for optimizing nitrogen and carbon management in staple crop systems;
• Data-driven models and machine learning-based spatial prediction technologies for enhancing crop yield and reducing greenhouse gas emissions.

This Topic aims to foster a deeper understanding of these critical issues and provide a platform for researchers and practitioners from diverse fields to share the latest developments and innovations, offering practical solutions for achieving sustainable, climate-smart agricultural practices. We look forward to receiving your contributions. 

Dr. Qiang Xu
Dr. Wei Yang
Dr. Ziyin Shang
Dr. Peng Zhang
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Agriculture agriculture	3.6	6.3	2011	18.8 Days	CHF 2600	Submit
Agronomy agronomy	3.4	6.7	2011	17 Days	CHF 2600	Submit
Atmosphere atmosphere	2.3	4.9	2010	19.7 Days	CHF 2400	Submit
Crops crops	1.9	2.4	2021	22.4 Days	CHF 1200	Submit
Land land	3.2	5.9	2012	17.5 Days	CHF 2600	Submit
Methane methane	-	-	2022	18.8 Days	CHF 1000	Submit
Nitrogen nitrogen	2.3	2.8	2020	16.7 Days	CHF 1200	Submit
Plants plants	4.1	7.6	2012	16.5 Days	CHF 2700	Submit

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All Agronomy Crops Land Plants Atmosphere Nitrogen Agriculture Methane

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Open AccessArticle

Spatio-Temporal Optimization of Rice Irrigation at Raster Scale: Synergies Between Water Productivity and Methane Emission Reduction

by Lijuan Wang, Haiyan Li, Yingshan Chen, Hongda Lian, Yan Sha and Wenhao Dong

Agriculture 2026, 16(5), 624; https://doi.org/10.3390/agriculture16050624 - 9 Mar 2026

Viewed by 485

Abstract

This study addresses the challenges of coordinating spatio-temporal water allocation to optimize water productivity and reduce carbon emissions in water resource management, particularly the lack of high-resolution, integrated optimization frameworks capable of simultaneously tackling water scarcity and greenhouse gas (GHG) emissions. We propose [...] Read more.

This study addresses the challenges of coordinating spatio-temporal water allocation to optimize water productivity and reduce carbon emissions in water resource management, particularly the lack of high-resolution, integrated optimization frameworks capable of simultaneously tackling water scarcity and greenhouse gas (GHG) emissions. We propose a modeling approach for large-scale regional rice irrigation that explicitly represents the physical-process-based relationships among irrigation water, yield, and methane (CH₄) emissions. Using GIS, a grid-based simulation domain was constructed at a 500 m × 500 m resolution, and the GIS-DSSAT and GIS-DNDC models were employed to simulate yield and CH₄ emissions under varying irrigation amounts. The Random Forest algorithm—selected for its ability to capture complex nonlinear interactions—was used to establish the response surfaces linking irrigation water, yield, and CH₄ emissions. A spatio-temporal irrigation optimization model was then developed to simultaneously reduce CH₄ emissions and enhance water productivity. This methodology was applied to the Sanjiang Plain in Heilongjiang Province, where the NSGA-II algorithm was used to derive optimal irrigation schemes for rice cultivation across 408,264 grid cells. The results revealed quadratic nonlinear relationships between irrigation water amount, yield, and CH₄ emissions. Compared to the conventional irrigation practice in the region, which typically involves 15–20 flood irrigation events per season, the optimized irrigation schedule comprised 7–14 events—with 12 events accounting for 42% of the cases—and an irrigation duration ranging from day 137 to 256. This led to a 10.3% reduction in total irrigation volume, a 9.6% decrease in CH₄ emissions per unit yield, and a 21.8% increase in water productivity. This study provides valuable decision support for optimizing regional water allocation and developing rice cultivation strategies that improve productivity while reducing emissions. Full article

(This article belongs to the Topic Multi-Objective Optimization of Staple Crop Production for Yield, Carbon Sequestration, and Greenhouse Gas Mitigation)

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