气候变化领域集成服务门户(CCPortal): Assessing the long-term effects of conservation agriculture on cotton production in Northeast Louisiana using the denitrification-decomposition model

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DOI	10.1002/agg2.20514
	Assessing the long-term effects of conservation agriculture on cotton production in Northeast Louisiana using the denitrification-decomposition model
	Ferdush, Janntul; Jeong, Changyoon; Jeon, Hwangju; Wang, Jim; Ro, Kyoung; Zhang, Xi; Lee, Meesook
发表日期	2024
EISSN	2639-6696
起始页码	7
结束页码	2
卷号	7 期号:2
英文摘要	Conservation agriculture (CA) aims to sustain agricultural production, soil, and environmental health in agroecosystems and has been promoted throughout the United States. The adoption of CA in cotton (Gossypium hirsutum) systems provides both agronomic and environmental benefits. Yet, there is limited information on the long-term effects of CA practices on crop yield and adaptation strategies. An integrated CA system, that is, cover crops with no-tillage (NT) instead of conventional agriculture, was implemented in the long-term field experiments and assessed with an integrated biogeochemical model. Using the denitrification-decomposition model, this study estimated the effects of four different cover crops, for example, native grass (NG), hairy vetch (Vicia villosa), winter wheat (Triticum aestivum L.), and crimson clover (Trifolium incarnatum), on cotton yield under four different nitrogen (N) levels (e.g., 0, 50, 100, and 150 kg N/ha) and estimated responses on carbon (C) sequestration, and ecosystem functionality over a 10-year study. The NT-NG 50 N was used as a calibration dataset to accurately estimate the cotton lint yield with a normalized root mean square error (NRMSE) of 21% and model efficiency of 0.3. The calibration data validated the effects of hairy vetch, winter wheat, and crimson clover under the NT-50 N with NRMSE of 24%, 21%, and 25%, respectively. According to the scenario analysis, the 50 kg N/ha application with a single-irrigation event (10-cm depth) was most beneficial for maximizing the cotton yield with cover crop incorporation at the NT system over the long term. The effects of increasing cover crop biomass (i.e., double seed rate) on C content, regardless of N application rates, varied based on the relationship between the main and cover crop species. Besides, the furrow plow tillage system provided efficient C sequestration. The proposed approach stands to provide agricultural and environmental sustainability with the implementation of cover crop or crop residue incorporation instead of increased N application, seed rates, and irrigation events under NT practices. Adopting sustainable agricultural practices using tillage and cover crops illustrated agricultural benefits. The denitrification-decomposition (DNDC) model predicted the implementation of cover crop incorporation instead of increased N application. The DNDC model simulated the maximum crop yields with cover crop incorporation at the non-till system.
语种	英语
WOS研究方向	Agriculture
WOS类目	Agronomy
WOS记录号	WOS:001215814800001
来源期刊	AGROSYSTEMS GEOSCIENCES & ENVIRONMENT
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/305941
作者单位	Louisiana State University System; Louisiana State University System; Louisiana State University; United States Department of Agriculture (USDA); University of Louisiana System; McNeese State University
推荐引用方式 GB/T 7714	Ferdush, Janntul,Jeong, Changyoon,Jeon, Hwangju,et al. Assessing the long-term effects of conservation agriculture on cotton production in Northeast Louisiana using the denitrification-decomposition model[J],2024,7(2).
APA	Ferdush, Janntul.,Jeong, Changyoon.,Jeon, Hwangju.,Wang, Jim.,Ro, Kyoung.,...&Lee, Meesook.(2024).Assessing the long-term effects of conservation agriculture on cotton production in Northeast Louisiana using the denitrification-decomposition model.AGROSYSTEMS GEOSCIENCES & ENVIRONMENT,7(2).
MLA	Ferdush, Janntul,et al."Assessing the long-term effects of conservation agriculture on cotton production in Northeast Louisiana using the denitrification-decomposition model".AGROSYSTEMS GEOSCIENCES & ENVIRONMENT 7.2(2024).