Satellite imagery and modeling contribute understanding cover crop effect on nitrogen dynamics and water availability

IF 6.4 1区 农林科学 Q1 AGRONOMY
Giorgia Raimondi, Carmelo Maucieri, Maurizio Borin, José Luis Pancorbo, Miguel Cabrera, Miguel Quemada
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引用次数: 0

Abstract

Cover crops (CCs) can affect the cropping systems’ N dynamics and soil water content (SWC), but optimizing their potential effects requires knowledge of their growth pattern, N accumulation, and mineralization. For this purpose, a 3-year field experiment was initiated in northeast Italy involving a maize-soybean rotation. The objectives of this study were to (i) evaluate the use of time series vegetation indices (VIs) obtained from the Sentinel-2 satellite for monitoring the growth of CCs and estimating their biomass and N uptake at termination; (ii) investigate the effects of different CCs on cash crop yield and SWC; and (iii) use the simulation model CC-NCALC to predict the nitrogen contribution of CCs to subsequent cash crops. Three CC systems were tested: a fixed treatment with triticale; a 3-year succession of rye, crimson clover, and mustard; and a control with no CCs. Satellite imagery revealed that rye and triticale grew faster during the winter season than clover but slower compared to mustard, which suffered a frost winterkilling. Both grasses and mustard produced greater biomass at termination compared to clover, but none of the CC species affected SWC or yield and N uptake of the cash crop. A net N mineralization of all the CC residues was estimated by the model (except for the N immobilization after triticale roots residues). During the subsequent cash crop season, the estimated clover and mustard N released was around 33%, and the triticale around 3% of their total N uptake, with a release peak 2 months after their termination. The use of remote sensing imagery and a prediction model of CC residue decomposition showed potential to be used as instruments for optimizing the CCs utilization and enhancing cropping water and N fertilization management efficiency; however, it must be further analyzed with other CCs species, environmental conditions, and cropping systems.

Abstract Image

卫星图像和模型有助于理解覆盖作物对氮动态和水分有效性的影响
覆盖作物(CCs)可以影响种植系统的氮动态和土壤含水量(SWC),但优化其潜在影响需要了解其生长模式、氮积累和矿化。为此,在意大利东北部开展了一项为期3年的玉米-大豆轮作田间试验。本研究的目的是:(i)评估从Sentinel-2卫星获得的时间序列植被指数(VIs)在监测CCs生长和估计其终止时的生物量和氮吸收量方面的应用;(ii)研究不同碳汇对经济作物产量和SWC的影响;(iii)利用CC-NCALC模拟模型预测CCs对后续经济作物的氮贡献。试验了三种CC体系:用小黑麦固定处理;连续3年种植黑麦、深红色三叶草和芥菜;另一组是没有CCs的对照组。卫星图像显示,黑麦和小黑麦在冬季的生长速度比三叶草快,但比遭受霜冻过冬的芥菜慢。与三叶草相比,草和芥菜在终止时产生了更大的生物量,但没有一种CC物种影响SWC或产量和经济作物的氮吸收。该模型估计了所有CC残基的净氮矿化(小黑麦根残基后的氮固定除外)。在随后的经济作物季节,估计三叶草和芥菜的氮素释放量约为33%,小黑麦的氮素释放量约为其总吸收量的3%,在终止后2个月达到释放高峰。利用遥感影像和秸秆秸秆分解预测模型可作为优化秸秆秸秆利用和提高作物水氮施肥管理效率的工具;然而,它必须与其他CCs物种、环境条件和种植制度进一步分析。
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来源期刊
Agronomy for Sustainable Development
Agronomy for Sustainable Development 农林科学-农艺学
CiteScore
10.70
自引率
8.20%
发文量
108
审稿时长
3 months
期刊介绍: Agronomy for Sustainable Development (ASD) is a peer-reviewed scientific journal of international scope, dedicated to publishing original research articles, review articles, and meta-analyses aimed at improving sustainability in agricultural and food systems. The journal serves as a bridge between agronomy, cropping, and farming system research and various other disciplines including ecology, genetics, economics, and social sciences. ASD encourages studies in agroecology, participatory research, and interdisciplinary approaches, with a focus on systems thinking applied at different scales from field to global levels. Research articles published in ASD should present significant scientific advancements compared to existing knowledge, within an international context. Review articles should critically evaluate emerging topics, and opinion papers may also be submitted as reviews. Meta-analysis articles should provide clear contributions to resolving widely debated scientific questions.
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