Giorgia Raimondi, Carmelo Maucieri, Maurizio Borin, José Luis Pancorbo, Miguel Cabrera, Miguel Quemada
{"title":"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","authors":"Giorgia Raimondi, Carmelo Maucieri, Maurizio Borin, José Luis Pancorbo, Miguel Cabrera, Miguel Quemada","doi":"10.1007/s13593-023-00922-8","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":7721,"journal":{"name":"Agronomy for Sustainable Development","volume":"43 5","pages":""},"PeriodicalIF":6.4000,"publicationDate":"2023-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13593-023-00922-8.pdf","citationCount":"0","resultStr":"{\"title\":\"Satellite imagery and modeling contribute understanding cover crop effect on nitrogen dynamics and water availability\",\"authors\":\"Giorgia Raimondi, Carmelo Maucieri, Maurizio Borin, José Luis Pancorbo, Miguel Cabrera, Miguel Quemada\",\"doi\":\"10.1007/s13593-023-00922-8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>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.</p></div>\",\"PeriodicalId\":7721,\"journal\":{\"name\":\"Agronomy for Sustainable Development\",\"volume\":\"43 5\",\"pages\":\"\"},\"PeriodicalIF\":6.4000,\"publicationDate\":\"2023-10-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://link.springer.com/content/pdf/10.1007/s13593-023-00922-8.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Agronomy for Sustainable Development\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s13593-023-00922-8\",\"RegionNum\":1,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AGRONOMY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Agronomy for Sustainable Development","FirstCategoryId":"97","ListUrlMain":"https://link.springer.com/article/10.1007/s13593-023-00922-8","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRONOMY","Score":null,"Total":0}
Satellite imagery and modeling contribute understanding cover crop effect on nitrogen dynamics and water availability
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.
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.