Remote sensing of quality traits in cereal and arable production systems:A review

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维普

外文摘要：Cereal is an essential source of calories and protein for the global population.Accurately predicting cereal quality before harvest is highly desirable in order to optimise management for farmers,grading harvest and categorised storage for enterprises,future trading prices,and policy planning.The use of remote sensing data with extensive spatial coverage demonstrates some potential in predicting crop quality traits.Many studies have also proposed models and methods for predicting such traits based on multi-platform remote sensing data.In this paper,the key quality traits that are of interest to producers and consumers are introduced.The literature related to grain quality prediction was analyzed in detail,and a review was conducted on remote sensing platforms,commonly used methods,potential gaps,and future trends in crop quality prediction.This review recommends new research directions that go beyond the traditional methods and discusses grain quality retrieval and the associated challenges from the per-spective of remote sensing data.

外文关键词：

Remote sensingQuality traitsGrain proteinCereal

作者：

Zhenhai Li、Chengzhi Fan、Yu Zhao、Xiuliang Jin、Raffaele Casa、Wenjiang Huang、Xiaoyu Song、Gerald Blasch、Guijun Yang、James Taylor、Zhenhong Li

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作者单位：

College of Geodesy and Geomatics,Shandong University of Science and Technology,Qingdao 266590,Shandong,China

Key Laboratory of Quantitative Remote Sensing in Ministry of Agriculture and Rural Affairs,Information Technology Research Center,Beijing Academy of Agriculture and Forestry Sciences,Beijing 100097,China

Institute of Crop Sciences,Chinese Academy of Agricultural Sciences/Key Laboratory of Crop Physiology and Ecology,Ministry of Agriculture and Rural Affairs,Beijing 100081,China

DAFNE,Università della Tuscia,Via San Camillo de Lellis,01100 Viterbo,Italy

Key Laboratory of Digital Earth Science,Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing 100094,China

International Maize and Wheat Improvement Center(CIMMYT),PO Box 5689,Addis Ababa,Ethiopia

ITAP,Univ.Montpellier,INRAE,Institut Agro,Montpellier 34000,France

College of Geological Engineering and Geomatics,Chang'an University,Xi'an 710054,Shaanxi,China

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基金：

National Natural Science Foundation of ChinaNatural Science Foundation of Shandong ProvinceKey R&D Project of Hebei ProvinceEuropean Space Agency(ESA)Ministry of Science and Technology of China(MOST)Dragon

项目编号：

42271396ZR2022MD01722326406D57457

出版年：

2024

DOI：

10.1016/j.cj.2023.10.005

作物学报(英文版)

CSTPCD

ISSN：

年,卷(期)：2024.12(1)

参考文献量107