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

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

机构地区：[1]College of Geodesy and Geomatics,Shandong University of Science and Technology,Qingdao 266590,Shandong,China [2]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 [3]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 [4]DAFNE,Universitàdella Tuscia,Via San Camillo de Lellis,01100 Viterbo,Italy [5]Key Laboratory of Digital Earth Science,Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing 100094,China [6]International Maize and Wheat Improvement Center(CIMMYT),PO Box 5689,Addis Ababa,Ethiopia [7]ITAP,Univ.Montpellier,INRAE,Institut Agro,Montpellier 34000,France [8]College of Geological Engineering and Geomatics,Chang’an University,Xi’an 710054,Shaanxi,China

出　　处：《The Crop Journal》2024年第1期45-57,共13页作物学报（英文版）

基　　金：This study was supported by the National Natural Science Foundation of China(42271396);the Natural Science Foundation of Shandong Province(ZR2022MD017);the Key R&D Project of Hebei Province(22326406D);The European Space Agency(ESA)and Ministry of Science and Technology of China(MOST)Dragon(57457).

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 multiplatform 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 perspective of remote sensing data.

关 键 词：Remote sensing Quality traits Grain protein CEREAL 

分 类 号：S127[农业科学—农业基础科学]