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Classification of Rice Yield Using UAV-Based Hyperspectral Imagery and Lodging Feature

Plant Phenomics 2021年第1期3卷 115-128页

作者： Jian Wang Bizhi Wu markus vkohnen Daqi Lin Changcai Yang Xiaowei Wang Ailing Qiang Wei Liu Jianbin Kang Hua Li Jing Shen Tianhao Yao Jun Su Bangyu Li Lianfeng Gu Institute of Crop Sciences Ningxia Academy of Agriculture and Forestry ScienceYinchuanNingxia 750105China Basic Forestry and Proteomics Research Center College of ForestryFujian Agriculture and Forestry UniversityFuzhou 350002China State Key Laboratory of Marine Environmental Science Xiamen UniversityChina Digital Fujian Institute of Big Data for Agriculture and Forestry Key Laboratory of Smart Agriculture and ForestryFujian Agriculture and Forestry UniversityFuzhou 350002China Seed Workstations of the Ningxia Hui Autonomous Region YinchuanNingxia 750004China Aerospace Information Research Center Institute of AutomationChinese Academic ScienceBeijing 100190China

High-yield rice cultivation is an effective way to address the increasing food demand *** classification of high-yield rice is a key step of ***,manual measurements within breeding programs are time consuming and have high cost and low throughput,which limit the application in large-scale field *** this study,we developed an accurate large-scale approach and presented the potential usage of hyperspectral data for rice yield measurement using the XGBoost algorithm to speed up the rice breeding process for many *** total,13 japonica rice lines in regional trials in northern China were divided into different categories according to the manual measurement of *** an Unmanned Aerial Vehicle(UAV)platform equipped with a hyperspectral camera to capture images over multiple time series,a rice yield classification model based on the XGBoost algorithm was *** comparison experiments were carried out through the intraline test and the interline test considering lodging characteristics at the midmature stage or *** result revealed that the degree of lodging in the midmature stage was an important feature affecting the classification accuracy of ***,we developed a low-cost,high-throughput phenotyping and nondestructive method by combining UAV-based hyperspectral measurements and machine learning for estimation of rice yield to improve rice breeding efficiency.

关键词： breeding equipped consuming

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