Advances and Developments in Monitoring and Inversion of the Biochemical Information of Crop Nutrients Based on Hyperspectral Technology

Author:

Zhang Yali123ORCID,Xiao Junqi123,Yan Kangting234,Lu Xiaoyang123,Li Wanjian123,Tian Haoxin5,Wang Linlin6,Deng Jizhong123,Lan Yubin234

Affiliation:

1. College of Engineering, South China Agricultural University, Wushan Road, Guangzhou 510642, China

2. Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, China

3. National Center for International Collaboration Research on Precision Agricultural Aviation Pesticide Spraying Technology, Guangzhou 510642, China

4. College of Electronic Engineering and College of Artificial Intelligence, South China Agricultural University, Wushan Road, Guangzhou 510642, China

5. College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China

6. School of Artifificial Intelligence, Shenzhen Polytechnic University, Shenzhen 518055, China

Abstract

Crop nutrient biochemical information (mainly including chlorophyll class and nutrient elements mainly nitrogen, phosphorus and potassium) is an important basis for revealing crop growth and development patterns and their relationship with the environment. Hyperspectral technology has been rapidly developed and applied in crop nutrient biochemical information monitoring research. This paper firstly describes the theoretical basis of hyperspectral technology for monitoring crop nutrients and biochemical information. Then, the research progress of hyperspectral technology in monitoring nutrient and biochemical information of crops in different growth periods or different growth environments is outlined. Meanwhile, the shortcomings of the current technology in these research directions and the future research trends are discussed. Finally, the modeling methods for building crop nutrient biochemical information monitoring models by applying hyperspectral data are systematically outlined. And the effects of different spectral pre-processing methods, spectral effective information extraction methods and modeling algorithms on the accuracy of monitoring models are analyzed. On this basis, the challenges and prospects of hyperspectral technology in monitoring crop nutrient biochemical information are presented, aiming to provide relevant theoretical basis and technical reference for the research related to monitoring and inversion of crop physiological parameters based on hyperspectral technology.

Funder

Laboratory of Lingnan Modern Agriculture Project

the Key Field Research and Development Plan of Guangdong Province

the 111 Project

Publisher

MDPI AG

Subject

Agronomy and Crop Science

Reference119 articles.

1. Critical Review of Fast Detection of Crop Nutrient and Physiological Information with Spectral and Imaging Technology;He;Trans. Chin. Soc. Agric. Eng.,2015

2. Growth, Physiology, and Biochemical Activities of Plant Responses with Foliar Potassium Application under Drought Stress—A Review;Ahmad;J. Plant Nutr.,2018

3. Precision Fertilization by UAV for Rice at Tillering Stage in Cold Region Based on Hyperspectral Remote Sensing Prescription Map;Yu;Trans. CSAE,2020

4. Simultaneous Inversion Method of Nitrogen and Phosphorus Contents in Rice Leaves Using CARS-RUN-ELM Algorithm;Tongyu;Trans. Chin. Soc. Agric. Eng.,2022

5. Study on Hyperspectral Estimation Models for Potassium Content of Rubber Tree Leaves;Li;Southwest China J. Agric. Sci.,2020

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3