首页|Integrating artificial intelligence and high-throughput phenotyping for crop improvement

Integrating artificial intelligence and high-throughput phenotyping for crop improvement

扫码查看
原文链接
  • 国家科技期刊平台
  • NETL
  • NSTL
  • 万方数据
Crop improvement is crucial for addressing the global challenges of food security and sustainable agriculture.Recent advancements in high-throughput phenotyping(HTP)technologies and artificial intelligence(AI)have revolutionized the field,enabling rapid and accurate assessment of crop traits on a large scale.The integration of AI and machine learning algorithms with HTP data has unlocked new opportunities for crop improvement.AI algorithms can analyze and interpret large datasets,and extract meaningful patterns and correlations between phenotypic traits and genetic factors.These technologies have the potential to revolutionize plant breeding programs by providing breeders with efficient and accurate tools for trait selection,thereby reducing the time and cost required for variety development.However,further research and collaboration are needed to overcome the existing challenges and fully unlock the power of HTP and AI in crop improvement.By leveraging AI algorithms,researchers can efficiently analyze phenotypic data,uncover complex patterns,and establish predictive models that enable precise trait selection and crop breeding.The aim of this review is to explore the transformative potential of integrating HTP and AI in crop improvement.This review will encompass an in-depth analysis of recent advances and applications,highlighting the numerous benefits and challenges associated with HTP and AI.

artificial intelligencecrop improvementdata analysishigh-throughput phenotypingmachine learningprecision agriculturetrait selection

Mansoor Sheikh、Farooq Iqra、Hamadani Ambreen、Kumar A Pravin、Manzoor Ikra、Yong Suk Chung

展开 >

Phenomics Laboratory,Department of Plant Resources and Environment,Jeju National University,Jeju 63234,Republic of Korea

Council of Scientific & Industrial Research,Indian Institute of Integrative Medicine,Pulwama,J&K 192301,India

Animal and Dairy Science,University of Wisconsin,Madison,WI 530706,United States of America

Division of Fruit Science,Faculty of Horticulture,Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir,Srinagar 190025,India

展开 >

Standardization and Integration of Resources Information for Seedcluster in Hub-Spoke Material Bank Program,Rural Developmen

PJ01587004

2024

10.1016/j.jia.2023.10.019

农业科学学报(英文)
中国农业科学院农业信息研究所

农业科学学报(英文)

CSTPCD
影响因子：0.576
ISSN：2095-3119
年,卷(期)：2024.23(6)
  • 106