Assessing the impact of low-temperature stress during anthesis stage on winter wheat grain development through computer vision and machine learning.

Ophthalmology Pediatrics
Journal: Journal of the science of food and agriculture
Published Date: May 12, 2025

Abstract

BACKGROUND: Extreme weather events, particularly spring low-temperature stress exacerbated by global warming, have become increasingly prevalent in the Huang-Huai-Hai Basin over the past 40 years, a key wheat-producing area in China. This study aims to assess the impact of low-temperature stress during the anthesis stage on the shape and texture parameters of RGB images of both superior and inferior grains of Jimai 22, utilizing computer vision and machine learning techniques.

Authors

  • Wenyi Zeng
    Jiangsu Provincial University Key Laboratory of Agricultural and Ecological Meteorology, Nanjing University of Information Science and Technology, Nanjing, China.
  • Xiaodong Jiang
    Jiangsu Provincial University Key Laboratory of Agricultural and Ecological Meteorology, Nanjing University of Information Science and Technology, Nanjing, China.
  • Qiuhui Chen
    Jiangsu Provincial University Key Laboratory of Agricultural and Ecological Meteorology, Nanjing University of Information Science and Technology, Nanjing, China.
  • Jianqu Zhang
    Jiangsu Provincial University Key Laboratory of Agricultural and Ecological Meteorology, Nanjing University of Information Science and Technology, Nanjing, China.
  • Chunnian Fan
    School of Computer Science, Nanjing University of Information Science and Technology, Nanjing, China.
  • Zaiqiang Yang
    Jiangsu Provincial University Key Laboratory of Agricultural and Ecological Meteorology, Nanjing University of Information Science and Technology, Nanjing, China.

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