基于三维模型的粮食作物多尺度表型研究：性状检测综述

IF 8.9 1区农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY

Computers and Electronics in Agriculture Pub Date : 2025-05-30 DOI:10.1016/j.compag.2025.110597

Jiangtao Qi , Fangfang Gao , Yang Wang , Weirong Zhang , Sisi Yang , Kangkang Qi , Ruirui Zhang

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引用次数: 0

摘要

作物表型分析是实现作物育种改良的可靠方法，可以为有效的农业管理和作物品种鉴定提供信息。由于作物在群体、个体和器官水平上的表型特征存在显著差异，快速准确地完成大规模作物表型仍然是一个挑战。基于三维（3D）模型的表型系统不断发展，使自动化、高精度的数据收集和细粒度的性状测量成为可能。本文对基于三维模型的粮食作物多尺度表型研究进展进行了综述和分析。研究的重点是能够评价玉米、小麦、水稻、大豆和高粱等粮食作物形态变化的性状。此外，还重点介绍了高通量表型平台、先进传感器技术和人工智能在表型数据处理中的应用。揭示了基因-环境-表型复杂相互作用的新趋势。最后对研究进展、主要挑战和未来展望进行了讨论，希望为研究者和准备进入该领域的研究者提供一定的视角。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Multiscale phenotyping of grain crops based on three-dimensional models: A comprehensive review of trait detection

Crop phenotyping is a reliable method for achieving crop breeding improvement, which can provide information for effective agricultural management and crop variety identification. Due to the significant differences in phenotypic characteristics of crops at the population, individual, and organ levels, it is still challenging to quickly and accurately complete large-scale crop phenotyping. Increasingly, phenotyping systems based on three-dimensional (3D) models have been continuously developed, making automated, high-precision data collection and fine-grained trait measurement possible. A review is performed to investigate and analyze the research work regarding multi-scale phenotyping of grain crops based on three-dimensional (3D) models. The focus is on traits that can evaluate the morphological changes of grain crops including maize, wheat, rice, soybean, and sorghum. Besides, the application of high-throughput phenotyping platforms, advanced sensor technologies, and artificial intelligence in phenotypic data processing is highlighted. New trends in the complex interaction of gene-environment-phenotype are revealed. Finally, research progress, major challenges and future prospects were discussed, hoping to provide a certain perspective for researchers and researchers preparing to enter this field.

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来源期刊

Computers and Electronics in Agriculture 工程技术-计算机：跨学科应用

CiteScore

15.30

自引率

14.50%

发文量

800

审稿时长

62 days

期刊介绍： Computers and Electronics in Agriculture provides international coverage of advancements in computer hardware, software, electronic instrumentation, and control systems applied to agricultural challenges. Encompassing agronomy, horticulture, forestry, aquaculture, and animal farming, the journal publishes original papers, reviews, and applications notes. It explores the use of computers and electronics in plant or animal agricultural production, covering topics like agricultural soils, water, pests, controlled environments, and waste. The scope extends to on-farm post-harvest operations and relevant technologies, including artificial intelligence, sensors, machine vision, robotics, networking, and simulation modeling. Its companion journal, Smart Agricultural Technology, continues the focus on smart applications in production agriculture.