Spectrum imaging for phenotypic detection of greenhouse vegetables: A review

IF 7.7 1区 农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY
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Abstract

Greenhouse vegetables have become increasingly important in global crop production due to their ability to be cultivated out of season and ensure a year-round supply of vegetables. With the rapid advancement of “phenomics”, accurately measuring the phenotypic information of greenhouse vegetables is crucial for enhancing both their yield and quality. Over the past two decades, various technologies have been developed for phenotypic detection of fruits, vegetables, and other crops, based on the interaction between electromagnetic waves and matter. While some articles have investigated these applications, there is a lack of a systematic review specifically focused on the phenotypic detection of greenhouse vegetables. In this review, RGB imaging, Multispectral/Hyperspectral imaging, Chlorophyll fluorescence imaging, Thermal imaging, Raman imaging, X-ray imaging, Magnetic resonance imaging, and Terahertz imaging are collectively referred to as spectrum imaging technologies. We provide a comprehensive review of the origins, research progress over the past twenty years, and current challenges of spectrum imaging in the field of greenhouse vegetable research. It focuses on identifying the most suitable spectrum imaging technologies for detecting four categories of phenotypic traits: biochemical, physiological, morphological, and yield-related traits. Additionally, we highlight the issues that need optimization in the practical application of these technologies and the bottlenecks faced in different trait studies. Finally, based on existing research, we propose several potential solutions and future research directions to maximize the utility of spectrum imaging technologies in the phenotypic detection of greenhouse vegetables.

用于温室蔬菜表型检测的光谱成像:综述
温室蔬菜可以反季节栽培,确保全年蔬菜供应,因此在全球作物生产中的地位日益重要。随着 "表型组学 "的快速发展,准确测量温室蔬菜的表型信息对于提高其产量和质量至关重要。在过去的二十年里,基于电磁波与物质之间的相互作用,已经开发出了各种用于水果、蔬菜和其他作物表型检测的技术。虽然一些文章对这些应用进行了研究,但缺乏专门针对温室蔬菜表型检测的系统综述。在本综述中,RGB 成像、多光谱/高光谱成像、叶绿素荧光成像、热成像、拉曼成像、X 射线成像、磁共振成像和太赫兹成像统称为光谱成像技术。我们全面回顾了光谱成像技术的起源、过去二十年的研究进展以及目前在温室蔬菜研究领域面临的挑战。重点是确定最适合检测四类表型性状(生化、生理、形态和产量相关性状)的光谱成像技术。此外,我们还强调了这些技术在实际应用中需要优化的问题以及不同性状研究中面临的瓶颈。最后,在现有研究的基础上,我们提出了几个潜在的解决方案和未来的研究方向,以最大限度地发挥光谱成像技术在温室蔬菜表型检测中的作用。
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来源期刊
Computers and Electronics in Agriculture
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.
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