[1]袁帅,王鑫鑫,侯升林,等.光谱成像技术在大田蔬菜种植中的应用研究进展[J].江苏农业科学,2023,51(24):1-11.
　Yuan Shuai,et al.Research progress on application of spectral imaging technology in field vegetable planting[J].Jiangsu Agricultural Sciences,2023,51(24):1-11.
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光谱成像技术在大田蔬菜种植中的应用研究进展()

《江苏农业科学》[ISSN:1002-1302/CN:32-1214/S]

卷:
第51卷
期数:
2023年第24期
页码:
1-11
栏目:
专论与综述
出版日期:
2023-12-20

文章信息/Info

Title:
Research progress on application of spectral imaging technology in field vegetable planting
作者:
袁帅1; 3; 王鑫鑫1; 4; 侯升林5; 申书兴1; 3; 范晓飞2
1.华北作物改良与调控国家重点实验室，河北保定 071000； 2.河北农业大学机电工程学院，河北保定 071000； 3.河北农业大学园艺学院，河北保定 071000； 4.河北农业大学河北省山区研究所，河北保定 071000； 5.河北省农林科学院，河北石家庄 050031
Author(s):
Yuan Shuai; et al
关键词:
蔬菜生产; 光谱传感器; 表型; 无人机成像; 品种选育
Keywords:
-
分类号:
S630.4；S127
DOI:
-
文献标志码:
A
摘要:
田间蔬菜种植周期短，因此准确掌握各种蔬菜的种植信息，及早发现蔬菜种植中的问题，对蔬菜生产有重要意义。目前，对田间蔬菜作物的生长调查通常采用肉眼观察、实验室提取等方法获取信息，不仅浪费大量人力，还可能因主观因素导致数据准确性降低。蔬菜生产与育种过程受益于高通量的表型信息获取，表型是研究“基因型-表型-环境”作用机制的桥梁。在蔬菜育种和生产中高通量表型获取技术已被广泛应用，通过高通量的表型观测，能够及早发现蔬菜生产中的问题，同时为品种选育提供支持。在大量评估田间蔬菜试验中，高通量表型信息获取常基于光谱数据。无人机搭载光谱传感器能够较全面获取蔬菜表型信息，结合机器学习以及深度学习的数据处理方法，可实现田间蔬菜种植过程中的实时监测。本文着重介绍光谱成像技术在蔬菜生产和育种上的应用，通过光谱成像技术，能够实现对田间蔬菜生长信息的监测、病虫害的早期诊断、田间土壤水分监测，并能在一定程度上辅助种植者对蔬菜进行产量预估。同时，通过无人机遥感光谱成像技术建立起的大规模生理性状和形态性状定量获取可为蔬菜新品种选育提供重要的数据支撑。
Abstract:
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备注/Memo

备注/Memo:
收稿日期：2023-03-01
基金项目：国家自然科学基金面上项目(编号：32072572)；河北省重点研发计划项目(编号：20327403D)；河北省现代农业技术体系陆地蔬菜创新团队项目(编号：HBCT2021200202)。
作者简介：袁帅(1998—)，男，河北邢台人，硕士研究生，主要从事数字化育种方向研究。E-mail：yuanshuai981003@163.com。
通信作者：申书兴，教授，主要从事蔬菜育种研究。E-mail：shensx@hebau.edu.cn。
更新日期/Last Update: 2023-12-20