Anhui Agricultural Science Bulletin >
2025 , Vol. 31 >Issue 5: 89 - 92
DOI: https://doi.org/10.16377/j.cnki.issn1007-7731.2025.05.019
Early diagnosis and comprehensive prevention and control techniques of wheat disease
Received date: 2024-10-24
Online published: 2025-03-13
Early diagnosis and comprehensive prevention and control techniques were explored for wheat disease, and strategies to improve the effectiveness of wheat disease prevention and control were proposed. Early diagnosis techniques include disease symptom recognition techniques that rely on disease symptom maps, deep learning algorithms, and remote sensing technology, and molecular biology techniques such as polymerase chain reaction and gene chips. Comprehensive prevention and control techniques include establishing and applying disease prediction models based on meteorological data, as well as disease prediction and warning systems; applying reasonable crop rotation systems, optimizing sowing time and density, and other agricultural operation techniques. The strategies to improve the effectiveness of wheat disease prevention and control include the research and promotion of new diagnostic technologies such as nanotechnology and biosensors, as well as the integration and application of comprehensive prevention and control technologies such as agricultural control, physical control, and chemical control, to promote the innovation of diagnosis and control technologies; the measures such as conducting on-site demonstrations, remote teaching, and organizing experience exchange meetings, and establishing demonstration bases to strengthen farmer education and technical training. The application of relevant techniques provides a reference for improving the scientific and timely prevention and control of wheat disease.
LI Yanli . Early diagnosis and comprehensive prevention and control techniques of wheat disease[J]. Anhui Agricultural Science Bulletin, 2025 , 31(5) : 89 -92 . DOI: 10.16377/j.cnki.issn1007-7731.2025.05.019
| 1 |
巴文静. 小麦早期赤霉病的近红外光谱诊断方法研究[D]. 合肥:安徽农业大学,2023.
|
| 2 |
李全凯. 小麦白粉病早期快速诊断及病情监测方法研究[D]. 泰安:山东农业大学,2022.
|
| 3 |
刘显元,李馨宇. 小麦主要病害及其综合防控技术[J]. 农业灾害研究,2022,12(11):149-151.
|
| 4 |
尹勋. 综合图谱特征信息的小麦赤霉病识别方法研究[D]. 合肥:安徽大学,2020.
|
| 5 |
崔文斌. 小麦病害图像的存储与识别技术的研究[D]. 泰安:山东农业大学,2016.
|
| 6 |
黄灿,陈沁. 现代生物技术在植物病原菌检测中的应用[J]. 食品研究与开发,2016,37(13):215-219.
|
| 7 |
李凤. 刺盘孢属真菌基因芯片检测方法研究[D]. 乌鲁木齐:新疆农业大学,2019.
|
| 8 |
马慧琴. 基于多源多时相遥感分析的小麦主要病害动态监测[D]. 南京:南京信息工程大学,2020.
|
| 9 |
郑增海. 小麦病虫害监测预警系统技术研究[J]. 粮油与饲料科技,2024(4):66-68.
|
| 10 |
刘林锋,陈松,陆松艳,等. 小麦主要病虫害发生特点及防治技术[J]. 种子科技,2023,41(18):115-117.
|
| 11 |
张俊梅,娄殿国. 信息技术在小麦玉米病虫害智能监测和诊断中的应用[J]. 农业工程技术,2024,44(26):58-59.
|
| 12 |
李春喜. 现代农业技术与管理策略对小麦产量的影响研究[J]. 粮油与饲料科技,2024(3):125-127.
|
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