Monitoring and predicting Fusarium wilt disease in cucumbers based on quantitative analysis of kinetic imaging of chlorophyll fluorescence-Reference-Cited by-同舟云学术

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Monitoring and predicting Fusarium wilt disease in cucumbers based on quantitative analysis of kinetic imaging of chlorophyll fluorescence

Published:2020-10-07 Issue:29 Volume:59 Page:9118
ISSN:1559-128X
Container-title:Applied Optics
language:en
Short-container-title:Appl. Opt.

Author:

Zhou Chunyan^ORCID,Mao Jiandong,Zhao Hu,Rao Zhimin,Zhang Bai

Funder

Ningxia Natural Science Foundation Projects

Ningxia First-class Discipline and Scientific Research Projects

Key Research Project of North Minzu University

Publisher

The Optical Society

Subject

Atomic and Molecular Physics, and Optics,Engineering (miscellaneous),Electrical and Electronic Engineering

Reference26 articles.

1. Natural Sources of Plant Disease Resistance and their Importance in the Breeding

2. Control of Fusarium wilt disease of cucumber plants with the application of a bioorganic fertilizer

3. Studies on Fusarium wilt Disease of Cucumber

4. Advanced methods of plant disease detection. A review

5. A review of advanced techniques for detecting plant diseases

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1. Application of Fluorescence Spectroscopy for Early Detection of Fungal Infection of Winter Wheat Grains;AgriEngineering;2024-09-04

2. Predictive analysis of effects of water stress on strawberry seedlings using fluorescent image channel components;Review of Scientific Instruments;2023-12-01

3. Application of Chlorophyll Fluorescence Dynamics Imaging in Leaf Blight Disease Diagnosis of Barbary Wolfberry by Implementing Machine Learning;Russian Journal of Plant Physiology;2023-06-22

4. Chlorophyll Fluorescence Imaging Combined with Active Oxygen Metabolism for Classification of Similar Diseases in Cucumber Plants;Agronomy;2023-02-27

5. Automatic leaf diseases detection and classification of cucumber leaves using internet of things and machine learning models;International Journal of Web and Grid Services;2023

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