Close Range Spectral Imaging for Disease Detection in Plants Using Autonomous Platforms: a Review on Recent Studies
Autor: | Gerrit Polder, Puneet Mishra, Nastassia Rajh Vilfan |
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Rok vydání: | 2020 |
Předmět: |
0106 biological sciences
0301 basic medicine medicine.medical_specialty Disease detection Fat content fungi food and beverages GTB Teelt & Gewasfysiologie A General Medicine 01 natural sciences Plant disease Close range Spectral imaging 03 medical and health sciences 030104 developmental biology Crop disease GTB Tuinbouw Technologie medicine Life Science Environmental science Post Harvest Technology Biochemical engineering 010606 plant biology & botany |
Zdroj: | Current Robotics Reports, 1, 43-48 Current Robotics Reports 1 (2020) |
ISSN: | 2662-4087 |
DOI: | 10.1007/s43154-020-00004-7 |
Popis: | Purpose of Review A short introduction to the spectral imaging (SI) of plants along with a comprehensive overview of the recent research works related to disease detection in plants using autonomous phenotyping platforms is provided. Key benefits and challenges of SI for plant disease detection on robotic platforms are highlighted. Recent Findings SI is becoming a potential tool for autonomous platforms for non-destructive plant assessment. This is because it can provide information on the plant pigments such as chlorophylls, anthocyanins and carotenoids and supports quantification of biochemical parameters such as sugars, proteins, different nutrients, water and fat content. A plant suffering from diseases will exhibit different physicochemical parameters compared with a healthy plant, allowing the SI to capture those differences as a function of reflected or absorbed light. Summary Potential of SI to non-destructively capture physicochemical parameters in plants makes it a key technique to support disease detection on autonomous platforms. SI can be broadly used for crop disease detection by quantification of physicochemical changes in the plants. |
Databáze: | OpenAIRE |
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