Trends and Prospect of Machine Vision Technology for Stresses and Diseases Detection in Precision Agriculture
Introducing machine vision-based automation to the agricultural sector is essential to meet the food demand of a rapidly growing population. Furthermore, extensive labor and time are required in agriculture; hence, agriculture automation is a major concern and an emerging subject. Machine vision-bas...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-12-01
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| Series: | AgriEngineering |
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| Online Access: | https://www.mdpi.com/2624-7402/5/1/3 |
| _version_ | 1797614047765463040 |
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| author | Jaemyung Shin Md. Sultan Mahmud Tanzeel U. Rehman Prabahar Ravichandran Brandon Heung Young K. Chang |
| author_facet | Jaemyung Shin Md. Sultan Mahmud Tanzeel U. Rehman Prabahar Ravichandran Brandon Heung Young K. Chang |
| author_sort | Jaemyung Shin |
| collection | DOAJ |
| description | Introducing machine vision-based automation to the agricultural sector is essential to meet the food demand of a rapidly growing population. Furthermore, extensive labor and time are required in agriculture; hence, agriculture automation is a major concern and an emerging subject. Machine vision-based automation can improve productivity and quality by reducing errors and adding flexibility to the work process. Primarily, machine vision technology has been used to develop crop production systems by detecting diseases more efficiently. This review provides a comprehensive overview of machine vision applications for stress/disease detection on crops, leaves, fruits, and vegetables with an exploration of new technology trends as well as the future expectation in precision agriculture. In conclusion, research on the advanced machine vision system is expected to develop the overall agricultural management system and provide rich recommendations and insights into decision-making for farmers. |
| first_indexed | 2024-03-11T07:04:08Z |
| format | Article |
| id | doaj.art-0dcd372ef387449694bb1a83c0c584ce |
| institution | Directory Open Access Journal |
| issn | 2624-7402 |
| language | English |
| last_indexed | 2024-03-11T07:04:08Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | AgriEngineering |
| spelling | doaj.art-0dcd372ef387449694bb1a83c0c584ce2023-11-17T09:02:54ZengMDPI AGAgriEngineering2624-74022022-12-0151203910.3390/agriengineering5010003Trends and Prospect of Machine Vision Technology for Stresses and Diseases Detection in Precision AgricultureJaemyung Shin0Md. Sultan Mahmud1Tanzeel U. Rehman2Prabahar Ravichandran3Brandon Heung4Young K. Chang5Department of Biomedical Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB T2N 1N4, CanadaDepartment of Engineering, Faculty of Agriculture, Dalhousie University, Truro, NS B2N 5E3, CanadaDepartment of Engineering, Faculty of Agriculture, Dalhousie University, Truro, NS B2N 5E3, CanadaDepartment of Engineering, Faculty of Agriculture, Dalhousie University, Truro, NS B2N 5E3, CanadaDepartment of Plant, Food, and Environmental Sciences, Faculty of Agriculture, Dalhousie University, Truro, NS B2N 5E3, CanadaDepartment of Agricultural & Biosystems Engineering, South Dakota State University, Brookings, SD 57006, USAIntroducing machine vision-based automation to the agricultural sector is essential to meet the food demand of a rapidly growing population. Furthermore, extensive labor and time are required in agriculture; hence, agriculture automation is a major concern and an emerging subject. Machine vision-based automation can improve productivity and quality by reducing errors and adding flexibility to the work process. Primarily, machine vision technology has been used to develop crop production systems by detecting diseases more efficiently. This review provides a comprehensive overview of machine vision applications for stress/disease detection on crops, leaves, fruits, and vegetables with an exploration of new technology trends as well as the future expectation in precision agriculture. In conclusion, research on the advanced machine vision system is expected to develop the overall agricultural management system and provide rich recommendations and insights into decision-making for farmers.https://www.mdpi.com/2624-7402/5/1/3stressdiseasemachine visionmachine learningimage processing |
| spellingShingle | Jaemyung Shin Md. Sultan Mahmud Tanzeel U. Rehman Prabahar Ravichandran Brandon Heung Young K. Chang Trends and Prospect of Machine Vision Technology for Stresses and Diseases Detection in Precision Agriculture AgriEngineering stress disease machine vision machine learning image processing |
| title | Trends and Prospect of Machine Vision Technology for Stresses and Diseases Detection in Precision Agriculture |
| title_full | Trends and Prospect of Machine Vision Technology for Stresses and Diseases Detection in Precision Agriculture |
| title_fullStr | Trends and Prospect of Machine Vision Technology for Stresses and Diseases Detection in Precision Agriculture |
| title_full_unstemmed | Trends and Prospect of Machine Vision Technology for Stresses and Diseases Detection in Precision Agriculture |
| title_short | Trends and Prospect of Machine Vision Technology for Stresses and Diseases Detection in Precision Agriculture |
| title_sort | trends and prospect of machine vision technology for stresses and diseases detection in precision agriculture |
| topic | stress disease machine vision machine learning image processing |
| url | https://www.mdpi.com/2624-7402/5/1/3 |
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