The Application Status and Trends of Machine Vision in Tea Production
The construction of standardized tea gardens is the main trend in the development of modern agriculture worldwide. As one of the most important economic crops, tea has increasingly stringent requirements placed on its planting capacity and quality. The application of machine vision technology has le...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-09-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/13/19/10744 |
| _version_ | 1797576229476368384 |
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| author | Zhiming Yang Wei Ma Jinzhu Lu Zhiwei Tian Kaiqian Peng |
| author_facet | Zhiming Yang Wei Ma Jinzhu Lu Zhiwei Tian Kaiqian Peng |
| author_sort | Zhiming Yang |
| collection | DOAJ |
| description | The construction of standardized tea gardens is the main trend in the development of modern agriculture worldwide. As one of the most important economic crops, tea has increasingly stringent requirements placed on its planting capacity and quality. The application of machine vision technology has led to the gradual development of tea production moving towards intelligence and informatization. In recent years, research on tea production based on machine vision technology has received widespread attention, as it can greatly improve production efficiency and reduce labor costs. This article reviews the current application status of machine vision technology in tea pest monitoring, intelligent harvesting, quality evaluation, and classification, and analyzes and discusses specific challenges around machine vision technology in tea production; for example, this technology lacks a standard database and weather interference, training errors in the model, and differences in the hardware computing speed can become a challenge. Based on the current research and application of machine vision technology in various fields, this article looks ahead to the development prospects and future trends of machine vision technology in tea production applications, such as future research to further integrate multiple types of sensors, improvements in the quality and usability of datasets, optimized model algorithms for existing problems, dissemination of research results, and intelligent management of tea production through machine vision technology. |
| first_indexed | 2024-03-10T21:49:20Z |
| format | Article |
| id | doaj.art-2ce584de133a4eaabb9c0c3836fcb9e4 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T21:49:20Z |
| publishDate | 2023-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-2ce584de133a4eaabb9c0c3836fcb9e42023-11-19T14:03:37ZengMDPI AGApplied Sciences2076-34172023-09-0113191074410.3390/app131910744The Application Status and Trends of Machine Vision in Tea ProductionZhiming Yang0Wei Ma1Jinzhu Lu2Zhiwei Tian3Kaiqian Peng4Modern Agricultural Equipment Research Institute, Xihua University, Chengdu 610039, ChinaInstitute of Urban Agriculture, Chinese Academy of Agriculture Sciences, Chengdu 610213, ChinaModern Agricultural Equipment Research Institute, Xihua University, Chengdu 610039, ChinaInstitute of Urban Agriculture, Chinese Academy of Agriculture Sciences, Chengdu 610213, ChinaModern Agricultural Equipment Research Institute, Xihua University, Chengdu 610039, ChinaThe construction of standardized tea gardens is the main trend in the development of modern agriculture worldwide. As one of the most important economic crops, tea has increasingly stringent requirements placed on its planting capacity and quality. The application of machine vision technology has led to the gradual development of tea production moving towards intelligence and informatization. In recent years, research on tea production based on machine vision technology has received widespread attention, as it can greatly improve production efficiency and reduce labor costs. This article reviews the current application status of machine vision technology in tea pest monitoring, intelligent harvesting, quality evaluation, and classification, and analyzes and discusses specific challenges around machine vision technology in tea production; for example, this technology lacks a standard database and weather interference, training errors in the model, and differences in the hardware computing speed can become a challenge. Based on the current research and application of machine vision technology in various fields, this article looks ahead to the development prospects and future trends of machine vision technology in tea production applications, such as future research to further integrate multiple types of sensors, improvements in the quality and usability of datasets, optimized model algorithms for existing problems, dissemination of research results, and intelligent management of tea production through machine vision technology.https://www.mdpi.com/2076-3417/13/19/10744machine visiontea productiondisease recognitionintelligent pickingquality grading |
| spellingShingle | Zhiming Yang Wei Ma Jinzhu Lu Zhiwei Tian Kaiqian Peng The Application Status and Trends of Machine Vision in Tea Production Applied Sciences machine vision tea production disease recognition intelligent picking quality grading |
| title | The Application Status and Trends of Machine Vision in Tea Production |
| title_full | The Application Status and Trends of Machine Vision in Tea Production |
| title_fullStr | The Application Status and Trends of Machine Vision in Tea Production |
| title_full_unstemmed | The Application Status and Trends of Machine Vision in Tea Production |
| title_short | The Application Status and Trends of Machine Vision in Tea Production |
| title_sort | application status and trends of machine vision in tea production |
| topic | machine vision tea production disease recognition intelligent picking quality grading |
| url | https://www.mdpi.com/2076-3417/13/19/10744 |
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