Cargando…
A comprehensive review on acquisition of phenotypic information of Prunoideae fruits: Image technology
Fruit phenotypic information reflects all the physical, physiological, biochemical characteristics and traits of fruit. Accurate access to phenotypic information is very necessary and meaningful for post-harvest storage, sales and deep processing. The methods of obtaining phenotypic information incl...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9909479/ https://www.ncbi.nlm.nih.gov/pubmed/36777535 http://dx.doi.org/10.3389/fpls.2022.1084847 |
_version_ | 1784884583879147520 |
---|---|
author | Liu, Xuan Li, Na Huang, Yirui Lin, Xiujun Ren, Zhenhui |
author_facet | Liu, Xuan Li, Na Huang, Yirui Lin, Xiujun Ren, Zhenhui |
author_sort | Liu, Xuan |
collection | PubMed |
description | Fruit phenotypic information reflects all the physical, physiological, biochemical characteristics and traits of fruit. Accurate access to phenotypic information is very necessary and meaningful for post-harvest storage, sales and deep processing. The methods of obtaining phenotypic information include traditional manual measurement and damage detection, which are inefficient and destructive. In the field of fruit phenotype research, image technology is increasingly mature, which greatly improves the efficiency of fruit phenotype information acquisition. This review paper mainly reviews the research on phenotypic information of Prunoideae fruit based on three imaging techniques (RGB imaging, hyperspectral imaging, multispectral imaging). Firstly, the classification was carried out according to the image type. On this basis, the review and summary of previous studies were completed from the perspectives of fruit maturity detection, fruit quality classification and fruit disease damage identification. Analysis of the advantages and disadvantages of various types of images in the study, and try to give the next research direction for improvement. |
format | Online Article Text |
id | pubmed-9909479 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-99094792023-02-10 A comprehensive review on acquisition of phenotypic information of Prunoideae fruits: Image technology Liu, Xuan Li, Na Huang, Yirui Lin, Xiujun Ren, Zhenhui Front Plant Sci Plant Science Fruit phenotypic information reflects all the physical, physiological, biochemical characteristics and traits of fruit. Accurate access to phenotypic information is very necessary and meaningful for post-harvest storage, sales and deep processing. The methods of obtaining phenotypic information include traditional manual measurement and damage detection, which are inefficient and destructive. In the field of fruit phenotype research, image technology is increasingly mature, which greatly improves the efficiency of fruit phenotype information acquisition. This review paper mainly reviews the research on phenotypic information of Prunoideae fruit based on three imaging techniques (RGB imaging, hyperspectral imaging, multispectral imaging). Firstly, the classification was carried out according to the image type. On this basis, the review and summary of previous studies were completed from the perspectives of fruit maturity detection, fruit quality classification and fruit disease damage identification. Analysis of the advantages and disadvantages of various types of images in the study, and try to give the next research direction for improvement. Frontiers Media S.A. 2023-01-26 /pmc/articles/PMC9909479/ /pubmed/36777535 http://dx.doi.org/10.3389/fpls.2022.1084847 Text en Copyright © 2023 Liu, Li, Huang, Lin and Ren https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Plant Science Liu, Xuan Li, Na Huang, Yirui Lin, Xiujun Ren, Zhenhui A comprehensive review on acquisition of phenotypic information of Prunoideae fruits: Image technology |
title | A comprehensive review on acquisition of phenotypic information of Prunoideae fruits: Image technology |
title_full | A comprehensive review on acquisition of phenotypic information of Prunoideae fruits: Image technology |
title_fullStr | A comprehensive review on acquisition of phenotypic information of Prunoideae fruits: Image technology |
title_full_unstemmed | A comprehensive review on acquisition of phenotypic information of Prunoideae fruits: Image technology |
title_short | A comprehensive review on acquisition of phenotypic information of Prunoideae fruits: Image technology |
title_sort | comprehensive review on acquisition of phenotypic information of prunoideae fruits: image technology |
topic | Plant Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9909479/ https://www.ncbi.nlm.nih.gov/pubmed/36777535 http://dx.doi.org/10.3389/fpls.2022.1084847 |
work_keys_str_mv | AT liuxuan acomprehensivereviewonacquisitionofphenotypicinformationofprunoideaefruitsimagetechnology AT lina acomprehensivereviewonacquisitionofphenotypicinformationofprunoideaefruitsimagetechnology AT huangyirui acomprehensivereviewonacquisitionofphenotypicinformationofprunoideaefruitsimagetechnology AT linxiujun acomprehensivereviewonacquisitionofphenotypicinformationofprunoideaefruitsimagetechnology AT renzhenhui acomprehensivereviewonacquisitionofphenotypicinformationofprunoideaefruitsimagetechnology AT liuxuan comprehensivereviewonacquisitionofphenotypicinformationofprunoideaefruitsimagetechnology AT lina comprehensivereviewonacquisitionofphenotypicinformationofprunoideaefruitsimagetechnology AT huangyirui comprehensivereviewonacquisitionofphenotypicinformationofprunoideaefruitsimagetechnology AT linxiujun comprehensivereviewonacquisitionofphenotypicinformationofprunoideaefruitsimagetechnology AT renzhenhui comprehensivereviewonacquisitionofphenotypicinformationofprunoideaefruitsimagetechnology |