Cargando…

ShinyFruit: interactive fruit phenotyping software and its application in blackberry

INTRODUCTION: Horticultural plant breeding programs often demand large volumes of phenotypic data to capture visual variation in quality of harvested products. Increasing the throughput potential of phenomic pipelines enables breeders to consider data-hungry molecular breeding strategies such as gen...

Descripción completa

Detalles Bibliográficos
Autores principales: Chizk, T. Mason, Lee, Jackie A., Clark, John R., Worthington, Margaret L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10585260/
https://www.ncbi.nlm.nih.gov/pubmed/37868309
http://dx.doi.org/10.3389/fpls.2023.1182819
_version_ 1785122916282662912
author Chizk, T. Mason
Lee, Jackie A.
Clark, John R.
Worthington, Margaret L.
author_facet Chizk, T. Mason
Lee, Jackie A.
Clark, John R.
Worthington, Margaret L.
author_sort Chizk, T. Mason
collection PubMed
description INTRODUCTION: Horticultural plant breeding programs often demand large volumes of phenotypic data to capture visual variation in quality of harvested products. Increasing the throughput potential of phenomic pipelines enables breeders to consider data-hungry molecular breeding strategies such as genome-wide association studies and genomic selection. METHODS: We present an R-based web application called ShinyFruit for image-based phenotyping of size, shape, and color-related qualities in fruits and vegetables. Here, we have demonstrated one potential application for ShinyFruit by comparing its estimates of fruit length, width, and red drupelet reversion (RDR) with ImageJ and analogous manual phenotyping techniques in a population of blackberry cultivars and breeding selections from the University of Arkansas System Division of Agriculture Fruit Breeding Program. RESULTS: ShinyFruit results shared a strong positive correlation with manual measurements for blackberry length (r = 0.96) and ImageJ estimates of RDR (r = 0.96) and significant, albeit weaker, correlations with manual RDR estimation methods (r = 0.62 - 0.70). Neither phenotyping method detected genotypic differences in blackberry fruit width, suggesting that this trait is unlikely to be heritable in the population observed. DISCUSSION: It is likely that implementing a treatment to promote RDR expression in future studies might strengthen the documented correlation between phenotyping methods by maximizing genotypic variance. Even so, our analysis has suggested that ShinyFruit provides a viable, open-source solution to efficient phenotyping of size and color in blackberry fruit. The ability for users to adjust analysis settings should also extend its utility to a wide range of fruits and vegetables.
format Online
Article
Text
id pubmed-10585260
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-105852602023-10-20 ShinyFruit: interactive fruit phenotyping software and its application in blackberry Chizk, T. Mason Lee, Jackie A. Clark, John R. Worthington, Margaret L. Front Plant Sci Plant Science INTRODUCTION: Horticultural plant breeding programs often demand large volumes of phenotypic data to capture visual variation in quality of harvested products. Increasing the throughput potential of phenomic pipelines enables breeders to consider data-hungry molecular breeding strategies such as genome-wide association studies and genomic selection. METHODS: We present an R-based web application called ShinyFruit for image-based phenotyping of size, shape, and color-related qualities in fruits and vegetables. Here, we have demonstrated one potential application for ShinyFruit by comparing its estimates of fruit length, width, and red drupelet reversion (RDR) with ImageJ and analogous manual phenotyping techniques in a population of blackberry cultivars and breeding selections from the University of Arkansas System Division of Agriculture Fruit Breeding Program. RESULTS: ShinyFruit results shared a strong positive correlation with manual measurements for blackberry length (r = 0.96) and ImageJ estimates of RDR (r = 0.96) and significant, albeit weaker, correlations with manual RDR estimation methods (r = 0.62 - 0.70). Neither phenotyping method detected genotypic differences in blackberry fruit width, suggesting that this trait is unlikely to be heritable in the population observed. DISCUSSION: It is likely that implementing a treatment to promote RDR expression in future studies might strengthen the documented correlation between phenotyping methods by maximizing genotypic variance. Even so, our analysis has suggested that ShinyFruit provides a viable, open-source solution to efficient phenotyping of size and color in blackberry fruit. The ability for users to adjust analysis settings should also extend its utility to a wide range of fruits and vegetables. Frontiers Media S.A. 2023-10-05 /pmc/articles/PMC10585260/ /pubmed/37868309 http://dx.doi.org/10.3389/fpls.2023.1182819 Text en Copyright © 2023 Chizk, Lee, Clark and Worthington 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
Chizk, T. Mason
Lee, Jackie A.
Clark, John R.
Worthington, Margaret L.
ShinyFruit: interactive fruit phenotyping software and its application in blackberry
title ShinyFruit: interactive fruit phenotyping software and its application in blackberry
title_full ShinyFruit: interactive fruit phenotyping software and its application in blackberry
title_fullStr ShinyFruit: interactive fruit phenotyping software and its application in blackberry
title_full_unstemmed ShinyFruit: interactive fruit phenotyping software and its application in blackberry
title_short ShinyFruit: interactive fruit phenotyping software and its application in blackberry
title_sort shinyfruit: interactive fruit phenotyping software and its application in blackberry
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10585260/
https://www.ncbi.nlm.nih.gov/pubmed/37868309
http://dx.doi.org/10.3389/fpls.2023.1182819
work_keys_str_mv AT chizktmason shinyfruitinteractivefruitphenotypingsoftwareanditsapplicationinblackberry
AT leejackiea shinyfruitinteractivefruitphenotypingsoftwareanditsapplicationinblackberry
AT clarkjohnr shinyfruitinteractivefruitphenotypingsoftwareanditsapplicationinblackberry
AT worthingtonmargaretl shinyfruitinteractivefruitphenotypingsoftwareanditsapplicationinblackberry