Michael D. Miller, Cari A. Schmitz Carley, Rachel A. Figueroa, Max J. Feldman, Darrin Haagenson, Laura M. Shannon
{"title":"TubAR: an R Package for Quantifying Tuber Shape and Skin Traits from Images","authors":"Michael D. Miller, Cari A. Schmitz Carley, Rachel A. Figueroa, Max J. Feldman, Darrin Haagenson, Laura M. Shannon","doi":"10.1007/s12230-022-09894-z","DOIUrl":null,"url":null,"abstract":"<div><p>Potato market value is heavily affected by tuber quality traits such as shape, color, and skinning. Despite this, potato breeders often rely on subjective scales that fail to precisely define phenotypes. Individual human evaluators and the environments in which ratings are taken can bias visual quality ratings. Collecting quality trait data using machine vision allows for precise measurements that will remain reliable between evaluators and breeding programs. Here we present TubAR (Tuber Analysis in R), an image analysis program designed to collect data for multiple tuber quality traits at low cost to breeders. To assess the efficacy of TubAR in comparison to visual scales, red-skinned potatoes were evaluated using both methods. Broad sense heritability was consistently higher for skinning, roundness, and length to width ratio using TubAR. TubAR collects essential data on fresh market potato breeding populations while maintaining efficiency by measuring multiple traits through one phenotyping protocol.</p></div>","PeriodicalId":7596,"journal":{"name":"American Journal of Potato Research","volume":"100 1","pages":"52 - 62"},"PeriodicalIF":1.2000,"publicationDate":"2022-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12230-022-09894-z.pdf","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"American Journal of Potato Research","FirstCategoryId":"97","ListUrlMain":"https://link.springer.com/article/10.1007/s12230-022-09894-z","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"AGRONOMY","Score":null,"Total":0}
引用次数: 2
Abstract
Potato market value is heavily affected by tuber quality traits such as shape, color, and skinning. Despite this, potato breeders often rely on subjective scales that fail to precisely define phenotypes. Individual human evaluators and the environments in which ratings are taken can bias visual quality ratings. Collecting quality trait data using machine vision allows for precise measurements that will remain reliable between evaluators and breeding programs. Here we present TubAR (Tuber Analysis in R), an image analysis program designed to collect data for multiple tuber quality traits at low cost to breeders. To assess the efficacy of TubAR in comparison to visual scales, red-skinned potatoes were evaluated using both methods. Broad sense heritability was consistently higher for skinning, roundness, and length to width ratio using TubAR. TubAR collects essential data on fresh market potato breeding populations while maintaining efficiency by measuring multiple traits through one phenotyping protocol.
期刊介绍:
The American Journal of Potato Research (AJPR), the journal of the Potato Association of America (PAA), publishes reports of basic and applied research on the potato, Solanum spp. It presents authoritative coverage of new scientific developments in potato science, including biotechnology, breeding and genetics, crop management, disease and pest research, economics and marketing, nutrition, physiology, and post-harvest handling and quality. Recognized internationally by contributors and readership, it promotes the exchange of information on all aspects of this fast-evolving global industry.