RGB-image method enables indirect selection for leaf spot resistance and yield estimation in a groundnut breeding program in Western Africa

Simple item page
dc.contributor.authorSie, Emmanuel Kofien
dc.contributor.authorOteng-Frimpong, Richarden
dc.contributor.authorKassim, Yussif Babaen
dc.contributor.authorPuozaa, Doris Kanvenaaen
dc.contributor.authorAdjebeng-Danquah, Josephen
dc.contributor.authorMasawudu, Abdul Rasheeden
dc.contributor.authorOfori, Kwadwoen
dc.contributor.authorDanquah, Agyemangen
dc.contributor.authorCazenave, Alexandre Briceen
dc.contributor.authorHoisington, Daviden
dc.contributor.authorRhoads, Jamesen
dc.contributor.authorBalota, Mariaen
dc.date.accessioned2022-10-19T14:23:16Zen
dc.date.available2022-10-19T14:23:16Zen
dc.date.issued2022-08-04en
dc.description.abstractEarly Leaf Spot (ELS) caused by the fungus Passalora arachidicola and Late Leaf Spot (LLS) also caused by the fungus Nothopassalora personata, are the two major groundnut (Arachis hypogaea L.) destructive diseases in Ghana. Accurate phenotyping and genotyping to develop groundnut genotypes resistant to Leaf Spot Diseases (LSD) and to increase groundnut production is critically important in Western Africa. Two experiments were conducted at the Council for Scientific and Industrial Research-Savanna Agricultural Research Institute located in Nyankpala, Ghana to explore the effectiveness of using RGB-image method as a high-throughput phenotyping tool to assess groundnut LSD and to estimate yield components. Replicated plots arranged in a rectangular alpha lattice design were conducted during the 2020 growing season using a set of 60 genotypes as the training population and 192 genotypes for validation. Indirect selection models were developed using Red-Green-Blue (RGB) color space indices. Data was collected on conventional LSD ratings, RGB imaging, pod weight per plant and number of pods per plant. Data was analyzed using a mixed linear model with R statistical software version 4.0.2. The results showed differences among the genotypes for the traits evaluated. The RGB-image method traits exhibited comparable or better broad sense heritability to the conventionally measured traits. Significant correlation existed between the RGB-image method traits and the conventionally measured traits. Genotypes 73-33, Gha-GAF 1723, Zam-ICGV-SM 07599, and Oug-ICGV 90099 were among the most resistant genotypes to ELS and LLS, and they represent suitable sources of resistance to LSD for the groundnut breeding programs in Western Africa.en
dc.description.notesThis project was funded by the USAID, Feed the Future Peanut Innovation Lab.en
dc.description.sponsorshipUSAID, Feed the Future Peanut Innovation Laben
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.3389/fpls.2022.957061en
dc.identifier.issn1664-462Xen
dc.identifier.other957061en
dc.identifier.pmid35991399en
dc.identifier.urihttp://hdl.handle.net/10919/112202en
dc.identifier.volume13en
dc.language.isoenen
dc.publisherFrontiersen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectRGB imageen
dc.subjectphenotypingen
dc.subjectleaf spoten
dc.subjectdiseasesen
dc.subjectgroundnuten
dc.subjectselectionen
dc.titleRGB-image method enables indirect selection for leaf spot resistance and yield estimation in a groundnut breeding program in Western Africaen
dc.title.serialFrontiers in Plant Scienceen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
fpls-13-957061.pdf
Size:
963.95 KB
Format:
Adobe Portable Document Format
Description:
Published version
Download

Collections

Scholarly Works, School of Plant and Environmental Sciences
Scholarly Works, Virginia Agricultural Experiment Station