Assessment of selection criteria using multi-year study for effective breeding program of Zingiber officinale L
Background Ginger has been an important cash crop with numerous applications since ancient times. As the demand for ginger is ever-growing and being a seasonal crop, a high-yielding variety of ginger would be economically profitable. Methods In this study, 150 germplasm were collected from different...
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PeerJ Inc.
2023-09-01
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author | Twahira Begum Roktim Gogoi Ankita Gogoi Tanmita Gupta Sanjoy Kumar Chanda Himangshu Lekhak Mohan Lal |
author_facet | Twahira Begum Roktim Gogoi Ankita Gogoi Tanmita Gupta Sanjoy Kumar Chanda Himangshu Lekhak Mohan Lal |
author_sort | Twahira Begum |
collection | DOAJ |
description | Background Ginger has been an important cash crop with numerous applications since ancient times. As the demand for ginger is ever-growing and being a seasonal crop, a high-yielding variety of ginger would be economically profitable. Methods In this study, 150 germplasm were collected from different regions of NE India and evaluated for three years in CRBD design with three replications. The present study thus focused on the variability, association, and diversity studies for the first time on 150 ginger germplasm from across North East India. The genotypic and phenotypic coefficient of variation, heritability, correlation, and path analysis were evaluated for the germplasm. Results Analysis of variance (ANOVA) revealed considerable differences among the studied germplasm for studied characters, revealing sufficient variability in the materials. The Mahalanobis D2 and Tocher methods grouped the 150 ginger germplasm into ten clusters. Based on the results of the path coefficient analysis determined for essential oil yield and rhizome yield per plant, it can be concluded that the characters’ initial rhizome weight, the weight of mother rhizome, and weight of secondary rhizome were the most important and appeared promising in improving the overall yield potential of ginger rhizome and essential oil yield. Thus, selection based on the identified traits would lead to an effective ginger breeding program for higher rhizome and essential oil yield. |
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spelling | doaj.art-192447b77eca4ad79d85230ed28309d52023-12-03T11:17:14ZengPeerJ Inc.PeerJ2167-83592023-09-0111e1596610.7717/peerj.15966Assessment of selection criteria using multi-year study for effective breeding program of Zingiber officinale LTwahira Begum0Roktim Gogoi1Ankita Gogoi2Tanmita Gupta3Sanjoy Kumar Chanda4Himangshu Lekhak5Mohan Lal6Agrotechnology and Rural Development Division, CSIR-North East Institute of Science and Technology, Jorhat, Assam, IndiaAgrotechnology and Rural Development Division, CSIR-North East Institute of Science and Technology, Jorhat, Assam, IndiaAgrotechnology and Rural Development Division, CSIR-North East Institute of Science and Technology, Jorhat, Assam, IndiaAgrotechnology and Rural Development Division, CSIR-North East Institute of Science and Technology, Jorhat, Assam, IndiaAgrotechnology and Rural Development Division, CSIR-North East Institute of Science and Technology, Jorhat, Assam, IndiaAgrotechnology and Rural Development Division, CSIR-North East Institute of Science and Technology, Jorhat, Assam, IndiaAgrotechnology and Rural Development Division, CSIR-North East Institute of Science and Technology, Jorhat, Assam, IndiaBackground Ginger has been an important cash crop with numerous applications since ancient times. As the demand for ginger is ever-growing and being a seasonal crop, a high-yielding variety of ginger would be economically profitable. Methods In this study, 150 germplasm were collected from different regions of NE India and evaluated for three years in CRBD design with three replications. The present study thus focused on the variability, association, and diversity studies for the first time on 150 ginger germplasm from across North East India. The genotypic and phenotypic coefficient of variation, heritability, correlation, and path analysis were evaluated for the germplasm. Results Analysis of variance (ANOVA) revealed considerable differences among the studied germplasm for studied characters, revealing sufficient variability in the materials. The Mahalanobis D2 and Tocher methods grouped the 150 ginger germplasm into ten clusters. Based on the results of the path coefficient analysis determined for essential oil yield and rhizome yield per plant, it can be concluded that the characters’ initial rhizome weight, the weight of mother rhizome, and weight of secondary rhizome were the most important and appeared promising in improving the overall yield potential of ginger rhizome and essential oil yield. Thus, selection based on the identified traits would lead to an effective ginger breeding program for higher rhizome and essential oil yield.https://peerj.com/articles/15966.pdfANOVAGenotypic coefficient of variationPhenotypic coefficient of variationHeritabilityCorrelationPath analysis |
spellingShingle | Twahira Begum Roktim Gogoi Ankita Gogoi Tanmita Gupta Sanjoy Kumar Chanda Himangshu Lekhak Mohan Lal Assessment of selection criteria using multi-year study for effective breeding program of Zingiber officinale L PeerJ ANOVA Genotypic coefficient of variation Phenotypic coefficient of variation Heritability Correlation Path analysis |
title | Assessment of selection criteria using multi-year study for effective breeding program of Zingiber officinale L |
title_full | Assessment of selection criteria using multi-year study for effective breeding program of Zingiber officinale L |
title_fullStr | Assessment of selection criteria using multi-year study for effective breeding program of Zingiber officinale L |
title_full_unstemmed | Assessment of selection criteria using multi-year study for effective breeding program of Zingiber officinale L |
title_short | Assessment of selection criteria using multi-year study for effective breeding program of Zingiber officinale L |
title_sort | assessment of selection criteria using multi year study for effective breeding program of zingiber officinale l |
topic | ANOVA Genotypic coefficient of variation Phenotypic coefficient of variation Heritability Correlation Path analysis |
url | https://peerj.com/articles/15966.pdf |
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