Assessment of selection criteria using multi-year study for effective breeding program of Zingiber officinale L

Author:

Begum Twahira1,Gogoi Roktim1,Gogoi Ankita1,Gupta Tanmita1,Chanda Sanjoy Kumar1,Lekhak Himangshu1,Lal Mohan1

Affiliation:

1. Agrotechnology and Rural Development Division, CSIR-North East Institute of Science and Technology, Jorhat, Assam, India

Abstract

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.

Funder

The CSIR-Aroma Mission

Publisher

PeerJ

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

Reference32 articles.

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