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  1. KRISHI Publication and Data Inventory Repository
  2. Natural Resource Management A8
  3. ICAR-Central Arid Zone Research Institute L7
  4. NRM-CAZRI-Publication
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Please use this identifier to cite or link to this item: http://krishi.icar.gov.in/jspui/handle/123456789/19445
Title: Cultivar identification and diversity analysis based on morphological descriptors and image analysis in chickpea (Cicer arietinum L.)
Other Titles: Not Available
Authors: Monika A. Joshi
Divya Aggarwal
Archana Sanyal
ICAR Data Use Licennce: http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf
Author's Affiliated institute: ICAR::Indian Agricultural Research Institute
Published/ Complete Date: 2016-12-01
Project Code: Not Available
Keywords: Chickpea
Distinctiveness
Essential characters
Grouping characters
Image analysis
Morphological descriptors
Publisher: Not Available
Citation: 0
Series/Report no.: Not Available;
Abstract/Description: Thirty three genotypes of chickpea including 9 kabuli and 24 desi types were evaluated for distinctiveness based on 13 qualitative and 7 quantitative morphological DUS descriptors. In desi type, only 4 traits were polymorphic whereas, in kabuli type, only 3 were polymorphic. Identification profiles were generated on the basis of grouping and essential characters prescribed by DUS Guidelines of PPV & FR Authority. However, out of twenty four desi genotypes, distinct profiles could be created only for sixteen varieties and in kabuli type, only three out of nine genotypes could be singled out individually. Image analysis using scanned images of flowers of desi types successfully complemented the morphological descriptors to establish genotypic identity based on differences in the petal colour intensity and venation pattern. Genetic parameters for all the quantitative traits revealed less environmental influence on the characters expression thus, signifying their utility in the varietal characterization. Seven agro-morphological traits were used to assess the variability using Ward’s Minimum Variance Cluster Analysis. Thirty three cultivars from both types were grouped into four cluster each, however, none of the clusters contained genotypes with all the desirable traits, which could be directly selected and utilized.
Description: Not Available
ISSN: Not Available
Type(s) of content: Article
Sponsors: Not Available
Language: English
Name of Journal: Legume Research
NAAS Rating: 6.53
Volume No.: Not Available
Page Number: Not Available
Name of the Division/Regional Station: Division of Seed Science and Technology
Source, DOI or any other URL: DOI:10.18805/lr.v0i0.7839
URI: http://krishi.icar.gov.in/jspui/handle/123456789/19445
Appears in Collections:NRM-CAZRI-Publication

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