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Differentiation of litchi genotypes based on leaf biochemical parameters: a feasibility study

Archana Prasada, Bikash Das* & Manju Gerardb
aICAR Research Complex for Eastern Region, Research Centre,  Plandu, Ranchi 834010, Jharkhand
bAllahabad Agricultural Institute-Deemed University, Allahabad  211007, U.P.
Received 21st December, 2009; Revised 27th February, 2010

Abstract : A study was undertaken at ICAR Research Complex for Eastern Region, Research Centre, Ranchi during 2006 with the objective to differentiate the litchi genotypes statistically, based on content of different biochemical constituents. Leaf samples collected from 25 genotypes of 25 year old litchi trees at 2 stages from fruit set to maturity were analyzed for content of Total free amino acid, total soluble protein, total phenol and total carbohydrate. At both the stages of observation, significant differences among the genotypes could be recorded for all the four parameters. During both the stage of observation, the content of total free amino acids was found to be the maximum in genotype Purbi whereas the genotype CHL-3 contained the maximum leaf carbohydrate content at both the stages of observation. Cluster analysis presented at as dendrograms based on Euclidean Distance coefficients resulted in grouping the entire genotypes in to 5 primary clusters. Although the phenotypically similar genotypes were present in the first cluster, a number of phenotypically distinct genotypes were also found under the same cluster. The genotypes Shahi and China which are distinct from each other in terms of morphological as well as phenological characters, were found to have close affinity. However, the cultivar Swarna Roopa which is phenotypically distinct from other genotypes was found as single member in a different cluster. Hence, classification of genotypes through D2-analysis based on leaf biochemical characters like total free amino acid, total phenol, total soluble protein and total carbohydrate was found to be insufficient, although the method holds promise by inclusion of more number of biochemical parameters.


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