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Plant sciences, sustainable farming systems and food quality
RESEARCH ARTICLE

Selecting elite tomato genotypes through a modified analytical hierarchy process

P. Eynizadeh https://orcid.org/0000-0002-7008-8285 A and H. Dehghani https://orcid.org/0000-0003-3267-5144 A B
+ Author Affiliations
- Author Affiliations

A Plant Genetics and Breeding Department, Faculty of Agriculture, Tarbiat Modares University, PO Box 14115-336, Tehran, Iran.

B Corresponding author. Email: hdehghani@ucdavis.edu, dehghanr@modares.ac.ir

Crop and Pasture Science 71(9) 822-830 https://doi.org/10.1071/CP20116
Submitted: 30 June 2020  Accepted: 14 July 2020   Published: 19 August 2020

Abstract

Plant genetic improvement may be done traditionally by selecting the most appropriate genotypes based on heritability, stability, genetic distance and other genetic parameters. In this paper, the analytical hierarchy process (AHP) with some modifications was used as a new multivariate method for determining the capability of elite tomato (Solanum lycopersicum L.) genotypes to form the next-generation breeding population. Modified AHP is performed in three steps: (i) aligning traits and genotypes, (ii) calculating weights of traits, and (iii) calculating weights of genotypes. Fruit quality and yield were evaluated in 20 F2 tomato families cultured along with their parents in a randomised complete block design with three replications in the research field. The traits fruit yield, plant cluster number and fruit number per plant were identified as the most effective for ordering genotypes. Four families were identified as the best (selection among families), and the best individuals selected from a total of 60 individuals (selection within families) almost all belonged to these four families. Because of the use of genetic parameters in modified AHP, the selected genotypes were the best choices with respect to fruit yield, lycopene content and capability to create a breeding population.

Additional keywords: heritability-based selection, hybrid cultivars, multivariate selection method, single plant selection.


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