Document Type : Original Article

Authors

• Hamid Reza Osmani Roudi ¹
• Baratali Fakheri ²
• Mahmood Solouki ²
• Saeed Khavari Khorasani ³
• Nafiseh Mahdi Nezhad ⁴

¹ PhD Student, University of Zabol, Zabol, Iran

² Professor, Department of Plant Breeding and Biotechnology. College of Agriculture, University of Zabol, Zabol, Iran

³ Seed and Plant Improvement Institue (SPII), Mashhad, Iran

⁴ Department of Plant Breeding and Biotechnology. College of Agriculture, University of Zabol, Zabol, Iran

Abstract

Introduction
To improve a complex character such as grain yield with low heritability, indirect selection through other characters and selection index based on different effective traits were used. Grain yield has quantitative heritance and can be affected by environment severely; therefore selection for genetic improvement only based on yield may have low efficiency. But selection based on proper index can be one of the most effective methods for indirect selection of yield and yield components simultaneously.
Materials and methods
In order to determine selection index for improvement of maize yield, 14 single cross maize hybrids (including 12 promising maize hybrids and KSC704 and KSC705 cultivars as control cultivars) were planted in two separate experiments (Saline stress and normal condition) based on randomized complete block design (RCBD) with four replication in Khorasan Razavi agricultural and natural resources research and education center (TOROQ Station and Abbas Abad Station), Mashhad Iran on 2017-2018. In this study silage yield, Dry Forage yield, number of total leaves, Ear Diameter, Ear Length, Ear Height, Kernel depth, anthesis silking interval (ASI) and Plant Height appearance was measured randomly from 10 sample. Then some of morphological and phonological traits, yield and yield components were recorded.
Results and discussion
The results of ANOVA showed significant differences between hybrids for many of measured traits in both conditions (P≤0.01). Thus, selection will be effective due to existence of enough variation. The results of correlation, multiple regression and principle component analysis were used for identification of traits that are more effective on grain yield. Selection indices were calculated based on results of stepwise regression considering to phenotype, genotypic and economic values. Based on stepwise regression results in normal condition, Plant Height, Number of Ear, Dry Forage Yield, Days to anthesis, Number of Leaves totally could explain 77.84 percent of gain yield variation, then these traits were used to calculate selection index. In Saline stress condition, Number of Ear, Ear Length, Days to anthesis, Number of Leaves, Plant height could explain 76.90 percent of grain yield variation that these traits were used to calculate of selection index. Smith-Hazel and Pesk-Baker selection indexes for dry silage yield performance, leaf total number, number of cob, plants length and days to pollination in non-stressed condition and number of cob, days to pollination, leaf total number and plants length were calculated under stressed situation. Moreover, relative efficiency of selection and expected gain of selection index using the Smith – Hazel index was higher than the Pesk – Baker index. The highest relative efficiency of selection under non-stressed condition was measured in index number 5 (Smith – Hazel 5) while in saline stressed condition it was achieved in index number 4 (Smith - Hazel 4).
Conclusion
In summary, by adjusting phenotype values in mentioned traits in index equivalent, the amount of each index was determined. Finally Based on grain yield and selection indices, 20 percent of the best genotypes were selected by each selection indices. The highest selection indices were obtained for the hybrids 1, 5, 2, 8 and 6 in normal condition and hybrids 13, 3, 4, 10 and 8 in saline condition.

Keywords

• Agronomic traits
• Breeding value
• Relative utility
• Selection

20.1001.1.22287604.1401.15.2.14.0

Main Subjects

• Salinity stress