Evidence map›Paper›PMID 39748095›Full record

ArticleScientific reports2025

Genetic analysis and association detection of agronomic traits in maize genotypes.

Seyyed Mohammad Sadegh Hosseini, Mohammadreza Shiri, Khodadad Mostafavi, Abdollah Mohammadi, Seyyed Mehdi Miri

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In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Seyyed Mohammad Sadegh HosseiniDepartment of Agronomy and Plant Breeding, Karaj Branch, Islamic Azad University, Karaj, Iran.
Mohammadreza ShiriSeed and Plant Improvement Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran. mshiri@spii.ir.
Khodadad MostafaviDepartment of Agronomy and Plant Breeding, Karaj Branch, Islamic Azad University, Karaj, Iran.
Abdollah MohammadiDepartment of Agronomy and Plant Breeding, Karaj Branch, Islamic Azad University, Karaj, Iran.
Seyyed Mehdi MiriDepartment of Horticulture, Karaj Branch, Islamic Azad University, Karaj, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In maize breeding, enhancing yield through genetic insights is crucial yet challenged by the complex interplay of agronomic traits. This study utilized a diallel mating design involving nine advanced early maize lines to dissect the genetic architecture underlying key agronomic traits and their impact on yield. Over two consecutive years (2018-2019 and 2019-2020), 36 hybrids derived from these lines were grown across two locations, Karaj, Alborz, Iran and Kermanshah (2019-2020), Iran, in a randomized complete block design with three replications. The study aimed to evaluate the general combining ability of the parental lines and the specific combining ability of their hybrids, alongside the mutual influences of critical traits on yield. The analysis of variance revealed significant differences at 1% and 5% probability levels among the hybrids for all traits studied, indicating substantial genetic variability. Diallel analysis suggested that both additive and non-additive genetic effects are crucial in controlling traits such as kernel yield, kernel rows, kernel in row, 1000 kernel weight, plant height, ear height, kernel moisture, and ear wood. Additive effects, as indicated by the Baker's ratio, predominated for these traits. Among the parental lines, KE 79,017/3211 demonstrated the strongest general combining ability for kernel yield. Hybrids K 1264/5-1 × KE 76,009/311, KE 77,005/2 × KE 75,016/321, KE 77,008/1 × KE 77,004/1, and KE 77,008/1 × KE 79,017/3211 exhibited significant and positive specific combining ability effects for kernel yield, highlighting their potential in yield-enhancing breeding programs. Correlation analysis showed no significant association between KY*KIN with the KY*KW. However, there were weak positive correlations between KY*KR with other traits such as KY*PH, KY*KR, and KY*EH. The biplot analyses identified genotypes 4, 12, and 31 as superior across various trait combinations. Genotype 12 emerged as notably high-yielding based on average tester coordinates. Using the multi-trait stability index and imposing a selection pressure of 25%, genotype 10 was ranked highest, followed by genotypes 9, 13, 11, 1, 2, and 16, which were considered the most stable and ideal across all evaluated traits. This comprehensive study underscores the importance of both general combining ability and specific combining ability in maize breeding and highlights specific genotypes and hybrid combinations with promising traits for yield enhancement.

Indexed as

GenotypePhenotypePlant BreedingZea maysGenetic VariationIranQuantitative Trait, HeritableQuantitative Trait LociBreedingCombinationCombining abilityEnhancement key trait

Identifiers

PMID39748095
PMCPMC11696145

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.