Grain yield and its contributing traits in promising sweetcorn hybrids

Author:

Shahrokhi Mohsen1ORCID,Khorasani Saeed Khavari2,Ortez Osler1ORCID

Affiliation:

1. Department of Horticulture and Crop Science Ohio State University Wooster Ohio USA

2. Seed and Plant Improvement Department, Khorasan Razavi Agricultural and Natural Resources Research and Education Center, ARREO Mashhad Iran

Abstract

AbstractThe augmentation of domestic sweetcorn (Zea mays L. saccharata) production in semiarid regions necessitates the development of new superior hybrids with high yield potential. This study aimed to identify the most influential characteristics contributing to sweetcorn grain yield in these regions. Nineteen promising sweetcorn hybrids and the commercial hybrid KSC403su as the control were examined using a randomized complete block design with three replications in a 2‐year study (2021–2022) at the Khorasan Razavi Agricultural and Natural Resources Research and Education Institute Center (ARREO) in Mashhad, Iran. The combined analysis of variance revealed significant variances attributed to genotype (G) for all studied traits, while year (Y) and G × Y effects were significant for most characteristics. Phenotypic correlations indicated a highly significant association of grain yield with grain depth (r = 0.79, p < 0.01), kernel number per row (r = 0.75, p < 0.01), row number per ear (r = 0.63, p < 0.01), ear length (r = 0.58, p < 0.01), and ear diameter (r = 0.57, p < 0.01) traits. Path analysis results emphasized the critical role of traits such as grain depth, row number per ear, and ear length, showcasing a highly significant positive direct impact on grain yield and also a significantly positive association with grain yield. In this study, hybrids PSM3, PSM4, PSM9, PSM16, and PSM19 exhibited the highest values for grain yield and yield‐contributing traits, suggesting their potential for further research in multiple locations with varying environmental conditions before being recommended to farmers.

Publisher

Wiley

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3