Germplasm Collection and Genetic Diversity Characterization of Squash (Cucurbita Moschata Duchesne Ex Lam) Based on Multivariate Analysis of Quantitative and Qualttative Attributes

Author:

Osuagwu Aniefiok N.1,Ubi Godwin M.1,Ikong Fredrick B.1

Affiliation:

1. University of Calabar

Abstract

Abstract

This research was focused on the evaluation of agro-morphological attributes of twenty-four accessions of Squash, Cucurbita moschata obtained from Abia, Benue, Cross River Ebonyi, Edo and Enugu States. Plant length, internode length, petiole length, fruit length, fruit diameter, fruit weight, flesh thickness, mature seed number, aborted seed number, leaf area, flower number and leaf number were evaluated. Data generated from the study for growth and yield attributes were analyzed using PAST 3 software for analysis of Variance, Principal Components Analysis, Correlation Coefficient Analysis and genetic distances-based similarity indices of the accessions. The results indicated that there were significant differences (P < 0.05) among the accessions in most of the growth and yield attributes evaluated. The best performing accessions were Abia creamy and Abia brown varieties which showed high performances in all growth and yield parameters evaluated. The Enugu 4 accession showed the least performance in most of the growth and yield attributes evaluated. Results of the variation in growth traits showed significant difference in all the growth attributes except stalk length. Also there was significant variation (P < 0.05) in yield attributes. Results of the Principal Components Analysis of the growth parameters showed that flower number, aborted seed number, fruit length, leaf number, fruit texture, flesh texture, flesh colour and secondary colour contributed to the total variation. Results of Correlation Analysis between quantitative and qualitative attributes showed that mature seeds correlated positively, strongly and significantly with fruit colour, flesh colour, flesh texture and colour pattern. Fruit diameter was found to be positively, strongly and significantly correlated with fruit texture, flesh texture, colour pattern, predominant colour and secondary colour. The hierarchical numeric cluster analysis classified the quantitative and qualitative traits in the 24 accessions into 2 major clusters with most of the accessions having similar quantitative attributes in cluster one and those accessions with similar qualitative traits in cluster two. It was concluded that Abia creamy and Abia brown were the most adaptable varieties from the results due to their high performances in all growth and yield parameters evaluated and thus recommended for farmers in this Agro-ecology of Calabar. Moreso, Abia creamy and Abia brown which showed high relatedness and performances can be used to improve Enugu brown with low performance by cross breeding to enhance performance for food security.

Publisher

Springer Science and Business Media LLC

Reference40 articles.

1. Genetic diversity of pumpkin accessions in Kenya revealed using morphological characters, diversity index, CATPCA and factor analysis;Kirimi JK;Int J Sci Res,2018

2. Correlation and path coefficient analysis studies in pumpkin (Cucurbita moschata Duch. Ex Poir) for yield and quality traits;Kumar R;Int J Curr Microbiol Appl Sci,2018

3. Studies on Genetics Divergence in pumpkin;Naik ML;Electron J Plant Breed,2015

4. National Biological Information Infrastructure. Introduction to Genetic diversity.U.S Geological Survey. Achieved from the original (on February, 25, 2011).Retrieved March 10, 2020.

5. An Assessment of morphology and yield characteristics of Pumpkin (Cucurbita moschata) genotypes in Northern Bangladesh;Ahmed KU;Trop Agricultural Res Extention,2011

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