C. Abikkumar, N. Senthil, B. Mohanapriya, G. Parathasarathi, S. Sivakumar, K. Gurusamy, M. Sudha
{"title":"Correlation and variability analysis for yield and related traits of sweet corn in backcross populations","authors":"C. Abikkumar, N. Senthil, B. Mohanapriya, G. Parathasarathi, S. Sivakumar, K. Gurusamy, M. Sudha","doi":"10.25081/jp.2023.v15.8608","DOIUrl":null,"url":null,"abstract":"The 14 biometrical traits of sweet corn were studied in BC2F2 and BC2F3 generations of SCM-Se-Y-1 x UMI 1230β+ to analyse the mean performance and frequency distribution patterns to select potential individuals with high yielding agronomic traits. The mean, GCV, PCV, heritability, and GAM were calculated for all the recorded traits. The Pearson correlation coefficient revealed the strong and positive association of cob weight with cob length, number of kernels in a row and number of kernel rows per cob. Similarly, single plant yield shows positive correlation with number of kernels per row, number of kernel rows per cob, cob length and cob weight. The populations exhibit high PCV than the GCV, which reflects the direct influence of environments on trait performance. The BC2F2 generation exhibits greater trait variability, while BC2F3 shows signs of stabilization. Both generations display high heritability, indicating strong genetic influences for yield related traits. Heritability and GAM for the trait cob weight and single plant yield were higher, which gives added advantage for isolating the superior individual. The results of this study suggest that the selection of agronomical traits to enhance yield in sweet corn is of utmost importance due to its far-reaching economic, nutritional, and environmental implications.","PeriodicalId":16777,"journal":{"name":"Journal of Phytology","volume":"42 4","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Phytology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.25081/jp.2023.v15.8608","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Agricultural and Biological Sciences","Score":null,"Total":0}
引用次数: 0
Abstract
The 14 biometrical traits of sweet corn were studied in BC2F2 and BC2F3 generations of SCM-Se-Y-1 x UMI 1230β+ to analyse the mean performance and frequency distribution patterns to select potential individuals with high yielding agronomic traits. The mean, GCV, PCV, heritability, and GAM were calculated for all the recorded traits. The Pearson correlation coefficient revealed the strong and positive association of cob weight with cob length, number of kernels in a row and number of kernel rows per cob. Similarly, single plant yield shows positive correlation with number of kernels per row, number of kernel rows per cob, cob length and cob weight. The populations exhibit high PCV than the GCV, which reflects the direct influence of environments on trait performance. The BC2F2 generation exhibits greater trait variability, while BC2F3 shows signs of stabilization. Both generations display high heritability, indicating strong genetic influences for yield related traits. Heritability and GAM for the trait cob weight and single plant yield were higher, which gives added advantage for isolating the superior individual. The results of this study suggest that the selection of agronomical traits to enhance yield in sweet corn is of utmost importance due to its far-reaching economic, nutritional, and environmental implications.
对cm - se - y -1 x UMI 1230β+的BC2F2和BC2F3代甜玉米的14个生物特征进行了研究,分析了平均表现和频率分布模式,以筛选具有高产农艺性状的潜在个体。意味着,GCV PCV、遗传和GAM计算的所有记录特征。培生相关系数显示,穗重与穗长、单行粒数和每穗粒行数呈正相关。单株产量与每行粒数、每芯粒行数、芯长、芯重呈显著正相关。人群表现出高PCV比GCV对特征性能反映了环境的直接影响。BC2F2代表现出更大的性状变异,而BC2F3代表现出稳定的迹象。两代均表现出较高的遗传力,表明对产量相关性状的遗传影响较大。该性状的穗轴重和单株产量的遗传率和GAM均较高,这为分离优良个体提供了额外的优势。本研究结果表明,选择提高甜玉米产量的农艺性状至关重要,因为它具有深远的经济、营养和环境意义。