M. Romena, Abdollah Najaphy, M. Saeidi, Mahmood Khoramivafa
{"title":"基于农艺性状和籽粒蛋白质含量的多性状选择方法在雨养条件下鉴定小麦优良基因型","authors":"M. Romena, Abdollah Najaphy, M. Saeidi, Mahmood Khoramivafa","doi":"10.2298/gensr2201015r","DOIUrl":null,"url":null,"abstract":"Several plant breeding methods have been successfully used to improve genetic resources in many crops such as wheat. However, selection of genotypes based on multiple traits is a complex task for the breeders. The selected genotypes should display high performance in a series of desired traits. The GT-biplot and the multiple selection index have been proposed to identify a superior genotype based on various desired traits. In the present study, thirty wheat genotypes were assessed using randomized complete block design with three replications under rain-fed conditions to evaluate the genotypes by using two different multiple-trait selection methods (i.e. the GT-biplot and the multiple selection index) for agronomic traits and grain protein content. Results indicated that almost the same genotypes (G7, G9 and G16) were selected as superior entries by the both methodologies. Among the superior selected genotypes, the entries G9 (394.6 gr/m2) and G16 (388.9 gr/m2) showed higher grain yield. Furthermore, the entry G7 had the highest level of grain protein (15.91%) in the flour and the entry G18 (40.9%) revealed highest harvest index. In addition, the both methods were appropriate to identify superior wheat genotypes based on the multiple traits but the multiple selection index could be simpler and fast, if proper weights would be selected.","PeriodicalId":50423,"journal":{"name":"Genetika-Belgrade","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identification of superior wheat genotypes using multiple-trait selection methods based on agronomic characters and grain protein content under rain-fed conditions\",\"authors\":\"M. Romena, Abdollah Najaphy, M. Saeidi, Mahmood Khoramivafa\",\"doi\":\"10.2298/gensr2201015r\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Several plant breeding methods have been successfully used to improve genetic resources in many crops such as wheat. However, selection of genotypes based on multiple traits is a complex task for the breeders. The selected genotypes should display high performance in a series of desired traits. The GT-biplot and the multiple selection index have been proposed to identify a superior genotype based on various desired traits. In the present study, thirty wheat genotypes were assessed using randomized complete block design with three replications under rain-fed conditions to evaluate the genotypes by using two different multiple-trait selection methods (i.e. the GT-biplot and the multiple selection index) for agronomic traits and grain protein content. Results indicated that almost the same genotypes (G7, G9 and G16) were selected as superior entries by the both methodologies. Among the superior selected genotypes, the entries G9 (394.6 gr/m2) and G16 (388.9 gr/m2) showed higher grain yield. Furthermore, the entry G7 had the highest level of grain protein (15.91%) in the flour and the entry G18 (40.9%) revealed highest harvest index. In addition, the both methods were appropriate to identify superior wheat genotypes based on the multiple traits but the multiple selection index could be simpler and fast, if proper weights would be selected.\",\"PeriodicalId\":50423,\"journal\":{\"name\":\"Genetika-Belgrade\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Genetika-Belgrade\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://doi.org/10.2298/gensr2201015r\",\"RegionNum\":4,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Agricultural and Biological Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Genetika-Belgrade","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.2298/gensr2201015r","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Agricultural and Biological Sciences","Score":null,"Total":0}
Identification of superior wheat genotypes using multiple-trait selection methods based on agronomic characters and grain protein content under rain-fed conditions
Several plant breeding methods have been successfully used to improve genetic resources in many crops such as wheat. However, selection of genotypes based on multiple traits is a complex task for the breeders. The selected genotypes should display high performance in a series of desired traits. The GT-biplot and the multiple selection index have been proposed to identify a superior genotype based on various desired traits. In the present study, thirty wheat genotypes were assessed using randomized complete block design with three replications under rain-fed conditions to evaluate the genotypes by using two different multiple-trait selection methods (i.e. the GT-biplot and the multiple selection index) for agronomic traits and grain protein content. Results indicated that almost the same genotypes (G7, G9 and G16) were selected as superior entries by the both methodologies. Among the superior selected genotypes, the entries G9 (394.6 gr/m2) and G16 (388.9 gr/m2) showed higher grain yield. Furthermore, the entry G7 had the highest level of grain protein (15.91%) in the flour and the entry G18 (40.9%) revealed highest harvest index. In addition, the both methods were appropriate to identify superior wheat genotypes based on the multiple traits but the multiple selection index could be simpler and fast, if proper weights would be selected.
期刊介绍:
The GENETIKA is dedicated to genetic studies of all organisms including genetics of microorganisms, plant genetics, animal genetics, human genetics, molecular genetics, genomics, functional genomics, plant and animal breeding, population and evolutionary genetics, mutagenesis and genotoxicology and biotechnology.