Affiliation:
1. Bahauddin Zakariya University
2. Khwaja Fareed University of Engineering and Information Technology
3. Chonnam National University
4. King Saud University
5. October University for Modern Sciences & Arts
6. Alexandria University
7. Atatürk University
Abstract
Abstract
In present study, twenty different wheat varieties were evaluated for various agronomic traits including plant height, number of tellers per plant, leaf area index, spike length, number of spikelets per spike, number of grains per spike, peduncle length, chlorophyll index, thousand-grain weight, grain yield, and biological yield at the research area of Agronomy, Hafiz Abad Research Station, College of Agriculture B.Z.U. Bahadur Campus Layyah during crop season 2020-2021 and 2021-2022. The study was designed following RCBD (Randomized Complete Block Design) with 3 replications of each treatment. Each plot in the study was 4 meters in length and 5 meters in width. The wheat genotypes that were evaluated exhibited significant variability for all of the attributes under investigation. Grain yield was significantly correlated with the spike length, number of spikelets per spike, plant height, 1000-grain weight, number of grains per spike and flag leaf area. Multivariate analysis showed that 20 different wheat varieties formed 3 different clusters. Cluster-1 showed maximum mean values for yield and yield-related attributes compared with cluster-2 and cluster-3. The genotypes accounted for 95% of the total variation in grain yield and associated characteristics, accounting for a significant proportion of the overall differences. In general, the results of this study showed that genotypes like FSD-08, Ujala-16, Fakhr-e-Bhakhar-19, and Akbar-19 have the highest yield potential when grown in the semi-arid climate of Layyah, Pakistan. Thus, all these genotypes were suggested for general cultivation in arid conditions of district Layyah.
Publisher
Research Square Platform LLC
Reference51 articles.
1. An assessment of the genetic diversity in selected wheat lines using molecular markers and PCA based cluster analysis;Ali Y;Applied Ecology and Environmental Research,2019
2. Climate change impact and adaptation for wheat protein;Asseng S;Glob. Chan. Biol.,2019
3. Abdi H, Williams LJ (2010). Principal component analysis. Wiley interdisciplinary reviews: computational statistics. 2(4): 433 – 59.
4. Genetic diversity based on morphological traits of 19 maize genotypes using principal component analysis and GT biplot;Al-Naggar AMM;Annual Research & Review in Biology,2020
5. Using different statistical procedures for evaluating drought tolerance indices of bread wheat genotypes;Abd El-Mohsen AA;Adv. Agric. Biol.,2015