Skip to content
Research Article Open access CC BY 4.0

Response of Cotton Genotypes to Water-deficit Stress using Drought Tolerance Indices and Principal Component Analysis

Waleed Mohamed Bassuny Yehia, Karima M. El-Absy

Asian Journal of Advances in Agricultural Research · pp. 13–27 · Published 12 Jan 2023

10.9734/ajaar/2023/v21i1407

Abstract

Drought impacts on cotton cultivation and production are expected to worsen as a result of global warming and water-deficit stress. Drought tolerance indices and PCA analysis were used to evaluate drought stress responses in eleven cotton genotypes and fifteen indices' ability to identify drought-tolerant genotypes under normal and drought circumstances. Seed cotton yield (Kentar feddan-1) was significantly affected by genotypes, years, and their interaction (p ≤ 0.05 or 0.01) under normal and water-deficit stress conditions, according to a combined ANOVA. Except for error variance, all genetic parameters studied for seed cotton yield were higher in normal irrigation conditions than in water-deficit stress conditions. According to PCA analysis, The STI, MP, GMP, HM, ATI, SSPI, and TOL are suitable indicators and were similar in their ability to screen, rank and detect tolerant genotypes, due to positive correlations among each other and also the highest association with seed cotton yield in both irrigation conditions. The genotypes G4, G9, and G10 (Group A) seemed to be the most drought-tolerant and cotton productive based on mean performance, GxY heatmap analysis, drought tolerance indices, and PCA analysis. The results of our study's drought tolerance indices and PCA could be useful and appropriate for studying drought tolerance mechanisms and cotton yield improvement in Egypt.

Cotton GY interaction drought stress indices PCA

Cited by 2

Screening for drought tolerance using physiological traits in upland cotton (Gossypium hirsutum L.)

Muhammad Nauman, Muhammad Asif Saleem, M. M. V. Baig · Agronomía Colombiana · 2024

Calibrating Hand Gesture Recognition for Stroke Rehabilitation Internet-of-Things (RIOT) Using MediaPipe in Smart Healthcare Systems

Ahmad Anwar Zainuddin, Nurul Hanis Mohd Dhuzuki, A. A. Puzi · International Journal of Advanced Computer Science and Applications · 2024

Article metrics

Real usage data collected on this platform.

14

Page views

0

PDF downloads

0

Outbound clicks

2

Citations

Views over time

Views by country

Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".

Traffic sources

Referring site, by host.

Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.