WHEAT STABILITY ASSESSMENT FOR LATE-PLANTING HEATSTRESS USING STRESS SELECTION INDICES, PRINCIPAL COMPONENT, AND BIPLOT ANALYSES
Z. Ahmad1, N.U. Khan1,*, S. Gul2, S.U. Khan3, S. Ahmed1, S. Ali4, N. Ali4, S.A. Khan4,
M. Amin4, A. Iqbal5, W. Ali6, K. Din1 and A. Khan1
1Department of Plant Breeding and Genetics, University of Agriculture, Peshawar, Pakistan
2Department of Plant Breeding and Genetics, University of Sargodha, Sargodha, Pakistan
3Institute of Biotechnology and Genetic Engineering, University of Agriculture, Peshawar, Pakistan
4Department of Plant Breeding and Genetics, University of Haripur, Haripur, Pakistan
5Department of Plant Breeding and Genetics, Lasbela University of Agriculture, Water and Marine Sciences (LUAWMS), Uthal, Balochistan, Pakistan
6Department of Soil and Environmental Science, University of Agriculture, Peshawar, Pakistan
*Corresponding author’s email: nukmarwat@yahoo.com; nukmarwat@aup.edu.pk
ABSTRACT
Wheat grain yield decreases by 1.50% per day with a subsequent delay in optimum sowing and the crop becomes vulnerable to numerous abiotic and biotic stresses. However, climate change had apparent effects on the environment and created an alarming scenario for wheat breeders to tackle the problem in different ways. The present research is aimed to identify the stable wheat genotypes through stress selection indices, principal component, and biplot analyses under genotype by environment interaction with non-stress and stress environments. Thirty-six wheat genotypes were appraised through genotype by environment interactions under optimum (non-stressed) and late (stressed) planting environments during 2017-18 at the Cereal Crops Research Institute (CCRI), Pirsabak - Nowshera, Pakistan. The experiment was laid out in a randomized complete block design with three replications. In addition to stress selection indices, the principal component and biplot analyses were also used to assess the performance and stability of the wheat genotypes under non-stress and stress environments. Genotypes, planting environments, and genotype-by-environment interactions (GEI) revealed significant differences for the majority of the traits. Across both planting environments, cultivar Pakistan-13 produced the highest grain yield, followed by genotypes Zincol-16 and PR-122. Under optimum planting environment, the best performing cultivar was Israr-17, followed by two other genotypes NIFA-Lalma-13 and Paseena-17. However, genotypes PR-122, Zincol-16, and Pakistan-13 produced higher grain yields under the stressed environment. According to stress selection indices, principal component, and biplot analyses, wheat cultivars Pirsabak-13, Zincol-16, and PR-122 were found as the most tolerant and high-yielding genotypes and could be used as source material for the development of stress-tolerant genotypes.
Keywords: Triticum aestivum L.; genetic diversity; optimum and late planting environments; genotype by environment interaction; stress selection indices; principal component and biplot analyses
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