Analysis of Genetic Parameters, Correlation and Path Analysis for Yield in F\(_4\) Population of Wheat (Triticum aestivum L.)
Kanneganti Raviteja *
Department of Genetics and Plant Breeding, Lovely Professional University, Phagwara-144411, Punjab, India.
Manisha Satyawan Mote
Department of Agriculture Botany, Rajarshee Chatrapati Shahu Maharaj Govt. College of Agriculture, Kolhapur 416004, Mahatma Phule Krishi Vidyapeeth, Rahuri, India.
Mouli Paul
Department of Genetics and Plant Breeding, Institute of Post Graduate Studies in Agricultural Sciences, Central Agricultural University, Imphal- 795004, Manipur, India.
Kaminee Singh
Department of Genetics and Plant Breeding, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi, India.
Aman Tutlani
Department of Genetics and Plant Breeding, Lovely Professional University, Phagwara-144411, Punjab, India and Division of Genetics and Plant Breeding, Faculty of Agriculture (FoA), Sher-e-Kashmir University of Agricultural Sciences and Technology (SKUAST–K), Wadura- 193 201, J & K, India.
Dhamni Patyal
Division of Agronomy, Sher-e-Kashmir University of Agricultural Sciences and Technology (SKUAST–J), Jammu-180009, India.
T N Dhanalakshmi
Department of Genetics and Plant Breeding, AINP Tobacco, ZAHRS, Navile, KSNUAHS, Shivamogga- 577204, Karnataka, India.
Vaishnavi Gajananrao Wuike
Department of Biochemistry, Uttar Banga Krishi Vishwavidyalaya, Pundibari, West Bengal, India.
Nidhi Dubey *
Department of Genetics and Plant Breeding, Lovely Professional University, Phagwara-144411, Punjab, India.
*Author to whom correspondence should be addressed.
Abstract
Wheat (Triticum aestivum L.) is a globally important staple cereal with a complex allohexaploid genome that provides substantial genetic variability for yield improvement under diverse agro-climatic conditions. However, enhancing grain yield remains challenging due to its polygenic nature and strong environmental influence, necessitating systematic evaluation of genetic parameters and trait associations in segregating populations. The present investigation was conducted to assess genetic variability, heritability, character association, and path coefficient analysis for yield and its component traits in an F₄ segregating population of bread wheat (Triticum aestivum L.). A total of 42 genotypes (37 F₄ lines and 5 checks) were evaluated during Rabi 2021–22 using an Augmented Block Design. Observations were recorded on fourteen quantitative traits, and statistical analyses were performed to estimate genotypic and phenotypic coefficients of variation (GCV and PCV), broad-sense heritability, genetic advance, correlation coefficients, and direct and indirect effects on grain yield. Analysis of variance revealed significant differences among genotypes for key traits including days to 50% heading, days to maturity, and plant height, indicating adequate genetic variability. PCV values were higher than GCV for all traits, suggesting environmental influence on trait expression. The highest PCV was recorded for biological yield per plant (19.65%), while plant height exhibited the highest GCV (12.40%). High heritability was observed for days to maturity (86.31%), chlorophyll content (78.81%), ear weight (78.51%), and plant height (71.97%). Plant height also showed high genetic advance as percent of mean (21.7%), indicating predominance of additive gene action. Correlation analysis revealed that biological yield per plant (0.9125) and test weight (0.6639) were positively and significantly associated with grain yield per plant at the genotypic level, whereas harvest index showed significant negative association (−0.6455). Path coefficient analysis demonstrated that biological yield per plant exerted the highest positive direct effect (1.6684) on grain yield, followed by harvest index (0.8050), number of grains per ear (0.1807), and days to maturity (0.1518). The low residual effect (0.1235) indicated that the studied traits sufficiently explained yield variation. Overall, biological yield per plant and test weight emerged as reliable selection indices for improving grain yield in wheat breeding programs.
Keywords: Heritability, genetic advance, coefficient analysis, covariance, path analysis