Association analysis studies in bread wheat (Triticum aestivum L.) genotypes under timely sown irrigated condition

Introduction

Wheat (Triticum aestivum L.) is a hexaploid (2n = 6x = 42; AABBDD genomes), annual, selfpollinated, cool-season rabi cereal belonging to the tribe Triticeae of the family Poaceae. The earliest cultivated forms included diploid einkorn (AA) and tetraploid emmer (AABB) wheat, which originated in the south-eastern region of Turkey, as revealed by genetic relationships. In India, wheat production during 2023-24 was estimated at 110.55 million metric tons, contributing nearly 14% of global production (Anonymous, 2024). Globally, wheat ranks second after rice and provides approximately 21% of total food calories and 20% of dietary protein to more than 4.5 billion people across 94 developing countries (Braun et al., 2010) [4] . Due to its extensive cultivation, high productivity, and crucial role in international food grain trade, wheat is often referred to as the "king of cereals." When consumed as whole grain, it is also a valuable source of minerals, dietary fibre, and micronutrients such as iron, zinc, and copper (Shewry & Hey, 2015) [14] . Nutritionally, wheat is rich in gluten protein, which governs dough strength and determines its suitability for a wide range of products. Hard wheat, with higher gluten content, is used for chapatti, roti, naan, and maida, while soft wheat is better suited for biscuits and bakery products. Given its global importance, understanding genetic variability, heritability, correlation, and path analysis in wheat genotypes is essential. Such studies provide insights into yield-attributing traits, identify promising lines for direct selection, and assist in choosing suitable parents for hybridization, thereby accelerating breeding programs aimed at developing improved cultivars.

Materials and Methods

The present investigation was carried out during rabi season of 2024, at BTC college of Agriculture and Research Station, Bilaspur, Chhattisgarh. Twenty-six wheat genotypes with four checks viz, GW322 (C), HI8737(d) (C), HI8713(d) (C) and MACS6768 (C) were used. Experimental material were planted in randomized block design (RBD) with four replications. Each genotype was grown in a plot size of 8 m 2 for each entry in each replication. The observations were recorded on five randomly selected plants from each plot in all the four replications of all the twelve characters viz, days to heading, days to maturity, plant height (cm), number of effective tillers/plant, spike length (cm), spike weight (g), total number of spikelet's/spike, peduncle length (cm), biological yield/plot (kg), grain yield/plot (kg), harvest index (%) and 1000 grains weight (g)

Results and Discussion

Analysis of variance

The analysis of variance showed the presence of significant difference among the genotypes for the characters studied viz. days to maturity, plant height (cm), number of effective tillers/plant, spike length (cm), spike weight (g), total number of spikelet's/spike, peduncle length (cm), biological yield/plot (kg), grain yield/plot (kg), harvest index (%) and 1000 grains weight (g). The results indicated a significant level of variability among the genotypes. This offers wheat breeders the potential to enhance these traits through selection and hybridization in order to improve the desired characteristics. Similar results were observed by Hassani et al., (2022) [6] , Sohail et al. (2018) [15] , Sharma et al., (2018) [13] and Chawla et al., (2018) [5] .

Genetic Parameters

From the study of variability parameters, moderate estimates of GCV and PCV were observed for grain yield/plot (kg) followed by biological yield/plot (kg), spike length (cm), low to moderate estimates of PCV and GCV were observed for number of effective tillers/plant and spike weight (g), low estimates of GCV and PCV were observed for 1000 grains weight (g), peduncle length (cm), total number of spikelet's/spike, days to heading, days to maturity and plant height (cm). The moderate magnitude of genotypic coefficient of variation revealed the presence of high amount of genetic variability for the characters studied in the population and thus offers scope for genetic improvement through selection for these traits. High heritability coupled with high genetic advance as% of mean was observed for biological yield/plot (kg) and grain yield/plot (kg) indicates that there in presence of additive gene action and less influenced by environmental effect suggesting that selection of these traits accumulate more additive genes leading to further improvement in their performance. Similar results were observed by Bayisa and Letta., (2020) [3] , Yadav et al., (2020) [16] , Malbhage et al., (2020) [10] , Kaur et al., (2019) [7] and Kumar et al., (2019) [9] .

Correlation coefficient analysis

The correlation study revealed that grain yield/plot (kg) has positive association with days to heading, number of effective tillers/plant, spike length (cm), total number of spikelet's/spike, biological yield/plot (kg), harvest index (%) and 1000 grains weight (g). The study suggested that wheat grain yield can be enhanced by selecting genotypes that exhibit superior performance in the mentioned traits under timely sown irrigated conditions. Similar result were observed by Devesh et al., (2021), Kumar et al., (2022) [8] and Phougat et al., (2017) observed grain yield/plot (kg) showed a significant positive correlation with the biological yield/plot (kg), plant height (cm), harvest index (%) and 1000 grains weight (g).

Path coefficient analysis

The path coefficient analysis between grain yield/plot (kg) and its related traits revealed biological yield/plot (kg), harvest index (%), plant height (cm), and spike weight (g) showed positive direct effect. From the correlation and path coefficient analysis it is investigated that biological yield/plot (kg), number of effective tillers/plant, spike length (cm), days to heading, 1000 grains weight (g), total number of spikelet's/spike were most important traits which should be given proper emphasis during selection programmes for the improvement of grain yield in wheat genotypes under timely sown irrigated condition. Similar results were observed by Kumar et al., (2022) [8] , Milkessa (2022) [11] , Sahu et al., (2021) [12] and Abdulhamed et al., (2021) [1] .

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