Study on Character Association and Path Coefficient Analysis in Bread Wheat (Triticum aestivum L.)

Introduction

Bread wheat (Triticum aestivum L.) is one of the most extensively cultivated cereal crops and constitutes a major component of the human diet across the world. Owing to its broad adaptability, high yield potential, and superior nutritional value, it plays a fundamental role in sustaining global food and nutritional security. Wheat grains provide an important source of carbohydrates, proteins, vitamins, and essential minerals, supplying a significant share of the daily energy requirements of millions of people. In India, wheat ranks second only to rice among food crops and is grown under both irrigated and rainfed production systems. The crop occupies approximately 31.23 million hectares, producing 112.92 million tonnes of grain with an average productivity of 3,615 kg ha⁻¹, which places India as the world's second-largest wheat-producing nation (Progress Report, 2023-24). The continuous increase in global population, together with the adverse impacts of climate change, evolving pathogen populations, and shrinking natural resources, has intensified the need to develop wheat cultivars with higher yield potential and improved resilience. Achieving sustainable genetic improvement requires the availability of broad genetic variability and a thorough understanding of the inheritance of economically important traits. Estimates of genetic parameters, particularly heritability and genetic advance, provide valuable insights into the magnitude of genetic variation, the nature of gene action, and the expected efficiency of selection, thereby assisting breeders in designing effective improvement programmes. Grain yield is a highly complex quantitative trait resulting from the combined expression of numerous morphological, physiological, and developmental characters. Consequently, simultaneous evaluation of these component traits is essential for improving selection efficiency in wheat breeding. Correlation analysis is widely employed to assess the magnitude and direction of relationships among yield and its associated traits, whereas path coefficient analysis further partitions these relationships into direct and indirect effects, enabling the identification of traits with the greatest contribution to grain yield. Such information provides a sound scientific basis for formulating effective selection strategies and accelerating the development of high-yielding bread wheat cultivars.

Materials and Methods

The present investigation was undertaken to evaluate the mean performance, characterize the relationships among yield-related traits, and quantify their direct and indirect contributions to grain yield in bread wheat (Triticum aestivum L.). The field experiment was conducted during the Rabi season of 2023-24 at the Crop Research Centre, Sardar Vallabhbhai Patel University of Agriculture and Technology, Meerut, Uttar Pradesh, India. The experimental material consisted of ten genetically diverse parental lines and forty-five F₁ hybrids developed through a halfdiallel mating design, excluding reciprocal crosses. The parental lines and their hybrids were evaluated using a Randomized Block Design (RBD) with three replications. Each genotype was sown in a single row of 3 m length, maintaining a spacing of 20 cm between rows and 10 cm between plants. All recommended agronomic and crop management practices were followed throughout the crop growth period to ensure uniform crop establishment and development. Data were collected on eleven agronomic and yield-attributing traits, namely days to flowering, days to maturity, plant height, productive tillers per plant, spike length, spikelets per spike, grains per spike, biological yield per plant, 1000-kernel weight, harvest index, and grain yield per plant. Observations for all characters were recorded from five randomly selected competitive plants in each replication, whereas days to flowering and days to maturity were recorded on a plot basis. The average performance of the parental lines and F₁ hybrids was estimated for each trait. Genotypic and phenotypic correlation coefficients were computed to assess the strength and direction of associations among grain yield and its component traits following the procedure described by Croxton and Cowden (1964) [4] . To further clarify the contribution of individual traits to grain yield, path coefficient analysis was carried out according to the method proposed by Dewey and Lu (1959) [6] . This analysis partitioned the observed correlation coefficients into their direct and indirect effects, thereby identifying the most influential yield-determining characters that could serve as effective selection criteria in bread wheat breeding programmes.

Results and discussion

Distribution of mean performance

The mean performance of the fifty-five bread wheat genotypes, comprising ten parental lines and forty-five F₁ hybrids, for eleven agronomic and yield-related traits is summarized in Noticeable differences in mean performance were observed among the evaluated genotypes for all the characters, indicating the existence of substantial genetic variability. The magnitude of this variation suggests considerable scope for genetic improvement and provides opportunities for the effective selection of superior genotypes aimed at enhancing grain yield and its associated traits in bread wheat.

Correlation coefficient analysis

The relationships between grain yield per plant and its associated agronomic traits were examined by estimating genotypic and phenotypic correlation coefficients, and the results are presented in Tables 3 and4. In general, both genotypic and phenotypic correlations exhibited similar trends with respect to the direction of association. However, the magnitude of the genotypic correlation coefficients was consistently greater than that of the corresponding phenotypic coefficients, indicating that the observed associations were primarily controlled by genetic factors, whereas environmental effects tended to reduce their phenotypic expression. [1,3,13,15] . At the phenotypic level, grain yield per plant showed a highly significant and positive association with the number of grains per spike (0.615), followed by harvest index (0.468), biological yield per plant (0.424), and 1000-kernel weight (0.283). Positive but relatively weaker correlations were also observed with plant height, productive tillers per plant, and spikelets per spike. Conversely, days to maturity (-0.324) and spike length (-0.139) were negatively correlated with grain yield, suggesting that delayed maturity and longer spikes were not advantageous for improving grain production under the present experimental conditions. These results emphasize the importance of grains per spike, harvest index, biological yield, and kernel weight as major yield-enhancing traits and indicate their usefulness as selection criteria in wheat breeding. [8,9,10,14,16] . A comparable pattern was observed at the genotypic level, where grain yield per plant exhibited the strongest positive association with the number of grains per spike (0.757), followed by harvest index (0.664), biological yield per plant (0.486), and 1000-kernel weight (0.302). In addition, plant height, productive tillers per plant, and spikelets per spike were positively associated with grain yield, whereas days to maturity (-0.464) and spike length (-0.250) showed significant negative relationships. The comparatively higher genotypic correlation coefficients further indicate that these associations are largely under genetic control and are less influenced by environmental variation.

The correlation matrix also revealed several favourable interrelationships among important yield-contributing characters.

Plant height exhibited positive associations with grains per spike, biological yield per plant, spike length, and 1000-kernel weight, while productive tillers per plant were positively correlated with spikelets per spike and grains per spike. Likewise, biological yield per plant maintained positive relationships with both grain number and 1000-kernel weight. These favourable associations suggest that simultaneous improvement of these component traits could indirectly enhance grain yield and thereby improve the efficiency of selection in bread wheat breeding programmes.

Path coefficient analysis

Path coefficient analysis was employed to partition the correlation coefficients into their direct and indirect components in order to quantify the relative contribution of individual agronomic traits to grain yield per plant. The results obtained at the genotypic and phenotypic levels are presented in Tables 5 and6. Although the pattern of direct and indirect effects remained largely consistent across both levels of analysis, the genotypic path coefficients were generally greater than the corresponding phenotypic estimates. This indicates that the expression of these traits was influenced predominantly by genetic factors, while environmental conditions moderated their phenotypic expression. At the genotypic level, harvest index exerted the largest positive direct effect on grain yield per plant (0.7717), demonstrating its major contribution to yield improvement. Other traits showing substantial positive direct effects included number of grains per spike (0.5741), spikelets per spike (0.5120), biological yield per plant (0.2599), and 1000-kernel weight (0.2437). A similar trend was evident at the phenotypic level, where harvest index (0.5591) remained the most influential trait, followed by 1000-kernel weight (0.3641), number of grains per spike (0.3434), and biological yield per plant (0.3152). The consistently high positive direct effects observed for these characters indicate that they play a pivotal role in determining grain yield and, therefore, represent reliable targets for selection in bread wheat breeding programmes. [2,5,7,8,12,13,14,15] . Conversely, plant height, productive tillers per plant, and days to maturity recorded negative direct effects on grain yield at the genotypic level. At the phenotypic level, negative direct effects were observed for days to maturity, plant height, productive tillers per plant, and spike length. Despite these negative direct influences, several of these traits exerted favourable indirect effects on grain yield through harvest index, number of grains per spike, and biological yield per plant. This finding suggests that their contribution to yield improvement is largely mediated through their association with key yield-determining traits rather than through their independent effects. The residual effects were relatively low at both the genotypic (0.128) and phenotypic (0.237) levels, indicating that the set of characters included in the present investigation accounted for a substantial proportion of the total variability in grain yield. Collectively, the results identify harvest index, number of grains per spike, biological yield per plant, and 1000-kernel weight as the most important determinants of grain yield. These traits may therefore be considered dependable selection criteria for improving yield potential and should receive priority in hybridization and selection programmes aimed at developing superior bread wheat cultivars.

Acknowledgement

AcknowledgementThe authors gratefully acknowledge the financial support provided through the University Fund of Sardar Vallabhbhai Patel University of Agriculture & Technology, Meerut, Uttar Pradesh, India (250110), for conducting the present study.

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