Genetic variability and trait association analysis for yield and quality attributes in parents, f₁ and f₂ generations of lentil (Lens Culinaris Medik)

Introduction

Lentil (Lens culinaris Medik.) is an important cool-season pulse crop valued for its nutritional quality, adaptability and contribution to sustainable agriculture. Its seeds are rich in protein, dietary fibre, minerals and other essential nutrients, making lentil an important component of food and nutritional security (Kaale et al., 2023; Bueckert et al., 2022) [8] . Improving both seed productivity and nutritional quality is therefore an important objective of lentil breeding programmes. Seed yield is a complex quantitative trait controlled by several component characters and strongly influenced by environmental conditions. The assessment of genetic variability is essential for identifying traits that can be effectively exploited through selection. Genotypic coefficient of variation (GCV), phenotypic coefficient of variation (PCV), heritability and genetic advance are important genetic parameters for understanding the magnitude and nature of variation and predicting the response to selection (Burton and DeVane 1953; Johnson et al., 1955) [6,7] . Previous studies have reported considerable genetic variability and high heritability for several yield and yield-related traits in lentil, indicating opportunities for genetic improvement (Alemu International Journal of Advanced Biochemistry Research 2026; SP-10(9): 888-892 et al., 2022) [3] . Evaluation of F₁ and F₂ generations is particularly useful in breeding programmes because the F₂ generation undergoes substantial segregation and recombination, creating opportunities for selecting desirable genetic combinations. Comparative assessment of these generations can provide information on the magnitude of genetic variation and the potential effectiveness of selection for important agronomic and yield traits. In addition to yield, nutritional traits such as protein and methionine content are important targets for improving the nutritional value of lentil. Considerable genetic variation for protein and nutritional quality has been reported in lentil germplasm (Bueckert et al., 2022). The association among yield and its component traits is also important for developing effective selection strategies. Correlation analysis helps determine the direction and magnitude of relationships among agronomic, yield and quality attributes and can identify traits that may serve as useful indirect selection criteria. Significant associations among yield and its component traits have been reported in lentil, demonstrating the usefulness of trait association analysis in breeding programmes (Alemu et al., 2022) [3] . Therefore, the present study was undertaken to assess genetic variability, heritability, genetic advance and trait associations for yield and quality attributes in F₁ and F₂ generations of lentil (Lens culinaris Medik.). The study aimed to identify traits with substantial heritable variation and favourable associations with seed yield that could be effectively utilized in selection and genetic improvement programmes.

Materials and methods

Experimental material

The present investigation entitled Genetic Variability and Trait Association Analysis for Yield and Quality Attributes in F₁ and F₂ Generations of Lentil (Lens culinaris Medik.) was conducted to assess the magnitude of genetic variability and the association among agronomic, yield-related and quality traits in F₁ and F₂ generations of lentil. The experimental material consisted of 10 diverse parental genotypes of lentil, namely KLS 1457, KLS 1465, KLS 1467, KLS 1469, PL 357, IPL 220, PL 370, IPL 241, LL 1655 and LL 1694. These parental lines were selected on the basis of their morphological and agronomic variation. The parental material was used for developing F₁ and subsequent F₂ generations through a half-diallel mating programme. The original experimental material comprised 10 parents, 45 F₁ crosses and 45 F₂ populations.

Development of f₁ hybrids and f₂ populations

The parental genotypes were grown during the rabi season under field conditions. The selected parents were crossed in a half-diallel mating design to generate 45 F₁ crosses. The resultant hybrid seeds were harvested separately for each cross and maintained for evaluation. The F₂ generation was developed by selfing the F₁ plants, and the resulting F₂ seed was harvested separately for each cross. The procedure of growing the parental lines for crossing and harvesting the resultant F₁ seed followed the methodology described in the experimental material.

Experimental design and layout

The experiment was conducted during the rabi season at the Student Instructional Farm, College of Agriculture, C. S. Azad University of Agriculture and Technology, Kanpur, Uttar Pradesh. A total of 100 genotypes/populations, comprising 10 parents, 45 F₁ crosses and 45 F₂ populations, were evaluated in a randomized block design (RBD) with three replications. Each parent and F₁ cross was grown in a single row, whereas the F₂ populations were grown in two rows. The experimental layout followed the design described for the final trial in the source material.

Observations recorded

Observations were recorded on individual plants selected from each treatment in each replication. A total of 15 agronomic, yield-related and quality traits were evaluated in both the F₁ and F₂ generations. The traits considered were days to 50% flowering, days to maturity, plant height, primary branches per plant, secondary branches per plant, number of clusters per plant, number of pods per cluster, total number of pods per plant, seeds per pod, 100-seed weight, biological yield per plant, seed yield per plant, harvest index, protein content and methionine content. Days to 50% flowering was recorded as the number of days from sowing to the stage when approximately 50% of the plants in a population exhibited flowering. Days to maturity was recorded as the number of days from sowing to the stage when the plants attained physiological maturity. Plant height (cm) was measured at maturity from ground level to the tip of the main shoot and expressed in centimetres. Primary branches per plant were recorded by counting the total number of branches arising directly from the main stem, whereas secondary branches per plant were determined by counting the branches originating from the primary branches. The number of clusters per plant was recorded by counting the total number of clusters borne by each selected plant at maturity. Number of pods per cluster was determined by counting the pods borne on individual clusters and calculating the average number of pods per cluster. Total number of pods per plant was recorded by counting all seedbearing pods produced by each selected plant at maturity. Seeds per pod were determined by counting the seeds obtained from randomly selected mature pods and calculating the average number of seeds per pod. For 100-seed weight (g), 100 randomly selected, well-dried seeds from each treatment were weighed using an electronic balance and the weight was expressed in grams. Biological yield per plant (g) was determined by harvesting the selected plants from the base after attaining complete maturity and drying, followed by weighing the total dry biomass of each plant. Seed yield per plant (g) was recorded after harvesting and thorough drying by weighing all the seeds obtained from each selected plant. Harvest index (%) was calculated as the ratio of seed yield (economic yield) to biological yield per plant and expressed as percentage:

Harvest index (%) = Seed yield per plant Biological yield per plant × 100

Protein content (%) was estimated from representative seed samples of each treatment using the prescribed biochemical laboratory assay and expressed as percentage protein content. Methionine content (%) was similarly estimated from representative seed samples using the prescribed biochemical assay and expressed as percentage of the sample. The observations obtained for these traits were subsequently used for the estimation of genetic variability parameters and trait association among the evaluated experimental materials.

Statistical analysis

Analysis of variance (ANOVA) was performed to assess differences among genotypes for each trait following the randomized block design described by Panse and Sukhatme (1967) [9] . The significance of genotype effects was tested using the F-test, and standard error, critical difference (CD), and coefficient of variation (CV) were estimated where appropriate. Genotypic variance (Vg) and phenotypic variance (Vp) were estimated for each trait in the F₁ and F₂ generations. Genotypic and phenotypic coefficients of variation were calculated according to Burton (1952) [4] . as: GCV (%) = (√Vg / X ̄) × 100 PCV (%) = (√Vp / X ̄) × 100 Broad-sense heritability was estimated as: H² (%) = (Vg / Vp) × 100 Expected genetic advance (GA) at 5% selection intensity was estimated according to Robinson et al. (1949) [12] :

where k = 2.06 and σp is the phenotypic standard deviation. Genetic advance as percentage of mean (GA%) was calculated as: GA% = (GA / X ̄) × 100 Correlation coefficients among the studied traits were estimated following Al-Jibouri et al. (1958) [2] , and their significance was tested statistically. The combined estimates of GCV, PCV, heritability and GA% were used to assess the genetic variability and potential response to selection.

Results and Discussion

Analysis of variance

The combined analysis of variance revealed highly significant differences among the treatments for all the characters studied, indicating the presence of substantial genetic variability in the experimental material. The combined analysis of variance for the studied traits is presented in ). The analysis also showed significant variation among parents and within both F₁ and F₂ generations for the majority of the traits, confirming the presence of sufficient variability for further genetic analysis and selection. The analysis of variance for the Parents, F₁ and F₂ generations is presented in Table 3, further confirming significant variation among the evaluated populations. The significant treatment effects observed in the present study indicate that the parental combinations generated considerable variation in the segregating populations.

Genetic variability for agronomic traits

The estimates of mean, range, genotypic and phenotypic variance, heritability, genetic advance, genetic advance as percentage of mean, GCV and PCV for the studied traits are presented in Table 1 Comparable high heritability and genetic advance for important yield-contributing traits have also been reported in lentil germplasm evaluated under Indian conditions (Akkati et al., 2024) [1] . Total number of pods per plant also showed substantial genetic variation. Its mean was 73.38 in F₁ and 70.61 in F₂, with ranges of 50.53-91.93 and 50.53-89.40, respectively. GCV and PCV were very close, at 13.35 and 13.41% in F₁ and 13.26 and 13.30% in F₂. Heritability was exceptionally high at 99.24% in F₁ and 99.39% in F₂, accompanied by GA% of 27.41 and 27.24%. These estimates indicated a strong genetic contribution to the observed variation and considerable potential for improvement through selection.

Seeds per pod showed a contrasting pattern. In F₁, GCV was 9.05%, PCV was 10.52% and heritability was 73.97%, with GA% of 16.03%. In F₂, however, GCV was 10.05%, whereas PCV increased markedly to 17.89%, resulting in a substantial decline in heritability to 31.57% and GA% to 11.64%. The wider difference between GCV and PCV in F₂ indicated a relatively greater environmental contribution to the phenotypic expression of seeds per pod, thereby reducing the reliability of direct selection. Similar differences between PCV and GCV and variation in heritability among yield-related traits have been documented in lentil (Rana et al., 2020) [10] . [3] . Seed yield per plant, the principal economic trait, had means of 3.28 g in F₁ and 3.14 g in F₂, with ranges of 2.28-4.00 and 2.19-3.85 g, respectively. GCV was 10.18% in F₁ and 10.41% in F₂, while PCV was slightly higher at 11.01 and 11.65%, respectively. Heritability was high in both generations (85.53% in F₁ and 79.83% in F₂), and GA% was 19.40 and 19.16%, respectively. The relatively close GCV and PCV values, together with high heritability and appreciable genetic advance, indicated substantial heritable variation for seed yield and suggested that selection for higher-yielding segregants could be effective. The favourable combination of heritability and genetic advance observed for seed yield agrees with previous lentil variability studies, where seed yield was identified as a trait with substantial genetic variation and selection potential (Akkati et al., 2024) [1] . The quality traits showed distinct genetic behaviour. Protein content had means of 27.50% in F₁ and 27.37% in F₂, with GCV values of 5.63 and 5.68% and PCV values of 5.71 and 5.69%, respectively. Heritability was exceptionally high, reaching 97.27% in F₁ and 99.74% in F₂, while GA% was 11.44 and 11.69%. Thus, protein content exhibited very high heritability but only moderate expected genetic advance, suggesting that although its variation was predominantly heritable, the magnitude of response to selection could be moderate. Methionine content showed a marked difference between generations. In F₁, its mean was 2.84%, with GCV of only 0.45%, PCV of 0.53%, heritability of 71.62% and GA% of 0.78%. In F₂, the mean was 2.77%, while GCV and PCV increased to 9.75 and 9.83%, respectively, with heritability of 98.38% and GA% of 19.91%. Therefore, methionine displayed very limited expected response to selection in F₁ but considerably greater genetic variability and selection potential in F₂. The high heritability observed for protein content is consistent with lentil studies demonstrating useful genetic variation for protein concentration and its potential integration into breeding programmes (Alemu et al., 2022) [3] .

Conclusion

The present study demonstrated substantial genetic variability among the lentil populations evaluated in the F₁ and F₂ generations for agronomic, yield-related and quality traits. Significant variability, coupled with high heritability and appreciable genetic advance, was particularly evident for plant height, primary and secondary branches, clusters per plant, pods per cluster, total pods per plant, 100-seed weight, biological yield and seed yield. Among these traits, number of pods per cluster exhibited the highest genetic advance as percentage of mean, indicating considerable potential for effective selection. Seed yield per plant also showed a favourable combination of heritability and genetic advance in both generations, suggesting that selection for superior yielding segregants could be effective. In contrast, days to 50% flowering and days to maturity exhibited relatively low genetic variability and genetic advance despite high heritability, indicating comparatively limited scope for improvement through direct selection. Seeds per pod showed a marked reduction in heritability in F₂, suggesting greater environmental influence and reduced selection efficiency for this trait at this generation. Protein content maintained exceptionally high heritability across generations, whereas methionine content showed greater selection potential in F₂ than in F₁. Overall, the combined assessment of GCV, PCV, heritability and genetic advance identified plant architecture, reproductive and yieldcontributing traits as promising selection criteria for improving seed yield and associated attributes in lentil. These findings provide useful guidance for selecting superior segregants and advancing promising breeding material in subsequent generations.

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