Genetic analysis and heterosis breeding of seed yield and yieldattributing traits in Indian mustard (Brassica juncea (L.) Czern & Coss.)

Abstract

This study aimed to assess the genetic basis and combining ability of 10 morphological traits in Indian mustard. The experiment involved eight parent lines and 28 crosses derived from a half-diallel mating design. Combining ability analysis is vital for identifying parents and hybrids with favorable genetic effects to enhance breeding efficiency. The study found significant variations across treatments, parents and parent vs. cross for all attributes related to seed yield. Some traits exhibited notable disparities between parents and crosses, underscoring the intricate genetic dynamics at play. The estimation of genetic components of variance underscored a predominant influence of non-additive gene action, especially in traits linked to yield. Specific combining ability (SCA) consistently surpassed general combining ability (GCA), underscoring the substantial role of non-additive genetic effects. Parental genotypes NPJ-194, DRMR-15-16, Kranti and NPJ-194 were identified as consistent and potent general combiners, indicating their potential to pass on favorable alleles to their offspring. Hybrid combinations such as SKJM-05 × Kranti, RW-85-59 × SKJM-05, and NPJ-194 × SKJM-05 exhibited notable GCA effects of parents, per se performance and SCA effects of hybrids for seed yield plant⁻¹. Heterosis breeding proved to be a viable strategy, with crosses such as RW-85-59 × SKJM-05, RW-85-59 × Giriraj, RW-85-59 × PHR-2, DRMR-15-16 × Giriraj, and SKJM-05 × PHR-2 exhibiting significant positive heterosis for OC over both mid-parent and better-parent values. Overall, this research provides valuable insights into the genetic basis of morphological traits in Indian mustard, offering strategic directions for focused breeding efforts and trait refinement.

Introduction

Indian mustard, scientifically known as Brassica juncea, is a versatile and vital oilseed crop native to the Indian subcontinent¹. It belongs to the Brassicaceae family and is widely cultivated for its pungent seeds, which are rich in oil content. Oilseeds, second only to cereals, hold a significant position in India’s agricultural economy. During the current millennium, the country’s imports have seen a twofold increase, rising from 9.5 to 19.5 kg per annum. As a result, it has now achieved the distinction of being the foremost global importer of vegetable oils. In India, oilseeds are cultivated annually across a vast expanse of 25.74 million hectares, yielding an impressive 30.55 million tonnes. The productivity for the quinquennium ending in 2019–20 stands at approximately 1188 kg per hectare. Notably, rapeseed-mustard plays a significant role in the country’s annual edible oilseed production, accounting for roughly a quarter of the total output².

Indian mustard (Brassica juncea) holds significant agricultural and economic importance in West Bengal but the region faces a critical challenge with regards to suboptimal seed yield and lower oil content. These limitations have substantial implications for the economic returns of farmers and the availability of mustard oil, a staple in both culinary and industrial sectors in the state. Prioritizing advanced breeding techniques is crucial for enhancing seed yield of the plant and oil content. A promising avenue in this regard involves the application of principles related to combining ability and heterosis³. Combining ability refers to the ability of specific parental lines to produce superior progeny when crossed, while heterosis (Hybrid Vigor) manifests as enhanced traits in hybrid offspring compared to their parents. These concepts are vital in plant breeding, helping to improve traits such as seed yield and oil content.

In West Bengal, mustard stands as the primary oil-producing crop. Nevertheless, the overall production of mustard in the state falls significantly below the demand, primarily due to insufficient genetic enhancements in line with the increasing needs. Combining ability, denoting the aptitude of specific parental lines to produce superior progeny while heterosis, or hybrid vigor, manifests as enhanced traits in hybrid offspring compared to their parents⁴. Both the concepts present valuable tools in the breeding arsenal. Through the meticulous selection and strategic crossing of parent lines possessing desirable traits such as high seed yield and elevated oil content, breeders aim to develop superior hybrids tailored to the unique agro-climatic conditions of West Bengal. This approach not only holds the promise of bolstering agricultural productivity but also contributes to the sustainable advancement of mustard cultivation in the region, benefitting both the farming community and consumers. By judiciously applying combining ability and heterosis principles, West Bengal stands to unlock the full potential of Indian mustard, thereby mitigating existing challenges and ensuring a more resilient and productive agricultural sector⁵.

The variation within general combining ability (GCA) encompasses the additive component of the total variance, while specific combining ability (SCA) accounts for the non-additive portion, primarily arising from dominance and epistatic deviations. Recognizing the relative importance of additive and non-additive genetic effects within a breeding population is essential for refining breeding procedures to improve trait performance. Earlier research on the amalgamation of traits has consistently detected noteworthy GCA and SCA impacts across morphological characteristics, yield, and yield-related traits as demonstrated by earlier studies^6–9. Both additive and non-additive genetic interactions have been recognized as significant factors in controlling the inheritance of yield and its constituent components, as evidenced by earlier studies^10–14. Recent studies, such as Yadav, et al.¹⁰, have emphasized the significance of combining ability analysis in Indian mustard (Brassica juncea L.) using diallel mating designs. This research highlights the potential of specific parental combinations and hybrids, demonstrating substantial GCA and SCA effects for yield and its contributing traits. Their findings underline the relevance of identifying superior combiners and cross combinations for enhancing yield through hybrid breeding. Within the array of breeding strategies, the diallel analysis stands out as a precise methodology extensively employed in crop plants. It serves the purpose of evaluating genotype performance in hybrid combinations and helps delineate the extent and manner of gene action governing quantitative traits^11,12.

This study uniquely applies diallel crossing to Indian mustard, focusing on combining ability and heterosis to address the specific yield and oil content challenges faced in West Bengal. Unlike previous work, which has largely focused on general genetic improvements, this research targets the development of high-yielding, high-oil hybrids tailored to the region’s agro-climatic conditions. Additionally, it offers a deeper exploration of gene action and heterosis, providing valuable insights for breeding superior mustard hybrids with both local and broader applications.

With this comprehensive outlook, the primary goal of our present study is to pinpoint the most proficient general combiners and their corresponding F₁ hybrids, evaluating them based on both general and specific combining abilities. Additionally, we seek to elucidate the type and magnitude of gene action, as well as the combining ability of parent and cross combinations. This investigation will also ascertain the degree of heterosis regarding yield and its component traits in Indian mustard, employing a diallel crossing system.

Materials and methods

Plant material

In this study, the genotype was obtained from Pulses and Oilseed Research Station in Kanpur, Banaras Hindu University located in Varanasi, Uttar Pradesh, and the Directorate of Rapeseed and Mustard Research and no special permissions were necessary to collect samples. During the 2018–2019 rabi season, a half diallel crossing was conducted among eight genetically diverse parents viz., NPJ-194, RW-85-59 (Sarma), DRMR-15-16, SKJM-05, Kranti, Giriraj, RNWR-09-3 and PHR 2, resulting in 28 direct crosses. These parents were carefully chosen from a pool of 71 genotypes obtained from Pulses and Oilseed Research Station in Kanpur, Banaras Hindu University located in Varanasi, Uttar Pradesh, and the Directorate of Rapeseed and Mustard Research (ICAR-DRMR) situated in Bharatpur, Rajasthan, based on Mahalanobis D² statistics¹³. A total of 36 treatments, comprising eight parents and 28 F₁s (Table 1), were cultivated using a randomized block design (RBD) with three replications. Each genotype, including parents and hybrids, was allotted a single plot measuring 0.5 m², accommodating 10 plants per row. The spacing maintained for proper growth and assessment was 50 cm between rows and 10 cm between plants within a row. A 0.5 m canal was retained between two plots to facilitate drainage and irrigation. This layout ensured adequate plant density and uniform crop management throughout the experimental field, followed by careful thinning. Standard cultural practices for mustard cultivation were rigorously followed to ensure a healthy and competitive crop stand.

Table 1.

List of parental genotypes and crosses developed from the genetically divergent parents.

S.No.	Parents	S.No.	Crosses	S.No.	Crosses
1.	NPJ-194	1.	NPJ-194 × RW-85-59	15.	DRMR-15-16 × Kranti
2.	RW-85-59 (Sarma)	2.	NPJ-194 × DRMR-15-16	16.	DRMR-15-16 × Giriraj
3.	DRMR-15-16	3.	NPJ-194 × SKJM-05	17.	DRMR-15-16 × RNWR-09-3
4.	SKJM-05	4.	NPJ-194 × Kranti	18.	DRMR-15-16 × PHR-2
5.	Kranti	5.	NPJ-194 × Giriraj	19.	SKJM-05 × Kranti
6.	Giriraj	6.	NPJ-194 × RNWR-09-3	20.	SKJM-05 × Giriraj
7.	RNWR-09-3	7.	NPJ-194 × PHR-2	21.	SKJM-05 × RNWR-09-3
8.	PHR 2	8.	RW-85-59 × DRMR-15-16	22.	SKJM-05 × PHR-2
		9.	RW-85-59 ×SKJM-05	23.	Kranti × Giriraj
		10.	RW-85-59 × Kranti	24.	Kranti × RNWR-09-3
		11.	RW-85-59 × Giriraj	25.	Kranti × PHR-2
		12.	RW-85-59 × RNWR-09-3	26.	Giriraj × RNWR-09-3
		13.	RW-85-59 × PHR-2	27.	Giriraj × PHR-2
		14.	DRMR-15-16 × SKJM-05	28.	RNWR-09-3 × PHR-2

Experimental location and environmental condition

The field trial took place during the rabi seasons at the Instructional Farm of Uttar Banga Krishi Viswavidyalaya situated in Pundibari, Cooch Behar, West Bengal. The farm is located at latitude of 26° 40′ N and a longitude of 89° 39′ E, with an elevation of 47 m above sea level. The site is characterized by sandy loam soil and is classified under the agro-climatic zone of the lower Gangetic plain region (III); specifically, the New Alluvial Zone (WB-4)-NARP. During the study period, the average temperature ranged from 9.9 to 30.1 °C, with a relative humidity range of 49.7–91.1%, ensuring favorable growing conditions. Rainfall during the season was minimal, at 37.6 mm, allowing controlled irrigation management. These conditions were conducive to healthy crop growth and optimal trait expression.

Yield traits

For every replication, five plants per genotype were selected at random, and the subsequent observations were documented.

Days to 50% flowering (DFPF) refers to the duration in days from the time of sowing until 50% of the plants within the plot have reached the flowering stage.

Primary branches per plant (PBPP) is defined as the average number of first-order branches that develop from the main shoot at maturity, based on a selection of five plants.

Secondary branches per plant (SBPP) is the average number of second-order fruiting branches that develop from the primary branches at maturity, determined by averaging the counts from five selected plants.

Siliqua per plant (SPP): The number of siliquae on each of the selected five plants at maturity, averaged.

Seeds per siliqua (SPS) were recorded by taking ten siliquae from each chosen plant and noting down the average number of seeds per siliqua.

Height up to first fruiting branch (cm) (HFTFB): The length from the ground to the first capsule-bearing branch on the main stem, measured in centimeters.

Plant height (PH) is the measurement in centimeters, taken from the base of the plant to its tip at maturity.

Seed yield per plant (SYPP) is determined by threshing, cleaning, and drying all siliquae from five selected plants per genotype. The resulting weight of the seeds is then recorded in grams.

Thousand seed weight (TSW) represents the weight of a thousand seeds randomly chosen from the overall yield of five plants of a genotype, measured in grams.

Oil content (%) (OC) can be determined by the Soxhlet method¹⁴. Two grams of seeds from each treatment were crushed, and the oil was extracted with n-Hexane. The weight of the oil obtained from 100 g of seeds was recorded.

These observations provide comprehensive data for assessing the traits and attributes related to seed yield and quality.

Statistical analysis

The average values of genotypes within each replication were employed for statistical analysis. A randomized block design was applied to evaluate the significance of variance among the genotypes (treatments) concerning different traits. The Analysis of Variance (ANOVA) was performed to evaluate the significance of variation among genotypes (parents and F₁s) across traits. The model included factors such as replication, treatments, and error to partition the variance. Mean sum of squares (MSS) values were computed for each source of variation—replications, genotypes (parents and hybrids), and the interaction between parents and hybrids (parents vs. F₁s). The F-test was used to assess the significance of treatment effects, comparing the observed variance with expected values under the null hypothesis. Significant F-values indicated meaningful genotypic differences, allowing further exploration of genetic effects like combining ability and heterosis.

The analysis adhered to the procedures as outlined by¹⁵. The combining ability of 36 entries (including parents and hybrids) was assessed based on the mean values, employing^11,12. This involved Method II, which includes parents and the set of F₁s without reciprocals and in Model I, it is assumed that genotypes and block effects are considered to be consistent (fixed) meanwhile, environmental effects are regarded as fluctuating or variable. The combining ability analysis was conducted following by Method-II, Model-1, which presupposes that both variety and block effects remain consistent and fixed¹⁵.

where, Y_ijk is the performance of hybrid of ijth cross in kth replication, i, j = 1,2,3…P (Number of parents). k = 1,2,3…b (Number of replications), µ is the General mean, g_i is the General combining ability effect of ith parent, g_j is the General combining ability effect of jth parent, S_ij is the Specific combining ability effect of the cross between ith and jth parent, e_ijk is the Environment effect pertaining to ijkth observation.

The gca and sca effects were calculated by applying the following formulae.

General Combining Ability (GCA) Effect:

Gi is the General combining ability effect of the ith parent, Yi is the Total of the ith parentacross all hybrids it is invoved in, Yii is the Mean value of the ith parent, Y.. is the Grand meanof all hybrids and parents, p is the total numbers of parents.

Specific Combining Ability (SCA) Effect:

Sij is the Specific combining ability effectof the hybrid between the ith and jthparents, Yij is the mean performance of ij hybrid, Yi. is the Total of ith parent across all hybrids it is involved in, Yj. is the Total of jth parent across all hybrids it is involved in, Yii is the Mean value of ith parent, Yjj is the Mean value of jth parent.

Each gca and sca effects were subjected to “t” test for testing of significance.

Heterosis was initially proposed by Mather and Jinks¹⁶. The calculation of heterosis, expressed as the percentage increase or decrease of F₁ hybrids over the better parent by Fonseca and Patterson¹⁷ and mid-parent suggested by Briggle¹⁸, followed the formula below:

where, mean value of F1

Test of significance of heterosis

Test of significance for heterosis was done following¹⁹:

where, SE₁ is the Standard error of heterosis over mid parent, SE₂ is the Standard error of heterosis over better parent, MSe is the Error mean square of ANOVA and r is the Number of replications.

All the mean values of the nine morphological traits in Indian mustard were subjected to a normality test. If the computed P-value is found to be greater than the significance level of the different normality tests, then the trait follows normality distribution or else it deviates and log transformation [log(x)] of the data is to be done. Also, if the individual value of the data for a character is all lower than 10 then instead of log(x), the transformation is log (x + 1). In the present study, it was found that among the morphological traits SPP, HFTFB, PH, SYPP and TSW. Hence, both log(x) and log(x + 1) transformations were carried out for the characters depending upon whether their values were greater or less than 10. Subsequently, all further statistical analyses were conducted utilizing the logarithmically transformed values of the trait. These computations were carried out using WINDOW STAT version 8.6 software provided by INDOSTAT Services Ltd., Hyderabad, India. ggplot2 package^20,21 in R programme was used to create Violin graph and lollipop graph to estimate the best general combiner and specific combiner for major yield and its attributing traits in Indian mustard.

Results

Mean performance of parents and crosses

The Violin graph representing the mean performance of parents and crosses for seed yield and its attributing traits in Indian mustard (Brassica juncea) showed in (Fig. 1). The violin plots illustrate the distribution of traits across the parents and their hybrids. The shape and width of the violins indicate the variability in the trait distribution. A wider section of the plot reflects a higher concentration of data points, suggesting a more uniform performance among the genotypes (both parents and hybrids) for that trait. Conversely, a narrower section indicates greater variation or fewer genotypes with similar trait values. These variations in shape demonstrate differences in the spread and central tendency of traits, allowing for a clearer visual comparison of trait distribution between the parents and their corresponding hybrids. The wider or more spread-out violins indicate a broader range of performance within the population, while those that are more compact suggest more consistent trait expression across the genotypes. This visualization allows for a detailed comparison of genetic diversity and performance within the set of parents and hybrids, highlighting both the mean values and the degree of variability for each trait under study.

Fig. 1.

Violin graph representing the mean performance of parents and crosses for seed yield and its attributing characters in Indian mustard (Brassica juncea).

When considering both parents and crosses collectively, NPJ-194 × SKJM-05 (51.00) and NPJ-194 × RW-85-59 (51.00) displayed the lowest mean value for DFPF (Days to 50% flowering), showing superior performance without significant differences from other crosses. In terms of PBPP (Primary branches per plant), RW-85-59 × Kranti (4.33) and SKJM-05 × PHR-2 (5.87) showed high mean values whereas SBPP (Secondary branches per plant), the cross NPJ-194 × Kranti (15.51) was the best-performing one, significantly outperforming other genotypes. For SPP (Siliqua per plant), PHR-2 (329.80) demonstrated the best performance, while in SPS (Seeds per siliqua), NPJ-194 × Kranti (15.43) excelled without significant differences from other genotypes. In HFTFB (Height up to first fruiting branch), NPJ-194 × Kranti (133.5) was the best-performing cross. For overall PH (Plant height), DRMR-15-16 × Kranti (175.93) exhibited tall stature without significant differences from other genotypes. Concerning SYPP (Seed yield per plant), Kranti × Giriraj (6.33) was the top performer, and in TSW (Thousand seed weight), DRMR-15-16 × Giriraj (2.76) showed the best performance. NPJ-194 (60.03) performed well among the parents, while Cross Giriraj × RNWR-09-3 (60.49) recorded the highest OC (Oil content).

Analysis of variance (ANOVA)

The ANOVA was conducted to assess the significance of variance among treatments, parents, and parent vs. crosses combinations for various morphological traits related to seed yield in Indian mustard. The experiment encompassed eight parental lines and 28 crosses, focusing on ten key attributes: DFPF, PBPP, SBPP, SPP, SPS, HFTFB, PH, SYPP, TSW and OC. The comprehensive ANOVA results for seed yield and its attributing traits are presented in (Table 2). The outcomes of this investigation demonstrated notable variations among the treatments for all the seed yield attributes. The mean sum of squares analysis highlighted significant disparities in both parental lines and crosses, attaining statistical significance at the 5% and 1% probability levels for all traits, except for SPS in the case of parents. Intriguingly, DFPF, PH, TSW, and OC displayed substantial variances between parents vs. crosses while in contrast, PBPP, SBPP, SPP, SPS, HFTFB, and SYPP exhibited non-significant differences. These findings underscore the intricate genetic dynamics underlying seed yield and its attributing traits in Indian mustard, shedding light on potential avenues for further research and targeted breeding efforts.

Table 2.

ANOVA for seed yield and its contributing traits in Indian mustard (Brassica juncea).

Sources of variation	df	DFPF	PBPP	SBPP	SPP	SPS	HFTFB (cm)	PH (cm)	SYPP (g)	TSW (g)	OC (%)
Replication	2	2.3982	5.5033**	19.8031**	0.0003	0.7487	0.0012	0.0001	0.0000	7.4444**	74.3430**
Treatments	35	40.2632**	0.9641**	7.8982**	0.0214**	4.9412**	0.0122**	0.0042**	0.0040**	135.664**	132.3710**
Parents	7	31.9048**	1.1483*	8.8283*	0.0334**	2.7323	0.0109**	0.0065**	0.0059**	125.4050**	156.1850**
Crosses	27	42.5340**	0.9309*	7.9494**	0.0190**	5.4574**	0.0130**	0.0034**	0.0037**	139.2710**	129.1660**
Parents vs. crosses	1	37.4630**	0.5717	0.0037	0.0007	6.4638	0.0001	0.0159**	0.0015	110.0950**	52.2223**
Error	70	3.2553	0.4904	3.1831	0.0002	2.5194	0.0009	0.0001	0.0009	1.4250	0.9810
Total	107	15.3447	0.7390	5.0361	0.0071	3.2785	0.0046	0.0014	0.0019	45.4480	45.3300

*Significant at p ≤ 0.05 and **Significant at p ≤ 0.01. DFPF = Days to 50% flowering; PBPP Primary branches per plant, SBPP Secondary branches per plant, SPP Siliqua per plant, SPS Seeds per siliqua, HFTFB Height up to first fruiting branch (cm), PH Plant height (cm), SYPP Seed yield per plant (g), TSW Thousand seed weight (g), OC Oil content (%).

Analysis of variance for combining ability

The results of the ANOVA for combining ability in Indian mustard are displayed in (Table 3). The research findings indicated significant contributions from both general combining ability (GCA) and specific combining ability (SCA) to the total mean sum of squares for all seed yield and its attributing traits. The GCA and SCA exhibited significance at both 5% and 1% probability levels, indicating their substantial roles in the inheritance of these traits. This emphasizes the crucial role played by both additive and non-additive genetic effects in influencing the manifestation of seed yield and its attributing traits. Notably, SPS displayed an exception in this pattern, as SCA did not reach significance. This implies that additive genetic effects play a primary role in the inheritance of this particular trait.

Table 3.

ANOVA for genetic interaction in seed yield and its contributing traits in Indian mustard (Brassica juncea).

Sources of variation	df	DFPF	PBPP	SBPP	SPP	SPS	HFTFB (cm)	PH (cm)	SYPP (g)	TSW (g)	OC (%)
GCA	7	42.659**	0.390*	5.032**	100.810**	3.0036**	114.860**	29.574**	10.221**	83.056**	49.828**
SCA	28	6.111**	0.304*	2.033*	63.813**	1.308	22.137**	10.065***	14.240**	36.763**	42.698**
Error	70	1.085	0.163	1.061	0.708	0.840	2.960	0.181	3.051	0.475	0.327

*Significant at p ≤ 0.05 and **Significant at p ≤ 0.01. DFPF Days to 50% flowering, PBPP Primary branches per plant, SBPP Secondary branches per plant, SPP Siliqua per plant, SPS Seeds per siliqua, HFTFB Height up to first fruiting branch (cm), PH Plant height (cm), SYPP Seed yield per plant (g)m TSW Thousand seed weight (g), OC Oil content (%).

Estimates of genetic components of variance and dominance

The genetic components of variances and dominance for the studied traits in Indian mustard showed in (Table 4). Remarkably, the variance component attributed to specific combining ability (σ²sca) consistently exceeded that of general combining ability (σ²gca) across all traits viz., DFPF, PBPP, SBPP, SPP, SPS, HFTFB, PH, SYPP, TSW and OC. The GCA to SCA variance ratio (σ²gca/σ²sca) remained below 1 for all traits. The mean degree of dominance (σ²sca/σ²gca) ^[0.5 was found to be greater than 1 for all the traits which indicated the involvement of over dominance. Furthermore, the dominance variance (σ²_D) exceeded additive genetic variance (σ²_A) for most traits, underscoring the substantial impact of dominance effects on trait expression. The ratio of additive variance to dominance variance (σ²_A/σ²_D) was generally lower than unity for all the traits except DFPF. The predictability ratio (σ²A/σ²A + σ²D) was consistently higher than 0.05 for all studied traits.

Table 4.

Assessments of the genetic variance components and level of dominance in relation to seed yield and its associated traits in Indian mustard (Brassica juncea).

Sources of variation	DFPF	PBPP	SBPP	SPP	SPS	HFTFB (cm)	PH (cm)	SYPP (g)	TSW (g)	OC (%)
σ2gca	3.65481	0.00860	0.29986	0.00037	0.16956	0.00093	0.00020	-0.00004	4.72936	0.71300
σ2sca	5.02637	0.14070	0.97198	0.00631	0.46812	0.00192	0.00099	0.00112	35.28757	42.37082
σ2gca/σ2sca	0.72713	0.06115	0.30851	0.05863	0.36222	0.48350	0.19735	-0.03591	0.13402	0.01683
(σ2sca/ σ2gca)0.5	1.17272	1.17272	1.80040	4.12965	1.66156	1.43684	2.22485	5.29150	2.73155	7.70883
σ2A	7.30961	0.01721	0.59973	0.00074	0.33913	0.00185	0.00039	0.00008	9.45873	1.42600
σ2D	5.02637	0.14070	0.97198	0.00631	0.46812	0.00192	0.00099	0.00112	35.28757	42.37082
σ2A/σ2D	1.45425	0.12232	0.61702	0.11727	0.72445	0.96354	0.39394	0.07143	0.26805	0.03366
σ2A/σ2A + σ2D	6.02637	1.14070	1.97198	1.00631	1.46812	1.00192	1.00099	1.00112	36.28757	43.37082

General Combining Ability (GCA) represents the additive genetic effects, while Specific Combining Ability (SCA) pertains to non-additive genetic effects. The variance of GCA is denoted as σ²GCA, and for SCA, it is σ²SCA. The square root of the ratio of σ²SCA to σ²GCA is referred to as the degree of dominance. Additive genetic variance is expressed as σ²A, whereas dominance variance is denoted as σ²D. The predictability ratio is calculated as σ²A divided by the sum of σ²A and σ²D.

DFPF Days to 50% flowering, PBPP Primary branches per plant, SBPP Secondary branches per plant, SPP Siliqua per plant, SPS Seeds per siliqua, HFTFB Height up to first fruiting branch (cm), PH Plant height (cm), SYPP Seed yield per plant (g), TSW Thousand seed weight (g), OC Oil content (%).

Estimation of general combining ability (gca) effects

The GCA effects for eight parental genotypes across the studied traits are outlined in (Table 5). Parents RW-85-59 (− 3.442) and DRMR-15-16 (− 1.775) exhibited significant negative GCA effects for early flowering. RW-85-59 (0.258) emerged as a strong general combiner for PBPP. Additionally, RW-85-59 (1.200) and Kranti (0.726) displayed noteworthy GCA effects for SBPP. Parents NPJ-194 (0.023), RW-85-59 (0.013), Kranti (0.030) and PHR-2 (0.038) exhibited positive significant GCA effects for SPP. The genotype DRMR-15-16 (0.636) demonstrated to be the best general combiner GCA effect for SPS. Genotypes RW-85-59 (0.057), DRMR-15-16 (0.021) and Kranti (0.024) showed significant GCA effects for HFTFB. NPJ-194 (-0.021), RW-85-59 (− 0.027) and DRMR-15-16 (− 0.008) exhibited significant negative GCA effects for PH, indicating their role in promoting dwarfness. SKJM-05 (0.013) emerged as a valuable general combiner for SYPP, demonstrating its significance in this crucial trait. Lastly, RW-85-59 (2.458), SKJM-05 (3.158), KRANTI (1.292), RNWR-09-3 (1.558) and PHR-2 (1.758) displayed substantial GCA effects for TSW, while NPJ-194 (3.625), KRANTI (0.358), RNWR-09-3 (2.125) and PHR-2 (0.458) exhibited significant and positive GCA effects for OC.

Table 5.

Combining ability effects of parents for seed yield and its related traits in Indian mustard (Brassica juncea).

S.No	Parents	DFPF	PBPP	SBPP	SPP	SPS	HFTFB (cm)	PH (cm)	SYPP (g)	TSW (g)	OC (%)
1	NPJ-194	1.658**	− 0.082	− 0.491	0.023**	− 1.057**	0.002	− 0.021**	0.006	− 3.275*	3.625*
2	RW-85–59 (Sarma)	− 3.442**	0.258*	1.200**	0.013**	0.282	0.057**	− 0.027**	0.000	2.458*	− 0.108*
3	DRMR-15–16	− 1.775**	− 0.015	− 0.318	− 0.012**	0.636*	0.021**	− 0.008**	0.003	− 3.642*	− 0.975*
4	SKJM-05	− 0.075	− 0.062	0.049	− 0.026**	0.209	− 0.009	0.010**	0.013*	3.158*	− 2.075*
5	Kranti	0.258	0.065	0.726*	0.030**	0.492	0.024**	0.011**	− 0.011*	1.292*	0.358*
6	Giriraj	0.158	− 0.375**	− 1.098**	− 0.055**	− 0.004	− 0.027**	0.007**	0.009	− 3.308*	− 3.408*
7	RNWR-09–3	− 0.242	− 0.015	− 0.078	− 0.011**	− 0.451	− 0.019**	0.006**	− 0.016**	1.558*	2.125*
8	PHR-2	3.458**	0.225	0.009	0.038**	− 0.107	− 0.050**	0.023**	− 0.005	1.758*	0.458*
	SE (gi)	0.308	0.120	0.305	0.002	0.271	0.005	0.001	0.005	0.203	0.1691
	SE(gi-gj)	0.466	0.181	0.461	0.004	0.410	0.008	0.002	0.008	0.3082	0.2556

*Significant at p ≤ 0.05 and **Significant at p ≤ 0.01. DFPF Days to 50% flowering, PBPP Primary branches per plant, SBPP Secondary branches per plant, SPP Siliqua per plant, SPS Seeds per siliqua, HFTFB Height up to first fruiting branch (cm), PH Plant height (cm), SYPP Seed yield per plant (g), TSW Thousand seed weight (g), OC Oil content (%).

Estimation of specific combining ability (sca) effects

The detailed account of the specific combining ability (SCA) effects for 28 crosses across the studied traits outlined in (Table 6). These results unveil noteworthy interactions that hold significant implications for trait improvement in Indian mustard.

Table 6.

Combining ability effects of crosses for seed yield and its associated traits in Indian mustard (Brassica juncea).

S.No	Crosses	DFPF	PBPP	SBPP	SPP	SPS	HFTFB (cm)	PH (cm)	SYPP (g)	TSW (g)	OC (%)
1	NPJ-194 × RW-85–59	− 0.819	− 0.771**	− 1.439**	− 0.042**	− 0.037	− 0.041**	− 0.021**	− 0.002	2.511**	0.659
2	NPJ-194 × DRMR-15–16	4.848**	0.369	0.411	0.053**	− 0.124	0.042**	0.016**	− 0.058**	− 5.722**	8.193**
3	NPJ-194 × SKJM-05	3.481**	0.349	0.111	0.047**	− 0.164	0.012	0.008**	0.065**	− 4.856**	− 0.374
4	NPJ-194 × Kranti	− 1.519**	0.089	− 0.633	− 0.080**	− 0.247	− 0.011	0.007**	0.009	6.344**	6.859**
5	NPJ-194 × Giriraj	0.581	− 0.204	− 0.342	− 0.034**	0.983	− 0.016	0.005	0.039**	1.611**	− 5.707**
6	NPJ-194 × RNWR-09–3	− 0.019	0.636**	1.038	0.141**	0.829	− 0.008	0.053**	− 0.016	7.078**	− 0.574
7	NPJ-194 × PHR − 2	5.281**	0.929**	1.551**	0.166**	− 2.781**	0.020	0.072**	0.026**	5.878**	− 14.907**
8	RW-85–59 × DRMR-15–16	− 0.052	0.896**	0.454	− 0.094**	− 0.197	0.056**	0.009**	0.025**	12.878**	− 1.741**
9	RW-85–59 × SKJM-05	− 3.085**	0.342	− 1.179	− 0.043**	− 0.570	− 0.020	− 0.012**	0.044**	1.744**	2.359**
10	RW-85–59 × Kranti	0.248	0.216	4.250**	0.097**	1.574**	0.133**	− 0.007**	− 0.028**	0.278	2.259**
11	RW-85–59 × Giriraj	1.681**	− 0.078	0.034	0.019**	0.843	− 0.012	0.018**	− 0.032**	4.211**	7.693**
12	RW-85–59 × RNWR-09–3	2.081**	− 0.238	− 0.586	− 0.022**	0.823	− 0.040**	− 0.004	− 0.010	− 5.656**	− 4.174**
13	RW-85–59 × PHR-2	− 0.619	− 0.811**	− 1.273	− 0.101**	− 0.020	− 0.066**	0.005	0.016	− 4.856**	10.159**
14	DRMR-15–16 × SKJM-05	− 0.752	− 0.584**	0.205	0.019**	0.409	− 0.077**	− 0.022**	0.015	9.178**	2.226**
15	DRMR-15–16 × Kranti	− 2.085**	− 0.511	− 1.006	− 0.055**	− 0.407	− 0.037**	− 0.006**	− 0.024**	− 3.622**	− 1.207**
16	DRMR-15–16 × Giriraj	− 0.319	− 0.338	− 1.449**	0.041**	1.223**	0.021	0.038**	− 0.027**	− 8.356**	3.893**
17	DRMR-15–16 × RNWR-09–3	− 3.252**	− 0.498	− 1.269	− 0.014**	1.536**	0.006	− 0.001	− 0.006	− 1.222**	− 7.307**
18	DRMR-15–16 × PHR-2	− 2.285**	− 0.204	0.311	0.041**	1.193	− 0.003	− 0.021**	0.003	0.911**	− 4.307**
19	SKJM-05 × Kranti	3.881**	0.469	0.294	− 0.084**	0.287	0.040**	0.056**	0.029**	2.578**	− 2.107**
20	SKJM-05 × Giriraj	− 0.685	− 0.024	0.518	− 0.039**	0.783	0.065**	− 0.026**	− 0.068**	− 2.489**	− 3.007**
21	SKJM-05 × RNWR-09–3	1.048	− 0.451	− 0.569	− 0.020**	− 0.637	− 0.043**	− 0.008**	− 0.033**	0.311	− 6.207**
22	SKJM-05 × PHR-2	0.348	− 0.358	− 1.455**	− 0.092**	0.886	0.017	0.001	− 0.041**	− 3.222**	8.459**
23	Kranti × Giriraj	0.648	0.316	− 1.359**	0.095**	1.033	0.021	− 0.001	− 0.027**	0.711	− 0.774**
24	Kranti × RNWR-09–3	− 0.285	− 0.578**	− 1.579**	− 0.013**	− 0.453	− 0.027**	− 0.026**	0.018	3.511**	− 0.307
25	Kranti × PHR-2	0.015	0.782**	1.067	− 0.065**	− 0.330	− 0.079**	− 0.013**	0.061**	− 3.356**	− 11.641**
26	Giriraj × RNWR-09–3	− 0.519	0.529**	1.445**	− 0.001	− 0.757	0.015	0.008**	− 0.009	− 12.222**	− 3.874**
27	Giriraj × PHR-2	− 0.219	0.556**	2.758**	0.060**	− 0.767	− 0.021	0.044**	− 0.030**	8.578**	− 4.207**
28	RNWR-09–3 × PHR-2	1.181	0.262	− 0.395	− 0.014**	− 1.254**	0.034**	0.006	0.002	2.378**	9.259**
	SE(sij))	0.822	0.367	0.934	0.008	0.831	0.016	0.004	0.016	0.625	0.518

*Significant at p ≤ 0.05 and **Significant at p ≤ 0.01. DFPF Days to 50% flowering, PBPP Primary branches per plant, SBPP Secondary branches per plant, SPP Siliqua per plant, SPS Seeds per siliqua, HFTFB Height up to first fruiting branch (cm), PH Plant height (cm), SYPP Seed yield per plant (g), TSW Thousand seed weight (g), OC Oil content (%).

Fifteen crosses exhibited desirable negative SCA effects for early flowering, suggesting their potential for breeding early maturing varieties. Notable combinations showing negative significant sca effects include NPJ-194 × Kranti (− 1.519), RW-85-59 × SKJM-05 (− 3.085), DRMR-15-16 × Kranti (− 2.085), DRMR-15-16 × RNWR-09-3 (− 3.252) and DRMR-15-16 × PHR-2 (− 2.285). For PBPP, fourteen cross combinations displayed significant and positive SCA effects, indicating their potential for enhancing branching characteristics. Crosses such as NPJ-194 × RNWR-09-3 (0.636), NPJ-194 × PHR-2 (0.929), RW-85-59 × DRMR-15-16 (0.896), Kranti × PHR-2 (0.782), Giriraj × RNWR-09-3 (0.529) and Giriraj × PHR-2 (0.556) emerged as particularly promising specific combiners for this trait.

Four cross combinations displayed substantial positive specific combining ability (SCA) effects for SBPP, indicating their potential for enhancing this trait. Prominent combinations include NPJ-194 × PHR-2 (1.551), RW-85-59 × Kranti (4.250), Giriraj × RNWR-09-3 (1.445) and Giriraj × PHR-2 (2.758). In total, ten crosses exhibited positive and statistically significant specific combining ability (SCA) effects for SPP, highlighting their potential for improving this important trait. The crosses viz., NPJ-194 × DRMR-15-16 (0.053), NPJ-194 × SKJM-05 (0.047), NPJ-194 × RNWR-09-3 (0.141), NPJ-194 × PHR-2 (0.166), RW-85-59 × Kranti (0.097), RW-85-59 × Giriraj (0.019), DRMR-15-16 × SKJM-05 (0.019), DRMR-15-16 × Giriraj (0.041), DRMR-15-16 × PHR-2 (0.041), Kranti × Giriraj (0.095) and Giriraj × PHR-2 (0.060) was found as good specific combiner.

Based on SCA effects, crosses RW-85-59 × Kranti (1.574), DRMR-15-16 × Giriraj (1.223) and DRMR-15-16 × RNWR-09-3 (1.536) were identified as particularly promising for SPS. Six combinations, namely NPJ-194 × DRMR-15-16 (0.042), RW-85-59 × DRMR-15-16 (0.056), RW-85-59 × Kranti (0.133), SKJM-05 × Kranti (0.040), SKJM-05 × Giriraj (0.065) and RNWR-09-3 × PHR-2 (0.034) exhibited significant and positive SCA effects for HFTFB. Thirteen crosses were identified with desirable negative SCA values. Significantly, the crosses viz., NPJ-194 × RW-85-59 (− 0.021), RW-85-59 × SKJM-05 (− 0.012), RW-85-59 × Kranti (− 0.007), DRMR-15-16 × SKJM-05 (− 0.022), DRMR-15-16 × Kranti (− 0.006), DRMR-15-16 × PHR-2 (− 0.021), SKJM-05 × GIRIRAJ (− 0.026), SKJM-05 × RNWR-09-3 (− 0.008), Kranti × RNWR-09-3 (− 0.026), and Kranti × PHR-2 (− 0.013) demonstrated noteworthy negative specific combining ability (SCA) effects for PH.

The positive and significant value of specific combining ability effect of SYPP were obtained by the crosses namely, NPJ-194 × SKJM-05 (0.065), NPJ-194 × Giriraj (0.039), NPJ-194 × PHR-2 (0.026), RW-85-59 × DRMR-15-16 (0.025), RW-85-59 × SKJM-05 (0.044), SKJM-05 × Kranti (0.029) and Kranti × PHR-2 (0.061). The crosses namely NPJ-194 × RW-85-59 (2.511), NPJ-194 × Kranti (6.344), NPJ-194 × Giriraj (1.611), NPJ-194 × RNWR-09-3 (7.078), NPJ-194 × PHR-2 (5.878), RW-85-59 × DRMR-15-16 (12.878), RW-85-59 ×SKJM-05 (1.744), RW-85-59 × Giriraj (4.211), DRMR-15-16 × SKJM-05 (9.178), DRMR-15-16 × PHR-2 (0.911), SKJM-05 × Kranti (2.578), Kranti × RNWR-09-3 (3.511), Giriraj × PHR-2 (8.578) and RNWR-09-3 × PHR-2 (2.378) were having positive and significant value of specific combining ability effects for TSW. The crosses NPJ-194 × DRMR-15-16 (8.193), NPJ-194 × Kranti (6.859), RW-85-59 ×SKJM-05 (2.359), RW-85-59 × Kranti (2.259), RW-85-59 × Giriraj (7.693), RW-85-59 × PHR-2 (10.159), DRMR-15-16 × SKJM-05 (2.226), DRMR-15-16 × Giriraj (3.893), SKJM-05 × PHR-2 (8.459) and RNWR-09-3 × PHR-2 (9.259) showed significant positive sca effects and thus, were good for OC.

Estimation of heterosis

The evaluation of heterosis for seed yield and its attributing traits is summarized in (Table 7), with corresponding graphical representation in (Fig. 4).

Table 7.

Percentage of heterosis over mid-parent (MP) and superior-parent (BP) for seed yield and its associated traits in Indian mustard.

S.No	Crosses	DFPF		PBPP		SBPP		SPP		SPS
		Mid Parent	Better Parent	Mid Parent	Better Parent	Mid Parent	Better Parent	Mid Parent	Better Parent	Mid Parent	Better Parent
1	NPJ-194 × RW-85–59	3.770	0.000	− 11.270	− 24.100*	− 12.240	− 25.860*	− 1.150*	− 5.260**	1.520	− 1.340
2	NPJ-194 × DRMR-15–16	12.310**	11.310**	10.950	− 2.560	0.000	− 9.460	5.060**	3.670**	3.300	0.000
3	NPJ-194 × SKJM-05	13.600**	13.250**	14.500	4.170	− 2.530	− 14.010	2.490**	− 0.430	− 2.430	− 7.180
4	NPJ-194 × Kranti	2.960	0.580	14.960	7.350	− 2.190	− 12.990	− 1.880**	− 5.830**	− 2.130	− 8.000
5	NPJ-194 × Giriraj	6.820**	4.650	8.770	5.080	− 3.260	− 7.500	2.930**	0.600	12.390	10.800
6	NPJ-194 × RNWR-09–3	5.360*	3.510	20.300	8.110	8.090	− 3.290	9.810**	9.080**	3.910	2.200
7	NPJ-194 × PHR − 2	15.580**	8.510**	36.430**	25.710*	29.460	28.930	9.900**	6.190**	− 30.100**	− 36.570**
8	RW-85–59 × DRMR-15–16	− 2.180	− 6.550*	10.560	7.230	− 0.620	− 8.050	− 6.130**	− 8.850**	10.550	10.110
9	RW-85–59 × SKJM-05	− 4.080	− 7.830**	3.230	− 3.610	− 14.800	− 18.970	− 6.030**	− 7.330**	2.230	0.000
10	RW-85–59 × Kranti	0.610	− 5.200*	5.960	− 3.610	41.800**	33.680**	0.970*	0.830	19.740*	15.700
11	RW-85–59 × Giriraj	3.380	− 2.330	0.000	− 16.870	5.580	− 18.390	0.290	− 5.950**	19.160*	14.210
12	RW-85–59 × RNWR-09–3	3.700	− 1.750	− 8.280	− 13.250	− 9.200	− 14.940	− 2.370**	− 5.810**	11.800	10.460
13	RW-85–59 × PHR-2	0.290	− 9.040**	− 12.420	− 19.280	− 5.760	− 20.110	− 6.280**	− 7.050**	− 1.370	− 8.100
14	DRMR-15–16 × SKJM-05	− 1.200	− 1.790	− 17.330	− 20.510	− 8.850	− 11.460	− 1.590**	− 3.130**	12.270	10.260
15	DRMR-15–16 × Kranti	− 4.990*	− 6.360*	− 10.960	− 16.670	− 13.250	− 14.940	− 3.570**	− 6.240**	6.700	3.500
16	DRMR-15–16 × Giriraj	− 1.760	− 2.910	− 8.270	− 21.790	− 20.160	− 34.460*	3.350**	− 0.290	24.790*	19.150
17	DRMR-15–16 × RNWR-09–3	− 7.370**	− 8.190**	− 15.790	− 17.950	− 23.330	− 24.340	− 0.070	− 0.730	20.000*	18.090
18	DRMR-15–16 × PHR-2	− 3.930	− 9.040**	− 2.700	− 7.690	4.090	− 5.410	1.580**	− 0.560	9.900	2.780
19	SKJM-05 × Kranti	9.140**	6.940**	12.860	9.720	0.320	− 0.640	− 6.880**	− 8.040**	6.840	5.500
20	SKJM-05 × Giriraj	1.180	− 0.580	2.360	− 9.720	4.760	− 15.920	− 2.540**	− 7.400**	15.300	8.210
21	SKJM-05 × RNWR-09–3	3.860	2.340	− 12.330	− 13.510	− 15.210	− 16.560	− 2.550**	− 4.690**	− 2.920	− 6.150
22	SKJM-05 × PHR-2	3.950	− 2.130	− 2.820	− 4.170	− 14.390	− 24.200	− 6.220**	− 6.750**	2.680	− 2.310
23	Kranti × Giriraj	2.030	1.730	17.070	5.880	− 8.430	− 25.970	4.580**	− 1.800**	18.060	9.500
24	Kranti × RNWR-09–3	0.000	− 0.580	− 9.860	− 13.510	− 17.650	− 18.180	− 1.080*	− 4.440**	− 0.520	− 5.000
25	Kranti × PHR-2	1.940	− 2.130	27.540*	25.710	− 21.450	8.440	− 3.910**	− 4.580**	− 5.290	− 8.800
26	Giriraj × RNWR-09–3	− 0.290	− 0.580	14.730	0.000	16.600	− 5.260	2.220**	− 0.740	0.850	− 2.200
27	Giriraj × PHR-2	1.670	− 2.660	24.800*	11.430	52.780**	36.360*	4.170**	− 1.550**	− 5.430	− 15.280
28	RNWR-09–3 × PHR-2	3.620	− 1.060	9.720	6.760	− 2.560	− 12.500	− 0.070	− 2.810**	− 15.080	− 21.760*
	SE ( ±)	0.902	1.042	0.350	0.404	0.892	1.030	0.007	0.008	0.794	0.917

S.No	Crosses	HFTFB (cm)		PH (cm)		SYPP (g)		TSW (g)		OC (%)
		Mid Parent	Better Parent	Mid Parent	Better Parent	Mid Parent	Better Parent	Mid Parent	Better Parent	Mid Parent	Better Parent
1	NPJ-194 × RW-85–59	− 1.950	− 4.460**	0.530*	− 0.890**	2.200	1.310	16.250**	3.910*	2.450**	− 3.560**
2	NPJ-194 × DRMR-15–16	2.240*	1.370	2.470**	0.440	− 7.690**	− 11.110**	− 2.720	− 6.540**	4.460**	0.630
3	NPJ-194 × SKJM-05	0.520	0.000	1.930**	− 1.010**	10.820**	8.020*	− 1.190	− 14.870**	− 0.880	− 5.450**
4	NPJ-194 × Kranti	− 0.090	− 0.690	2.000**	− 0.860**	4.740	3.110	21.250**	8.380**	2.450**	0.630
5	NPJ-194 × Giriraj	0.090	− 2.430	2.770**	0.880**	2.070	− 4.630	5.730**	− 4.050*	− 5.590**	− 9.640**
6	NPJ-194 × RNWR-09–3	− 1.220	− 1.570	4.240**	1.740**	− 1.760	− 2.620	15.880**	− 1.010	− 3.240**	− 3.540**
7	NPJ-194 × PHR − 2	− 0.260	− 1.740	5.880**	3.340**	6.940*	6.220	20.120**	6.590**	− 11.510**	− 13.000**
8	RW-85–59 × DRMR-15–16	3.110**	1.320	0.440	− 0.150	1.270	1.650	29.730**	20.000**	1.860**	− 0.680
9	RW-85–59 × SKJM-05	− 0.940	− 3.960**	− 0.660**	− 2.160**	6.440*	4.640	8.270**	4.100**	5.040**	3.460**
10	RW-85–59 × Kranti	7.410**	5.280**	− 0.290	− 1.730**	− 2.010	− 4.370	7.520**	7.220****	3.410**	− 1.090*
11	RW-85–59 × Giriraj	0.520	− 4.460**	1.620**	1.180**	− 8.200**	− 13.510**	8.220**	6.110**	7.480**	5.500**
12	RW-85–59 × RNWR-09–3	− 2.630*	− 5.450**	0.000	− 1.020**	− 2.620	− 2.620	− 7.120**	− 11.560**	− 2.000**	− 8.130**
13	RW-85–59 × PHR-2	− 4.470**	8.250**	1.170**	0.150	3.770	2.180	− 1.100	− 1.650	8.740**	3.900**
14	DRMR-15–16 × SKJM-05	− 3.990**	− 5.300**	− 0.800**	− 1.730**	0.000	− 1.230	18.970**	6.150**	1.830**	0.910
15	DRMR-15–16 × Kranti	− 1.290	− 1.540	0.000	− 0.860**	− 4.120	− 9.050**	− 1.810	− 8.940**	− 1.890**	− 3.910**
16	DRMR-15–16 × Giriraj	2.210	− 1.200	2.790**	2.640**	− 9.960**	− 12.740**	− 17.180**	− 21.970**	1.710**	1.130*
17	DRMR-15–16 × RNWR-09–3	− 0.350	− 1.540	0.440	0.000	− 4.660	− 7.410*	− 2.840	− 14.070**	− 6.840**	− 10.630**
18	DRMR-15–16 × PHR-2	− 1.310	− 3.590**	0.290	− 0.150	− 0.650	− 4.940	6.270**	− 2.200	3.990**	− 6.070**
19	SKJM-05 × Kranti	2.520*	1.370	2.520**	2.450**	5.490	1.270	8.020**	3.590*	− 2.240**	− 5.220**
20	SKJM-05 × Giriraj	4.390**	2.280	− 0.220	− 1.290**	− 12.500**	− 16.220**	− 5.980**	− 11.280**	− 2.760**	− 3.210**
21	SKJM-05 × RNWR-09–3	− 3.160	− 3.330*	− 0.070	− 0.580*	− 5.580*	− 7.170*	− 0.510	− 1.510	− 5.920**	− 10.630**
22	SKJM-05 × PHR-2	− 0.440	− 1.410	1.080**	0.580*	− 3.700	− 6.750*	− 1.330	− 4.620**	4.820**	1.520**
23	Kranti × Giriraj	2.660*	− 0.520	1.020**	0.000	− 6.920*	− 14.290**	0.280	− 1.670	− 2.570**	− 5.010**
24	Kranti × RNWR-09–3	− 1.650	− 2.580*	− 0.720**	− 1.150**	2.010	− 0.440	5.540**	0.500	− 3.300**	− 5.420**
25	Kranti × PHR-2	− 4.910**	− 6.870**	0.580*	0.140	10.910**	9.910**	− 0.550	− 1.100	− 9.780**	− 9.980**
26	Giriraj × RNWR-09–3	0.980	− 1.230	1.610**	1.020**	− 7.380**	− 12.740**	− 25.470**	− 30.150**	− 5.570**	− 10.000**
27	Giriraj × PHR-2	− 1.450	− 2.510	3.950**	3.340**	− 7.280**	− 13.900**	13.480**	10.990**	− 4.910**	− 7.590**
28	RNWR-09–3 × PHR-2	− 0.270	− 1.400	1.600**	1.600**	− 0.220	− 1.750	4.210**	0.000	2.660**	0.630
	SE ( ±)	0.015	0.017	0.004	0.004	0.015	0.017	0.597	0.689	0.495	0.572

*Significant at p ≤ 0.05 and **Significant at p ≤ 0.01. DFPF Days to 50% flowering, PBPP Primary branches per plant, SBPP Secondary branches per plant, SPP Siliqua per plant, SPS Seeds per siliqua, HFTFB, Height up to first fruiting branch (cm), PH Plant height (cm), SYPP Seed yield per plant (g), TSW Thousand seed weight (g), OC Oil content (%).

Fig. 4.

Heterosis range for the different seed yield and its attributing characters in Indian mustard. DFPF Days to 50% flowering, PBPP Primary branches per plant, SBPP Secondary branches per plant, SPP Siliqua per plant, SPS Seeds per siliqua, HFTFB Height up to first fruiting branch (cm), PH Plant height (cm), SYPP Seed yield per plant (g), TSW Thousand seed weight (g), OC Oil content (%).

In the assessment of relative heterosis, it was noteworthy that DRMR-15-16 × RNWR-09-3 (− 7.370) and DRMR-15-16 × PHR-2 (− 3.930) exhibited significant and desirable negative heterosis. Among the 28 crosses evaluated, 7 F₁ hybrids demonstrated highly significant and desirable negative heterosis over the better parent for early flowering, namely RW-85-59 × DRMR-15-16 (− 6.550), RW-85-59 × SKJM-05 (− 7.830), RW-85-59 × Kranti (− 5.200), RW-85-59 × PHR-2 (− 9.040), DRMR-15-16 × Kranti (− 6.360), DRMR-15-16 × RNWR-09-3 (− 8.190), and DRMR-15-16 × PHR-2 (− 9.040). The crosses NPJ-194 × PHR-2 (36.430), Kranti × PHR-2 (27.540), and Giriraj × PHR-2 (24.800) exhibited the highest and statistically significant positive values in relation to the mid-parent. Furthermore, NPJ-194 × PHR-2 (25.710) displayed noteworthy positive and significant heterosis over the better parent for the trait of PBPP. Among the evaluated crosses, the PBPP trait exhibited the highest and statistically significant positive values in relation to the mid-parent for NPJ-194 × PHR-2 (36.430), Kranti × PHR-2 (27.540), and Giriraj × PHR-2 (24.800). Additionally, NPJ-194 × PHR-2 (25.710) demonstrated a significant and desirable positive heterosis over the better parent for this particular trait.

Two crosses, Giriraj × PHR-2 (52.780) and RW-85-59 × Kranti (41.800), exhibited significant positive heterosis over the mid-parent for SBPP. Additionally, Giriraj × PHR-2 (36.360) and RW-85-59 × Kranti (33.680) displayed significant positive heterosis over the better parent for the same trait. In terms of SPP, NPJ-194 × DRMR-15-16 (5.060), NPJ-194 × SKJM-05 (2.490), NPJ-194 × Giriraj (2.930), NPJ-194 × RNWR-09-3 (9.810), NPJ-194 × PHR-2 (9.900), RW-85-59 × Kranti (0.970), DRMR-15-16 × Giriraj (3.350), DRMR-15-16 × PHR-2 (1.580), Kranti × Giriraj (4.580), Giriraj × RNWR-09-3 (2.220), and Giriraj × PHR-2 (4.170) demonstrated the highest positive and significant values of heterosis over the mid-parent. Meanwhile, three crosses, NPJ-194 × DRMR-15-16 (3.670), NPJ-194 × RNWR-09-3 (9.080), and NPJ-194 × PHR-2 (6.190), exhibited significant positive heterosis over the better parent, indicating their superiority for this particular trait. The crosses Giriraj (24.790), DRMR-15-16 × RNWR-09-3 (20.000), RW-85-59 × Kranti (19.740), and RW-85-59 × Giriraj (19.160) displayed positive and notable heterosis over the better parent. However, among the 16 crosses exhibiting positive heterosis over the better parent, none made a significant contribution to the trait seed siliquae^[-1.

Regarding HFTFB, the crosses RW-85-59 × Kranti (7.410), SKJM-05 × Giriraj (4.390), RW-85-59 × DRMR-15-16 (3.110), Kranti × Giriraj (2.660), SKJM-05 × Kranti (2.520), and NPJ-194 × DRMR-15-16 (2.240) showcased the highest positive and statistically significant values. Notably, two F₁ hybrids, RW-85-59 × Kranti (5.280) and RW-85-59 × PHR-2 (8.250), expressed desirable positive and significant heterosis over the better parent for this trait. Positive and statistically significant mid-parent heterosis values were observed for PH in several crosses, including NPJ-194 × RW-85-59 (0.530), NPJ-194 × DRMR-15-16 (2.470), NPJ-194 × SKJM-05 (1.930), NPJ-194 × Kranti (2.000), NPJ-194 × Giriraj (2.770), NPJ-194 × RNWR-09-3 (4.240), NPJ-194 × PHR-2 (5.880), RW-85-59 × Giriraj (1.620), RW-85-59 × PHR-2 (1.170), DRMR-15-16 × Giriraj (2.790), SKJM-05 × Kranti (2.520), SKJM-05 × PHR-2 (1.080), Kranti × Giriraj (1.020), Kranti × PHR-2 (0.580), GIRIRAJ × RNWR-09-3 (1.610), Giriraj × PHR-2 (3.950), and RNWR-09-3 × PHR-2 (1.600). Additionally, 10 crosses displayed significant and positive heterosis over the better parent, including NPJ-194 × Giriraj (0.880), NPJ-194 × RNWR-09-3 (1.740), NPJ-194 × PHR-2 (3.340), RW-85-59 × Giriraj (1.180), DRMR-15-16 × Giriraj (2.640), SKJM-05 × Kranti (2.450), SKJM-05 × PHR-2 (0.580), Giriraj × RNWR-09-3 (1.020), Giriraj × PHR-2 (3.340), and RNWR-09-3 × PHR-2 (1.600).

Out of the 12 crosses demonstrating positive mid-parent heterosis, only four were significantly positive, namely NPJ-194 × SKJM-05 (10.820), NPJ-194 × PHR-2 (6.940), RW-85-59 × SKJM-05 (6.440), and Kranti × PHR-2 (10.910). Furthermore, only two crosses exhibited significant positive heterosis over the better parent: NPJ-194 × SKJM-05 (8.020) and Kranti × PHR-2 (9.910) for SYPP. In the assessment of TSW, a notable pattern of positive and significant mid-parent heterosis values emerged. The crosses NPJ-194 × RW-85-59 and NPJ-194 × Kranti stood out with impressive values of 16.250 and 21.250, respectively. Additionally, NPJ-194 × PHR − 2 displayed a significant value of 20.120. RW-85-59 × DRMR-15-16 exhibited the highest heterosis at 29.730, followed by DRMR-15-16 × SKJM-05 with 18.970, both showing considerable significance. Other crosses like NPJ-194 × RNWR-09-3 (15.880), RW-85–59 × Giriraj (8.220), and Giriraj × PHR-2 (13.480) also demonstrated substantial positive heterosis over the mid-parent. Furthermore, several crosses displayed positive heterosis over the better parent. Noteworthy crosses included NPJ-194 × Kranti (8.380), RW-85–59 × DRMR-15-16 (20.200), and RW-85–59 × Giriraj (6.110). These crosses showcased significant enhancements in TSW compared to the better parent. In terms of specific crosses, NPJ-194 × RW-85–59 (2.450), NPJ-194 × DRMR-15–16 (4.460), and RW-85–59 × PHR-2 (8.740) exhibited positive and significant heterosis over the mid-parent, indicating substantial improvements in this trait. Conversely, RW-85–59 × SKJM-05 (3.460), RW-85–59 × Giriraj (5.500), and RW-85–59 × PHR-2 (3.900) demonstrated positive heterosis over the better parent for OC. These findings collectively highlight the potential of specific crosses to contribute positively to the improvement of seed weight and OC in the studied population.

Discussions

The results of the present investigation provide valuable insights into the genetic basis of key morphological traits in Indian mustard. The significant differences observed in the comparison of mean squares between parents vs. crosses for DFPF, PH, TSW, and OC underscore the presence of substantial variations between these two groups. This finding suggests that the genetic composition of the parents exerts a significant influence on the expression of these traits in the resulting crosses. Arifullah et al.²² revealed that there were highly significant differences among the treatments for all the traits studied also supports the experimental results of the analysis of variance.

One of the notable findings of this study is the significant difference observed in the general combining ability (GCA) of eight parents and the specific combining ability (SCA) of twenty-eight crosses. This distinction highlights the importance of both additive and non-additive gene effects in the inheritance of the studied morphological traits. Similarly, other researchers^9,23–26 also reported significant mean squares due to GCA and SCA for various morphological and seed yield traits in brown mustard.

The examination of variance components revealed a noteworthy pattern: the specific combining ability component of variance (σ²sca) surpassed the general combining ability component of variance (σ²gca) for all yield-related traits. This observation signifies a prevalent influence of non-additive gene action in governing these traits. This finding aligns with previous studies by other researchers^24,26,27 which reported similar results.

The ratio of additive genetic variance to dominance genetic variance (σ²A/σ²D) offered further insights into the genetic basis of the traits under consideration. For all yield-related traits except DFPF, this ratio was found to be less than unity, indicating a predominant role of dominance gene action. This suggests that the genetic factors governing the majority of these traits are characterized by interactions between alleles rather than individual gene contributions. This observation concurs with the findings of Baker²⁸, who proposed the predictability ratio (σ²A/σ²A + σ²D) as a means to assess the relative importance of general and specific combining abilities in predicting progeny performance. In contrast to the aforementioned studies, the present investigation yielded a σ²A/σ²A + σ²D ratio exceeding 0.50 in all cases. This implies a greater influence of additive genetic effects in shaping the traits under examination. This variance pattern indicates that the additive contributions of individual genes play a substantial role in determining the expression of these yield-related traits. The prevailing preponderance of non-additive gene action observed in most of the traits studied is consistent with the findings of other researchers^22,29–31. Their research similarly reported a dominant role of non-additive genetic effects in shaping various agronomic characteristics.

Assessments of general combining ability (GCA) effects and individual performance would aid breeders in discerning suitable parent combinations to leverage genetic diversity and derive superior genotypes through recombination breeding³². The general combining ability (GCA) effects in this study revealed that none of the parents exhibited uniformly superior combining abilities across all yield-related traits. This highlights the complexity of genetic interactions and the trait-specific nature of combining abilities. However, it was observed that the parent RW-85–59 demonstrated commendable combining abilities for several important traits, including DFPF, PBPP, SBPP, SPP, HFTFB and PH. Similarly, Kranti emerged as a noteworthy general combiner, particularly excelling in SBPP, SPP and HFTFB. These findings emphasize the importance of carefully selecting parents based on their specific strengths in order to achieve desired trait combinations in the progeny. This strategic approach aligns with the fundamental principles of hybrid breeding, which aims to exploit the complementarity of parental traits to achieve superior performance in the offspring. To further enhance the potential for genetic recombination and gene pyramiding, it is recommended to undertake multiple cycles of artificial hybridization and subsequent selection among the parental genotypes and their progenies. This iterative process enables the fixation of transgressive segregants, which carry combinations of favourable alleles from both parental lines. Earlier investigations employing combining ability analysis in mustard have likewise been documented to pinpoint the most proficient general combiner for seed yield by other researchers^23,27.

In the context of our study, it is advisable to prioritize hybrids that exhibit positively significant specific combining ability (SCA) effects for heterosis breeding, except in the cases of DFPF and PH, where negatively significant SCA effects are more favourable. Noteworthy cross combinations, such as NPJ-194 × SKJM-05, NPJ-194 × Giriraj, NPJ-194 × PHR-2, RW-85-59 × DRMR-15-16, RW-85-59 × SKJM-05, SKJM-05 × Kranti, and Kranti × PHR-2, demonstrated favorable specific combining ability effects for SYPP, along with significant contributions to key yield-contributing traits. These findings align with previous studies by other researchers^33–35 reinforcing the reliability of our results. The significant SCA effects observed in this study highlight the importance of non-additive genetic variance in determining hybrid performance. Biologically, these effects indicate the presence of dominance and epistatic interactions, which contribute to heterosis and superior hybrid Vigor in yield-related traits. This aligns with the goal of heterosis breeding, where such interactions are strategically exploited to achieve enhanced productivity and adaptability in Indian mustard.

Best general combiners and a few specific combiners for yield and its attributing characters in Indian mustard (Brassica juncea) presented in (Table 8) and (Figs. 2 and 3). The identification of best general combiners and specific combiners for yield components is crucial for optimizing breeding strategies. Crosses involving high × low general combiners for yield components tend to outperform others. Notably, high specific combining ability (SCA) effects can arise in crosses with high × low and low × low general combiners, attributed to over-dominance and epistasis, according to Jinks. Conversely, crossing parents with low general combining ability can lead to superior performance due to complementary gene activity.

Table 8.

Top performers in general combining ability and selected specific combining ability for yield and its associated traits in Indian mustard (Brassica juncea).

Characters	Best general combiners	gca effects	Per se performance of the parent	Top specific combiners	sca effects	Individual performance of crosses	gca status of parents
SYPP (g)	SKJM-05	0.013*	6.133	RW-85-59 × DRMR-15-16	0.025**	5.507	NS × NS	M × M
				NPJ-194 × PHR-2	0.026**	5.090	NS × NS	M × L
				SKJM-05 × Kranti	0.029**	4.327	S × NS	M × L
				NPJ-194 × Giriraj	0.039**	4.587	NS × NS	M × M
				RW-85-59 × SKJM-05	0.044**	5.313	NS × S	M × M
				Kranti × PHR-2	0.061**	4.527	NS × NS	M × L
				NPJ-194 × SKJM-05	0.065**	5.733	NS × S	M × M
SBPP	RW-85-59 Kranti	1.200** 0.726*	8.60 8.93	RW-85-59 ×Kranti	4.250**	8.730	S × S	H × M
				Giriraj × PHR-2	2.758**	8.870	NS × NS	L × M
				NPJ-194 × PHR-2	1.551**	9.270	NS × NS	L × M
				Giriraj ×RNWR-09-3	1.445**	10.130	NS × NS	L × L
TSW (g)	SKJM-05 RW-85-59 PHR-2 RNWR-09-3 Kranti	3.158* 2.458* 1.758* 1.558* 1.292*	2.570 3.173 16.853 32.963 40.980	NPJ-194 × RW-85-59	2.511**	2.953	NS × S	L × H
				NPJ-194 × Kranti	6.344**	3.430	NS × S	L × H
				NPJ-194 × Giriraj	1.611**	3.343	NS × NS	L × L
				NPJ-194 × RNWR-09-3	7.078**	2.850	NS × S	L × H
				NPJ-194 × PHR − 2	5.878**	2.967	NS × S	L × H
				RW-85-59 × DRMR-15-16	12.878**	2.220	S × NS	H × L
				RW-85-59 × SKJM-05	1.744**	3.893	S × S	H × H
				RW-85-59 × Giriraj	4.211**	1.820	S × NS	H × L
				DRMR-15-16 × SKJM-05	9.178**	3.463	NS × S	L × H
				DRMR-15-16 × PHR-2	0.911**	3.183	NS × S	L × H
				SKJM-05 × Kranti	2.578**	2.957	S × S	H × H
				Kranti × RNWR-09-3	3.511**	1.900	S × S	H × H
				Giriraj × PHR-2	8.578**	3.573	NS × S	L × H
				RNWR-09-3 × PHR-2	2.378**	3.060	S × S	H × H
SPP	PHR 2 NPJ-194 RW-85-59 Kranti	0.038*** 0.023** 0.013** 0.030**	329.800 162.13 192.00 184.27	NPJ-194× PHR − 2	0.166**	173.733	S × S	M × M
				NPJ-194× RNWR-09-3	0.141**	185.600	S × NS	M × L
				RW-85-59× Kranti	0.097**	178.333	S × S	M × M
				Kranti× Giriraj	0.095**	128.800	S × NS	M × L
				Giriraj× PHR-2	0.060**	201.000	NS ×S	L × M
				NPJ-194× DRMR-15-16	0.053**	158.200	S × NS	M × L
				NPJ-194× SKJM-05	0.047**	172.067	S × NS	M × L
				DRMR-15-16× PHR-2	0.041**	162.467	NS ×S	L × M
				DRMR-15-16× Giriraj	0.041**	148.267	NS ×NS	L × L
				DRMR-15-16× SKJM-05	0.019**	220.800	NS ×NS	L × L
				RW-85-59× Giriraj	0.019**	183.267	S × NS	M × L

*Significant at p ≤ 0.05 and **Significant at p ≤ 0.01. H indicates a high general combining ability effect, M represents a medium general combining ability effect, and L stands for a low general combining ability effect. S denotes a significant parent, while NS signifies a non-significant parent. SBPP Secondary branches per plant, SPP Siliqua per plant, SYPP Seed yield per plant (g), TSW Thousand seed weight (g).

Fig. 2.

Best general combiner for major yield and its attributing traits in Indian mustard. SBPP Secondary branches per plant, SPP Siliqua per plant, SYPP Seed yield per plant, TSW Thousand seed weight.

Fig. 3.

Best specific combiner for major yield and its attributing traits in Indian mustard. SBPP Secondary branches per plant, SPP Siliqua per plant, SYPP Seed yield per plant (g), TSW Thousand seed weight (g).

SKJM-05 emerged as a key general combiner, displaying positive significant SCA effects for SYPP. Crosses involving this parent exhibited both positive and significant SCA effects, with commendable individual performance. The crosses showed M × M general combining ability status of parents. RW-85–59 and Kranti stood out as best general combiners for SBPP, displaying positive significant GCA effects. One cross between these parents demonstrated significant SCA effects, while others exhibited non-significant GCA effects and significant SCA effects. This cross showed H × M general combining ability status of parents. For TSW, five parents displayed positive significant GCA effects, with corresponding significant SCA effects in crosses, indicative of good individual performance. These cross showed H × H and H × L general combining ability status of parents. Additionally, four parents exhibited positive significant GCA effects for SPP, suggesting their potential use in breeding programs. Hybrids involving these parents displayed significant and desirable SCA effects, with various GCA status combinations (M × M, M × L, and L × L). Similar results were observed by Singh et al.³⁶ and Chaudhary et al.²³, who reported the involvement of additive × additive, additive × dominance, and epistatic gene action in the expression of seed yield and other related traits in Brassica.

The assessment of combining ability effects in our study has shed light on potential strategies for improving Indian mustard through recombination and heterosis breeding. It was observed that most hybrids had one parent exhibiting a positively significant general combining ability (GCA) effect, making them prime candidates for recombination breeding programs. However, the significant Specific Combining Ability (SCA) effects in these hybrids suggest that the selection of superior plants should be deferred to subsequent generations. This approach aligns with established breeding practices that emphasize the importance of allowing multiple generations for the manifestation and stabilization of desirable traits. Parallel discoveries were documented in earlier investigations conducted by other researchers^5,24,37,38. This convergence of findings underscores the robustness and consistency of the reported outcomes, lending further support to the validity of the research.

In contrast, certain hybrids displayed non-significant GCA effects but significant SCA effects. These hybrids are particularly promising candidates for heterosis breeding. Heterosis breeding represents a viable strategy for enhancing the productivity of Indian mustard. In this study, 28 crosses were carefully developed to investigate the extent of heterosis for both yield and its component traits. Notably, two hybrids demonstrated significant heterosis over mid-parent values, while five hybrids exhibited significant heterosis over better-parent values for both SYPP and OC. These specific cross-combinations have the potential to serve as commercially viable F₁ hybrids, offering the prospect of increased yields and improved OC in Indian mustard. Liton et al.³⁹ have documented noteworthy heterosis in oilseed Brassica for both yield and its constituent traits. This observed phenomenon attests to the potential for substantial genetic gains in this important oilseed crop. Similar results were obtained in our study, where several hybrids exhibited high better-parent heterosis, significant SCA effects, and superior per se performance for seed yield, reinforcing the findings reported by Meena et al.³¹ for hybrids such as DRMR 2243/NRCHB 101, DRMR 2269/NRCHB 101, and DRMR 2326/NRCHB 101.

A potential limitation of the study is that it primarily focuses on a limited number of genotypes and does not explore a broader genetic base, which may restrict the generalizability of the findings. Future research could expand the scope by including a wider range of parental lines and crosses, as well as evaluating the stability of hybrid performance across multiple locations and years. Additionally, investigating the molecular basis of heterosis in these hybrids through genomic studies could provide valuable insights into the genetic mechanisms driving yield and oil content improvements.

Conclusions

The study demonstrates promising prospects for selecting progenies with enhanced seed yield as well as associated traits in Indian mustard. Both additive and non-additive gene effects were found influential in the transmission of these traits, with a prevailing emphasis on additive gene action. This highlights the importance of incorporating breeding strategies that leverage both types of genetic effects in Indian mustard breeding programs. The significant General Combining Ability (GCA) and Specific Combining Ability (SCA) effects observed for most traits underscore the relevance of both additive and non-additive genetic influences in trait expression. Parental genotypes RW-85–59, DRMR-15–16, Kranti, and NPJ-194 emerged as consistent and potent general combiners, indicating their potential to transmit favorable alleles to their progeny. The inclusion of low combiners in hybridization highlights the significance of over dominance and epistasis, suggesting the value of rigorous selection for specific combining ability (SCA) in subsequent generations. The participation of both high and low combiners underscores the importance of non-additive genetic effects, a crucial factor in heterosis breeding.

Specific hybrid combinations, such as SKJM-05 × Kranti, RW-85-59 × SKJM-05, NPJ-194 × SKJM-05 for SYPP, RW-85-59 × Kranti for SBPP, RNWR-09-3 × PHR-2, and NPJ-194 × RNWR-09-3 for TSW, NPJ-194 × PHR-2, NPJ-194 × RNWR-09-3, RW-85-59 × Kranti, Kranti × Giriraj, Giriraj × PHR-2, NPJ-194 × DRMR-15-16, NPJ-194 × SKJM-05, DRMR-15-16 × PHR-2, and RW-85-59 × Giriraj for SPP displayed notable specific combining ability (SCA) effects, presenting promising avenues for further research and breeding efforts. The most promising parental crosses for seed yield were NPJ-194 × SKJM-05 and Kranti × PHR-2, exhibiting substantial mid-parent and better-parent heterosis. Additionally, crosses including RW-85-59 × SKJM-05, RW-85-59 × Giriraj, RW-85-59 × PHR-2, DRMR-15-16 × Giriraj, and SKJM-05 × PHR-2 displayed significant positive heterosis for OC over mid and better parent. These identified heterotic crosses present strategic opportunities for effectively enhancing yield and OC in Indian mustard.

The findings of this study offer significant practical applications for breeding programs aimed at improving Indian mustard. The identification of both high and low combiners provides breeders with actionable targets for optimizing hybridization strategies. Crosses showing positive specific combining ability (SCA) effects for seed yield and oil content, offer valuable avenues for recombination breeding and heterosis breeding. By incorporating these promising hybrids into future breeding programs, there is potential for substantial improvements not only higher yield but also improved oil content, addressing the growing demand for high-quality mustard production.

Author contributions

All authors contributed to this study and design. Research was conceptualized and designed by S.K.Roy. and T.S.G.; Investigation: S.R.; Data curation: B.S., N.U. and S.N.; Formal analysis: S.R.; Writing—original draft: S.R., R.M., S.S. and M.K.D.; Writing—review & editing: S.R., S.K.R., M.R., M.C. and L.H. All authors read and approved the final manuscript and agreed to submit this manuscript.

Funding

The authors received no specific funding for this work.

Data availability

The datasets used and/or analyses during the current study are included in this article.

Declarations

Ethics approval and consent to participate

“The genotype was obtained from Pulses and Oilseed Research Station in Kanpur, Banaras Hindu University located in Varanasi, Uttar Pradesh, and the Directorate of Rapeseed and Mustard Research and no special permissions were necessary to collect samples and comply with India’s guidelines and legislation. The plant collection and use were in accordance with all the relevant guidelines and legislation of India”.

Competing interests

The authors declare no competing interests.