Characterization of Brown Mustard Accessions for Yield Contributing Traits

Pakistan has a constant scarcity of edible oil which results in high import costs. An abundant amount of edible oil is needed to bridge the gap between local production and use. Furthermore, rising demand for edible oil, combined with static production, has accelerated the global edible oil production process. As a result, there is an urgent need to enhance edible oil output or production to meet national demand while reducing import bills (Ahmad et al., 2023). According to current analysis and research by Polaris Market, the worldwide mustard seed market will be worth USD 1062.31 million in 2030. Canola varieties or hybrids are mustard varieties with less than 2% erucic acid in oil and less than 30 U mole/g glucosinolate in oil-free meals. Canola oil and meal are preferable for human consumption, while meal is a good feed for animals and birds. Additionally, canola meal has balanced and well-suited profile of amino acid, ideal for poultry and cattle consumption. It is grown in all provinces of Pakistan on an area of 26.02 thousand hectares, with an annual production of 215.0 thousand tones (2022-23). According to the observatory of economic complexcity mustard seeds were the 3317^th most traded product in the world in 2021(out of 4,641) (Observatory of Economic Complexity (OECD, 2021).Rapeseed and Mustard are grown in Chakwal, Rahim Yar Khan, Sargodha, Attock, Rawalpindi, Jehlum, Faisalabad, Multan, Bahawalpur, and Muzaffargarh. Originating from the Indian subcontinent, Brown Mustard (Raya) is globally recognized for its adaptability and practical applications. Widely cultivated for edible leaves, oil-rich seeds, and flavorful profile, it plays a crucial role in regional cuisines, particularly in South Asia. The plant’s mustard oil, known for its nutritional worth and potential health advantages, is used in food preparation, medicines, and traditional therapeutic practices Devi et al. (2018). The Brassicaceae family has 338 genera and 3709 species which include weeds, ornamental plants of aesthetic value, and economically valuable crops (Sharma et al., 2021). Though classified as a perennial herb, mustard (Brassica juncea L.) is primarily cultivated as an annual or biennial crop While Central Asia is considered the primary center of origin for this species, secondary centers of diversity are western and central China. (Shar et al., 2020). The plant is also used as a forage crop, vegetable, and in countless medicines and the seeds are extracted for edible oil. The plant’s oil is highly prized for its aroma, flavor, food preservation, skin tonics and hair oil. Raya counts for global food security and agricultural sustainability due to its tolerance to a broad range of climatic conditions and nutritional value (Yadav et al., 2017). Raya contributes significantly to the nation’s cooking oil supply providing one-third of all edible oil needs. It also has a high-calorie level and the right amount of vitamins (A, D, E, and K) that are fat-soluble for human consumption (Iqbal et al., 2016). Indian mustard, which is primarily grown in India & Pakistan for oil seed, is starting to take center stage in Canada and the USA as a replacement for Brassica napus or rapeseed (Saikia and Gupta, 2018).

Experimental material

The germplasm was collected from the following institutions such as Plant Genetic Resource Institute at the National Agriculture Research Center (NARC), Research Council Pakistan, and Oil Seed Research Institute, Ayyub Agriculture Research Faisalabad. All 45 accessions namely 4037, 19511, 24087, 24067, 24107, 24122, 24142, 24047, 24052, 24027, 24042, 19527, 23680, 24062, 24133, 24032, 24117, 22854, 24127, 24112, 19493, 24137, 24007, 24702, 24162, 24152, 24157, 24057, 24102, 24167, RBJ-15017, ZBJ-17019, Super Raya, RBJ-17003, ZBJ-19008, RBJ-16012, ZBJ-18008, ZBJ-17008, AARI Canola, RBJ-18007, Bagho Bahaar, Raya Anmol, Khanpur Raya, Faisalabad Mustard, FMC Raya were maintained in Department of Plant Breeding & Genetics College of Agriculture, University of Sargodha during 2022-2023.

Field conditions

The experimental material was sown a loamy soil under optimum moisture condition. Field soil was prepared after single irrigation under water condition using two ploughs followed by single planking. The seed of all accessions was manually dibble with row to row (30 cm) distance carefully handled under optimal soil moisture conditions and germination data was meticulously recorded. During soil preparation, 50 kg of di-ammonium phosphate and 20 kg of sulfate of potash per acre were added. Seed materials of all accessions were manually sown at a depth of 1 inch. Additionally, sowing material off all genotypes was sown under two sowing dates (17^th September and 17^th October 2022-2023).

Experiment design

The experimental design was Split Plot Design in which the sowing dates were assigned to the mean plots and the accessions was sown in the sub-plot. There were three replications for each of the accession. The weeds were controlled manually and plants were also thinned when they reached at the height of 6 inch.

Data collection

Research material was planted at two different sowing dates i.e. (17 September and 17 October). Ten randomly selected plants were marked to record data on Days to Germination, Days to Flowering, Leaf Area (cm), Stem Diameter (mm), 1000 Seed Weight (g), Pods per plant, Seeds per pods, Plant Height (cm), Total Biomass (g), Oil Content (%), Harvested yield (g) and Harvest index.

Statistical analysis

Statistical Analysis was done using the split plot design on R Studio using the library Agricola and program functioning Split Plot Design. The significance of the mean value was also determined by using the multiple comparison test LSD on the R-Program using the Library Agricola and least significant design. Several biometrical parameters such as phenotypical coefficient of variation, genotypic coefficient of variation, genotypic correlation and phenotypic correlation were also determined by using the R-program.

Days to germination are an essential trait in Brassica juncea which influence the overall performance and yield of the crop.Table 1 indicates that the days to flowering was maximum on G2 (73) and minimum on G41 (52 days ). This result depicted that genotype G2 (line 19511) takes more time to reach flowering stage. However, the other Genotype G41 (Bagho Bahar) needs less time duration to initiate its flowering. So, we can also infer that G41 exhibits high yield because it shows early flowering. It also tells that sowing date greatly affects the days to flowering trait and flower bud development. Such results were also aligning with the findings of Nanjundan et al. (2020). Leaf area was maximum on G27 (351.3958) and mean value of leaf area was minimum on G28 (156.0833). Larger leaf area generally correlates with an increased capacity for photosynthesis. Genotypes with a larger maximum leaf area often exhibit greater biomass production. Maximum leaf area of B. juncea can influence not only overall biomass but also the yield and quality of the harvested product. Such results were also aligning with the findings of Babu et al. (2020). The association tests revealed a strong and positive correlation between seed production and 1000 seed weight at both the genotypic and phenotypic levels. This finding of 1000 seed weight trait resemble with the research and statistical findings of Kumar et al., (2021). The height and width of a plant are important geometric traits that can be used as indicators of plant growth, site-specific applications, and yield estimation Rajametov et al., 2021. Plant height, days to 50% flowering and days to maturity had negative direct effect on seed yield. If plants show more vertical growth or vegetative growth then reproductive stage may affect and number of pods per plant also affects yield Pal et al. (2019). The result also showed that the G38 has a high mean value of pods per plant and G5 showed the lowest mean value of pods per plant. It means that almost all plants of replication of G38 (ZBJ-17008) have more number of pods than other genotypes even at different sowing dates. So, we can infer that this genotype will show maximum yield production than others and may be further used in a breeding program to maximize yield potential. These results were further supported by the results of Ray et al. (2019). The result also showed that the G23 and G19 has a high mean value of stem diameter and G2 shows minimum mean value of stem diameter. These genotypes with good stem diameter also gave good seed yield per plant at harvesting stage These findings were similar to the results of Jat et al. (2001).The highest seeds per pods with a mean value of 17.33333 which is donated by ‘a’. G9 showed the lowest mean value of pods per plant which is donated by letter ‘o’. These findings were in line with the final results of

Table 1: Genetic parameters for yield related traits of Brassica juncea genotypes

DTG (Days to Germination)DTF (Days to Flowering)LA(Leaf Area) SW(Seed Weight)PH(Plant Height) PPP(Pods per plant)SD (Stem Diameter)SPP(Seeds per Pod)OC (Oil Content)HY(Yield)TB(Total Biomass) HI(Harvest Index)

Table 2: Mean values for different yield related traits of Brassica juncea genotypes

DTG (Days to Germination)DTF (Days to Flowering)LA(Leaf Area) SW(Seed Weight)PH(Plant Height) PPP(Pods per plant)SD (Stem Diameter)SPP(Seeds per Pod)OC (Oil Content)HY(Yield)TB(Total Biomass) HI(Harvest Index)

Table 3: Genotypic and phenotypic correlation (1st sowing date)

DTG (Days to Germination)DTF (Days to Flowering)LA(Leaf Area) SW(Seed Weight)PH(Plant Height) PPP(Pods per plant)SD (Stem Diameter)SPP(Seeds per Pod)OC (Oil Content)HY(Yield)TB(Total Biomass) HI(Harvest Index)

These findings were in line with the final results of Halim et al. (2023). Oil content value of 51.7% was recorded in G2 while the minimum mean value of oil content was 32.8% which was recorded in G35. These results also showed significantly negative relation because G2, G9 and G28 showed maximum oil content percentage but at the same time these genotypes did not show good, harvested yield. These findings were in accordance with the results of Belt et al. (2023). It was determined that high-yielding genotypes in mustard should be selected on the basis of seeds per plant and 1000-seed weight, because they showed a positive association and the greatest positive direct effects on seed yield. Similar results were also observed and concluded by Chowhan et al. (2023).

Table 2 indicated that seeds per plant and plant height had high values of heritability in the broad sense (0.99 and 0.95, respectively). Yadav et al. (2011) also reported high heritability for these traits. Maximum genotypic and phenotypic variances were found for seeds per plant (7874.22 and 7919.26) and maximum genotypic and phenotypic coefficients of variance were found for pods per plant (21.60 and 23.32%) respectively. Similar results were reported by Ali et al. (2002).

The genotypic and phenotypic correlations between traits on first sowing date are summarized in Table 3. Harvest index was significantly correlated with days to flowering (0.574) and total biomass, showing accessions with high harvest index took lower days to flowering and also had low biomass. Stem diameter positively correlated with seed weight (0.07), oil content (0.35), and total biomass (0.138). Plant height also had negative relationship with days to flowering (-0.24) showing tall accessions had early flowering. Seed per plant had positive relationships with pods per plants (0.32) and negative relationship with oil contents (-0.25).

On the second sowing date harvest index was significantly correlated with days to flowering (-0.371), leaf area (-0.205), 1000 seed weight (0.227) and total biomass (-0.42), showing accessions with high harvest index took lower days to flowering, small leaf area and also had low biomass but larger 1000 seed weight (Table 4.) A positive and highly significant genotypic correlation between branches per plant and yield per plant was also concluded by Tunkturk et al. (2007). A highly positive correlation was determined between plant height and yield per plant by Khayat et al. (2012).

Path analysis

In phenotypic path analysis, leaf area (0.208) had the highest direct effects on seed yield followed by seeds per pod (0.19) and stem diameter (0.08) which had small positive direct effect on seed yield (Table 5a & 5b) Days to flowering (-0.18) had negative direct effect on seed yield but positive indirect effects on seed yield via pods per plant (0.06). Leaf area (0.208) had positive direct effect on seed yield but also displayed positive indirect effect through days to 50% floweing (0.02). Parameter like stem diameter (0.08) had positive direct effect on seed yield. Moreover, oil contents (-0.03) had negative direct effects on seed yield but actually positive indirect effects via plant height (0.008). Pods per plant (-0.23) had negative direct effects on harvested yield and positive indirect effect via days to flowering (0.08). Seed per pod (0.19) had positive direct effect on seed yield. Plant height (-0.19) had significant negative direct effects on seed yield and positive indirect effects via days to flowering and days to germination (0.04). Alike findings were specified by Tahira et al. (2011), but these results were a part from earlier findings of Dar et al. (2010). This extensive research improves our understanding of the complex interactions between phenotypic parameters in raya during the first planting date, providing useful insights for crop improvement techniques.

Table 4: Genotypic and phenotypic correlation of 2^nd sowing date

Table 5a: Genotypic path analysis of 1st sowing date

Table 5b: Genotypic path analysis of 2nd sowing date

Table 6a: Phenotypic path analysis of 1st sowing date

Table 6b: Phenotypic Path Analysis of 2nd sowing date

DTG (Days to Germination)DTF (Days to Flowering)LA(Leaf Area) SW(Seed Weight)PH(Plant Height) PPP(Pods per plant)SD (Stem Diameter)SPP(Seeds per Pod)OC (Oil Content)HY(Yield)TB(Total Biomass) HI(Harvest Index)

In genotypic path analysis, 1000-seed mass (0.048) had the highest direct effects on seed yield followed by stem diameter (0.009) which had small positive direct effect on seed yield (Table 6a & 6b). Days to flowering (-0.168) had negative direct effect on seed yield but positive indirect effects on seed yield via plant height (0.04). Leaf area (0.26) had negligible direct effect on seed yield. Oil contents (-0.153) also had negative effects on seed yield but positive indirect effects via total biomass. Dar et al. (2010) found positive direct effect of seeds per pod on yield. Rameeh (2011) reported that plant height had negative direct effect on yield per plant. It is observed that branches per plant, plant height, and pods per plant exerted negative direct effects on yield in that study. Sinha et al. (2001) also confirmed that the negative direct effects of plant height and branches plant on raya yield. Pods per plant (0.01) had positive indirect effects via days to flowering. Seed per pod had negative indirect via total biomass (-0.015). Plant height (-0.35) had significant negative direct effects on seed yield and positive indirect effects via days to flowering (0.11) and total biomass (0.08). Total biomass (-0.68) had the highest negative direct effects over seed yield. Residual effects of the genotypic coefficient path analysis are 0.21 which may be unexplained effects over seed yield under current environmental conditions.

The authors highly appreciate Department of Plant Breeding and Genetics College of Agriculture University of Sargodha for providing the necessary research facilities to conduct this study. We also extend our gratitude to our colleagues and lab technicians for their field and technical assistance during data collection.

This study provides a comprehensive agro-morphological characterization of diverse brown mustard (Brassica juncea) accessions to identify high-yielding genotypes tailored for specific agro-ecological conditions. By establishing precise correlation patterns among major yield-contributing traits, this work identifies elite germplasm lines that can serve as excellent parental stock for future marker-assisted selection and robust breeding programs aimed at optimizing oilseed productivity.

Ayesha Sadiqa: Conceptualization, methodology, data curation, writing – original draft.

Saba Tabasum: Supervision, software, validation, writing – review and editing..

​Sehar Nawaz: Formal analysis, investigation, field management.

Generative AI and AI-assisted technology statement

The authors declare that no generative AI and AI assisted technology was used in the creation of this manuscript.

Conflict of interest

The authors have declared no conflict of interest.