1 Introduction

Agriculture is the backbone of the Nepalese economy, employing approximately 60% of the population and contributing nearly 23.8% of the Gross Domestic Product (GDP). Most people depend on agriculture for their livelihoods, particularly in rural areas (MOALD, 2024). Nepal is gradually shifting from subsistence farming to commercial agriculture to reduce poverty, enhance food security, and promote economic growth (Bist et al., 2025). Pulses play a vital role as an important source of nutrition and as a cash crop that plays a significant role in enhancing household income in rural areas of Nepal (Ghimire et al., 2022). Pulses, such as lentils, beans, peas, and other grain legumes, are of major importance for both human nutrition and sustainable farming, as they form a key component of the Nepalese diet by providing essential proteins and micronutrients and contributing to soil health through their capacity for biological nitrogen fixation (Dhakal, 2020; Basnet et al., 2022).

French bean (Phaseolus vulgaris L.), also known as common bean, is an herbaceous annual plant in the Fabaceae family. It exhibits bush (20-60 cm tall) or pole (2-3 m vines) growth habits, with trifoliate leaves (6-15 cm long leaflets) and white-to-purple flowers producing flat pods with 5-12 seeds. Roots are taproot systems with nodules for nitrogen fixation. Stems are herbaceous and angular; pods are straight or sickle-shaped, 8-20 cm long, containing kidney-shaped seeds (1-2 cm) (Bharti et al., 2023; Sinkovič et al., 2024).

French beans (Phaseolus vulgaris L.) are an important legume crop in Nepal, particularly in the Karnali region, where they provide a crucial source of income and nutrition for local farmers (Luitel et al., 2019; Mira, 2021). It is extensively cultivated from the Terai to the high hills, occupying approximately 10,529 hectares with a total production of 15,550 metric tonnes and an average productivity of 1,477 kg/ha. Among the commonly grown genotypes, PB0001, KBL-5, and KBL-8 exhibit a bush growth habit, whereas PB0002, PB0048, and other KBL genotypes are of the trailing type. French beans or common beans, which are recognized for their high protein content and wide adaptability, are a major legume crop in the mid-hill and mountainous regions of Nepal (Chhetri and Bhatta, 2017; Luitel et al., 2021). The beans grown in the Karnali zone of Nepal are known as Jumli simi, which are traditional high-altitude landraces of French beans. (Prasad et al., 2016). Mixed bean cultivation has traditionally been an integral practice in mountain farming systems, although it is gradually being replaced by monocropping (Joshi et al., 2025). The three-year average results showed that the Chaumase genotype produced the highest green pod yield (35.0 t/ha), followed by Trishuli (28.0 t/ha), WP Con Bean (24.6 t/ha), and White OP (22.9 t/ha). Similarly, in terms of seed yield, Chaumase and Trishuli (2.1 t/ha each) performed best, while Dhankute Chirrke (1.44 t/ha) and White OP (1.09 t/ha) were found to be promising genotypes for seed production (Kalauni et al., 2019).

In the Tilagufa municipality of Kalikot, French beans are traditionally produced on a small scale, with limited access to quality seeds, irrigation, fertilizers, and pesticides, resulting in high production costs. Pests and diseases were major challenges in production and limited market information is the major marketing problem. Despite low yields due to these constraints, French bean cultivation is economically important in the Karnali region, offering significant income opportunities and potential to improve food security and rural livelihoods (Adhikari et al., 2024).

2 Materials and Methods

2.1 Study area and sample size

For this study, the Kalikot district was purposively selected because it is one of the most French bean producing districts in the high hills of the Karnali region. A total of 100 farmers were chosen from a population of 3,022 for data collection using proportionate stratified random sampling across the different local levels. A field survey was conducted in February 2025 to collect primary data from farmers through semi-structured questionnaires, focus group discussions, and key informant interviews, while secondary data were obtained from various sources. Data analysis was performed using Microsoft Excel 10 and STATA V12. Descriptive statistics such as means and frequencies, as well as gross margin, profitability index, multiple linear regression, independent sample t-tests, and severity indices for major bean production problems were computed.

2.2 Gross margin and profitability index analysis

Gross margin is the difference between the Gross return (GR) and the Total Variable Cost (TVC). It is a useful planning tool in situations where fixed capital is a negligible portion of the farming enterprise in the case of small-scale subsistence agriculture (Olukosi and Erhabor, 1988). Gross margin was calculated as follows:

Gross margin (GM) = Gross return (GR)－Total variable cost (TVC)

Net profit = Gross margin (Rs.)－Fixed cost (Rs.)

Where, Gross return (Rs.) = Price of French beans (Rs. /kg) × total quantity sold (kg)

Total variable cost (Rs.) = Summation of the cost of all variable inputs

Profitability index = Net farm Income / Total variable cost (NFI/TVC)

2.3 Indexing

Scaling techniques provide the direction and extremity attitude of the respondent towards any proposition (Miah, 1993). The problems faced by the bean farmers in the study area were ranked by using a scaling technique comparing the intensity of different levels of using scale values 1, (1-1/n), (1- 2/n), (1-3/n) and so on:

I= ∑ S_i*f_i/N

Where, I=index 0< I<1; I=index value (ranging from 0 to 1); S_i= scale value for the i^th severity category; f_i= frequency of responses in the i^th severity category; N= total number of respondents (= ∑fi)

3 Results and Analysis

3.1 Descriptive statistics of household and income variables

The results show that bean-producing households had an average family size of 6.15 members (Table 1). On average, 2.42 members per household were actively involved in agriculture, indicating reliance on family labor alongside hired labor. The mean age of the farmers was 43.02 years, suggesting that production is mainly managed by middle-aged, experienced farmers. The average annual household income was NPR 1,041,800, of which agriculture contributed NPR 624,200, highlighting farming as a major income source.

Table 1 Descriptive statistics of household and income variables Note: SD = Standard deviation; Min = Minimum; Max = Maximum; NPR = Nepalese rupee

3.2 Cost of production of French bean

The results reveals that the variable costs accounted for almost the entire cost of cultivation (99.64%), indicating a labor- and input-intensive production system. Among the variable cost components, labor cost was the dominant expense constituting 45.32% of the total cost (Table 2). This was followed by expenditures on organic manure (24.71%), land preparation (14.94%), and seeds (14.66%), suggesting that soil fertility management and field operations also require substantial investment. It emphasizes that production costs are largely driven by variable inputs, particularly labor, and that any increase in labor efficiency or access to improved inputs could reduce the cost of cultivation and improve farm profitability

Table 2 Cost of production of French bean per ropani

3.3 Price of French beans

It reveals that the average farmgate price of French beans was NRs. 202/kg while the market price was NRs. 260/kg, resulting in a price margin of NRs. 58/kg (Table 3). Price variability was greater at the farm level than in the market, highlighting challenges in price stability and the need for better market access and information for the farmers.

Table 3 Price of French beans

3.4 Production and productivity of French beans

It reveals that the average productivity of French beans in the study area was 76.10 kg per ropani, indicating a moderate yield under the prevailing traditional production practices (Table 4). The average annual production per household was 429.7 kg, which reflects the small-scale nature of bean cultivation and limited land allocation to the crop. Households consumed an average of 132 kg per year out of the total production, which highlights the importance of French beans as a key component of household nutrition and food security. The marketed surplus was 255.7 kg per household per year, with a monetary value of NRs 51,550, which represents a substantial share of total production, indicating that the French bean is not only grown for subsistence but also serves as an important cash crop.

Table 4 Production and productivity of French beans

3.5 Gross margin, net margin and benefit cost ratio

The results show that average gross return was NRs. 15,372.2 per ropani, resulting in a gross margin of NRs. 4,062.2. After deducting fixed costs, the net margin was NRs. 4,022.2 per ropani, indicating that French bean cultivation is financially viable under the existing production conditions in the study area. The B:C ratio of 1.35 further confirms profitability, as returns exceeded costs by 35 percent (Table 5).

Table 5 Gross margin, net margin and benefit cost ratio

3.6 Mean yield comparison of farmers

The results show that French bean productivity was significantly higher among farmers who received training and those who were members of cooperatives, indicating the positive role of institutional support and access to information (Table 6). Literate farmers also achieved markedly higher yields than illiterate farmers, highlighting the importance of education in improving farm productivity. In contrast, male farmers recorded slightly higher yields than female farmers, but the difference was not statistically significant. Overall, training, cooperative membership, and literacy emerged as key factors influencing french bean productivity in the study area.

Table 6 Mean yield comparision of farmers by independent sample t-test

3.7 Factors affecting production of French bean in the study area

Table 7 reveals that multiple regression model was statistically significant (F = 28.00, p < 0.001), indicating that the explanatory variables jointly influenced the bean production. The model explained approximately 75.9% of the variation in production (R² = 0.758,8), and the high adjusted R² (0.731,7) confirmed strong explanatory power even after accounting for the number of predictors. With 100 observations and a relatively low Root MSE (229.25), the model demonstrated good statistical reliability and robustness.

Table 7 Summary statistics of the multiple regression model for bean production (N = 100)

The regression results show that total cultivated area, irrigated land, training, and annual income had a significant positive effect on bean production, indicating the importance of resource availability and capacity building (Table 8). In contrast, education, cooperative membership, experience, gender, age, and family size did not significantly influence the total production of French beans in the study area. It was found that production was mainly driven by access to land, irrigation, financial resources, and training rather than by socio-demographic characteristics.

Table 8  Factors affecting production of French bean in the study area Note: ** and *** represents significance at 5% and 1% respectively

3.8 Level of satisfaction of farmers

It reveals that most farmers (40%) were moderately satisfied with their bean production, while 26% were not satisfied, 21% were neutral, and only 13% were strongly satisfied, indicating moderate overall satisfaction with room for improvement in addressing their concerns and enhancing overall satisfaction (Table 9).

Table 9 Satisfaction level of farmers

3.9 Severity of constraints

3.9.1 Severity of production problems in the study area

The major constraints in French bean production were ranked based on weighted scores in Table 10, where disease and pest incidence were found to be the most severe (0.856), followed by irrigation issues (0.820).

Table 10 Severity of production problems in the study area

3.9.2 Severity of bean pests in the study area

The results reveal that aphids and pod borer are the most severe insect pests of French beans, followed by leaf miners, with weevils and Mexican bean beetles posing lesser threats, which suggests that pest management should prioritize the first two for effective yield protection (Table 11).

Table 11 Severity of bean pests in the study area

3.9.3 Severity of major diseases of beans in the study area

Table 12 reveals that anthracnose was the most severe (0.880), followed by rust (0.764) and root rot (0.630). Powdery mildew (0.404) and mosaic virus (0.294) are comparatively less serious, which suggests that disease management should primarily focus on anthracnose, rust, and root rot to reduce crop losses.

Table 12 Severity of major diseases of beans in the study area

3.9.4 Severity of major marketing problems in the study area

The results show that the major marketing constraints for French beans are unorganized marketing (0.748), followed by limited storage facilities (0.636) and seasonal oversupply (0.634), which indicates that improving market organization, storage, and information access could enhance farmer income and reduce post-harvest losses (Table 13).

Table 13 Severity of major marketing problems in the study area

4 Discussion

The bean producing household size in the study area is higher than the average of the country, which is 4.37 (National Statistics Office, 2021), indicating relatively large family units, which is common in rural Nepal. Such family sizes can be advantageous for labor-intensive agricultural activities, as family labor remains a primary input in smallholder farming systems (Bhandari and Ghimire, 2013). The wide range of annual income values of farmers reflects considerable variation among households in terms of resource access and production capacity (Gáfaro et al., 2025).

The human labor constitutes 45.32% of total cost of production highlighting the heavy reliance on manual labor in bean cultivation which is slightly higher than 41.14% reported by Tongbram et al. (2021). Joshi et al. (2022) reported that the total cost of production of Kidney beans per ropani was NRs 21,815 in Darchula district of Nepal, while Tongbram et al. (2021) reported the cost of cultivation of French beans is INR 238,894 per hectare in Manipur, Northeast India. Tongbram et al. (2021) reported a B:C ratio of 1.9,6 and Joshi et al. (2022) reported a B:C ratio of 1.29.

Farmer training programs improve knowledge, awareness, adoption of technologies, efficiency, and overall farm productivity through extension services (Baral and Gyawali, 2024). Cooperatives in Nepal enhance vegetable productivity for smallholders by improving input access, extension services, market linkages, and technology adoption, thereby serving as economic pillars for sustainable agricultural development (Bhattarai and Pandit, 2023). Literacy enhances agricultural productivity in Nepal by enabling farmers to adopt modern technologies, interpret extension advice, and optimize resource allocation in smallholder systems (Pudasaini, 1983a; 1983b). Nakano et al. (2018) documented that farmer training increases the adoption of technologies and increases productivity and profitability in farming. Higher household income and access to credit enable the purchase of quality seeds, fertilizers, and other inputs, which increase yields and returns (Boansi et al., 2024).

Adhikari et al. (2024) also found that pest and disease infestations, followed by inadequate irrigation were the main challenges in bean production in Tilagufa municipality of Kalikot. The incidence of insect pests, such as aphids, whiteflies, jassids, leaf miners, and pod borers, was initiated 25 days after sowing until harvesting (Kumar et al., 2023). Agricultural productivity is reduced by anthracnose in beans by 61.5% (Dhungana et al., 2025). Plant diseases are among the major constraints to achieving potential crop yields, and the costs associated with disease damage and management can substantially influence the overall economics of crop production (Oerke, 2006). Agronomic attributes were enhanced, and anthracnose infection was reduced under cultivar mixtures of beans compared to their sole cropping, both for trailing- and bushy-type beans (Prasad et al., 2016). Improving the efficiency of vegetable marketing in Nepal requires strengthening market information systems that provide timely demand and supply information to producers, traders, and consumers, which helps in making better production and marketing decisions and supporting the country’s goal of becoming self-reliant in vegetable production (Malla, 2021).

5 Conclusion

French bean cultivation in Kalikot district is a profitable and important source of food and income, which is reflected by a B:C ratio greater than 1.0, indicating good potential for expansion and commercialization. However, production is constrained mainly by inadequate irrigation, high disease and pest incidence, particularly anthracnose disease and pests such as aphids and pod borer, limited access to quality inputs, and reliance on traditional practices. Marketing problems, such as unorganized markets and dependence on intermediaries, further reduce farmers returns. The MLR results indicated that cultivated area, irrigation, annual household income, and training significantly influenced production. Productivity is greater for farmers with training, cooperative membership, and literacy. French bean production is promising in the Kalikot district of Nepal, but sustainable growth requires integrated improvements in irrigation, technical training, input supply, pest and disease management, and market organization to enhance productivity and farmer income.

Authors’ contributions

S Panta conceived and designed the study, led the fieldwork, performed the data analysis, and prepared the manuscript. S Pandey provided methodological support and assisted in interpreting the findings. P Dhungana contributed to literature review, data validation, and manuscript revision. L Pokhrel coordinated data collection and supported field activities. S Pant assisted with fieldwork and data entry. S Regmi supervised data collection and contributed to data analysis. All authors read and approved the final manuscript.

References

Adhikari S., Chapai A., Shrestha S., Bhandari N., Acharya P., Thapa K., and Keshari S.K., 2024, Economics of production and marketing for French bean in Kalikot District (Tilagupha Municipality), Nepal, International Journal of Horticulture, 14: 0010.

https://doi.org/10.5376/ijh.2024.14.0010

Basnet D.B., Basnet K.B., and Acharya P., 2022, Influence of nitrogen level on growth pattern and yield performance of French bean (Phaseolus vulgaris L.) in Nepal, International Journal of Applied Sciences and Biotechnology, 10(1): 31-40.

https://doi.org/10.3126/ijasbt.v10i1.44157

Bhandari P., and Ghimire D., 2013, Rural agricultural change and fertility transition in Nepal, Rural Sociology, 78(2): 229-252.

https://doi.org/10.1111/ruso.12007

Bhattarai R., and Pandit M., 2023, Cooperatives as pillar of economy to improve agriculture production and marketing, Nepal Public Policy Review, 3(1): 221-238.

https://doi.org/10.59552/nppr.v3i1.61

Bist D.R., Kunwar A., Chapagaee P., Khatri L., Bhatt B., and Mandal A., 2025, The role of hybrid varieties in enhancing crop productivity and sustainability in Nepalese agriculture, Scientifica, 1: 8275428.

https://doi.org/10.1155/sci5/8275428

Boansi D., Gyasi M., Nuamah S., Tham-Agyekum E.K., Ankuyi F., Frimpong R., Gbafah A., and Gyan C.B., 2024, Impact of agricultural credit on productivity, cost and returns from cocoa production in Ghana, Cogent Economics & Finance, 12(1): 2402035.

https://doi.org/10.1080/23322039.2024.2402035

Baral R.S., and Gyawali K., 2024, Effectiveness of farmer’s training in Nepal: a review, Journal of Advances in Agriculture, 15: 18-24.

https://doi.org/10.24297/jaa.v15i.9680

Chhetri A., and Bhatta A., 2017, Agro-morphological variability assessment of common bean (Phaseolus vulgaris L.) genotypes in High Hill Jumla, Nepal, International Journal of Environment, Agriculture and Biotechnology, 2(6): 3110-3115.

https://doi.org/10.22161/ijeab/2.6.42

Dhakal A., 2020, Present status of grain legumes production in Nepal, Food & Agribusiness Management, 2(1): 6-9.

https://doi.org/10.26480/fabm.01.2021.06.09

Dhungana P., Pokhrel N., Puri K., Neupane B.K., Subedi D., Bhattarai N., Chhetri P., and Shrestha A., 2025, Perceptions, impacts, and adaptation to climate change among farmers in Jumla District, Nepal: a community survey, International Journal of Horticulture, 15(5): 257-266.

https://doi.org/10.5376/ijh.2025.15.0026

Gáfaro M., Ibáñez A.M., Sánchez-Ordóñez D., and Ortiz M.C., 2025, Farm size and income distribution of Latin American agriculture: new perspectives on an old issue, Oxford Open Economics, 4(Supplement_1): 148-166.

https://doi.org/10.1093/ooec/odae024

Ghimire B., Dhakal S.C., Marattha S., and Bastakoti R.C., 2022, Lentil production in Nepal: analysis of trends, instability and decomposition (1989-2019), Research Journal of Agriculture and Forestry Sciences, 10(4): 27-34.

Joshi B.K., Prasad R.C., Gurung R., Gautam S., Subedi A., Adhikari A.R., Karkee A., and Gauchan D., 2025, Tradition of cultivating bean mixture for multiple benefits and sustainable production system in mountain agriculture: bean mixture cultivation for sustainable mountain farming, SAARC Journal of Agriculture, 22(2): 209-226.

https://doi.org/10.3329/sja.v22i2.76809

Joshi D., Banjade D., Singh A.K., and Chauhan B., 2022, Value chain analysis of kidney beans (Phaseolus vulgaris L.) in the Api region of Darchula District, Nepal, Food and Agri Economics Review, 2(2): 60-70.

https://doi.org/10.26480/faer.02.2022.60.70

Kalauni S., Pant S., Luitel B.P., and Bhandari B., 2019, Evaluation of pole-type French bean (Phaseolus vulgaris L.) genotypes for agro-morphological variability and yield in the mid-hills of Nepal, Acta Scientifica Agriculture, 3(12): 113-121.

https://doi.org/10.31080/ASAG.2019.03.0733

Kumar B., Singh S.K., Yadav P.K., and Verma R.K., 2023, Relative abundance of insect pests on French bean (Phaseolus vulgaris L.) in relation to abiotic factors, International Journal of Plant & Soil Science, 35(21): 735-742.

https://doi.org/10.9734/ijpss/2023/v35i214035

Luitel B.P., Kalauni S., and Bhandari B.B., 2021, Morphological and yield traits of pole-type French bean genotypes, Journal of Nepal Agricultural Research Council, 7: 10-21.

https://doi.org/10.3126/jnarc.v7i1.36914

Malla S., 2021, Situation of vegetable production and its marketing in the context of rural farmers: a case study, Food and Agri Economics Review, 1(2): 124-126.

https://doi.org/10.26480/faer.02.2021.124.126

Manandhar H.K., Timila R.D., Sharma S., and Joshi S., 2016, A field guide for identification and scoring methods of diseases in the mountain crops of Nepal, pp.9-171.

Miah M., and Q. A., 1993, Applied statistics: a course handbook for human settlements planning, Asian Institute of Technology, Division of Human Settlements Development, Bangkok, Thailand.

Nakano Y., Tsusaka T.W., Aida T., and Pede V.O., 2018, Is farmer-to-farmer extension effective? the impact of training on technology adoption and rice farming productivity in Tanzania, World Development, 105: 336-351.

https://doi.org/10.1016/j.worlddev.2017.12.013

Oerke E.C., 2006, Crop losses to pests, Journal of Agricultural Science, 144(1): 31-43.

https://doi.org/10.1017/S0021859605005708

Prasad R.C., Paudel M.N., Ghimire N.H., and Joshi B.K., 2016, Cultivar mixtures in bean reduced disease infection and increased grain yield under mountain environment of Nepal, Agronomy Journal of Nepal, 4: 128-135.

Pudasaini S.P., 1983a, Education in agricultural productivity, efficiency, and development: the Nepalese case, 3.

https://doi.org/10.22004/AG.ECON.197279

Pudasaini S.P., 1983b, The effects of education in agriculture: evidence from Nepal, American Journal of Agricultural Economics, 65(3): 509-515.

https://doi.org/10.2307/1240499

Tongbram K., Singh Y.C., Ram D., Singh N.G., Singh K.R., and Singh O.K., 2021, An economic analysis of French bean (Phaseolus vulgaris L.) production in Bishnupur district of Manipur, Asian Journal of Agricultural Extension, Economics & Sociology, 39(8): 33-39.

https://doi.org/10.9734/ajaees/2021/v39i830621