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International Journal of Horticulture (online), 2026, Vol. 16, No.2 ISSN 1927-5803 http://hortherbpublisher.com/index.php/ijh © 2026 HortHerb Publisher, registered at the publishing platform that is operated by Sophia Publishing Group, founded in British Columbia of Canada. All Rights Reserved. Latest Content Profitability and Constraints of French Bean Production in Kalikot District of Nepal Sudarsan Panta, Satish Pandey, Prakash Dhungana, Lalit Pokhrel, Shishir Pant, Sita Regmi International Journal of Horticulture, 2026, Vol. 16, No. 2, 68-76 Effect of Seed Priming on Germination and Seedling Growth of Cucumber (Cucumis sativus cv. Bhaktapur Local) in Syangja, Nepal Saroj Yadav, Bibas Chaulagai, Promise Shrestha, Ganesh Lamsal International Journal of Horticulture, 2026, Vol. 16, No. 2, 77-87 Application of Plant Growth Regulators in Enhancing Loquat Fruit Set Xicheng Wang, Zhen Li International Journal of Horticulture, 2026, Vol. 16, No. 2, 88-97 Effects of Different Mulching Materials on Growth and Yield of Okra (Abelmoschus esculentus L. Moench) cv. Arka Anamika in East Rukum, Nepal Princess Magar, Jenisha Lama, Rakshya Devkota International Journal of Horticulture, 2026, Vol. 16, No. 2, 98-104 Current Status and Development Trends of Integrated Pest and Disease Management Technologies in Grapevine Minghua Li, Dandan Huang International Journal of Horticulture, 2026, Vol. 16, No. 2, 105-121 Influence of Plant Growth Regulators on Eggplant Yield and Uniformity Zhonggang Li, Weichang Wu International Journal of Horticulture, 2026, Vol. 16, No. 2, 122-134
International Journal of Horticulture, 2026, Vol.16, No.2, 68-76 http://hortherbpublisher.com/index.php/ijh 68 Research Article Open Access Profitability and Constraints of French Bean Production in Kalikot District of Nepal Sudarsan Panta , Satish Pandey, Prakash Dhungana, Lalit Pokhrel, Shishir Pant, Sita Regmi Agriculture and Forestry University, Faculty of Agriculture, Rampur, Chitwan, 44209, Nepal Corresponding author: pantasudarshan979@gmail.com International Journal of Horticulture, 2026, Vol.16, No.2 doi: 10.5376/ijh.2026.16.0006 Received: 15 Dec., 2025 Accepted: 10 Feb., 2026 Published: 23 Mar., 2026 Copyright © 2026 Panta et al., This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Panta S., Pandey S., Dhungana P., Pokhrel L., Pant S., and Regmi S., 2026, Profitability and constraints of French bean production in Kalikot District of Nepal, International Journal of Horticulture, 16(2): 68-76 (doi: 10.5376/ijh.2026.16.0006) Abstract French bean cultivation is an important agricultural enterprise in the high hills of Nepal; however, farmers face substantial production and marketing constraints. A study was conducted in the Kalikot district to assess the profitability and key constraints of French bean production. Data were collected through household surveys from 100 bean-growing households selected through proportionate stratified random sampling across different local levels in the Kalikot district. The results revealed an average productivity of 76.10 kg per ropani, with 59.5% of the total production marketed and the remainder used for household consumption and seed purposes. The average cost of production was NRs 11,350 per ropani, while gross returns amounted to NRs 15,372, yielding a gross margin of NRs 4,062 and a benefit cost ratio of 1.35, indicating that French bean cultivation is economically profitable. The independent sample t-test results showed significantly higher productivity among trained, literate farmers, and farmers who were members of cooperatives. Multiple regression analysis (R2 = 0.7588, p < 0.001) identified cultivated area, irrigated land, annual income, and training as significant determinants of total bean production. Major constraints in production include high disease and pest incidence (0.856), particularly anthracnose (0.880) and aphids (0.853), while the key marketing challenge was unorganized marketing systems (0.748). The study concludes that targeted interventions in training, disease and pest management, and market organization can substantially enhance the productivity, profitability, and sustainability of French bean production in Kalikot, Nepal. Keywords French bean (Phaseolus vulgaris L.); Benefit cost ratio; High hills; Production economics; Smallholder farming 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
International Journal of Horticulture, 2026, Vol.16, No.2, 68-76 http://hortherbpublisher.com/index.php/ijh 69 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=∑ ��*��/N Where, I = index 0 < I <1; �= index value (ranging from 0 to 1); ��= scale value for the ith severity category; � �= frequency of responses in the ith severity category; �= total number of respondents (= ∑fi)
International Journal of Horticulture, 2026, Vol.16, No.2, 68-76 http://hortherbpublisher.com/index.php/ijh 70 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 Variable Unit Mean SD Min Max Family members Number of members 6.15 1.81 2 10 Active members involved in agriculture Number of members 2.42 1.14 1 5 Age Years 43.02 6.03 29 67 Total income NPR 1,041,800 499,176 160,000 4,500,000 Agriculture income NPR 624,200 563,677 60,000 3,200,000 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 Particulars Cost (NRs.) Percentage (%) of total cost Variable cost Seed 1,665 14.66 Organic manure 2,805 24.71 Land preparation 1,696 14.94 Labour cost 5,144 45.32 Total variable cost (A) 11,310 99.64 Fixed cost Land tax 40 0.36 Total fixed cost (B) 40 0.36 Total cost (A+B) 11,350 100 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 Price Observations Mean Std. Dev. Farmgate price (Rs) 100 202 15 Market price (Rs) 100 260 7.5
International Journal of Horticulture, 2026, Vol.16, No.2, 68-76 http://hortherbpublisher.com/index.php/ijh 71 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 Variables Value Productivity 76.10 kg/ropani Average total production from household 429.7 kg/year Average family consumption 132 kg/year Average stored for seed 42 kg/year Marketed Surplus 255.7 kg/year 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 Variables Average value NRs/ropani Total cost 11,350 Total fixed cost 40 Total variable cost 11,310 Gross returns 15,372.2 Gross margin 4,062.2 Netmargin 4,022.2 B:C ratio 1.35 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. 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.
International Journal of Horticulture, 2026, Vol.16, No.2, 68-76 http://hortherbpublisher.com/index.php/ijh 72 Table 6 Mean yield comparision of farmers by independent sample t-test S. N Categories N Mean (kg/ropani) df p-value t-value 1 Training received 51 79.27 98 <0.001 4.66*** 2 Training not received 49 69.48 - - - 3 Cooperative member 64 76.62 98 0.006 2.80*** 4 Nonmember 36 70.11 - - - 5 Male 73 75.05 98 0.270 1.11 6 Female 27 72.17 - - - 7 Literate 65 78.21 98 <0.001 5.22*** 8 Illiterate 35 66.97 - - - Note: *** represents significance at 1% Table 7 Summary statistics of the multiple regression model for bean production (N = 100) Statistic Value Number of observations (N) 100 F-value 28.00*** R2 0.758 AdjustedR2 0.731 Root Mean Square Error 229.25 Significance level p <0.001 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 S. N Variable Coefficient B Standard error t-value p-value 1 Education -5.94 33.43 -0.18 0.859 2 Total area 37.97 4.79 7.93 <0.001*** 3 Irrigated land 20.44 6.90 2.96 0.004*** 4 Cooperative -25.84 62.88 -0.41 0.682 5 Experience -1.24 3.86 -0.32 0.749 6 Gender -51.89 53.84 -0.96 0.338 7 Age -2.70 3.91 -0.69 0.492 8 Family size 11.35 19.75 0.57 0.567 9 Training 129.11 57.37 2.25 0.027** 10 Annual income 19.37 6.03 3.21 0.002*** 11 Constant -288.52 309.16 -0.93 0.353 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).
International Journal of Horticulture, 2026, Vol.16, No.2, 68-76 http://hortherbpublisher.com/index.php/ijh 73 Table 9 Satisfaction level of farmers Level of satisfaction Frequency Percentage (%) Not satisfied 26 26 Neutral 21 21 Moderately satisfied 40 40 Strongly satisfied 13 13 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 Factor Weighted score Rank Disease/Pest 0.856 1 Irrigation 0.820 2 Lesser alternatives for organic agriculture 0.470 3 Lack of technical knowledge 0.440 4 Labor shortage 0.418 5 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 Factor Weighted score Rank Aphids 0.853 1 Pod borer 0.829 2 Leafminer 0.582 3 Weevils 0.419 4 Mexican bean beetle 0.388 5 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 Factor Weighted score Rank Anthracnose of bean 0.880 1 Rust of bean 0.764 2 Root rot 0.630 3 Powdery mildew 0.404 4 Mosaic virus 0.294 5 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).
International Journal of Horticulture, 2026, Vol.16, No.2, 68-76 http://hortherbpublisher.com/index.php/ijh 74 Table 13 Severity of major marketing problems in the study area Factor Weighted score Rank Unorganized Marketing 0.748 1 Dependence on intermediaries 0.636 2 Seasonal oversupply 0.634 3 High Transportation cost 0.542 4 Limited market information 0.474 5 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
International Journal of Horticulture, 2026, Vol.16, No.2, 68-76 http://hortherbpublisher.com/index.php/ijh 75 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
International Journal of Horticulture, 2026, Vol.16, No.2, 68-76 http://hortherbpublisher.com/index.php/ijh 76 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
International Journal of Horticulture, 2026, Vol.16, No.2, 77-87 http://hortherbpublisher.com/index.php/ijh 77 Research Article Open Access Effect of Seed Priming on Germination and Seedling Growth of Cucumber (Cucumis sativus cv. Bhaktapur Local) in Syangja, Nepal Saroj Yadav , Bibas Chaulagai, Promise Shrestha, Ganesh Lamsal Agriculture and Forestry University, Faculty of Agriculture, Rampur, Chitwan, 44209, Nepal Corresponding author: saroj8030y@gmail.com International Journal of Horticulture, 2026, Vol.16, No.2 doi: 10.5376/ijh.2026.16.0007 Received: 05 Nov., 2025 Accepted: 26 Feb., 2026 Published: 30 Mar., 2026 Copyright © 2026 Yadav et al., This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Yadav S., Chaulagai B., Shrestha P., and Lamsal G., 2026, Effect of seed priming on germination and seedling growth of cucumber (Cucumis sativus cv. Bhaktapur Local) in Syangja, Nepal, International Journal of Horticulture, 16(2): 77-87 (doi: 10.5376/ijh.2026.16.0007) Abstract Cucumber (Cucumis sativus L.) is high-value vegetable in Nepal, known for its high nutritive value, high water and fiber content. However, cucumber faces low and inconsistent germination rates and poor seedling growth. Seed priming is a viable option to address these issues. Hence, an experiment was conducted from March to July, 2024 in Syangja, Nepal to analyse the effect of seed priming on germination and seedling growth of cucumber under high-tech polyhouse condition. The experiment was laid out in Completely Randomized Design (CRD) with ten treatments i.e. T1: Control, T2: Hot water (45 °C for 5 minutes), T3: GA3 100 ppm, T4: GA3 200 ppm, T5: KNO3 1%, T6: KNO3 3%, T7: Cow urine 5%, T8: Cow urine 10%, T9: Vermiwash 10%, and T10: Vermiwash 20%, each replicated three times. The results revealed that significantly the highest germination percentage (88%), seed vigour index-I (2,643.83), seed vigour index-II (22,555.33), fresh root weight (0.51 g) and earliest days to 50% germination (6 days) were recorded from the seed primed with hot water (45 °C for 5 minutes). Significantly the earliest mean germination time (6.06 days), highest speed of germination (0.49) and highest dry shoot weight (240 mg) were recorded in KNO3 1%, while dry root weight was maximum in GA3 200 ppm (46.00 mg). Hot water significantly enhanced germination percentage and overall seed vigour; KNO3 1% reduced MGT and improved germination speed; GA3 200 ppm promoted root dry matter accumulation. In practical applications, the choice of priming method should be based on target trait, as well as cost and availability considerations. Keywords Cucumber (Cucumis sativus L.); Germination; Hot water; Potassium nitrate; Seed priming 1 Introduction Cucumber (Cucumis sativus L.) is one of the economically important cucurbits grown during summer season in hills and terai region of Nepal. Cucumber is low in calories and contains soluble fiber, high level of vitamins like C, K, other traces of minerals and antioxidants (Murad and Nyc, 2016). The nutritive value of 100 g of edible cucumber contains 12 calories of energy, 0.6 g of protein, 0.1 g of fat, 2.2-3.6 g of carbohydrates, 0.5 g of dietary fiber, 14 mg of Ca, 15 mg of Mg, 124 mg of K, 24 mg of P (Shakuntala et al., 2020). Seed priming is a pre-sowing strategy for influencing seedling development by modulating pre-germination metabolic activity prior to the emergence of radicle and generally enhance rapid, uniform emergence and plant development to achieve higher yield (Black and Bewley, 2000). It is a technique to elevate the germination percentage and reduce the time of seedling emergence along with improvement in uniformity of germination and emergence in field condition (Dhal et al., 2022). Hydro-priming enhance the seed germination, growth and uniform seedling growth in the field in various crops (Adebisi et al., 2012), and increases the speed of germination, decreases mean germination time (MGT), increases seed vigour index (SVI) (Shakuntala et al., 2020). GA3 play essential role in plant growth and development (Bai et al., 2016), chlorophyll biosynthesis, carbohydrate metabolism (Varier et al., 2010), and increases germination by 30.56% (Behera, 2016). KNO3 improves seed parameters of cucumber and other vegetables (Ghassemi-Golezani and Esmaeilpour, 2008). Cow urine 10% shows positive influence in capsicum due to presence of physiologically active substances (Ambika and Balakrishnan, 2015). Vermiwash priming increases the first and final count germination compared to control (Sowmya et al., 2022). Fathima and Sekar (2014) revealed that vermiwash treatment was most effective in promoting seedling growth, including maximum hypocotyl and radicle length.
International Journal of Horticulture, 2026, Vol.16, No.2, 77-87 http://hortherbpublisher.com/index.php/ijh 78 Poor germination and erratic seedling growth were major factors to obstruct the seedling emergence and lower production of cucumber respectively. Effective results of seed priming on germination and seedling growth may be useful in making cucumber growers aware about the benefits of seed priming. Hence, the experiment was conducted to assess the effect of seed priming on germination and seedling growth of cucumber. 2 Materials and Methods 2.1 Experimental site The study was conducted in high-tech polyhouse at the demonstration site of Agriculture Knowledge Center (AKC) Office, Putalibazar, Syangja from March to July, 2024. Syangja district lies in mid-hill region at altitude 300-2,266 masl. It lies at latitude 28º4ˈ6̎̎ N and longitude 83º52ˈ0̎ E. The morning temperature at 6:00 am remained relatively stable (20 °C–23 °C) (Figure 1). The afternoon temperature at 2:00 pm consistently recorded the highest values (35 °C–40 °C), while the evening temperature at 6:00 pm was moderate (30 °C–35 °C). This pattern indicates a clear diurnal fluctuation, with peak temperatures occurring in the afternoon and minimum values in the early morning. Relative humidity was highest during the morning (80%–100%), lowest in the afternoon (25%–35%), and moderate in the evening (35%–50%) (Figure 2). An inverse relationship between temperature and relative humidity was evident, with higher daytime temperatures corresponding to lower humidity levels. Figure 1 Daily temperature of the high-tech polyhouse during experimental period Figure 2 Daily relative humidity of the high-tech polyhouse during experimental period
International Journal of Horticulture, 2026, Vol.16, No.2, 77-87 http://hortherbpublisher.com/index.php/ijh 79 2.2 Plant material and seed source The seeds were purchased from Agrovet and produced by Muktinath Krishi Company. The packet included following labellings: Variety name: Bhaktapur Local Moisture content: 6% Thousand-seed weight: 32 g 2.3 Seed priming treatments Ten different types of treatments and concentrations were evaluated for an experiment. Control, Hot water, Gibberellic acid (GA3), Potassium nitrate (KNO3), Cow urine and Vermiwash were used with selective concentration (Table 1). Table 1 Details of the treatments evaluated in the experiment Treatments Details T1 Control (unsoaked) T2 Hot water (45 °Cfor 5 minutes) T3 GA3 100 ppm T4 GA3 200 ppm T5 KNO3 1% T6 KNO3 3% T7 Cow urine 5% T8 Cow urine 10% T9 Vermiwash 10% T10 Vermiwash 20% Note:GA3- gibberellic acid; KNO3- potassium nitrate; ppm- parts per million 2.4 Procedure of seed priming Seeds were primed for 24 hours in priming solution of KNO3, GA3, Cow urine and Vermiwash. Similarly, hot water (45 C) priming of seed was done for 5 minutes. Seeds were soaked in 100 mL priming solutions of the respective treatment solutions. Then the seeds were re-dried to near original moisture level at room temperature for 24 hrs. For control, seeds were not treated and it were used as in the original condition. For priming with GA3, 1 g of GA3 was taken in a test tube and 3 mL of 70% ethyl alcohol was added and it was shaked with low heat. The heated solution of the test tube was diluted with distilled water to make 1,000 ppm of 1 litre stock solution of GA3. Finally, it was diluted with distilled water to prepare 100 ppm and 200 ppm GA3 solutions. For the preparation of KNO3 1% solution, 1 g of KNO3 was taken and diluted with distilled water to make 100 mL solution and 3 g of KNO3 was taken and diluted with distilled water to make 100 mL solution of KNO3 3%. 2.5 Experimental design and layout The experiment was laid out in Completely Randomized Design (CRD) with ten treatments and three replications. “Each treatment consisted 50 seeds, with 3 replications, resulting in total sample size of 150 seeds per treatment.” For seedling measurements, the 10 sample plants were randomly selected from each tray, and then tray mean were calculated. Subsequently, ANOVA were performed using the tray as an experimental unit (n=3). 2.6 Germination assessment Among 50 seeds sown in each tray, the number of seed got emerged were only taken for an assessment considering 50 as a whole. Observation was done on daily basis in the morning time and data were recorded according to the data observed. Calculation of germination parameters are given below:
International Journal of Horticulture, 2026, Vol.16, No.2, 77-87 http://hortherbpublisher.com/index.php/ijh 80 Number of normal seedlings from each replication were counted and germination percentage was calculated by using formula given by Piri et al. (2009): Seed germination percentage = Number of normal seedlings Total number of seeds ×100% Mean germination time (MGT) was the time taken for a lot to germinate. The lower the MGT the faster the population of seeds were germinated (Dhakal and Subedi, 2020): MGT= ∑(D*n) ∑n Where, D =the number of days counted from the beginning of germination, n = number of seed germinated on each day. Seedling Vigour Index (SVI) was calculated by using following formula (Dhakal and Subedi, 2020): SVI-I = Germination percentage × Total seedling length (cm) SVI-II = Germination percentage × seedling dry weight (mg) Where, SVI-I indicates vigour of seed in relation with length of seedling while SVI-II indicates vigour of seed in relation with dry matter accumulates of seedling. Days to 50% germination was the time taken to get 50% germination of final germination percentages (Coolber et al., 1990). Speed of germination (BRI) was calculated by using following formula (Bartlett, 1937): BRI= p1+ p1+p2 + p1+p2+p3 +…+(p1+p2+p3+...+pn N(p1+p2+...+pn) Where, p1+p2+p3+...and pn are the germination (%) at 1st, 2nd, 3rd and nth day, respectively and ‘N’ is the total number of days taken for germination. 2.7 Seedling growth measurement Seedling growth was evaluated by sampling plants at 21 days after sowing. The sampled seedlings were carefully uprooted to avoid damaging the roots. After collection, the roots were separated from the stem portions and different growth parameters were measured. For each treatment, ten representative seedlings were selected, and the mean values were calculated and recorded for further analysis. Root length was measured after the seedlings were uprooted. The measurement was taken from the tip of the root apex to the base of the root system at 21 days after sowing, following the method described by Dhakal and Subedi (2020). Shoot length was determined by measuring the distance from the base of the growing medium to the tip of the shoot apex. For fresh weight determination, sample plants from each experimental unit were collected and separated into root and shoot portions by cutting with a knife. The stem portion was weighed using a weighing machine to determine shoot fresh weight, and the values were recorded in grams. Similarly, the root portion was weighed separately to obtain root fresh weight, and the average values were calculated for each treatment. To determine dry weight, the shoot portions were first weighed to obtain fresh weight and then placed in envelopes. These samples were dried in a hot air oven at 105 °C for 24 hours and then allowed to cool as described by Khatiwada and Adhikari (2020). After drying, the shoot samples were weighed and the shoot dry weight was recorded in milligrams. The same procedure was followed for the root portions: after measuring fresh weight, the root samples were packed in envelopes, dried in a hot air oven at 105 °C for 24 hours, cooled, and then weighed to obtain root dry weight in milligrams. The average values were calculated for analysis.
International Journal of Horticulture, 2026, Vol.16, No.2, 77-87 http://hortherbpublisher.com/index.php/ijh 81 2.8 Statistical analysis All the recorded data were arranged systematically treatment wise under three replications using Microsoft Excel version 16.89.1. To determine the significant result between the treatments, Analysis of variance (ANOVA) was carried out using R studio version 4.4.1 and DMRT was used for mean separation at 5% level of significance (p<0.05). 3 Results and Analysis 3.1 Germination percentage, mean germination time (MGT) and days to 50% germination (T50) The results on germination percentage, mean germination time (MGT) and days to 50% germination (T50) affected by different seed priming method are presented in Table 2. Germination percentage, mean germination time, and days to 50% germination were significantly affected by different seed priming techniques. Table 2 Effect of seed priming on germination percentage, mean germination time (MGT) and days to 50 % germination (T50) of cucumber (Cucumis sativus cv. Bhaktapur Local) in Syangja, Nepal, 2024 Treatments Germination parameters Germination percentage MGT (Days) T50 (Days) Control 73.34c 6.90a 6.83a Hot water (45C for 5 minutes) 88.00a 6.30b 6.00b GA3 100 ppm 84.00ab 6.22bc 6.00b GA3 200 ppm 81.34abc 6.34bc 6.00b KNO3 1% 80.67abc 6.06c 6.00b KNO3 3% 80.00abc 6.19bc 6.00b Cow urine 5% 77.34bc 6.27bc 6.00b Cow urine 10% 80.00abc 6.26bc 6.00b Vermiwash 10% 76.67bc 6.17bc 6.00b Vermiwash 20% 80.67abc 6.41b 6.00b CV(%) 5.52 1.98 0.75 LSD0.05 7.54 0.21 0.07 Grandmean 80.20 6.31 6.08 SEm() 2.55 0.07 0.02 F-test * *** *** Note: Mean within the column followed by the same letter/s are not significantly different at 5% level of significance by DMRT. * Significant at 5% (p<0.05), ** Significant at 1% (p<0.01), *** Significant at 0.1% (p<0.001), NS= non-significant at 5% (p>0.05), SEm= Standard Error of mean, LSD= Least significant difference, CV= Coefficient of variance, MGT= Mean germination time and T50= Days to 50% germination Significantly the highest germination percentage (88.00%) was found in hot water (45 C for 5 minutes). GA3 100 ppm (84.00%), GA3 200 ppm (81.34%), KNO3 1% (80.67%), Vermiwash 20% (80.67%), KNO3 3% (80.67%) and Cow urine 10% (80.00%), also showed increased germination percentage but were non-significant among themselves (LSD=7.54), while the lowest germination percentage (73.34%) was observed in control. Significantly the highest mean germination time was recorded in control (6.90 days), while the lowest MGT was found in KNO3 1% (6.06 days), which was not significantly different from Vermiwash 10% (6.17 days), KNO3 3% (6.19 days), GA3100 ppm (6.22 days), Cow urine 10% (6.26 days), Cow urine 5% (6.27 days) and GA3 200 ppm (6.34 days). Significantly the highest T50 (6.83 days) was found in control and the lowest T50 was found in hot water (6.00 days) which was not significantly different from Vermiwash 10% and 20%, Cow urine 5% and 10%, KNO3 1% and 3%, GA3 100 ppm and 200 ppm. 3.2 Seed vigour index (SVI-I and SVI-II) and speed of germination (BRI) The results on Seed vigour index I (SVI-I), Seed vigour index II (SVI-II) and speed of germination (BRI) are presented in Table 3. Significantly the highest SVI-I (2,643.83) was found in hot water (45 °C for 5 minutes)
International Journal of Horticulture, 2026, Vol.16, No.2, 77-87 http://hortherbpublisher.com/index.php/ijh 82 which was not significantly different from KNO3 1% (2,506.23) and GA3 200 ppm (2,502.24), while the lowest SVI-I (1,828.13) was found in control. Table 3 Effect of seed priming on seed vigour index and speed of germination of cucumber (Cucumis sativus cv. Bhaktapur Local) in Syangja, Nepal, 2024 Treatments Seed vigour index (SVI) Speed of germination SVI-I SVI-II BRI Control 1,828.13d 16,823.33d 0.40d Hot water (45C for 5 minutes) 2,643.83a 22,555.33a 0.46bc GA3 100 ppm 2,202.97bcd 21,026.00ab 0.47abc GA3 200 ppm 2,502.24ab 21,933.33ab 0.46bc KNO3 1% 2,306.23abc 22,006.67ab 0.49a KNO3 3% 2,031.86cd 17,776.00cd 0.48abc Cow urine 5% 2,044.51cd 19,702.67bc 0.47abc Cow urine 10% 2,167.02bcd 20,877.33ab 0.47abc Vermiwash 10% 1,966.06cd 17,946.00cd 0.48ab Vermiwash 20% 2,106.60cd 19,580.67bc 0.45c CV(%) 9.40 6.41 0.46 LSD0.05 349.07 2,188.86 0.02 Grandmean 2,179.94 20,022.73 0.46 SEm() 118.30 741.98 0.00 F-test ** *** *** Note: Mean within the column followed by the same letter/s are not significantly different at 5% level of significance by DMRT. * Significant at 5% (p<0.05), ** Significant at 1% (p<0.01), *** Significant at 0.1% (p<0.001), NS= non-significant at 5% (p>0.05), SEm= Standard Error of mean, LSD= Least significant difference, CV= Coefficient of variance, SVI-I= Seed vigour index-I, SVI-II= Seed vigour index-II and BRI= Speed of germination Significantly the highest SVI-II (22,555.33) was found in hot water which was not significantly different from KNO3 1% (22006.67), GA3 200 ppm (21,933.33), GA3 100 ppm (21,026.00) and Cow urine 10% (20,877.33), while the lowest SVI-II (16,823.33) was found in control. This finding was also supported by Sowmya et al. (2013), where KNO3 1% had highest SVI-II. Significantly the highest BRI (0.49) was found in KNO3 1% which was not significantly different from KNO3 3% and Vermiwash 10% (0.48), Cow urine 5% and 10% (0.47), GA3 100 ppm (0.47), while the lowest BRI (0.40) was found in control. 3.3 Shoot length and root length (cm) The results on shoot length and root length are presented in Table 4. The effect of different seed priming treatments on shoot length did not show significant differences. Similar finding was reported by Al Sahil (2016). Root length was highly significant for different seed priming techniques. Significantly, the highest root length was found in GA3 200 ppm (21.15 cm) which did not differ significantly from the hot water (20.09 cm) treatment, while the lowest root length was found in control (15.49 cm). Vermiwash 10% (15.75 cm), Cow urine 5% (16.56 cm), Vermiwash 20% (16.62 cm), KNO3 3% (16.67 cm), GA3 100 ppm (17.08 cm), Cow urine 10% (17.26 cm) andKNO3 1% (17.76 cm) also showed lower root length but were non-significant among themselves. 3.4 Fresh shoot weight and fresh root weight (g) The results on fresh shoot and fresh root weight are presented in Table 5. The effect of different seed priming treatments on fresh shoot weight did not show significant differences. According to Farooq et al. (2007), Osmo-priming or chemo-priming did not improve the seedling fresh weight in melon. Seed pre-soaking treatments were recorded non-significant for seedling fresh weight in cucumber (Al Sahil, 2016).
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