Global Sustainability Research ISSN: 2833-986X https://doi.org/10.56556/gssr.v3i4.1070 Global Scientific Research 74 RESEARCH ARTICLE Production economics of jute farming in Sunsari district, Nepal Surakshya Sharma1*, Eishaina Chaudhary1, Pratik Gautam1, Kamal Regmi1, Huma Neupane2 1Institute of Agriculture and Animal Science, Paklihawa, Rupandehi, Nepal 2Tribhuvan University, Nepal Corresponding Author: Surakshya Sharma. Email: surakshyasharma111@gmail.com Received: 06 November, 2024, Accepted: 23 November, 2024, Published: 24 November, 2024 Abstract Jute cultivation has shown decreasing trend in recent years globally despite the prospective demand. Being labor- intensive, with labor making up over 70% of the entire cost and technological advancements still not evident in farmers' fields limits productivity of jute in Nepal. This study aims to analyze the economic viability of jute production, factors affecting it and constraints of jute production in Sunsari district, Nepal. Well-structured and pretested interview schedule was used to acquire required data from 120 jute cultivators of Bhokhraha Narsingh and Duhabi municipality using random and purposive sampling technique. Benefit-cost ratio analysis and multiple regression were conducted using Excel 2019 and SPSS Version 25. Jute production is found profitable as shown by positive gross margin and the average Benefit-Cost ratio of 1.52. Highest education of the family, machinery and subsidy were positively significant with Benefit-cost ratio. Number of economically active female members had shown negative influence on benefit-cost ratio of jute production. Distance to nearest extension service center showed highly significant negative relation with benefit-cost ratio implying increasing distance lowers BC ratio by a greater extent. High cost of production and labor problem were ranked as major problem in sustainable jute production. To increase the jute productivity and sustainability, this study recommends focusing on labor issues and enhancing technology interventions. The findings of this study offer policymakers a foundation to implement strategies that strengthen jute production, fostering both economic stability and environmental sustainability in Sunsari district, Nepal. Keywords: BC ratio; economic viability; regression Introduction Jute, often known as the golden fiber, is a natural fiber. It is one of the most affordable and durable natural fibers, and it is regarded as the fiber of the future (Uddin & Chowdhury, 2015). Jute is the cash crop for the poor and the marginal farmers and it continues to be an important commodity for employment and source of income for them (Kumari et al., 2018). Jute (Corchorus capsularis L. & Corchorus olitorius L.) is the world's second most produced natural bast fiber, with an anticipated average production of 2.39 million tons in 2020/21(Singh et al., 2019). The fibers are used to manufacture twine and rope, either alone or in combination with other types of fibers. Jute butts, which are the coarse ends of the stalks, are used to manufacture cheap cloth. In contrast, very fine jute threads can be extracted and turned into imitation silk (Islam & Ali, 2018). Jute has a long history of use in the sacking, carpet, wrapping fabric (cotton bale), and building fabric production industries (Islam & Ali, 2018). Man-made synthetic Global Sustainability Research Global Scientific Research 75 fibers are created in many nations due to insufficient production to fulfill demand and limited geographical distribution in India, Pakistan, Bangladesh, and other Asian countries (Maiti & Singh, 2019). Countries are currently focusing heavily on developing eco-friendly products such as jute bags in order to reduce climate impact and save the environment. Farmers are returning to jute production as the price of jute continues to rise. Jute's market is rapidly expanding (Islam, 2018). To meet industry demands, jute and associated fiber production must be expanded. Increased productivity and increased jute cultivation area are two major ways to do this (Kumari et al., 2018). By lowering dependency on synthetic materials, improving soil health through rotation, and increasing biodiversity, increased jute production could be crucial to the advancement of sustainable agriculture techniques. Additionally, jute supports the creation of environmentally friendly products by offering biodegradable substitutes for plastics, which is in line with international sustainability objectives. Economically, by stabilizing farmer incomes and generating job opportunities, increased jute production strengthens rural communities. Despite such prospective demand, jute cultivation and area in the regions have shown changing trends in recent years. As a result, an attempt must be made to comprehend the current state of Jute farming, as well as the identification of limits from the perspective of growers. The dominance of marginal and small-scale farmers in jute farming is one of the limiting elements in the process of achieving cost competitiveness, resource use efficiency, and marketing efficacy (Kalita & Bhuyan, 2018). Technological progress is still not noticeable in the farmers' fields, and jute cultivation is labor intensive, accounting for almost 70% of the cost of human labor (S. Dutta & Mondal, 2021). The yield and quality of olitorius jute are now diminishing due to a lack of improved jute cultivars and other biotic stress factors. Insect pests are the most important biotic stressors in jute farming. Identifying the best jute varieties to grow on farms and utilizing quality tossa fibers in the jute sector industry would assist farmers in selecting the best jute varieties to grow (Karki et al., 2021). In relation to this, knowing the economics of jute production and identifying the key factors affecting and/or causing variations among producers in this study area is found very imperative in the course of planning for improvement. In this regard, there was no similar study conducted on similar issue in the specific targeted study area and hence this study is meant to fill this information gap. This study sets out to analyze economics of jute farming in Sunsari district, and to identify characteristics that explain variation in the economic viability of the farmers. An understanding of these relationships could provide policymakers with information to design programs that can contribute to measures needed to expand the jute production potential of Sunsari district. To analyze economics of jute farming in Sunsari district, the objectives are; To analyze the economic viability of jute farming, to identify factors affecting economic viability of jute farming and to identify problems associated with of jute farming in Sunsari district. Methodology Study Area Sunsari District is a district in Koshi Zone, Eastern Development Region, Nepal at latitude 26°38′29.76″ North, longitude 87°07′44.76″ East. Sunsari district is the second highest jute producing district of Nepal where jute is cultivated in 1392 hectares with productivity 1.48 mt/ha. Sunsari has a moderate climate. There is a lot of rainfall in the summer, and in the winter, it is quite dry. Bhokraha Narsingh Rural Municipality and Duhabi Municipality were selected for the study as population of jute cultivating farmers is relatively high. Sources of Data Both primary and secondary data will be used. Primary data will be collected through well prepared and pretested questionnaire to the sampled farmers. Secondary data will be collected from different journals, publications, reports and different internet sites. Global Sustainability Research Global Scientific Research 76 Sample Size Determination From two selected municipalities, the representative respondents will be selected to enhance reliability and validity of the study. Accordingly, the sample size of the study is determined by using Kothari sampling design formula, (Kothari, 2004) n = N 1+N(e2) Where, n = sample size N = total population e = acceptable error term (0.1) Simple random sampling was done to collect data from 120 jute farmers. Sampling and Data Collection The required quantitative data was collected through household survey using structured questionnaire which was pretested in 10 randomly selected jute growers of selected municipalities. We collected a list of jute cultivating farmers of Bhokhraha Narsingh and Duhabi municipality and selected 120 jute growers using simple random sampling technique. The data collection was carried out by visiting each household personally and interviewing them with the help of a pretested interview schedule. In each of jute producing respondent households, the household head or any adult who had lived with the household for at least one previous crop production seasons and conversant with the farming activities of the other household members were interviewed. Data Analysis Data collection was done by interview schedule, data was entered in SPSS version 25 and data was analyzed using SPSS version 25 and MS Excel 2019. Following analysis were done: Gross margin analysis Gross margin is the gross return over variable cost. Gross margin is calculated by deducting the total variable cost from the gross return (Bristy, 2020). Gross margin = Gross return – Variable cost Gross return Gross return is calculated by multiplying the total amount of product with respective per unit price and adding value of by-product. Gross return of jute production = Unit price of jute * Total production + value of by-product. Net return Net return or profit was calculated by deducting the total cultivation/production cost from the total return or gross return. Net return = Total return – Total cultivation cost Global Sustainability Research Global Scientific Research 77 Benefit cost ratio Benefit Cost Ratio (BCR) is a relative measure, which is used to compare benefit per unit of cost. BC ratio= Total return/Total cost Factors affecting benefit cost ratio Factors affecting benefit cost ratio were identified using multiple regression (Kothari, 2004). Regression is the determination of a statistical relationship between two or more variables. In simple regression, we have only two variables, one variable (defined as independent) is the cause of the behavior of another one (defined as dependent variable). Regression can only interpret what exists physically i.e., there must be a physical way in which independent variable X can affect dependent variable Y. The basic relationship between X and Y is given by Y = a + bX This equation is known as the regression equation of Y on X (also represents the regression line of Y on X when drawn on a graph) which means that each unit change in X produces a change of b in Y, which is positive for direct and negative for inverse relationships. When there are two or more than two independent variables, the analysis concerning relationship is known as multiple correlation and the equation describing such relationship as the multiple regression equation. Multiple regression equation assumes the form ; Y = a + b₁X₁ + b₂X₂ + b₃X₃ + ⋯ … … … . + bₙXₙ The multiple regression equation for jute production is defined as; Y = a + b₁X₁ + b₂X₂ + b₃X₃ + b₄X₄ + b₅X₅ + b₆X₆ + b₇X₇ + b₈X₈ Where, Y = B/C ratio a = y-intercept b = coefficient or slope for each variable X1 = Sex of Household X2 = Highest education in family X3 = Number of females economically active members X4 = Machinery X5 = Member of cooperatives X6 = Loan for jute Global Sustainability Research Global Scientific Research 78 X7 = Subsidy X8 = Distance to nearest extension service Preference ranking Indexing was done in order to rank the problem by using the formula. I = Σ SiFi / N (Miah, 1993) Where, I= Index Score Si = Scale value of ith level Fi = Frequency of ith level N =Total number of observations Result and discussion Descriptive Statistical Analysis of the Variables Table 11 shows the population characteristics of continuous variables with their mean and standard deviation. The study found the overall mean highest education of family to be 11.89 years with standard deviation 2.83. Higher education among farmers helps to maximize yield per unit area by improving crop management practices. Average of 1.38 number of females were found to be economically active in study area. Furthermore, the study found nearest extension service center was 3.53 km far from household in average. Table 1. Population characteristics (Continuous variables) Variables Mean Std. Deviation Highest education of family (years) 11.89 2.83 Number of economically active females 1.38 0.60 Distance to nearest extension service (km) 3.53 1.70 Source: Field survey 2024 Table 22 shows the population characteristics of categorical variables with their frequencies. Study shows majority of households (87.50%) have male household head while only 12.50% of female household head. 74.20% of farmers had some kind of machineries which indicated 25.80% of farmers are deprived of any kind of machineries. Very few farmers were member of cooperatives which might be due to low abundance of cooperatives or ineffective functions of cooperatives available there. Meanwhile 68.30% of farmers received subsidy on seed and fertilizer reducing cost of production. 31.70% of farmers were found to be out of reach from any kind of subsidy. Very few farmers were found to have drawn loan especially for jute production. Global Sustainability Research Global Scientific Research 79 Table 2. Population Characteristics (Categorical variables) Variables Category Frequency Sex of HH Male 105 (87.50%) Female 15 (12.50%) Machinery Yes 89 (74.20%) No 31 (25.80%) Member of cooperatives Yes 19 (15.80%) No 101 (84.20%) Subsidy Yes 82 (68.30%) No 38 (31.70%) Loan for jute Yes 3 (2.50%) No 117 (97.5%) Source: Field survey 2024 Cost Structure of Jute Production The average total cost of jute production per ha per season was found to be Nrs. 205891.23. Among all the costs contributing to total cost in jute production, labor cost accounts the highest cost (36%) followed by processing cost (25%), machinery cost (15%), variable cost (12%) and land rent (12%). This indicates jute production is labor intensive mostly used during weeding and harvesting. Machine introduced for harvesting of jute was rejected by farmers due to loss of jute sticks by breakage which is high value jute byproduct in study area. Introducing effective machineries to lower human labor requirement is recommended. Improvement in mechanization in jute farming will result in increased yield efficiency while minimizing labor requirement aligning with sustainable agriculture. Dutta (2012) also found labor cost constitute highest cost (55%) followed by variable cost. Within various variable costs, cost of fertilizer (urea, DAP and MOP) i.e. 48% was found highest followed by irrigation (31%), pesticide (12%), and seed (9%). This result is in line with result found by (Dutta, 2012) who also reported cost of fertilizer highest followed by irrigation. Figure 2 shows cost of pesticide is relatively lower which indicates farmers in study area use relatively lower quantity of pesticide. This highly contributes to sustainable agriculture. Figure 1: Pie-chart showing share of various cost in total cost Land rent 12% Total variable … Machinery cost…Labour cost 36% Processing cost… Global Sustainability Research Global Scientific Research 80 Figure 2: Pie-chart showing share of various inputs in total variable cost Source: Field survey 2024 Gross Margin, Gross Return and BC Ratio The study found gross return per ha land to be NPR 313423.36 which includes return from both main product and by-product with gross margin NPR 107532.13. Gross margin was found to be low due to high cost of production but low price of jute. Study found out BC ratio of jute production in study area to be 1.52. This implies with every 1-rupee investment 1.52 will be returned. Therefore, jute production is found profitable as shown by positive gross margin and the BC ratio greater than one. This result is similar with result found by (Islam, 2018) who also found BC ratio to be 1.52. Table 3. Economic viability of jute production Variable Value Total cost 205891.23 Gross margin 107532.13 Gross return 313423.36 BC ratio 1.52 Source: Field survey 2024 Factors Affecting Economic Viability Table 44 shows highest education of family in years was found positively significant with BC ratio at 5% level of significance with coefficient 0.03 which implies 1 years increase in highest education of family increases BC ratio by 3%. Number of females economically active members in family was found to be highly significant with negative Seed 9% Urea 5% DAP 28% MOP 15% Irrigation 31% Pesticide 12% Global Sustainability Research Global Scientific Research 81 coefficient at 1% level of significance. This explains with increase in one female economically active member, BC ratio decreases by 6%. This is due to less efficiency of female as compared to male during various works on jute production increasing cost of production. Presence of machinery had shown positive significant relation with BC ratio at 5% level of significance. Similarly, subsidy had also shown positive significant relation with BC ratio at 5% level of significance with coefficient 0.20 which describes one unit increase in subsidy will increase BC ratio by 20%. Providing subsidy to the farmers is seen to be highly effective in increasing profitability in jute production. Distance to nearest extension service center was found to be affecting BC ratio negatively at 1% level of significance. Increase in distance by 1 km decreases BC ratio by 31%. This is due to decrease in reach of farmers with extension service center in relation to subsidy and training with increase in distance. Table 44 shows that the R2 value for jute is 0.32 which means that 32% variation in the gross return of jute was explained by the independent variables included in the model respectively. The values of adjusted R2 was found 0.27. This means that after considering the degrees of freedom (df), independent variables in the model still explained 27% of the variation in the gross return of jute. The F value for jute was found 6.58 which was highly significant at 1% level indicating the good fit of the model. Table 4. Factors affecting economic viability of jute production Variable Beta coefficient Sex of HH -0.18 (0.12) Highest education of family (years) 0.03 (0.01)** Female economically active members -0.06 (0.04)* Machinery 0.23 (0.09)** Member of cooperatives -0.01 (0.11) Loan for jute -0.24 (0.25) Subsidy 0.20 (0.08)** Distance to nearest extension service -0.31 (0.06)*** Constant 1.70 (0.21)*** F value 6.58*** R value 0.56 R square 0.32 Note: ***, ** and * signifies 1%, 5% and 10% level of significance respectively Value in parenthesis indicates standard error Source: Field survey 2024 Problem in Jute Production The study found out high cost of production as primary problem with index 0.93 followed by labor problem (0.92), technology constraint (0.86), lack of irrigation facility (0.58), lack of retting pond (0.53) and unavailability of quality seed (0.53). So, the study suggests decreasing the cost of production which may be achieved by increasing subsidy and solving labor problem by technology intervention may result higher return in jute production. Rashid (2022) also found high cost of production as primary problem followed by unavailability and high cost of labor. Global Sustainability Research Global Scientific Research 82 Table 5. Problems in jute production Problem in production Index Rank Unavailability of quality seed 0.53 VI Labor problem 0.92 II Lack of irrigation Facility 0.58 IV High cost of production 0.93 I Technology constraint 0.86 III Lack of retting pond 0.53 V Disease problem 0.36 VIII Pest problem 0.42 VII Source: Field survey 2024 Problem in Jute Marketing The study found out low price of jute as major problem with index 0.94 followed by unstable price of jute (0.91), inadequate marketing infrastructures (0.71), fluctuating demand (0.68) and dominance of Indian market (0.61). Providing fair price to the farmers will improve return in jute production. Nowadays, many farmers were found to be shifting towards sugarcane and maize cultivation due to low profitability resulting from low price of jute as compared to cost of jute production. Rashid (2022) also found 55% farmers had problem of low price of jute as compared to production cost. Table 6. Problems in jute marketing Problem in marketing Index Rank Dominance of Indian market 0.61 V Low price of jute 0.94 I Unstable price of jute 0.91 II Fluctuating demand 0.68 IV Transportation 0.26 VIII Lack of market information 0.54 VI Inadequate marketing infrastructures 0.71 III Loss during marketing 0.32 VII Source: Field survey 2024 Conclusion This study presents significant results in jute production in Sunsari district, Nepal. The study found jute production profitable as shown by Benefit-cost ratio of 1.52 and positive gross margin. Highest education of the family, machinery and subsidy were found to be positively significant with Benefit-cost ratio. While, distance to nearest extension service center showed highly significant negative relation with benefit-cost ratio implying increasing distance lowers B/C ratio by a greater extent. High cost of production was found major problem in jute production and low price of jute as marketing problem. This study recommends providing subsidy and enhancing technology interventions is necessary to increase profitability in jute production. Also providing fair price of jute to the farmers Global Sustainability Research Global Scientific Research 83 is necessary to stop jute growers from shifting towards other farming practices as shifting towards maize and sugarcane cultivation is seen more prevalent in Sunsari district. Increased income will enable farmers to afford nutritious food and help address hunger in long run. Strengthening jute farming can enhance Nepal’s export revenue which eventually contributes to national economic growth. Jute being biodegradable and renewable, promoting jute usage aligns with responsible consumption practices. Jute farming also reduces environmental impact and improve soil health. So, we can conclude that enhancing jute sector in Nepal can reduce poverty, promote economic growth and improve environment. This describes jute farming as significant part of sustainable agriculture and sustainable development. Declaration Acknowledgment: We acknowledge Institute of Agriculture and Animal Science, Paklihawa Campus, Nepal for providing required materials and facilities for conducting this experiment. We also acknowledge Mr. Surendra Chaudhary for his unforgettable help during data collection. We heartfully acknowledge all the farmers who helped us with our research. Funding: Not applicable (N/A) Conflict of interest: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Ethics approval/declaration: N/A Consent to participate: N/A Consent for publication: N/A Data availability: Data will be made available on request. Authors contribution: Data collection, S Sharma, E Chaudhary; Data analysis, S Sharma; manuscript, S Sharma; Review and editing, S Sharma, K Regmi, P Gautam; Guidance and manuscript final review, K Regmi, H Neupane. References Dutta, J. (2012). Comparative economics of production of jute and mesta in Dakshin Dinajpur district of West Bengal. 8(2), 91–96. Dutta, S., & Mondal, T. (2021). A review on physical, chemical and integrated weed management in jute. The Pharma Innov. J, 10(8), 1106–1109. Islam, M., & Ali, S. (2018). 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