https://orcid.org/0000-0001-7705-3686
?Mathematical formulae have been encoded as MathML and are displayed in this HTML version using MathJax in order to improve their display. Uncheck the box to turn MathJax off. This feature requires Javascript. Click on a formula to zoom.Abstract
Banana is a high-value commercial summer fruit growing in Nepal. The study was conducted to examine the profitability and resource use efficiency in banana production in the Chitwan district. Categorization of banana farmers was done according to the farm size as small-scale and large-scale farmers. A total of 80 banana farmers were randomly selected, including 45 small-scale and 35 large-scale farmers. Results revealed that the average cost of production of bananas per Kattha per year was NPR 11,769.85 and the gross benefit was NPR 15,470.687 per Kattha per year. Similarly, the overall BC ratio was 1.37 showing a profitable farming business with the significant economy of scale. The return to scale was 0.699 showing a decreasing return to scale. In production function analysis, the cost of land preparation, fertilizer, manure, pesticides, and insurance premium were positively significant and micronutrient cost was negatively significant to gross returns from banana farming. All the resources were found overutilized except insurance premiums. This showed that lowering the cost of overutilized resources and increasing the insurance premium can help to maximize profit in the long run in banana farming.
Keywords:
1. Introduction
Banana is a high-value commercial agricultural product and the major summer fruit growing in Nepal (ICIMOD, 2015). Banana is served as a delicious fruit, subsidiary food, and some varieties to use for the culinary purpose and yield fiber (Parvin et al., Citation2013). Commercialization of a banana is tremendously increasing and accounts for about 21% of the total summer fruit area and 37% of total summer fruit production in Nepal (Pandey et al., Citation2017). Meanwhile, the production area has reached to 16,699 ha with the production of 254,161 mt and average productivity of 15.22 mt/ha in Nepal (MoALD, Citation2019). Currently, the demand for banana is so high that it even exceeds the national produce. In the fiscal year 2019/20, the import was about 50,651,756 kg with the negligible export quantity (MoF, Citation2019). This ballooning import is to make up for the domestic production gap caused by the country’s low productivity. The demand for bananas is increasing each day with the increasing population and awareness of their nutritive value for it.
Chitwan is the leading district for the commercialization of banana farming for a few years. The production in the district has increased at a whopping rate, i.e., 566% over the past decade (Y. N. Ghimire et al., Citation2016). The availability of suitable climatic conditions, soil characteristics, and easy market access favors the district to be one of the prime hubs for banana production. The Agriculture Development strategy recognized banana as the major cash crop while One Village One Product (OVOP) and Prime Minister Agriculture Modernization Project (PMAMP) also prioritized it and emphasized in commercial production. Development of the Banana subsector aids in the generation of employment opportunities and improves local economy and sustainable livelihood. Many non-governmental organizations like United Nations Development Program (UNDP), International Centre for Integrated Mountain Development (ICIMOD), Korean International Cooperation Agency (KOICA), etc., are working in the upliftment of banana farmers in Chitwan. Several studies showed that commercial banana farming in Chitwan as the profitable agriculture business with a higher benefit–cost ratio (MRSMP, 2014; Dulal & Kattel, Citation2020; S. Ghimire et al., Citation2019; Sharma et al., Citation2021). However, farmers faced various production challenges, marketing constraints and post-harvest losses resulting in lower productivity (Dave et al., Citation2016; Phulara et al., Citation2020; S. Ghimire et al., Citation2019). Incidences of disease, pest attacks, unavailability of the inputs like quality saplings, and poor agriculture credit flow are some of the problems faced during farming practices. As mentioned by Tinzaara et al. (Citation2018), banana farmers in developing countries also faced challenges on resource allocation and technical knowledge. Farmers do not practice economic optimum level of resources due to inadequate knowledge on it (Dhakal et al., Citation2015b). All agribusiness firms have the objectives of profit maximization with the optimum resources implied in it. Profitability of banana farming has been assessed, but there is extremely limited research on the optimum resources to be implied by the farmers for maximum profit. It is also said that improvement in the investment and advancement of production system will help to achieve self-sufficiency on banana production in Nepal (N. P. Joshi et al., Citation2017).
Thus, this paper attempts to assess the profitability of the banana farming as per the scale of production along with the optimum resources to be used for maximum profit. Furthermore, commercialization in banana farming will flourish with the awareness on profitability and resource use efficiency in context of other cash crops.
2. Methodology
As the primary hub for banana production, the Chitwan district of Nepal was specifically chosen for the study. Government programs like One Village One Product (OVOP) program, Fruit Development Project (Nhpc, Citation2017) and Banana Zone established under Prime Minister Agriculture Modernization Project (PMAMP) had given priority for banana production in Chitwan. Commercialization of banana is increasing tremendously in Chitwan from few years. The total area of banana production in Chitwan is 2329 ha with average production of 28,193 mt and productivity 12.11 mt/ha (MoALD, Citation2019).
The study population included all the banana farmers of Chitwan District. The total of 80 banana farmers were taken for the study to represent 10% of the total study population, i.e., 798. Simple random sampling technique was employed for sample farmers selection. The categorization of farmers was done as small-scale farmers and large-scale farmers based on the mean farm size of sampled banana farmers, which was 4 ha.
To obtain primary data, field observation, a household survey using structured and semi-structured questionnaires, focus group discussion, and key informant interview was done. To validate the questionnaire, pre-testing was done in the intended respondents. The secondary data was collected from government and nongovernment organization’s report, annual agricultural statistical books, newsletters, bulletins, different journals, Central Bureau of Statistics, and different study report of concerned agricultural offices.
Data collected from the survey were coded, entered, and analyzed through MS Excel, SPSS, and STATA version 12.1.
Socio-demographic and economic characteristics were analyzed using simple descriptive statistics, t test, and chi-square test.
2.1. Cost, return, and profitability
The cost of production was calculated after considering and pricing all variable inputs such as land preparation by tractors, human labor, suckers, fertilizers, manure, irrigation, pesticides, and micronutrient costs associated with banana cultivation at current market prices. Both purchased and owned inputs were considered for cost estimation. Main fixed cost was accounted for land lease and insurance premium cost.
Thus,
Total cost = Total variable cost +Total fixed cost
The average banana price was multiplied by the volume of bananas sold to determine the gross return.
To measure the profitability of the farm, benefit–cost ratio was assessed. The following formula was used for benefit–cost analysis:
B/C ratio =Gross return (NPR/Kattha)/Total cost (NPR/Kattha)
2.2. Production function analysis
The input–output relationship was calculated using the Cobb–Douglas production function in many studies (Bhatta et al., Citation2020; S. C. Dhakal et al., Citation2015a; Sahota, Citation1968). Cobb–Douglas production function can be expressed as below in the mathematical form:
where Y= returns from banana farming (in price per Kattha)
χ1 = cost of land preparation per Kattha
χ2 = cost of suckers per Kattha
χ3 = cost of labor per Kattha
χ4 = cost of fertilizer per Kattha
χ5 = cost of manure per Kattha
χ6 = cost of irrigation per Kattha
χ7 = cost of pesticide per Kattha
χ8 = cost of micronutrient per Kattha
χ9 = cost of insurance premium per Kattha
e = base of natural logarithm
u = stochastic random error term
Hence, the production function can be written as below after log transformation:
The output elasticity with respect to a specific input was β’, which reflected the marginal increase in the return from bananas with the increase in input and are predicted to bear a positive sign with them.
The following formula was used to calculate efficiency ratio:
r = MVP/MFC
Where MVP = marginal value product
MFC = marginal factor cost
Similarly, the formula for the calculation of MVP is
where bi = estimated regression coefficients
Y = geometric mean of total income from banana production
Xi = geometric mean of ith inputs
Lastly, the decision criteria for the utilization of resources were given as
r = 1 implies the efficient use of the resource
r > 1 implies underuse of the resource (gross return could be increased by employing more of the resource)
r < 1 implies overuse of the resource (excess use of resource was seen and should be decreased to minimize the loss)
3. Results
3.1. Socioeconomic characteristics of continuous variables by farm category
As shown in Table , out of the total sample of 80 banana farmers, 56.25% were small-scale farmers (45) and 43.75% were large-scale farmers (35). Table revealed the average age of small-scale farmers was 51.58 years and large-scale farmers were 43.49 years, which is significantly different at 1% level. The overall mean age was 48.038 years. Similarly, the average years of schooling small-scale and large-scale farmers was 9.24 and 12.29 years, respectively, significant at a 1% level of significance. The overall average family size was 2.75, and the overall experience of banana farming was 8.238 years in the study area. The average farm size was also found significantly different at 1% level, which accounted for 24.31 Kattha for small and 243.657 Kattha large-scale farms. The yearly income of small and large-scale banana farmers was found NPR 361,577.78 and NPR 3,865,714.29, respectivel,y and was significant at a 1% level.
Table 1. Categorization of farmers according to farm size
Table 2. Socioeconomic characteristics of continuous variables by farm category
3.2. Socioeconomic characteristics of categorical data by farm category
shows the majority of male-headed household in the study area. Agriculture was found as the major source of income in both small and large-scale farm. Overall, 72.5% of respondents were dependent on the agriculture sector only. Meanwhile, only 20% of small farm holders and 31.4% of large-scale farm holders were in contact with extension workers. In the study area, 24.4% of small-scale and 62.9% of large-scale farmers were member of cooperatives, which is significantly different at 1% level. Similarly, 51.1% of small-scale and 80% of large-scale farmers were members to formal organization, which is also significantly different at 1% level. Most of the farmers, i.e., 55% and 73% of overall respondents did not use ICT and tissue culture, respectively.
Table 3. Socioeconomic characteristics of categorical data by farm category
3.3. Cost of production
Table shows the details of the cost of banana production per Kattha per year. The total cost of banana production per Kattha per year was NPR 11,018.026 on small-scale and NPR 12,736.473 on large-scale farm. The average cost of banana production was found NPR 11,769.85 per Kattha per year.
Table 4. Total cost incurred during banana production per Kattha per year in NPR
Among the variable cost, the costs for suckers, irrigation charges, and other costs were highly significant at 1% level among small land large-scale farm. Fixed cost mainly lands lease and insurance premium costs were also highly significant, whereas the cost for land preparation, labor, chemical fertilizers, manure, pesticides, and micronutrients was found insignificant among farm categories.
The major share of the variable cost was of land preparation, i.e., 31.14% in small-scale farms and accounted NPR 3431.285 per Kattha per year. Similarly, in large-scale farms, the cost of chemical fertilizers accounted for the highest share in variable cost, which is 28.39% of the total average cost, i.e., NPR 3615.416 per Kattha per year, which is aligned with the. Among fixed costs, the share of land lease cost was the highest irrespective of farm scale.
3.4. Benefit–cost analysis
The average cost of banana cultivation per Kattha per year was found to be NPR 11769.85 and the average gross revenue was NPR 15470.687 as shown in Table . The gross revenue and net revenue of small- and large-scale farm were significant at 5% and 10% level, respectively. The BC ratio was 1.43 and 2.37 in small and large banana farms, respectively, and significantly different at 1 level of significance, and overall BC ratio was 1.37.
Table 5. Benefit–cost analysis of banana farmers in different scales of production
3.5. Production function analysis
Table shows the descriptive statistics of the variables used in the model. To determine the impact of various factors on the gross return of banana production in the research area, a Cobb–Douglas production model was used. The explanatory variables included in this model were cost of land preparation, suckers, labor, chemical fertilizers, manure, irrigation, pesticides, micronutrients, and insurance premium. The regression model obtained for banana production is presented in Table . The sum of elasticity was found to be 0.669, which is less than 1, indicating a decreasing return to scale.
Table 6. Description of the variables used in the Cobb–Douglas model for production function analysis
Table 7. Production function analysis
The adjusted R2 value of the estimated model for banana production was 0.375. This means 37.5% of the variation is due to the explanatory variable used in the model. The model fitted well since the F ratio was significant. Apart from the cost of micronutrients, all explanatory factors exhibited positive coefficients.
The cost for land preparation, and chemical fertilizers were positively significant at 5% level to gross returns from banana farming. These findings were supported by S. Ghimire et al. (Citation2019); Dulal and Kattel (Citation2020). The result from Alagumani (Citation2005) showed the significance of fertilizers cost, and Mukul and Rahman (Citation2013) had significant land preparation cost to gross returns of bananas at a 5% level of significance.
The coefficient value for land preparation cost was 0.188, which revealed that a 1 % increase in land preparation cost would increase gross return by 0.188%. The coefficient of chemical fertilizers cost was 0.121, which revealed that a 1% increase in chemical fertilizers cost would increase gross return by 0.121%. Chemical fertilizer provides the essential soil requirement that aid in higher production and hence return may increase. Similarly, the coefficient of insurance premium 0.035 showed that a unit increase in insurance premium increase in gross return by 0.035%. Here, the cost for insurance premiums was positive and significant at 5% level of significance. In addition to this, the coefficient for cost of manure was also found to be positive and significant at a 1% level of significance. The result showed that a 1% increase in the manure cost keeping another factor constant would increase the gross return by 0.241%. Here, manure includes all the farmyard manure and organic manure protecting soil health and enhancing production of banana. Along with this, the coefficient of pesticide cost was 0.178, which was significant at 10% level of significance and has a positive impact on gross returns. Pest attack and disease incidence are the major problems in banana farming in the study area, which lowers its productivity. Timely application in a judicious manner with expert advice can increase the gross return. While the coefficient of micronutrient was −0.133, significant at 10% level on gross returns from banana production. Keeping other factors constant, 1% increase in micronutrients would decrease the gross return by 0.133%. This may be due to the high cost of micronutrients and application without prior knowledge of their use technique.
3.6. Resource use efficiency
Table shows the estimated MVP of those inputs that were used in banana production. The study presented that MVP to MFC ratio of the land preparation, chemical fertilizer, manure, and pesticides cost was positive, which was also less than o1, indicating their overutilization.
Table 8. Resource use efficiency of various inputs used in banana farming
Similarly, the ratio is negative for micronutrients and less than 1, which indicated overutilization and less profit could be derived by increasing micronutrient cost. The MVP to MFC ratio was more than 1 for insurance premiums, in line with Sharma et al. (Citation2021), indicating underutilization. There is room to increase the gross return from banana farming increasing the insurance, probably encouraging the farmers in commercializing.
4. Discussion
The progressive development of recent research on bananas from Latin American tropical zones establishes that the banana industry to export the final product must begin to carry out exhaustive control from the agricultural fields where the costs begin to affect the climatic stays (B. Olivares, Citation2018)., edaphic conditions (Araya-Alman et al., Citation2020; Campos et al., Citation2022), phytosanitary aspects (Vega et al., Citation2022; Vega et al. 2022b), and natural factors that affect fruit development; therefore, it is necessary to properly evaluate and control each process to make a fruit that benefits and does not incur costs, and our results are a sample of this.
Studies by J. Pitti and Montenegro (Citation2020); Montenegro-Gracia et al. (Citation2021); J. E. Pitti et al. (Citation2021); show the conditions faced by banana growers, who consider that external factors affect growth and product development in countries such as Panama, Venezuela, and Colombia. Most production systems are constantly threatened by the presence of pests and diseases (B. Olivares et al., Citation2021) that manifest themselves in production, economic instability that makes large-scale production impossible, lack of technological adaptation in processes, and lack of advice. In this situation, the uncertainty and risks to which producers are exposed are greater, and the limitations to investing in technology do not allow them to change the traditional paradigm and implement new cost control mechanisms.
Our study establishes that production costs are fundamental to making operational decisions. Ignorance of costs can cause false expectations about profitability and feeling threatened by external factors that are difficult to control. In the study of the South Asian country, i.e., Nepal, we found that socioeconomic characteristics were different in different scales of production. Commercial growers utilized the membership of cooperatives for agriculture credit flow to finance their farm business, acquire technical assistance, and coordinate market information and infrastructures (D. Dhakal, Citation2021). Similarly, with realized benefits of the ICT use in agro-advisory services, Nepalese farmers do not practice it due to illiteracy and less accessibility to the means of ICT (Paudel et al., Citation2018). Farmers prefer suckers to the tissue culture in banana farming of Chitwan District due to their lesser cost and easy availability (A. Joshi et al., Citation2019).
Banana cultivation is regarded as labor intensive and incurred high costs (Rathod & Gavali, Citation2021). The major cost reported was for suckers, irrigation, and land preparation. In this study, total annual cost for production of banana per kg was lesser than the result of S. Ghimire et al. (Citation2019) and Sharma et al. (Citation2021). However, the cost is slightly more than the MRSMP (2014). In addition to this, the reported annual average variable cost for unit production of banana was in line with the result of Gowri and Shanmugam (Citation2015); Memon et al. (Citation2016), indicating high chemical fertilizers cost in banana cultivation and for fixed cost, land lease cost was highest in support of Jondhale (Citation2018).
Banana business was found profitable, which aligns with the result of Raman and Umanath (Citation2016). We found BC ratio lesser than Kamal et al. (Citation2015); S. Ghimire et al. (Citation2019); Dulal and Kattel (Citation2020); Rahman et al. (Citation2020); Phulara et al. (Citation2020). The decreasing return to scale was found, which is in line with Mahalakshmi et al. (Citation2016); Dulal and Kattel (Citation2020) and in contrast to Sharma et al. (Citation2021); Dave et al. (Citation2016).
In production efficiency analysis, the relation of cost for land preparation and chemical fertilizers were positive to gross returns, which were supported by Alagumani (Citation2005); Mukul and Rahman (Citation2013); S. Ghimire et al. (Citation2019); Dulal and Kattel (Citation2020). Mechanization for extensive farming practices aids in better land preparation in commercial farms and increases the production, productivity, and profitability (Gauchan & Shrestha, Citation2017). Banana requires the continuous supply of nutrients for high yield through soil application (Al-Harthi & Al-Yahyai, Citation2009). Chemical fertilizers like urea, potash, DAP, etc., and organic manures like vermicompost, poultry manures, and FYM are used in the field, which increases the production and hence gross returns. Foliar spray of micronutrients using improved technologies is required for higher yield and returns of banana (Kumar & Jeyakumar, Citation2001; Pathak et al., Citation2011). Crop insurance is regarded as a risk management tool that also encourages farmers to opt for commercialization. Large-scale production of banana is practiced due to lesser risk and available insurance schemes facilitates a greater stabilized income (Gautam et al., Citation2018).
The overutilization of cost of land preparation and fertilizer was found, which is in contrast to the result of Sakamma et al. (Citation2018). Similarly, in the result of Sharma et al. (Citation2021), pesticide and manures cost were also overutilized. Insurance premiums were underutilized in line with Sharma et al. (Citation2021).
5. Conclusion
Commercial banana farming is tremendously increasing in Chitwan district over the years. The average cost of production of bananas per Kattha per year was NPR 11,769.85 (99.75 USD) and gross benefit was NPR 15,470.687 (131.11 USD) per Kattha per year. The benefit–cost ratio of banana farmers was found greater than 1 in every scale enterprise, indicating banana farming as a highly profitable business. The result showed the economy of scale. With the Cobb–Douglas production function analysis, the cost of land preparation, fertilizer, manure, insurance premium, and pesticides was positively significant, and micronutrient cost was negatively significant to gross returns from banana farming. This means the increase in the cost of micronutrient will decrease the gross returns while the cost of land preparation, fertilizers, manure, pesticide, and insurance premium will add more gross returns from banana farming. The return to scale was diminishing for farmers. In addition to this, all the resources were overutilized except insurance premium, which gives ample opportunities to increase returns with increasing insurance. The research findings suggest the optimum use of resources rather than overusing them to increase profit. Farmers need to emphasize the positive contributing factors like fertilizers, irrigation, and other input used for more gross income from bananas. Likewise, a reliable and strengthened insurance framework should be established more to encourage for commercialization.
Acknowledgments
The authors express their deepest gratitude to all the stakeholders.
Disclosure statement
No potential conflict of interest was reported by the authors.
Additional information
Funding
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