How to Improve Smallholder Potato Production in Myanmar: Determinants of Potato Production Function

How to Improve Smallholder Potato Production in Myanmar: Determinants of Potato Production Function

Published: 2022.11.18
Accepted: 2022.11.18
212
Director and Researcher
Department of Planning Ministry of Agriculture, Livestock and Irrigation
Professor
Department of Agricultural Economics Yezin Agricultural University, Myanmar
Deputy Director
Department of Agriculture, Myanmar
Staff Officer
Department of Agriculture, Myanmar
Deputy Staff Officer
Department of Agriculture, Myanmar
Deputy Staff Officer
Department of Agriculture, Myanmar

ABSTRACT

This research attempted to analyze the determinants of potato production in Southern Shan State and Magway Region of Myanmar. Potato plays a significant role in increasing food security and income for the smallholder farmers of Myanmar. Data for the study were collected from both primary and secondary sources. The primary data were collected from 96 farmers and analyzed using SPSS software. The multiple linear regression model results showed that three variables such as family size, potato sown area and access to extension service significantly affect the potato production. Policy implications drawn from the study findings are that it needs to expand the sown area allocated for potato that is available in the study areas with a major subsidy scheme for the availability of the quality improved potato seeds and fertilizers. Productivity of potato per hectare should be increased through proper utilization of land resource and promoting and delivering technology packages (like improved seed varieties, chemicals and fertilizers) to farmers. Strengthening efficient and area specific extension systems should be done by giving continuous capacity building trainings and separating extension work from other administrative activities, all of which increase potato productivity. Smallholder potato farmers should also expose more on the importance of using quality farm inputs. Key stakeholders such as policy makers, planners and development practitioners, value chain stakeholders are required to give due attention to these determinants in order to support smallholder farmers in improving potato production in Myanmar.

Keywords: Potato, Production, Smallholders, Sown area, Myanmar

INTRODUCTION

Agriculture plays a vital role in Myanmar which economically accounts for 21% of GDP, 10 to 15% of total export earnings in 2019-2020, and about 50% of the population relying on crop production and animal husbandry for their livelihoods of households engaged in each income strategy (CSO, 2022). The sector still remains largely dominated by smallholder farmers that are more than half of all agricultural households (53%) cultivating landholdings of two hectares or less (Lowder et al., 2016).

Potato is one of the advantageous crops in the food security system when the yield of other cereal crops is close to the limit. It is the third most important food crop in the world with 359 million tons as a total global output in 2020. Out of these, 62% of total production comes from developing countries with an average annual growth rate of 3.37% (Dongyu, 2022). Therefore, the developing countries are now the world’s biggest producers of potato. In Myanmar, the total production of potato in 2020-2021 was 450,116 tons with an average productivity of 15.45 ton/ha (DoA, 2022). The potato area decreased by 22% from 2011 to 2021 with slightly increased in the total production by 2%.

Southern Shan State (SSS) is the major potato producing region contributing 89% in monsoon and 45% in winter to the national potato production (DoA 2022). In Heho and Naungtayar Townships of SSS, there has been diversification from staple food subsistence production into more market oriented and high value commodities. Potato is a major food and cash crop produced in these townships of SSS. Therefore, potato production is a major source of livelihood for various value chain actors in SSS where it produced two times per year without any irrigation. Magway Region is also one of the major potato production areas which is marketable in Myanmar. Despite its growing area which was only 4% in winter (DoA, 2022), the potatoes from Sinphyukyun Township have been more marketable in Myanmar and a large market share for processing particularly potato chips. Productivity of the crop is constrained by multidimensional factors such as lack of disease resistant and high yielding varieties with desirable market qualities, limited knowledge of agronomic and crop protection management technologies, and poor post-harvest handling (Nigussie et al., 2012). Over the past period, the average potato yields in Myanmar have steadily increased up to 15 ton/ha but seem to stabilize for recent years (FAOSTAT, 2015). On the other hand, production costs continue to increase. Eventually production costs will meet financial yields and profits reduce. It is so far not clear which improvements can be made in the potato cultivation in order to secure high yields, low input costs, and efficient use of inputs and thus improve income of smallholder potato farmers in Myanmar. Therefore, this study was initiated to identify factors affecting potato production at smallholder farmers’ level.

Objectives of the study

•      To analyze key information characterizing socio-demographics of smallholder potato farmers

•      To identify and analyze factors influencing potato production in Southern Shan State and Magway Region

METHODOLOGY

Description of the study areas

The research was conducted in the Southern Shan State production regions in the surroundings of Naungtayar and Heho. Naungtayar is located at approximately 1,400 meters above sea level at a hilly area. Heho is a town located at approximately 1,100 meters above sea level on a flat plateau. Both townships have potato growers on small plots. Potatoes are grown as a valuable cash crop. In Shan State, over 20,000 ha potatoes are cultivated yearly, which resembles about 70% of the total countries area cultivated with potatoes for both monsoon and winter seasons. The average yield in the Southern Shan State is estimated at 17.12 ton/ha (Hnin, 2021). Sinphyukyun Township is located in Magway Region which is a central dry zone and is located 65 meters above sea level. In this township, about 400 ha of potatoes are cultivated and the average yield is 20 ton/ha (DoA 2022). Most of the potatoes produced from Sinphyukyun are of high quality, marketable and sold to the processing enterprises.

Sampling technique and sample size

A combination of purposive and simple random sampling was used. Southern Shan State and Magway Region were selected purposively based on their potential for potato production. From the State, two townships namely Heho and Naungtayar with higher production, from nearest to wholesale market were selected while Sinphyukyun Township, Magway Region with high in market share for potato chip processing was selected. Finally, the study used a total of 96 respondents using simple random sampling technique. Field data were collected with the aid of structured questionnaire using interview technique. In addition to data gathering using standardized questionnaire, informal interviews with key farmers were also conducted.

Data and sources

Both primary and secondary data were used for this study. Secondary data sources include Department of Planning (DoP), Department of Agriculture (DoA), Department of Agricultural Land Management and Statistics (DALMS), published and unpublished reports, bulletins and websites. Primary data source was smallholder farmers by using formal surveys. The formal survey was undertaken through formal interviews with structured questionnaire.  

Both qualitative and quantitative data were collected and used for the study. Qualitative information from farmers and key informants was also collected from each township. Quantitative data incorporated information on demographic and socio-economic characteristics, land holdings, farming practices, potato production, sales and consumption and institutional factors.

Methods of data analysis

Both descriptive statistics and econometric model were used for analyzing the data. Descriptive statistics was applied to the basic characteristics of the sample households to assess differences or similarities among the households. The descriptive statistics such as mean, standard deviations, minimum and maximum values, frequencies, and percentages were used to describe the households.

Econometric model

This part of the analysis deals with the understanding of the factors affecting production of potato by smallholder farmers in Southern Shan State and Magway Region. Quantity of potato produced is a continuous variable that represents the actual potato produced by individual households measured in tons. Multiple linear regression model was appropriate to analyze factors affecting production of potato because all sampled households are producers of potato.

The multiple linear regression model was specified as:

Y = α + α1 X1   + α2 X2 + α3 X3   + α4 X4  + α5 X5   + α6 X6   + α7 X7  +  α8 X8 + α9 X+ α10 X10 + α11 X11 + Ɛi

Y          = Total production (tons)

α0            = constant term

αi             = parameters to be estimated, Xi = vector of explanatory variables

Ɛi             = error term

X1            = household head's sex (dummy, 1 = male, 0 = otherwise)

X2           = household head’s age (years)

X3           = household head’s education (years in schooling)

X4            = household size (No. of individuals in a household)

X5            = experience in potato farming (No. of years)

X6           = sown area (total amount of potato sown area)

X7           = type of seed used in production (dummy, 1 = high yield variety, 0 = local variety)

X8           = access to extension services (dummy, 1 = access, 0 = not access)

X9            = access to credit (dummy, 1 = access, 0 = not access)

X10 = access to market information (dummy, 1 = access, 0 = not access)

X11 = seed sources (dummy, 1 = purchased, 0 = saved)

RESULTS AND DISCUSSION

Socio-demographic characteristics

Age group of the respondents

In Table 1, 26% of the respondents were below 35 years old, 60% were between 35 and 60 years while 14% were above 60 years old. According to the study results, most of the respondents involved in potato production fell in the age group between 35 and 60 years implying that most of the smallholder potato farmers in the study areas were middle aged. Middle aged and young farmers have proved to be active and ready to try new innovations and can provide the needed labor during crop production (Kimaru-Muchai et al., 2020). Elderly farmers have more experiences, resources and authority that would give them more possibilities for trying new innovations; however receptiveness to new ideas and technologies typically decreases with age as a result of an increase in risk aversion and a decreased interest in farming (Relf-Eckstein et al., 2019).

Gender of the respondents

The largest number of the respondents was male at 94 % while women were only at 6 % as presented in Figure 1. The findings in Figure 1 infer that number of men involved in potato production was higher compared to women. Gender influences an individual’s attitude, behavior, interaction, status and participation in the decision-making processes. Because of family practices concerning the ownership of property, women often lack the collateral that would enable them to obtain the credit needed to purchase fertilizers and other inputs that would increase both their output and their income.

Educational level of the respondents

Results in Table 2 reveal that only 6% of the respondents attended monetary education that is informal; 21% completed primary level of education; 33% finished middle school education; 25% accomplished high school education and 15% attained graduated level. Regarding the results, the majority of the respondents had attained the middle school educational level. It can be concluded that literacy levels in the study area were high with 94% of respondents attaining formal education and thus can read and understand information about potato production practices.

Family size of the respondents

The study results reveal that a family had 5 members on average; the maximum family size was 9 members and the minimum was 2 members. The family size is one of the factors influencing potato production (Table 3). The potato production is a farming labor intensive activity during peak seasons i.e. planting, weeding, harvesting and post-harvest operations. Consequently, a big family size and availability of cheap labor could enhance the potato production.

Potato farming experience of the respondents

The experiences in farming also have an influence potato production. Farming experiences do generally lead to better managerial skills being acquired over time and eliminate unnecessary production costs. The respondents’ responses on potato farming experiences are also shown in Table 3. The average experience of farmers in potato cultivation was 19 years; the maximum and minimum potato farming experience was 50 and 2 years, respectively. As pointed out by Salau et al. (2014), the experience in farming is important for effective day-to-day running of farming activities and therefore determines the farmer ability to address issues of crop production.

Sown area of potato production

The sown area owned by the farmers determines the farming system to be utilized, farmers’ adoption of new technologies and output obtained from the land. The average size of potato sown area was 3.37 ha; the maximum was 37.65 ha and the minimum was 0.20 ha. In the study areas, there was a large size gap between the maximum and the minimum. In this case, the maximum sown area was caused by private sector involvement that has produced the seed potato for local potato production. Generally, most potato in Southern Shan State has predominantly been grown by smallholder farmers in the study areas.

Institutional factors

Access to extension service, credit service and market information service

The extension services help to equip the farmers with improved technologies and innovations that improve the production efficiency leading to high yields. The extension activities help farmers to accumulate knowledge on new agricultural technologies which help them to improve the production methods. The knowledge gained from extension agents led the farmers to adopt improved technologies and management practices which have resulted in improvements in potato yield and production. Having access to credits helps the farmers to conduct field operations on time because they are able to pay for agricultural services and inputs needed in potato production. According to the Table 4 results, 47%, 74% and 96% of the respondents had the access of extension service, credit service and market information service, respectively whereas 51%, 26% and 4% of the respondents did not have access to those services.

Potato seed sources and type of varieties

According to the result of survey data, the potato farmers have been using the Markies and Carolus varieties introduced from the Netherlands, Lichu-6 from China, Kufri Jyoti from India in Southern Shan State and Magway Region. Some smallholder farmers grew the local variety, Mya Sein Ni. These varieties were either farmer saved seed or purchased from neighbor farmers, traders/wholesalers and potato seed growers. As potato seed sources, 21% was from farmer saved seeds and 79% was purchased (Figure 2). The 91% of farmers used the improved varieties while only 9% used the local variety (Figure 3). In the study areas, the farmers were using any potato seeds available in the region through potato imported by a producer association or saved by farmers/traders during sowing time.

Regression results of factors affecting on potato production of selected farmers

From the fitting indicators in Table 5, the R square and the adjusted R square are 0.938 and 0.930, respectively, and indicate the extent of the independent variables which can explain 93% of the variation in the dependent variable. The F value is 116.102, and Sig.= 0.000, reaching a highly significant level, indicating that the model has excellent fitness. That is to say, the constructed regression model is effective, and the independent variable and the dependent variable are linear. The Durbin-Watson value is 1.851, which is close to the suggested value of 2, indicates that there is no serious autocorrelation problem in the model.

From the regression results in Table 5, it can be seen that: the family size had a highly significant effect on the total potato production (B = 0.225, Sig. = 0.007<0.01); the sown area of potato had a highly significant effect on the total potato production (B = 9.097, Sig. = 0.000<0.01); the access of extension service has a significant effect on the total potato production (B = 12.650, Sig. = 0.097<0.1). The other independent variables had no significant impact on the total potato production.

According to the regression results, the total potato production was positively influenced by the family size at highly significant level (99 % confidence interval). The total potato production will increase in tons by 0.225 if there was 1 member increment in the family member as family labor. The total potato production was also influenced by the sown area of potato at 1% level of significance. This implied that the sown area of potato would likely lead to increase in potato yield. Specifically, 1 ha increase in potato sown area will lead to increase by 9.097 tons of potato yield. The access of extension service had affected on the total potato production at 10% level of significance. The total potato production through access of extension services will be increased than that of lack of extension services by 12%.

CONCLUSION AND POLICY IMPLICATIONS

This paper examined the factors affecting the total production of potato at smallholder farmers’ level. Descriptive results showed that most of the respondents involved in potato production fell in the age group between 35 and 60 years implying that most of the smallholder potato farmers in the study areas were middle aged. The largest number of the respondents was male at 94% while women at only 6%. The majority of the respondents had attained the middle school educational level and the family had 5 members in average. The average experience of farmers in potato cultivation was 19 years and the average size of potato sown area was 3.37 ha. 47%, 74% and 96% of the respondents had the access of extension service, credit service and market information service, respectively. As potato seed sources, 21% was from farmer saved seed and 79% was purchased. The 91% of farmers used the improved varieties while only 9% used the local variety.

According to the regression results, the family size and the sown area of potato had a highly significant effect on the total potato production; the access of extension service has a significant effect on the total potato production. The other independent variables had no significant impact on the total potato production. Therefore, family size, potato sown area and extension service access, are required to give special attention for intervention if the state wants to promote total potato production.

Regarding the regression function of factor affecting the potato productivity, the sown area of potato affected the smallholder potato production positively and significantly. However, horizontal production that increases the sown area of potato cannot be an option to increase potato production since land is a limited resource. Therefore, productivity of potato per hectare should be increased through proper utilization of land resource. On the other hand, it needs to expand the sown area for potato that is available in the study areas with the support of inputs especially the quality improved potato seeds and fertilizers. Farmers’ potato production was significantly and positively affected by extension service. Therefore, strengthening efficient and area specific extension systems by giving continuous capacity building trainings and separating extension work from other administrative activities increases the potato productivity. Smallholder potato farmers should expose more on importance of using quality farm inputs. Hence, government should subsidize input dealers farm input prices to enable farmers to be affordable for them. Trainings should be conducted more frequently on pests and diseases control and management. Research on potato production improvement should be intensified to establish ways of boosting production.

REFERENCES

CSO. (2022). Report of the FAO of the United Nations on agricultural and rural statistics.

DOA. (2021). Data Records from Department of Agriculture (DOA), Ministry of Agriculture, Livestock and Irrigation, Nay Pyi Taw, Myanmar.

Dongyu, Q. (2022). Role and potential of potato in global food security. FAO.

FAO (2015). Food and Agricultural Organization of the United Nations: FAOSTAT

Hnin. C.H. (2021). Cost, Benefit and Breakeven Analysis of Monsoon Potato Production in Southern Shan State, Myanmar

Kimaru-Muchai, S. W., Ngetich, F. K., Baaru, M., & Mucheru-Muna, M. W. (2020). Adoption and utilisation of Zai pits for improved farm productivity in drier upper Eastern Kenya. Journal of Agriculture and Rural Development in the Tropics and Subtropics (JARTS), 121(1), 13–22.

Lowder, S.K., J. Skoet, and T. Raney. (2016). The Number, Size, and Distribution of Farms, Smallholder Farms, and Family Farms Worldwide. World Development. 87:16-29

Nigussie D., Mengistu K., Haile D.,Wole K., Tamiru A., Olkaba B., Solomon A., and Samuel T. (2012). Participatory rural appraisal for Gurawa, Haramaya, Kombolcha, and Habro districts (woredas) of East and West Hararghe zones in Ethiopia.

Relf-Eckstein, J. E., Ballantyne, A. T., & Phillips, P. W. B. (2019). Farming Reimagined: A case study of autonomous farm equipment and creating an innovation opportunity space for broadacre smart farming. NJAS-Wageningen Journal of Life Sciences, 90, 100307.

Salau, E. S., Lawee, A. Y., Luka, G. E., & Bello, D. (2014). Adoption of improved fisheries technologies by fish farmers in southern agricultural zone of Nasarawa State, Nigeria. Journal of Agricultural Extension and Rural Development, 6(11), 339–346.

Comment