Agriculture is mainly commercial; cultivated for profit in the developed countries, whereas in developing countries, like Myanmar, the objectives of agriculture are to maximize the production to meet the food requirements as well as to supply other financial obligations of the farmer’s family and to export the agricultural products for foreign exchange of country. An ideal crops plan should not only fulfill requirement of the local people or food for the  farmers   and   their  families,  but  also  meet  fodder requirement of the farm animals. Moreover, the adoption of cropping pattern in any region is a product of varied factors, which includes the important role, such as physical, social and economic factors. Cropping patterns based on climate and land capability are sustainable but market forces and farmers’ aspirations are forcing unsustainable systems (Shekara et al., 2016).

Fertilizer is critical in achieving higher yield needed to feed the  rapidly  growing  population. Inorganic fertilizers contain mineral nutrients which are easily available and absorbed by plants and the convenience and potency of fertilizers make them appeal strongly to traditional farmers who are major food producers in the humid tropics (Wilken, 1987). Soil fertility was depleted once inadequate fertilizer application that limits crop yield, results in nutrient mining. Conversely, the excessive or imbalanced application not only wastes a limited resource, but also pollutes the environment. Therefore, there is a direct link between farmers’ fertilization practices and the resultant effects on soil quality status. The proper and efficient use of fertilizers is essential for increasing soil productivity. As a result, the best fertilizer management is a major consideration in agricultural production (Omari, 2017).

The different rate of nutrient application is possible only if experts can give correct site-specific recommendations, and result revealed that precise information about nutrient status of the soil is required (Godwin, 2001). However, Myanmar farmers have limited knowledge of modern agricultural technologies, including fertilizers. The linkages between the research and extension services to the farmers had not been underdeveloped, resulting in poor soil and fertilizer information dissemination. Farmer knowledge of integrated soil fertilizer management and 4Rs (right sources, right rate, right time, right place) concept has been low. Little or no improvement in research facility and skills and training of research and extension personnel was observed in my study area. Thus, the studies of soil productivity and soil fertility levels are required annually as time series information because they will change over time. In Zeyarthiri Township, most of the farmers in Sipintharyar village grow different crops in both wet and dry seasons and their income mainly depends on their crops yields and market prices. It is one of the intensive cropping zones which is dominated by small scale farming. The research aims to observe the demographic characteristics of farmers, to study the present status of  different  fertilizers application practices in farming and to identify the current status of cropping pattern in the study area.  

Description of study area

The research area is located in the middle region of Myanmar, Naypyitaw, Zeyarthiri Township, Sipintharyar Village, situated between 19°44'43" N - 19°45'22" N and 96°17'42" E - 96°18'02" E (Figure 1) and a total study area of 60 ha. The study area receives a mean annual rainfall of about 1265 mm and the average temperature of 26.8°C. Farmers have practiced rice and maize in monsoon and tomato and lablab bean in winter, as dominant crops in the study area.

Pilot survey was conducted in February 2020 with 10 farmers in the study area. The required secondary data were collected by interviewing the village-head, and meeting with township staff officers from the Department of Agriculture. The purposive random sampling technique was used for selection of farmers who included their field in the boundary area of the study area. Accordingly, 60 farmers were selected as sample respondents and interviewed with structured questionnaire at Sipintharyar village, Zeyarthiri Township, Naypyitaw, Myanmar during February 2020. The questionnaire consisted of social information, field and crop history information that includes soil fertility status, method of land preparation, cropping pattern; and soil management practices information such as fertilizer application (e.g. organic, inorganic or foliar), name and type of fertilizers, rate, time and frequency of fertilizer application, number of years for fertilizer application, use of herbicides, practices of crop residues incorporation, method of harvesting, income, cost and profit of farming.

Data analysis

The data were calculated using Statistical Package for Social Science, SPSS (version 17) software. The descriptive statistics was used for data analysis for all studied variables.

Socio-demographic factors of the respondents in the study area

Distribution of the surveyed respondents according to their demographic characteristics is shown in Table 1. The age of the respondents ranged from 30 to 78 years with an average of 46 years. Of the total 60 respondents, about 82% respondents aged between 40 and 70 years, 3.3% of respondents are above 70 years while the rest 15% of respondents are below 40 years (Figure 2). Respondents’ educational levels had 21% in read and write, 40% in Primary, 28% in Middle, and 10% in High School level in Sipintharyar village (Figure 3). The education status of the respondents in survey areas was found to be low. It showed that respondents could only read posters and magazines for more innovation and it could be weak to communicate their experiences among them. Thus, the finding of Omamo et al. (2002) also reported that education level of the household head may be taken as a proxy for enabling access to technical information on fertilizer use, and hence may be  positively related with fertilizer use.

According to the findings, the respondents in survey areas possessed five groups of land-holding level ranging from 0.10 to 2.8 ha of farm size (Figure 4). About 65% of the respondents possessed the total sown area of 0.10-0.81 ha, 26.7% possessed in >0.81-2.02 ha, and 8.3% possessed in >2.02-2.8 ha. It indicated that the study area is occupied by the small-scale farmers. This finding is in agreement with those of Olayide et al. (1980) who classified small-scale farmers as those having 0.1 to 5.99 ha of farm size.

Most of the respondents started their farming activities at an early age and after getting married with varying wide ranged farming experience from 3 to 60 years (Table 1). Response on farming experience showed that 13% of the respondents had practiced in (<10) years, 20% in (>10-20) years, 33.4% in (>20-30) years, 21.6% in (>30-40) years, 6.7% in (>40-50) years and 5% in (>50-60) years, respectively (Figure 5). This implies that almost all of the respondents have been in the farming profession for quite some period of time and are not novices in farming activities that may enhance the better soil management practices. These are in line with those of Ridler and Hishamunda (2001) who reported that the experienced farmers were a lower risk compared to new farmers. In  the survey  area,  all  respondents except rice growers practiced mixed cropping, crop rotation and intercropping systems for fertility management.

Crop management practices

The detailed information of crop management practices was presented in Table 3. The opinion of respondents for their soil fertility condition was found to be three classes in the study area (Figure 6). Most of respondents (68.3%) said that the fertility condition of their soils were medium while only 13.3% of respondents answered poor fertility condition. It might be the addition of cow dung, chemical fertilizers, and the cultivation of pulses in the study area.

Machine was used in rice and black gram cultivation but it was used in ploughing while animal and human power were used for making bunds, planting rows, planting, weeding and harvesting for other crops in the study area. All of farmers have grown their seeds in lablab bean, black gram, chickpea, tomato (traditional varieties). They usually preferred to store  their  seeds  or  exchange  with neighboring farms for the next crop season. However, farmers bought seeds from merchant for high yielding tomato varieties and maize (CP 888). Okra and Japanese mustard seeds were bought from Myanmar Agri Food Company. The horticultural crops such as banana, ambarella, mango and guava seedling were purchased from Private Farm. The seeding rate for broadcasting was 60 kg ha^-1 in rice, 2.5 kg ha^-1 in sesame and 20 kg ha^-1 in green gram. The seed rates were 5-7.5 kg ha^-1, 5-7.5 kg ha^-1 and 20 kg ha^-1 for maize, okra and lablab bean, respectively. For plant density, 10000 -12000 plants per acre for tomato and 9000 plants per acre with lablab bean intercropping were used. Guava was grown as 6ft × 6ft, 20ft × 20ft for mango and 30ft × 30ft for ambarella and 10ft × 9ft for banana. With the availability of pump irrigation facilities, farmers have adopted different crops in their field (Table 2). Most of the cropping patterns were rice-black gram, rice–fallow, maize-tomato, maize- tomato and lablab bean intercropping, green gram- tomato, okra – tomato, okra- maize- tomato and sesame- lablab bean. The sowing and harvesting time of crops were shown in Table 3.

In addition, many kinds of foliar fertilizer are used at 10-15 days interval according to their crop performance and market demand in these cash crops. During crop seasons, farmers applied 4-5 times of foliar fertilizer together with pesticide or hormones in tomato and okra. Myanmar Agri Food Company sold the seeds (okra and Japanese mustard) to be grown by the farmers and also Blagate and Biofoliar to be used as foliar fertilizers for those crops, and then bought those products daily. The data observed in Figure 7 obviously showed the most common types of fertilizers used by the farmers in the study area. There was little knowledge for using phosphorus and potash fertilizers for crop production. The respondents stated that the fertilizer was always applied to the crops (tomato, okra) when needed by plant performance.

The results of this study showed that farmers’ fertilization practice was just mainly determined by the availability of fertilizers by credit and crop performance, yield response and market price of products. The respondents had high awareness for using chemical fertilizers as they understood that it was needed for the crop to give the yield increase. In Sipintharyar village, the weed management in their field was done manually and by  oxen   for   inter-cultivation   between   planting   rows; however, only rice was managed by using weedicide. Weedicide was applied in rice field whereas other crops were done manually at 2 weeks intervals from 14 days after sowing to flowering time. According to survey data, 78% of respondents did not know about soil fertility test or analysis whereas the rest 22% were unaffordable for the soil analysis.

Correlation between demographic characters of farmers with cropping patterns

Age, educational level, farm size, incorporation of crop residue and farmers’ opinion on soil fertility status had positive relationship with cropping pattern at 5% level of significance (Table 4). Among them, farm size was a highly significant positive relationship (p=0.003) than age, educational level, incorporate crop residue and opinion of soil fertility status. Conversely, farm experience was an insignificant negative relationship. As described in Table 4, R² value is 0.251 and indicates 25% of the variance of cropping pattern is explained by the selected demographic characteristics of farmers in the model. Table 4 indicates that farm size makes the highest contribution (β = 0.388) to explain respondents demographic characters on cropping pattern. It implies that the larger the farm size, the higher the possibility of growing diversity of crops or adopting more than one cropping pattern. Incorporate crop residue (β = 0.236) is the second most contributor on farmers’ demographic characters followed by Age (β = 0.226), opinion of soil fertility status (β = 0.114), educational level (β = 0.105) and farm experience (β = -0.248) of farmers, respectively. This result indicates that farm experience was no contributor to cropping pattern. Therefore, farmers with a large  farm  size  have to be depending more on cropping pattern.

The study reveals that most of farmers (35%) fell under age group 51-60 years and 40% of respondents had primary educational level. Maximum number of respondents (65%) had small holding (0.10-0.81 ha) of cultivated land. One-third of respondents (33.4%) had farming experience of > 20-30 years. Most of the farmers grow maize in wet season and tomato in dry season while others grew rice in their fields. According to linear regression analysis results, age, educational level, farm size, incorporation of crop residue and opinion of soil fertility status of farmers had positive relationship with their cropping pattern but farm size was highly statistically significant and farm experience was negatively insignificant. During the study period, the major problem of farmers was the lower market price of tomato (one kyats per 1.5 kg). The income from selling of tomato could not yield tangible benefit; hence  farmers  were  not picking up tomatoes from plants in the study area. In fertilizer usage, all farmers applied NPK compound and urea fertilizers in their farming. Most of the farmers challenged financial difficulties as well as the market price of products although the farmers are aware that fertilizer application is necessary for increased crop production. This study observed that the limited farmers’ knowledge on fertilizer use and lack of information related to fertilizer management was according to their kind of crops. Thus, it is urgently necessary to project the soil fertility maps and to conduct soil fertility assessment to observe the appropriate use of fertilizer in their farming for the study area.

The authors have not declared any conflict of interests.

This study was funded by a research grant from the Japan International Cooperation Agency Technical Cooperation Projects (JICA-TCP) and facilitated by Yezin Agricultural University (YAU) of Myanmar. The authors also express thankfulness to the Supervisory Committee, Dr. Sein Sein Mu, (Assistant manager, DOA, Pyinoolwin), students from Soil and Water Science Department, the managers and staff of the Department of Agriculture, as well as to all the farmers who participated in this study.