Alternative cropping adoption in Thailand: A case study of rice and sugarcane production.

This research analyzed farmers' acceptance to switch from rice to sugarcane farming and their support preferences in this regard using choice models. The results showed that farm size, crop conversion experience, sugarcane price, household asset and sugarcane price guarantee significantly influenced the farmers' land-use decisions in this regard. Farmers' concerns over cash flow and ability to access the sugarcane market critically decreased their likelihood to switch to sugarcane production. They were also less inclined to grow sugarcane when climatic conditions and soil fertility were favorable. Loan burden and unclear support policies were also a major hindrance. However, attractive sugarcane price along with price guarantee policy had a positive influence on the farmers' willingness to cultivate sugarcane. Farmers mostly prioritized sugarcane price guarantees in the first year, followed by low-interest credit support for production costs and harvesting and logistic services. This shows that effective policy solutions to encourage farmers to switch from rice to sugarcane production should incorporate capacity building, improve credit access, and implement price controls, particularly in the early stages of the transition.

Introduction

Rice farming substantially contributes to the economy of Thailand, which had a total cultivation area of roughly 9.4 million ha in 2018 and 2019. Paddy production is widespread across Thailand, with the northeast and central regions accounting for over 60% of the total production in 2020 (Office of Agricultural Economics, 2021). However, data from the Land Development Department show that 9% of the paddy fields (1.072 million ha) are unsuitable for rice production, and 0.022 million ha of these are better suited for sugarcane production (Land Development Department, 2020). The average rice yield in the unsuitable areas is around 2,187.5 kg per ha compared to 4,687.5 kg per ha for suitable areas (Office of Agricultural Economics, 2017). Bamrungrai et al. (2014) reported that farmers earned higher income from sugarcane cultivation in the unsuitable areas than from paddy production. Also, Khansila et al. (2014) showed that in the unsuitable areas, farmers earned net incomes of 29,362.5 and -3,568.75 baht per ha from sugarcane and rice farming, respectively. Thus, farmers whose land was not suitable for paddy production but suited to sugarcane could increase their incomes by opting to cultivate sugarcane instead, which would also help stabilize the rice market by preventing an oversupply.

At a projected annual growth of 1.4%, sugar consumption would reach 202 million tons globally and 105 million tons in Asia by 2028, with annual import volumes of 63 and 33 million tons, respectively (OECD/FAO, 2019), representing large market opportunities for sugarcane, including in the food and bioenergy industries. Thailand had 57 sugar factories with a daily production capacity of 1.3 million tons each while the total sugarcane production was 116.78 million tons in 2019. In the five-year period from 2014 to 2019, sugarcane production increased from 1.68 million ha to 1.79 million ha. Thus, the industry has enough capacity to support a further increase in sugarcane production and also the opportunity to export more sugar. Rice farmers whose fields are particularly unsuitable for rice production should be encouraged to cultivate sugarcane instead to make the most of their resources and enhance their income. Previous studies identified insufficient capital, lack of knowledge about production and market, limited labor, and unsupportive family as obstacles to farmers adoption of sugarcane cultivation (Bamrungrai et al. (2014), Meesungnoen and Taweekul (2019)). Overcoming these would require the implementation of policies acceptable to farmers to effectively persuade them to switch to sugarcane. Therefore, this study investigated factors that influence farmers’ decisions to change from rice to sugarcane farming and proposed effective supportive measures.

Literature review

Several studies have identified key factors central to farmers' decision-making regarding adopting sugarcane cultivation. Khansila, Mongkonthum and Phetcharaburanin (2014) stated that sugarcane production accounted for about 25 percent of the agricultural area in Nam Phong District, KhonKhaen province. They identified land suitability, water availability, productivity per unit cost, price, ease of cultivation, decreasing prices of original crops, and distance to sugar factories as important factors affecting farmers' willingness to switch to sugarcane cultivation. However, a drawback of sugarcane production was the negative environmental impact from sugarcane burning during harvesting; thus, the promotion of sugarcane cultivation should incorporate regulatory policies on sugarcane burning. Bamrungrai et al. (2014) also indicated that farmers' decisions to switch from rice to sugarcane cultivation were influenced by higher income, land unsuitability for paddy production, and government promotion. The farmers were, however, faced with problems such as high production cost, insufficient market and labor and climate viability. Similar findings were made by Meesungnoen and Taweekul (2019) who stated that 48.2 percent of the sugarcane cultivation area in Khao Suan Kwang District, Khonkaen was converted from paddy fields. They identified suitable land, land fertility, soil characteristics, transportation and distance to market, support from family, labor force, advice from model farmers, higher income, household debt, and government support as factors influencing farmers’ decisions to adopt sugarcane cultivation.

As for adopting other alternative crops, Duangpoch (1998) demonstrated that the willingness of farmers in Chiang Mai, Thailand to cultivate alternative crops in place of opium poppy was influenced mostly by their level of Thai language literacy, prices of alternative crops, number of years of experience in farming, and the frequency of staff contact. However, obstacles such as high input prices, marketing problems, insufficient capital and labor force hindered farmers from adopting alternative crops. Mialhe, Becu and Gunnell (2012) identified policy-related variables as important factors influencing farmers' decision-making on land utilization in Philippines. Similarly, Buntaotook (2014) found that political factors such as supportive government policy on oil palm, support from agricultural officers, and price guarantee policy influenced farmers' decision-making. In addition to policies, socioeconomic factors such as the age of breadwinners, water use in the area, household asset value, household average income per capita, and size of arable land were found to be significant determinants. Similarly, Mishra et al. (2018) indicated that age, gender, irrigation, perception of climatic change, and location specific factors affected farmers' decision on land allocation to paddy cultivation in the Vietnam's delta region. Also, Embaye et al. (2018), using a probit model, demonstrated that farmer's experience, distance from crushing facility, use of no-till farming, and education had positive effects on western US farmers' decision to adopt oilseed crop. Farm income and gender also positively impacted farmer's decision on land allocation. Moreover, Osabuohien et al. (2018) validated that high investment and operating cost, lack of capital and labor, and weak linkage to rice market prevented famers in Ogun state, Nigeria from growing rice. Therefore, financial support and clusters formation for farmer to pool resources such as farm machineries, labor, and accessibility to market affected farmers' decision on adopting rice cultivation. Khanna et al. (2017) conducted a choice experiment to examine crop-contract attributes that influenced US farmers' adoption of energy crops. They found that contracts that provided lower upfront investment costs encouraged farmers to adopt and allocate more land to energy crops.

Thus, from our literature review, the factors influencing farmers' decision on adopting alternative crops are 1) internal factors such as land suitability, farmer's age, farmer's education, labor force, family support and 2) external factors such as climate variability, crop price, input price, market access, community support, government support.

Methodology

In this study, two statistical models were applied for data analysis as follows.

First, a probit model was used to analyze the likelihood of farmers’ decisions to adopt sugarcane production and factors that influence their decisions. The probit model was presented as following equation:where y = 1 when farmer decides to adopt sugarcane, otherwise y = 0. is a vector of factors influencing farmers' adoption decisions namely i) socioeconomic variables — sex, age, level of education, number of household members working full-time on the farm, income earned growing rice (baht/ha), farm size, the experience of switching crops in the past five years, and number of problems (production, price, market, etc.) encountered growing rice; ii) basic knowledge of sugarcane production, based on aggregate scores; iii) risk-perception of sugarcane production (high capital investment, household cash flow, production risks, market access, price risks); and iv) perception of important factors on adopting alternative cropping were scored on a scale of 0–5 (the suitability of soil and weather conditions for sugarcane production, sugarcane price, rice price, household debt, household asset, government support policy for sugarcane production, sugarcane price guarantee).

Since the coefficients estimated from the probit model presented only the direction of relationship and not the magnitude of the effect between dependent and independent variables. Thus, the marginal effect was necessary to explain the effect of factor and was expressed as Eq. (2).

Second, a choice experiment model1 was used to analyze the types of governmental support available to farmers as motivation to convert unsuitable rice farms to sugarcane plantations. Since the individual's preference on attribute was heterogeneous across farmers, the mixed logit model was employed in our estimation. The probability of farmer using a support package can be expressed as (Train, 2009):where the is the density function specifying distribution of , and is farmer ’s indirect utility from using support package . The indirect utility function is generally defined as linear (Hojjati and Bockstael (1988) and Champ et al. (2002)) as:where is a vector of attributes of support package j for farmer . is the coefficient associated with support package . Attributes of the support packages are shown in Table 1. Orthogonal design2 was used to generate 16 alternatives (out of total 72 alternatives), then the alternatives were matched into 8 pairs which were divided into two choice sets. Each farmer was presented with a choice set which was randomly selected. Farmers were asked to choose the most preferred choices with the possibility of not choosing any (opt-out option).

Table 1

Attributes and levels used in the choice models.

Attributes	level	Details of the incentives
Compensation for farmers to quit rice production	Subsidy	THB 6,250 per ha
		THB 7,500 per ha
		THB 9,375 per ha
Financial assistance (Low interest rate credit support)	1-time_payment	Pay all the money once after planting the sugarcane cuttings
	2-time_payment	Payment in two installments: 50% in the 1st month after planting the sugarcane cuttings and 50% in the 7th month
	3-time_payment	Payment in three installments: 50% in the 1st month, 30% in the 5th month, and 20% in the 9th month after planting the sugarcane cuttings
Production cost support	credit_support	Low-interest credit support
	input_support	Provide inputs at lower prices than the market
Price guarantee	price_guarantee	Minimum price guarantee for sugarcane in the first year of cultivation
	no_price_guarantee	No price guarantee for sugarcane in the first year of cultivation
Harvesting and logistics	service_provided	Harvesting and logistic services are available at the farmers' expense
	self_management	Farmers are fully responsible for harvesting and logistic operations

The probit and mixed logit models were estimated by STATA13 software.

Data collection

Primary data were obtained from field surveys during 2016 and interviewed with rice growers in areas considered unsuitable for rice production (N)3 but suitable for sugarcane plantations (S1–S3) within a 50 km distance to a sugar factory. The samples were selected by stratified random sampling as follows. First, we purposively selected representative provinces in each region. The representative provinces were chosen as they had large numbers of rice farmers, and there was a sugar factory within 50 km of the study area4. Then, we randomly selected farmers who were cultivating paddy in our study area. A total of2335 participants6 were selected as shown in Table 2.

Table 2

Number of participants in each studied province.

Provinces	Number of participants
Northern region	62
Kampaengpetch	32
Nakonsawan	30
Central and western region	115
Kanchanaburi	22
Lopburi	17
Ratchaburi	20
Supanburi	22
Chachoengsao	17
Prachuabkirikhan	17
Northeastern region	56
KhonKean	25
Chaiyapoom	31
total	233

The variable description and descriptive statistics from the sample are shown as Table3. The gender of the farmers are generally male, accounted for 62.66% with an average age of 52 years. Most of the farmers’ educations were lower than high school level, 74.25%. The households had two members on average, working full-time with income from rice 27,709.27 baht/ha, and the average farm size was 12.6 ha.

Table 3

Variable description and descriptive statistics.

Variables	Denoted	Mean/ratio
Sex (1 = female, 0 = male)	female	0.3734
Age (years)	age	51.75
Level of education (1 = lower than high school, 0 = otherwise)	edu	0.7425
Number of household member working full-time (head)	member_full	2
Income from rice cultivation (baht/ha)	income_rice	27,709.27
Farm size (ha)	farm size	12.6
Experience of switching crop during past 5 years (1 = yes, 0 = no)	exp	0.1853
Number of problems encountered growing rice	rice_problems	2.57
Basic knowledge of sugarcane production (score 0 to 6)	sugar_knowledge	3.85
Risk-perception of sugarcane cultivation (1 = agree, 0 = disagree)
High capital investment	high_cap	0.7639
Household cash flow	cash_flow	0.3348
Production risk	production_risk	0.3777
Market access	market_access	0.1073
Price risk	price_risk	0.4163
Perception of important factors influencing adoption alternative cropping (score 0 to 5)
Suitability of soil and weather	suitability	3.60
Sugarcane price	sugarcane_price	3.91
Rice price	rice_price	3.82
Household debt	debt	3.29
Household asset	household_asset	2.93
Government support policy for sugarcane production	gov_policy	3.56
Sugarcane price guarantee	price_guarantee	4.21

Note:1) The basic knowledge of sugarcane production was measured by six questions related to sugarcane production. The Farmers' scores were counted from their correct answers to the questions.

2) The descriptive statistic of dummy variables were expressed in ratio.

The majority of farmers had no experience of switching crop during past 5 years. Considering problems associated with rice cultivation, they had faced around 3 problems on average. The sample farmers had moderate basic knowledge of sugarcane production. The considering risk-perception of sugarcane production, most farmers concerned about high capital investment of sugarcane cultivation, 76.39%. The factors influencing adoption of sugarcane cultivation, the sugarcane price guarantee was the most important in farmers’ perspective.

Results

Table 4 presents the results of the probit regression analysis. Empirical evidence suggested that female farmers were 22% more likely to adopt sugarcane cultivation as compared to male farmers. The female farmers in our survey owned larger land sizes than male farmers; thus, they were more able to do crop diversification as their risk management strategy. Also, for every increase in farm size by 1 ha, there was 0.0039% more likely to increase in conversion to sugarcane farming. The reason for this is that growing sugarcane requires sufficient land to achieve the target return on investment. Rice farmers in the northeast, in particular, were mostly into subsistence production, and only those with fields to spare were likely to embrace sugarcane farming. Our results are consistent with Buntaotook (2014) and Mishra et al. (2018) who found that socioeconomics factors influenced farmers’ decisions to adopt alternative crops.

Table 4

Marginal effect estimates of factors influencing farmers’ decisions to adopt sugarcane production using probit models.

Variables	coefficients	Variables	coefficients
female	0.222∗∗	production_risk	0.0845
	(0.0883)		(0.0766)
age	-0.000314	market_access	-0.211∗∗
	(0.00485)		(0.099)
edu	-0.00607	price_risk	0.0886
	(0.104)		(0.0861)
member_full	-0.0617	suitability	-0.0866∗∗
	(0.0452)		(0.0429)
income_rice	-1.21E-07	sugarcane_price	0.130∗
	(5.1E-07)		(0.0685)
farm size	0.000039∗∗	rice_price	-0.0526
	(0.00002)		(0.0492)
exp	0.148	debt	-0.134∗∗
	(0.109)		(0.058)
rice_problems	0.06	household_asset	0.106∗
	(0.0719)		(0.0571)
sugar_knowledge	0.112∗∗∗	gov_policy	-0.192∗∗∗
	(0.037)		(0.0554)
high_cap	-0.0836	price_guarantee	0.223∗∗∗
	(0.0838)		(0.0599)
cash_flow	-0.167∗∗
	(0.0763)	chi2	70.49

Remark: The values ​in ​parentheses ​represent the standard errors.

Significance at ∗∗∗p < 0.01, ∗∗p < 0.05, ∗p < 0.1.

Furthermore, the farmers’ basic knowledge of sugarcane cultivation significantly affected their decision-making. Farmers who were knowledgeable about sugarcane farming were more inclined to allocate some parts of their land for sugarcane production, with likelihood of 11.2%. In particular, farmers were risk averse; having knowledge provided more confidence to farmers adopting new crops.

Also, considering farmers' risk perception of sugarcane production, concerns over household cash flow and access to the sugarcane market had a significant effect on farmers' willingness to switch to sugarcane production. Farmers who were concerned about household cash flow and access to the sugarcane market were less likely to switch to sugarcane production compared to those who were not bothered in the least, by 16.7% and 21.1%, respectively. Because sugarcane takes a longer time to grow than rice, farmers who have insufficient assets or inadequate savings usually prefer to grow rice, which has a shorter turnaround, so as to earn some money to cover household expenses. Moreover, the farmers' risk perception of accessibility to the sugarcane market, which is far more complex than other crops, also had a significant effect on their decisions. Khansila et al. (2014), Embaye et al. (2018), and Meesungnoen and Taweekul (2019) also found that the distance to market (factory) influenced farmers’ decisions to cultivate sugarcane or other crops.

Farmers' opinions on the suitability of soil and weather conditions for sugarcane production also influenced their decisions to adopt sugarcane farming. The more favorable these opinions were, the lower the chance they would adopt sugarcane farming by 8.66%. From our interviews, farmers were unaware that their lands were suitable for sugarcane farming; thus, adoption of sugarcane farming was less likely based on their perception of the suitability of their lands. Furthermore, the price of sugarcane was another influential factor that increased the likelihood of farmers allocating parts of their land for sugarcane production, by 13%. This is because crop prices directly affect farmers’ income. Likewise, farmers who owned more household assets were more 10.6% likely to grow sugarcane as they had the ability to invest in sugarcane cultivation which requires higher capital than paddy. In contrast, those who had liabilities were 13.4% less likely to allot parts of their land for sugarcane production. Sugarcane production involves high capital investment and takes a longer time compared to paddy. Therefore, farmers with liability tended to have little or no wiggle room to consider alternative crops.

Regarding the policy factors, the sugarcane promotion policy and price guarantee significantly influenced farmers' decisions. Contrary to expectation, farmers who closely monitored the government's sugarcane promotion policy were 19.2% less likely to utilize their land for sugarcane production. This could be due to the policies' lack of concrete measures on ways to support the farmers, especially at the initial phase, as compared to the rice pledging scheme and rice insurance. In addition, farmers who had a positive opinion on the price guarantee were more likely to switch to sugarcane farming, by 22.3%, as they believed that the price guarantee program would resolve sugarcane price volatility. Similarly, Khansila et al. (2014), Bamrungrai et al. (2014), and Meesungnoen and Taweekul (2019) reported that land suitability and government policy had a sufficient impact on farmers' sugarcane cultivation decisions.

Farmers' preferences for governmental incentives to convert unsuitable rice fields to sugarcane plantations are presented in Table 5. Farmers were mostly in favor of sugarcane price guarantee in the first year of production, as indicated by the highest estimated mean utility (0.4647), which is consistent with the result of the probit model. In the absence of price guarantees in the first year, the utility value would decrease by 0.941. This might be because farmers felt more confident to manage their production if they were certain about the revenue they would receive in the future. This is consistent with Buntaotook (2014), who showed that price guarantee supported farmers’ decisions on adopting alternative crops.

Table 5

Estimation of farmers’ support preferences using mixed logit models.

Incentives	(1)	(2)
	Mean	Standard deviation (SD)
subsidy	0.00121∗∗∗	0.000651∗∗∗
	(0.000320)	(0.000235)
2-time_ payment	-0.0749	0.651∗∗∗
	(0.149)	(0.237)
3-time_ payment	-0.562∗∗∗	0.738∗∗
	(0.185)	(0.294)
input_support	-0.0688	0.863∗∗∗
	(0.128)	(0.152)
no_price_guarantee	-0.941∗∗∗	0.740∗∗∗
	(0.133)	(0.179)
self_management	-0.452∗∗∗	0.586∗∗∗
	(0.104)	(0.164)
rice_preferred	-2.595∗∗∗	2.912∗∗∗
	(0.616)	(0.474)
Average utility value of each attribute
Amount of financial aid to quit rice farming	0.000598
Allocation of payment	0.277529
Production cost support	0.033975
First year price guarantee	0.464689
Harvesting and logistic services	0.223209
Observations	2,796	2,796
chi2	155.2	155.2

Remark: The values ​in ​parentheses ​represent the standard errors.

Significant at ∗∗∗p < 0.01, ∗∗p < 0.05, ∗p < 0.1.

In addition, the low-interest credit support and sugarcane harvesting and logistic services significantly influenced farmers' willingness to switch to sugarcane production. Khanna et al. (2017) also showed that farmers would adopt and allocate more land if they were offered a contract that lowers their investment costs. Similarly, Osabuohien et al. (2018) indicated that financial support had positive impact on farmers’ crop decision. Furthermore, production cost support and subsidies were less effective in motivating farmers to adopt sugarcane farming. Regarding the low-interest credit support, the farmers would rather choose a one-time payment than a two or three-time payment. Although a one-time payment involves a higher interest amount, the farmers are better able to manage their expenses as compared to periodic installments where farmers worry they might not have sufficient cash for the production. The multiple payment scheme posed more uncertainties to their expense management strategies, hence giving them less incentive to choose it.

Farmers also showed interest in the harvesting and logistics support. The absence of these support services reduced the utility value by 0.452 compared to self-management. This highlighted the problem of insufficient manpower in harvesting and transportation. Previous studies also stated that high production costs (Bamrungrai et al., 2014) and indebtedness (Meesungnoen and Taweekul, 2019) would prohibit farmers from adopting sugarcane cultivation. Finally, when comparing the benefits of growing rice and sugarcane (rice_preferred), rice farmers were interested in switching to sugarcane production as doing otherwise would decrease the utility by 2.595.

Conclusions and recommendations

Based on our findings on factors influencing the decisions of farmers in this study to switch from rice to sugarcane farming, it was evident that social-economic factors such as the gender of household heads, farm size and basic knowledge of sugarcane production significantly affected the likelihood of switching from rice to sugarcane cultivation. Farmers' concerns over cash flow and ability to access the sugarcane market were critical factors that decreased their likelihood to switch to sugarcane production. Moreover, climatic conditions, soil fertility, loan burden and unclear support policies were barriers to farmers' conversion from rice to sugarcane farming. On the other hand, attractive sugarcane price along with price guarantee policy had a positive influence on the farmers' willingness to cultivate sugarcane. Several studies have demonstrated the importance of crop prices for farmers' crop choice decisions and the direct effect on farmers’ incomes.

When considering the type of support farmers prefer, the results of the choice experiment model showed farmers mostly prioritized sugarcane price guarantees in the first year, followed by the low-interest credit support for production costs, and harvesting and logistic services. For the low-interest credit support, farmers preferred a one-time payment at the beginning of the cropping season over several installments to better manage their expenses. These findings highlight the importance of capital and labor in farmers’ decision-making regarding switching to sugarcane production.

Thus, an effective policy to encourage farmers to switch from rice cultivation to sugarcane production should consider participatory knowledge transfer schemes, especially on sugarcane cultivation techniques, quota systems and pricing mechanisms. In addition, incentives should be provided through sugarcane price guarantee and provision of low-interest credit support, particularly in the early stages of the shift from rice to sugarcane production.

Declarations

Author contribution statement

Atchara Patoomnakul and Ravissa Suchato: Conceived and designed the experiments; Performed the experiments; Analyzed and interpreted the data; Contributed reagents, materials, analysis tools or data; Wrote the paper.

Nuttapon Photchanaprasert: Conceived and designed the experiments; Contributed reagents, materials, analysis tools or data; Wrote the paper.

Funding statement

This work was supported by Thailand Research Fund.

Data availability statement

The authors do not have permission to share data.

Declaration of interests statement

The authors declare no conflict of interest.

Additional information

No additional information is available for this paper.