Drivers and Barriers for Adopting Rice–Fish Farming in the Hau Giang Province of the Mekong Delta

Abstract

This study investigates factors that encourage and discourage farmers to adopt rice–fish (RF) farming in the Hau Giang province in the Mekong Delta, Vietnam. A mixed-method approach was employed to collect data, comprising focus group discussions, face-to-face interviews with rice (R) and rice–fish (RF) farmers, as well as in-depth interviews with agricultural officers and selected R and RF farmers. Economic benefits are the main motivation for adopting RF farming, but suitable agro-ecological conditions, farm size and access to social networks, technical training, and support from extension officers also positively influence the adoption of RF farming. Environmental and health factors have less impact on farmers’ choice of farming. The study also identifies several barriers to the adoption of RF farming, including spatial, operational, and market barriers. To enhance the adoption of RF farming, policymakers should prioritize promoting RF farming in areas with suitable agro-ecological conditions and implement supportive measures, particularly financial assistance and technical training. Additionally, raising farmers’ awareness of both the economic advantages and long-term ecological benefits of RF farming is essential.

1. Introduction

The Mekong Delta, covering an area of 40,923 km², is home to 17.4 million people [1] and is a key region for agri- and aquaculture production in Vietnam. In 2022, it accounted for 55% of the country’s rice yield (90% of exports) and 70% of the aquaculture output [1]. With government policies on food security and the development of dike systems, the area for rice growing increased significantly during the period of 1990–1999, with a transition from one rice crop to two rice crops, and even three rice crops, expanding the areas of intensive rice farming [2]. While intensive farming boosts yields and income, its heavy reliance on agrochemicals can make it environmentally unsustainable [3], leading to soil degradation, water pollution, and reduced biodiversity [4]. It has been followed by declining populations of wild fish and other aquatic organisms [5,6,7,8,9], increased pest invasions and costs [10,11], and even declining yields and profits over time [3].

To address the environmental challenges of intensive rice farming, the Vietnamese government has acknowledged the need for a tranformation towards more sustainable agricultural practices. The government’s Resolution 120 [12] was issued in 2017 to address these problems and provide a roadmap to improve the quality, not the quantity, of rice farming and diversify rice-based farming to optimize each agro-ecological zone in the Delta. One of its goals is to promote sustainable agriculture by reducing the rice cultivation area and providing opportunities for the development of aquaculture and fruit farming [13]. The promotion of converting rice cultivation areas to increase the proportion of rice areas in rotation with vegetables and aquatic products was also outlined in Decision No. 555-QD-BNNTT in 2021 [14]

In such systems, integrated RF farming is practiced, where fish are raised in flooded paddy fields. These systems have been shown to provide a form of ecological intensification that is able to produce more food from the same area of land and water, increasing economic profitability with less environmental impacts [15,16,17]. Integrated RF farming offers many benefits, including improved incomes, diverse nutritious foods, and livelihood opportunities for women and youths. They also support biodiversity, resource-use efficiency, and resilience to climate change [18]. RF farming reduces pesticide use by increasing natural pest predators [6] and lowers nitrogen fertilizer needs, as fish waste provides nutrients. The nutrient uptake by rice plants in turn improves water quality [19].

In the Mekong Delta, RF farming has also been promoted by governmental agricultural extension agencies and organizations like the Farmers’ Association and the Women’s Union. Their approaches have relied on top-down technology transfer and favorable credit provisions but lacked consideration of local contexts, potentially limiting the success of integrated farming systems [16]. In addition, international organizations like the World Bank, IUCN, and WWF have recently provided significant support in facilitating RF farming in the Mekong Delta, where climate change impacts threaten traditional livelihoods and food security. Although RF farming has demonstated numerous benefits and received considerable support from both the Vietnamese government and international development agencies, the adoption of RF farming in the Mekong Delta remains limited. Even though RF farming offers a more sustainable and resilient alternative to rice monocultures [4,6], many R farmers hesitate to adopt RF farming because they are reluctant to abandon their long-standing reliance on pesticides and chemical fertilizers. Field observations indicated that some farmers who were encouraged to adopt RF farming under externally funded projects have even returned to R farming after a few years. Therefore, gaining deeper insights into key factors influencing farmers’ adoption of RF farming, including the barriers and challenges they encounter, is vital for designing effective interventions and policies aimed at promoting the wider uptake of sustainable farming practices in the region.

Feola et al. [20] mentioned that an increased use of more sustainable agricultural practices often needs to be supported by a change in many different factors influencing the farmers. Previous research has identified numerous internal and external factors influencing the adoption of sustainable agricultural practices. Firstly, human capital was found to be one of the significant influential factors. The educational level of farmers was identified as a factor positively influencing the adoption of sustainable farming practices [21,22]. The farming experience of the household head has also been shown to have positive effects on the adoption of new practices [23,24,25], while limited skills in rice and fish farming often provide a challenge that can hinder further expansion of RF farming [3]. Additionally, age tends to negatively affect the adoption of sustainable farming practices [26,27]. Older farmers are normally more conservative in their thinking about farming practices [28] and are usually more risk-averse and have less time to invest in long-term changes than younger farmers [29]. These studies suggest that younger farmers with higher education are more likely to adopt RF farming. Additionally, resource availability is a signicant and indispensable factor that fundamentally determines farmers’ capacities and willingness to adopt a new farming practice. Household labor availability and farm size influence the successful adoption of RF farming [16,30]. Furthermore, better access to extension services and technologies play significant roles in facilitating farmers’ conversion to sustainable farming methods [27]. Social networks such as farming neighbors or peers are valuable sources of information and knowledge that could motivate conventional farmers towards sustainable farming practices [30,31]. Financial capital and subsidies also play an important role in adopting pro-environmental rice farming strategies [16,27,32,33,34,35]. Collectively, these studies show that farmers’ access to resources, including household labor, large farm sizes, extension services, financial capital and subsidies, technology, and social network, influence farmers’ willingness to adopt new farming practices. High levels of awareness regarding environmental and health issues have also been shown to be crucial for converting to sustainable farming practices [28,36,37]. However, Bui and Nguyen [27] argued that in less-developed regions, such awareness does not always influence farmers’ decisions to change their farming practices. In addition, higher prices for eco-friendly products constitute an important incitement for adopting pro-environmental rice farming [16,27,32,33,34,35]. Dang et al. [30] and Bosma et al. [16] also highlighted the importance of appropriate agro-ecological contexts, such as short distance between field and homestead and accessibility to irrigation water, for the successful adoption of RF farming.

Other studies indicated challenges that can hinder the further expansion of RF cultivation, including the high labor demand of RF farming [15] and ineffective water and fish management, including water scarcity, poor irrigation, low water quality, insufficient water depth and fish escapes [15]. Unstable fish prices and erratic floods could be barriers to farmers for adopting RF farming. Market access and the market price of rice and fish play significant roles in facilitating farmers’ conversion to sustainable farming methods [16,27]. Additionally, unpredictable rainfall and extreme hydrological events, such as abnormal tides and elevated flood levels, have posed significant escalating challenges for farm management throughout the Mekong Delta [38].

The novelty of this research lies in the updated socio-ecological context of RF farming in the Mekong Delta and its mixed-methods triangulation, which significantly advances prior studies by addressing these farming practices under current regional stressors. Most studies have focused broadly on factors influencing farmers’ adoption of sustainable agricultural practices and RF farming in other regions, while limited attention has been given to integrated RF farming in the Mekong Delta. Only one notable study, conducted by Bosma et al. (2012) [16], has specifically examined factors influencing farmers’ adoption of RF farming in the Mekong Delta. Given the quickly evolving socio-economic and environmental context in the Mekong Delta, it is timely and necessary to conduct follow-up research to gain a deeper understanding of what motivates farmers to adopt RF farming in the Mekong Delta. By triangulating quantitative metrics of socio-demographics and agro-ecological context with data on local farmers’ perceptions, constraints, and successful adoption mechanisms, this study uncovers factors that drive and hinder the adoption RF farming. The study provides evidence-based and context-specific policy insights for designing sustainable, adaptive agriculture strategies in the Mekong Delta. The study also makes significant contributions to the existing literature by providing policy-relevant data and insights on local gender roles and crucial farm management considerations, which are essential for informing the successful scaling-up of RF farming in the region.

As discussed above, despite substantial institutional and policy support to promote RF farming as a pathway toward sustainable food systems and climate resilience, the uptake of RF farming by local farmers remains limited. This suggests the presence of deeper socio-economic, institutional, natural, or perceptual barriers that hinder farmers from adopting RF farming. This study seeks to identify and analyze the critical factors shaping farmers’ decisions to adopt RF farming in the Mekong Delta. A clearer understanding of these enabling and constraining factors is essential to bridging the gap between policy support and the actual adoption of new farming practices, ensuring that sustainability initiatives translate into tangible agricultural transformation.

2. Materials and Methods

2.1. Study Area

The Hau Giang province is located in the middle of the Mekong Delta (Figure 1). The province has a low terrain, with an average altitude of less than 2 m above sea level. The average annual temperature is 26–27 °C [39]. The province is divided into three characteristic regions: the tidal zone, the intertidal zone, and the flooded areas [40].

The Hau Giang province has four large sources of surface water supply. Hau river is the main water supply, followed by the Cai Lon river, the Cai Tu river, and the Nuoc Trong river. The flood season in Hau Giang starts in August and ends in December. Floods reach their highest levels in October and November, which often coincides with periods of heavy rain. Flood, heavy local rain, and high tide occur at the same time, causing the water level to rise, resulting in flooding over large areas and prolonged flooding periods. The dry season in the Hau Giang province starts in December and ends in April. The lowest water flow is in June and is about 1/20 of the flood season flow [39].

With its favorable natural conditions, agriculture is predominant in the Hau Giang province, encompassing 83.8% of its total area, totaling 135,899 hectares. Rice cultivation is the main crop, occupying the majority of agricultural land with 78,865 hectares (58.0%). Concurrently, aquaculture has experienced substantial growth in recent years, expanding from 7782 hectares in 2019 to 12,242 hectares in 2023 [41]. This increase is due to the province’s proactive shift in recent years from less efficient Winter–Spring rice cultivation to integrated RF farming [42].

RF farming has become an increasingly vital farming strategy across the Hau Giang province. Phung Hiep, Long My, and Vi Thuy are the leading districts in the Hau Giang province in terms of the largest RF farming areas. Our data was collected through field research conducted in the Vi Thuy district (Figure 1), which was seen as a representative study area for examining factors influencing farmers’ adoption of RF farming in the Hau Giang province. This farming has been implemented by local residents for several years and is planned to be expanded to 1380 hectares in this district [42].

2.2. Sample and Data Collection

The data collection included the following steps. First, in-depth interviews with two key informants were conducted, including a provincial agricultural officer and a local extension officer with the aim of gaining an overview of RF farming in the province, the development of RF farming, and the advantages and disadvantages of expanding RF farming in the area (Figure 2). Then, two focus group discussions were carried out with local participants; one group with eight RF farmers (farming both rice and fish) and one group with eight R farmers (only farming rice). Focus group discussions were conducted to obtain a general understanding at the community level of natural conditions affecting the development of RF farming, other factors influencing farmers’ adoption of RF farming, and the difficulties they face in practicing this farming. Additionally, face-to-face interviews were conducted with a total of 61 farmers. The study employed a convenience and snowball sampling approach. The majority of the 61 farmers were recruited through the local agricultural extension officer and interviewed farmers. This approach enabled the research team to effectively reach farmers with relevant experience related to the study topic. However, this method may carry a risk of selection bias. To enhance the external validity of findings and ensure that the results better reflect the diversity of farmers in the study area, a clear selection criterion was developed in advance to ensure the inclusion of farmers who represent diverse experiences, age, education, and incomes. Four of the farmers were selected from the focus group participants to provide an opportunity to explore deeper insights and follow-up on the focus group discussions. The remaining farmers (57) were new, in order to expand and capture the full diversity of viewpoints. The sampling method was designed to collect the data needed to assess factors influencing the adoption and non-adoption of RF farming by R farmers in parts of the Mekong Delta where these could be expected to be developed. A total of 32 farmers that had adopted RF farming and 29 farmers that practiced only rice farming were interviewed. The R farmers were considered potential adopters of RF farming based on geographic proximity to RF farmers. Because of the geographic proximity between farmers, it was assumed that R farmers were aware of RF farming, but they still chose not to practice RF farming. The number of interviewees were determined by the availability of farmers for the survey and the minimum numbers required for robust statistical analysis. A pre-test survey was carried out to make sure that farmers could understand the questions and provide clear anwers to all questions. The questionnaire was tested with two RF farmers and two R farmers before the survey and then revised accordingly. In addition, in-depth interviews with three experienced RF farmers and three experienced R farmers among the interviewed farmers were conducted to gain a deeper insight into and assess the factors motivating and hindering farmers from adopting RF farming and the problems they experienced in practicing such integrated farming In the results, pseudonyms are applied to protect interviewees’ privacy.

The questionnaire for the farmers included key questions about (1) the demographic characteristics of farmers, such as age, education level, household resources (labor and land area), household income sources, and the level of women’s participation in agricultural production; (2) farmers’ access to credit, social relationships, and agricultural extension services; (3) farmers’ awareness of the health, economic, and environmental efficiency of the farming processes using a set of questions with a 5-point Likert scale (strongly disagree = 1, disagree = 2, neutral = 3, agree = 4, completely agree = 5); (4) views on the motivations and necessary conditions for applying RF farming, as well as the difficulties in implementing RF farming and the reasons why R farmers did not apply RF farming.

It should be noted that the data collected in this study were cross-sectional and largely based on farmers’ recall of the preceding year. While this approach provides valuable insights into adoption decisions, it cannot fully capture inter-annual variability or the long-term dynamics of profitability and ecosystem impacts. Consequently, we refrain from making any causal claims regarding temporal changes in farmers’ incomes, adaptation behavior, or environmental outcomes, as these require longitudinal evidence. This limitation is common in adoption studies in the Mekong Delta [11]. Future research could address this constraint by employing a panel or season-tracking design that follows the same households across multiple cropping or flood seasons, thereby allowing an examination of year-to-year fluctuations and long-term trends in both economic performance and ecosystem services.

2.3. Data Analysis

The survey data underwent analysis using descriptive and inferential statistics, utilizing the IBM SPSS version 26 (IBM, Chicago, IL, USA). Cronbach’s alpha analysis was employed to assess the reliability of the Likert scale data reflecting farmers’ perceptions (Appendix A 

Table A1. Cronbach’s alpha analysis results.

Observed Variables	Scale Mean If Item Deleted	Scale Variance If Item Deleted	Corrected Item-Total Correlation	Squared Multiple Correlation	Cronbach’s Alpha If Item Deleted
Access to credit—Cronbach’s Alpha Value: 0.710
Information of credit.	12.23	8.480	0.411	0.187	0.684
The loan procedures are too complicated.	13.31	8.785	0.389	0.154	0.692
To access the loan, farmers need to have collateral.	12.67	7.557	0.519	0.299	0.639
Loaning from joint-stock commercial banks, credit institutions, and individuals have high interest rates.	12.98	7.983	0.480	0.254	0.656
Low credit limit for agricultural production.	12.74	7.863	0.538	0.297	0.633
Social network—Cronbach’s Alpha Value: 0.839
Participating in farmer groups (farmers’ associations, friends, etc.) has made production easier and effective.	10.77	7.246	0.729	0.609	0.774
It is important to discuss farming techniques with other farmers/friends.	10.90	7.123	0.630	0.426	0.816
Farmers can learn and share experiences in agricultural production in the farmer groups.	10.72	7.504	0.668	0.557	0.800
Joining in farmer groups helps me to sell rice quicker and with higher price.	11.28	6.771	0.674	0.481	0.797
Access to extension service support—Cronbach’s Alpha Value: 0.925
Lessons learned from agricultural extension officers are easy to apply in production.	12.00	18.600	0.841	0.776	0.901
Participating in agricultural extension programs helps me increase my current income from agricultural production.	12.33	18.724	0.851	0.787	0.899
Participating in agricultural extension programs helped me change farming practices.	12.34	19.196	0.802	0.717	0.909
Participating in agricultural extension programs helped me increase yields.	12.46	19.486	0.872	0.789	0.896
From the training program of agricultural extension officers.	13.10	21.623	0.668	0.456	0.933
Perception of health—Cronbach’s Alpha Value: 0.749
Present agricultural products are not safe for consumers’ health.	10.70	6.545	0.549	0.353	0.693
Overuse of pesticides and fertilizers in farming cause serious food safety problems.	10.13	6.316	0.756	0.574	0.565
Overuse of pesticides and fertilizers in farming negatively affects the health of rice farmers and their family members.	10.26	6.163	0.596	0.423	0.665
The limited use of chemical fertilizers and pesticides is good for human health.	9.67	10.024	0.343	0.164	0.785
Perception of economic benefit—Cronbach’s Alpha Value: 0.776
Overuse of pesticide and fertilizer reduces economic efficiency.	10.54	4.119	0.511	0.425	0.760
Integrated RF models decrease production costs for farmers.	10.46	3.419	0.751	0.564	0.623
Rice and fish farmed with less agrochemicals can be sold at higher prices.	11.15	4.895	0.382	0.298	0.811
Integrated RF models provide higher profits than rice monoculture.	10.44	3.751	0.701	0.498	0.657
Perception of environment—Cronbach’s Alpha Value: 0.726
Overuse of chemical fertilizer and pesticide negatively affects the biodiversity in rice fields.	11.59	3.513	0.502	0.281	0.676
Climate change (drought, unseasonal rain, and little rain) negatively affects rice farming.	11.54	2.919	0.553	0.312	0.643
Intensive mono-rice crops are the main cause of land deterioration.	11.43	3.049	0.552	0.329	0.643
Adoption of rice–fish farming helps to protect the environment.	11.77	3.413	0.464	0.233	0.694

). Additionally, the choice of statistical test was based on the characteristics of the data. An independent samples t-test was used to compare mean differences between the two groups of farmers applying the RF and R models for quantitative variables that followed a normal distribution. For variables in the form of ordinal data, the non-parametric Mann–Whitney test was applied. Statistical significance was determined at p < 0.05.

The qualitative data from group discussions and in-depth interviews were analyzed using thematic analyses. The qualitative data were sorted according to the themes developed from the quantitative results.

3. Results and Discussions

The present study investigates factors that encourage and discourage farmers from adopting RF farming in the Hau Giang province in the Mekong Delta in Vietnam. Overall, the study identified many factors that influence the decision of farmers to adopt RF farming or not, including economic, environmental, and socio-demographic factors.

3.1. Encouraging Factors

3.1.1. Socio-Demographic Characteristics of R and RF Farmers

The average age of both R and RF farmers exceeded 50 years, with RF farmers being slightly older (

Table 1. Physical characteristics of the surveyed farms and socio-demographic attributes of farmers in the Vi Thuy district of the Hau Giang province.

Variable	Unit	Rice Farming HHs (N = 29)	Rice–Fish Farming HHs (N = 32)	Mean Diff. (t-Test/M-W)
				t/Z	p
Age	Years	50.9 (9.0) a	56.0 (12.0)	1.871	0.066
Experience in rice farming	Years	28.6 (10.4)	31.9 (15.5)	0.995	0.324
Education	Years of formal education	5.7 (3.6)	6.3 (3.7)	0.601	0.550
Household size	Persons	4.6 (1.4)	4.3 (1.5)	−0.731	0.468
Female members in HH	Persons	2.3 (1.0)	2.0 (1.0)	−1.374	0.175
Family labor	Number of working adults	1.9 (0.6)	1.9 (0.8)	−0.321	0.749
Percentage female labor	%	24.0 (19.3)	28.1 (25.2)
Participation of women in farming c	Likert scale b	3.3 (0.4)	3.7 (0.5)	−2.838	0.050 *
Average farm size	Hectares	1.1 (0.6)	1.7 (1.8)	1.715	0.094
Average Income per HH	Millions (VND)	92.4 (47.9)	160.7 (207.4)	1.811	0.079
Distance from house to rice farm	Km	1.1 (1.06)	0.22 (0.17)	−5.794	0.000 ***
Access to credit	Likert scale	3.1 (0.7)	3.3 (0.7)	−0.443	0.658
Social network	Likert scale	3.5 (1.0)	3.8 (0.7)	−0.896	0.371
Access to extension service support	Likert scale	3.1 (1.2)	3.1 (1.0)	−0.298	0.766

^a Average over all households per category. Standard deviations are in parentheses. Significance tests refer to a two-sample t-test of the differences in means: * p = 0.05, and *** p = 0.001. ^b Likert scale used: ^c 1 = very low (supportive involvement), 2 = low (labor participation), 3 = average (participatory voice), 4 = high (joint decision-making), and 5 = very high (decisive maker). (Sources: surveys with 29 R farmers and 32 RF farmers, 2023).

). This result can be attributed to the agricultural sector in the Mekong Delta, which in recent years has been predominantly composed of older workers, while young workers have increasingly shifted from agriculture to other economic sectors, such as industry, commercial services, and non-agricultural occupations [43]. Both RF and R farmer groups had over 20 years of experience in rice cultivation, with RF farmers having slightly more experience (31.9 years) than R farmers (28.6 years) (Table 1).

The respondents’ educational levels were generally below junior middle school (Table 1). Notably, a large proportion of agricultural workers in the Mekong Delta have limited education and lack professional training [43]. The difference in educational level between RF and R farmers was not statistically significant, with the RF farmers averaging 6.3 years of schooling, which was slightly higher than the 5.7 years of the R farmers (Table 1).

The average household size was 4.6 in the R households (R HHs) and 4.3 in the RF households (RF HHs) (Table 1). Both had an equal number of family laborers, averaging 1.9 per household (Table 1). However, the role of female labor in the RF HHs is noteworthy. The research uncovered that women’s participation in RF farming (3.7) was significantly higher than that in R farming (3.3) (p = 0.050) (Table 1). Women in the RF farming group played a more significant role across various stages in the value chain, including feed preparation, fish feeding, marketing, and financial management. In contrast, women’s involvement in rice farming was primarily focused on transplanting, weeding, and selling rice. The study aligns with findings on gender roles in aquaculture in the Northern Uplands of Vietnam, which highlight women’s vital roles in aquaculture activities. The total time women spent on production was generally comparable to that of men [44]. This emphasizes the importance of women’s participation in trainings on, for example, technical, marketing, and financial management.

The average farm size of the RF HHs (1.7 ha) was larger than that of the R HHs (1.1 ha) (Table 1). Although not statistically significant, the difference still indicates that farmers with larger farms are more likely to adopt RF farming, which is in line with other studies [16,27,30]. This indicates that farm size positively influences farmers’ adoption of new farming practices. Households with larger fields are more likely to adopt new farming practices, possibly because they have greater resources and could afford to allocate part of their land for trying new farming methods.

3.1.2. Economic Factors

The results revealed that economic benefits were the primary motivation for adopting RF farming. Almost all the RF farmers (29 of 32 RF farmers) were motivated to apply RF farming because of improved economic profit (Figure 3). The local agricultural officer highlighted the economic efficiency of RF farming, noting that this farmingmethod benefits from rice fields providing rotten straw and insects as food for fish, thereby reducing production costs (interview with local agricultural official, 2023). The RF HHs had a significantly higher gross income than the R HHs, VND 160.7 million and VND 92.4 million, respectively (Table 1). Many other studies confirm that RF farming is more profitable than R farming [3,5,6]. Among the RF HHs, the average income from fish was VND 26.5 million (interview with RF farmers, 2023), indicating that integrating fish in their rice farming activities substantially increases their income, which confirms findings from earlier studies (ibid). RF farmers also agreed at a significantly higher degree than R farmers that integrated RF farming provides higher profit than rice monoculture, because of lower production costs and the higher selling values of rice and fish produced with less pesticides (

Table 2. Perceptions about issues related to health, economy, and the environment among R (29) and RF (32) farmers in the Vi Thuy district of the Hau Giang province.

Variable		Rice Farming HHs (29 Farmers)	Rice–Fish Farming HHs (32 Farmers)	Z	p
Perception of economic benefit
Overuse of pesticide and fertilizer reduces economic efficiency.	Mean SD	3.5 a (0.9)	3.8 (0.8)	−1.645	0.100
Integrated RF models decrease production costs for farmers.	Mean SD	3.5 (0.8)	4.0 (0.9)	−2.299	0.021
Rice and fish farmed with less agrochemicals can be sold at higher prices.	Mean SD	2.9 (0.68)	3.2 (0.8)	−1.849	0.064
Integrated RF farming provides higher profits than rice monoculture.	Mean SD	3.5 (0.8)	4.0 (0.8)	−2.065	0.039
Perception of environment
Overuse of chemical fertilizer and pesticide negatively affects the biodiversity in rice fields.	Mean SD	3.7 (0.8)	4.0 (0.5)	−0.961	0.336
Climate change (drought, unseasonal rain, and little rain) negatively affects rice farming.	Mean SD	4.0 (0.6)	3.8 (1.0)	−0.086	0.932
Intensive rice mono-cropping are the main cause of land deterioration.	Mean SD	4.0 (0.9)	4.0 (0.7)	−0.121	0.904
Adoption of rice–fish farming helps to protect the environment.	Mean SD	3.3 (0.6)	4.0 (0.7)	−3.635	0.000
Pests and diseases are increasing.	Mean SD	3.4 (1.2)	2.7 (1.0)	−2.474	0.013
Perception of health
Present agricultural products are not safe for consumers’ health.	Mean SD	2.9 (1.2)	2.9 (1.4)	−0.030	0.976
Overuse of pesticides and fertilizers in farming causes serious food safety problems.	Mean SD	3.4 (0.98)	3.5 (1.3)	−0.653	0.513
Overuse of pesticides and fertilizers in farming negatively affects the health of rice farmers and their family members.	Mean SD	3.4 (1.2)	3.3 (1.5)	−0.076	0.939
Limited use of chemical fertilizers and pesticides is good for human health.	Mean SD	3.5 (0.5)	4.3 (0.6)	−4.472	0.000

^a Average over all households per category. Standard deviations are in parentheses. Significance tests refer to a two-sample t-test of the difference in means. (Sources: surveys with 29 R farmers and 32 RF farmers, 2023).

).

This finding is consistent with the results from a previous study, which conducted a detailed cost–benefit analysis of R and RF farming in the province [11]. The analysis showed that concurrent RF farming had lower costsfor agrochemicals and higher incomes because of the fish, generating a higher profitability as compared with rice monoculture. The average net income and B/C ratio of RF farming reached VND 105,216 thousand ha/year and 3.54, respectively, compared with VND 34,568 thousand ha/year and 1.73, respectively, for rice monoculture (R). Similar patterns were observed in other studies in the Mekong Delta [6,9], which confirmed that reduced pesticide and fertilizer use, combined with the income from fish farming, can substantially increase overall farm profitability. These findings align with international evidence that rice–fish integration often enhances farm household resilience, provides diversified income, and reduces vulnerability to market or climatic shocks [45,46]. These findings strengthen the results from this study, which only provide a snapshot in time.

A shared experience in the group discussion with RF farmers was that “For many years, rice farming brought us little or no profit, leaving us stuck in a cycle of poor harvests and declining rice value. This motivated us to find alternative farming to increase income from the same land area. After learning that RF farming was more profitable, we adopted this farming and have practiced it for years. Implementing the RF farming has allowed us to maximize profits by raising fish during the flood season, generating more income than leaving the land unused” (group discussion with RF farmers, 2023). In-depth interviews with RF farmers confirmed that additional income from the fish in RF farming encouraged them to adopt this practice. Additionally, the reduced use of fertilizers and pesticides, thanks to the fish providing natural pest control and nutrients through their feces, helped to lower production costs (in-depth interview with Mr. An, a RF farmer, 2023).

The results align with studies by Berg et al. [11] and Bosma et al. [16], which highlighted the benefits of RF, noting that it can increase farm income and improve farm productivity. Moreover, these findings support earlier results by Rigby et al. [32] and Bui and Nguyen [27], which demonstrated that economic benefits were significant determinants in farmers’ decisions to adopt new practices, and that in developing regions, farmers tend to prioritize improving their basic living standards before they can focus on broader issues such as health and environmental protection.

Both RF and R farmers were able to obtain credit for their production costs, thanks to various government support programs aligned with policies promoting sustainable agriculture practices [12,47], and there was little difference in credit access between RF and R farmers (3.3 and 3.1, respectively) (Table 1). A total of 15 out of 31 RF farmers obtained credit from the government [48,49] to invest in RF farming (interview with RF farmers, 2023). Additionally, support to provide fish seed for farmers helped them to start with RF farming [42]. These findings align with previous research indicating that access to financial capital facilitates the adoption of RF farming [16] and organic farming practices [27,35,50], which in turn encourage the transformation towards more sustainable livelihoods [24,33,51,52,53,54]. Therefore, existing credit and investment support policies [12,47,48,49] are crucial for scaling up RF farming, as they enable farmers to adopt and sustain more resilient production systems. In addition, effective extension services could amplify these gains by improving management practices and demonstrating the higher profitabiliy of RF farming compared to rice farming. This is essential to encourage the wider adoption of RF farming among R farmers.

3.1.3. Natural Environmental Factors

Favorable natural conditions were the second-most-important factor for farmers to adopt RF farming. A total of 19 out of 32 RF farmers mentioned favorable natural conditions as a motivation for their decision to integrate fish in their R fields (Figure 3). Many had rice fields located near main rivers or canals, allowing them to utilize water and wild fish resources to support their farming activities. Mr. Binh explained that he tried to optimize the use of existing natural conditions by digging ponds and ditch banks around his rice field to store fish. Each year, after harvesting the rice, he allowed river water to flow into the field, bringing in fish to feed on the available natural food. When the floodwaters receded, he harvested the larger fish for sale, while the smaller fish were kept in separate ponds and ditches for further culture (in-depth interview with a RF farmer, 2023). A short distance between the home and the field was also mentioned as a motivation for adopting RF farming by three RF farmers (Figure 3), since managing fish and protecting farms from theft were seen as a major challenge in RF farming. The RF farmers typically had small homesteads near their farms, with an average distance of just 0.2 km to their fields, compared to 1.1 km for the R farmers (p = 0.000) (Table 1).

This finding is consistent with research by Dang et al. [30] and Bosma et al. [16], who emphasized that suitable agro-ecological conditions such as the proximity between fields and homesteads and access to irrigation water are key factors in the successful adoption of RF farming. Similarly, a previous study showed that the adoption of new technologies and practices depends on the compatibility with the farmers’ local contexts [55]. The study aligns closely with the Vietnamese government’s Resolution No. 120/NQ-CP on the sustainable and climate-resilient development of the Mekong Delta. The resolution emphasizes the principle of ‘adapting to nature’ and promotes agricultural restructuring based on local ecological advantages. By prioritizing the expansion of RF farming in areas with favorable natural conditions, policy implementation adheres to this adaptive, ecosystem-based approach, ensuring both environmental sustainability and improved livelihoods for farming communities in the Delta.

3.1.4. Environment and Health Awareness Factors

Environment awareness was another motivation for adopting RF farming. A local agricultural officer highlighted the ecological sustainability of RF farming: “Raising fish in rice fields in the flood season is regarded as a nature-favored farming that adapt to climate change. This farming practice benefits farmers by utilizing accumulated fish waste as natural fertilizer, increasing mud for rice fields, reducing the need of weeding and soil preparation after each harvest” (interview with local agricultural officer, 2023). There was a statistically significant difference between R and RF farmers’ perception of the benefits of RF farming in protecting the environment and decreasing pests and diseases (Table 2). RF farmers were more aware of the ecological sustainability of RF farming, which motivated 11 of them to adopt RF farming (Figure 3).

The findings also indicated that both R and RF farmers were aware of the health risks associated with the overuse of pesticides and chemical fertilizers in rice farming. The RF farmers, in particular, demonstrated a strong awareness that a reduction in the use of chemical fertilizers and pesticides benefits human health (4.3), which was significantly higher than the R farmers’ perception (3.5) (p = 0.000) (Table 2). The results align with other studies that suggest farmers with a strong understanding of and positive attitudes toward pro-environmental behaviors are more likely to embrace new changes and practices in farming [27,36,37].

Farmers’ growing awareness of environmental protection and health concerns has translated into tangible changes in reducing agrochemicals in their farming practice. One RF farmer shared that in RF farming, after harvesting rice, farmers released fish into the fields to feed on pests, stubble, and natural microorganisms. This practice significantly reduced the use of fertilizers and pesticides and was seen as very helpful for limiting pests and diseases for the next rice crop while enhancing biodiversity and environmental sustainability (in-depth interview with Mr. An, a RF farmer, 2023). Additionally, farmers noticed greater biodiversity in rice fields after implementing RF farming compared to R farming. For example, more crabs, frogs, and insects were present in RF fields, as farmers rarely used toxic pesticides, and only applied approved substances without banned active ingredients (group discussion with RF farmers, 2023). These findings support Berg’s study [3], which highlights that integrated RF farming enhances ecological sustainability by reducing pesticide use and promoting nutrient recycling. They are also consistent with experimental research showing that RF farming reduces agrochemical dependence, sustains rice yields, and improves ecological efficiency across multiple seasons [45]. The study aligns with previous research in suggesting that integrated RF farming is a sustainable alternative to intensive R farming. Its more balanced use of multiple ecosystem services benefits the farmers’ health, the economy, and the environment [5,56].

3.1.5. Social Factors

Both RF and R farmers acknowledged the importance of social networks in relation to their farming activities, but no statistically significant difference was found in the perception of its importance between the RF farmers (3.8) and the R farmers (3.5) (p = 0.371) (Table 1). These networks allowed them to exchange farming techniques, share agricultural experiences, and facilitate product sales at better prices. Social networks, particularly among farming neighbors or peers, serve as valuable sources of information, knowledge, and motivation, encouraging conventional farmers to adopt sustainable practices, which maybe could explain why the perceived importance of social networks was slightly higher for the RF farmers than for R farmers. Local male farmers gathered daily in the early mornings to discuss various aspects of farming, including effective techniques, disease treatments, and the optimal use of pesticides and fertilizers. Through these conversations, they learned about the RF farming practiced by their neighbors and its higher economic efficiency compared to rice monocropping. These interactions provided opportunities to exchange experiences and insights on implementing and adopting RF farming (group discussion with RF farmers, 2023). Neighbors were cited as a key influencing factor, motivating seven farmers to adopt RF farming (Figure 3). Mr. Binh, one of the early RF farmers in the region, shared that some neighboring farmers visited his RF field, inquiring about his farming experience and the economic advantages of RF farming compared to R farming before deciding to adopt this farming practice (in-depth interview with a RF farmer, 2023).

This finding aligns with previous research, which demonstrated that household social networks play a crucial role in the successful adoption of rainfed farming [30]. Additionally, social factors can shape farmers’ decision-making processes, encouraging them to adopt more positive attitudes toward organic farming [31,57]. This, in turn, raises environmental awareness and encourages the adoption of pro-environmental farming practices [37,58,59]. Through this re-enforcing process, farmers gradually adopt new practices by learning from their peers [60].

3.1.6. Support from Agricultural Extension Officers

Both the RF and R farmers received support from extension services for farming techniques and disease treatments and found it to be an important factor, with a rating of 3.1 in both groups (Table 1). With the aim of promoting sustainable agriculture practices that incorporate traditional knowledge, ecological principles, and diversified production [12,47], RF farming has been actively encouraged through farmers receiving support by extension officers in the province. In 2022, the model “Cultivating broadhead catfish (Clarias macrocephalus) in rice fields with a focus on product marketing” was implemented in 15 ha in the Vi Thuy district, Hau Giang province [61]. Farmers who adopted this farming received extensive support from extension officers, including guidance on pond and ditch design, optimizing dike height based on estimated annual flood levels, and other technical aspects. Additionally, the extension officers made frequent visits every 1–2 weeks to monitor and offer further advice on farming activities (group discussion with RF farmers, 2023). Mr. An said that extention officer was highly supportive and played a crucial role in the successful adoption of RF farming (in-depth interview with a RF farmer, 2023). This experience emphasizes that sufficient support from extension services, especially on farming techniques and disease management is essential for motivating farmers to adopt RF farming. These findings align with previous research, which highlights the positive impact of access to extension services and technology for the adoption of sustainable agricultural practices [62].

Besides the aforementioned motivations, the diversity of food produced in RF farming was also mentioned by three RF farmers as a reason for adopting RF farming (Figure 3). The diversity of food not only provided additional income sources but also more nutritional food. Mr. Binh stated that the integrated RF fields support a rich biodiversity, which provides habitats to frogs, eels, and various fish species, including silver carp, snakehead fish, broadhead catfish, three-spot gourami, moonlight gourami, and the bronze featherback (in-depth interview with a RF farmer, 2023). The study aligns with Berg et al. [6,11], showing that integrated RF farming enhances food production and diversity. The integration of fish and rice improves dietary diversity, contributing to food security [8,63,64].

3.2. Barriers to Farmers’ Adoption of RF Farming

3.2.1. Spatial Barrier

Spatial issues, such as long distances from water sources, small land size, and a long distance between farmers’ rice fields and their homes, were cited as the most important barrier hindering most R farmers (89.7%) from adopting RF farming (

Table 3. Reasons why R farmers do not practice RF farming, according to R farmers.

Reasons	Respondents
	Number of Respondents	Percentage of Respondents (%)
Spatial	26	89.7
Operational	10	34.5
Market	5	17.2

Note: The R farmers had the option of selecting none or several of the alternatives. (Source: survey with 29 R farmers, 2023).

). Since many R farmers had rice fields located far from water sources, they had little control over the water resources. Moreover, as their rice fields often were surrounded by other farmers’ rice fields, they were exposed to the heavy use of agrochemicals from neighboring fields, making it difficult for them to implement RF farming (group discussion with R farmers, 2023). Among the RF farmers, 6.3% reported fish diseases due to polluted water from neigbouring fields (

Table 4. Problems with RF farming according to RF farmers.

Problems	Respondents
	Number of Respondents	Percentage of Respondents (%)
Operational	8	25.0
Market	6	18.8
Spatial	2	6.3

Note: The RF farmers had the option to select none or several of the alternatives. (Source: survey with 32 RF farmers, 2023).

). Mr. Binh recomended that the homestead should be located close to the RF fields to reduce the risk of fish theft (in-depth interview with a RF farmer, 2023). This study shows that the average distance from the rice fields to the farmers’ houses was 0.22 km for the RF farmers, while it was 1.1 km for the R farmers (Table 1).

The results are consistent with Ahmed and Turchini’s [17] study, which indicates that farmers lacking these natural advantages face significant challenges in practicing RF farming, particularly in managing water, which remains a critical issue. Our findings also support Connor et al.’s [65] recommendation that farming practices should be easy for the farmers to implement and suited to local environmental conditions. In general, agro-ecological suitability is a basic precondition for the viable scaling of RF farming. Thus, scaling efforts must prioritize areas with natural environmental compatibility—proximity to water and short homestead–field distances.

3.2.2. Operational Barriers

The second reason that hindered 34.5% of the R farmers from practicing RF farming was operational barriers (Table 3). Practicing RF farming was perceived as time- and labor-intensive, particularly as fish get diseases. Additionaly, during the flood season or heavy rains, farmers had to regularly check the dyke and net to prevent fish losses (group discussions with RF farmers, 2023). Fish theft has also become a serious problem in rural areas in recent years. Mr. Loc, who has been practicing RF farming since 2015, stated that RF farming requires significant time and effort to regularly care for and monitor the fish. He also noted that it is challenging for farmers to protect their fish, as poachers use electric tools to catch them (in-depth interview with a RF farmer, 2023).

Similarly, RF farmers mentioned that operational issues, including theft, lack of labor, and unpredictable flood levels, were critical challenges they encountered when practicing RF farming (25% of respondents) (Table 4). The lack of labor was mentioned as a barrier hindering some R famers from practicing RF farming because this type of farming is labor-intensive. This issue is amplified in the Mekong Delta because younger workers increasingly leave the agricultural sector for other industries, commercial services, and non-agricultural occupations [43]. Out-migration is particularly high among those under 35, including skilled workers, resulting in an increasingly aging, low-skilled, and less adaptable workforce remaining [10]. Our findings also support Connor et al.’s [65] recomendation that farming practices should be easy for the farmers to implement and not require additional labor or increased labor costs.

In addition, agricultural production in the Mekong Delta has been severely affected by extreme climate events, including heatwaves, drought, erratic rainfall, and saltwater intrusion. Farmers expressed significant concerns about these changing weather conditions. Although RF farming is generally more resilient to climate change thanRfarming, RF farming remains vulnerable to unstable weather patterns and unpredictable flood levels (survey with R and RF farmers, 2023). For instance, low flood levels and short flooding periods provided insufficient water for fish growth, while erratic rainfall in 2022 raised water levels in ditches, leading to fish escaping and causing significant losses for the RF farmers (in-depth interview with RF farmers, 2023). Thus, unpredictable flooding and rainfall were cited as operational problems by the RF farmers, potentially discouraging the R farmers from adopting RF farming.

The study supports the findings of Truong et al. [38], which highlight that heavy rainfall, abnormal tides, and flood levels, along with unpredictable timing, have made farm management increasingly challenging in the Mekong Delta. Farmers struggle to anticipate water levels and the occurrence of these irregular events.

3.2.3. Market Barriers

The unstable market was identified as a challenge in implementing RF farming, as reported by 18.8% of respondents (Table 4), potentially hindering the R farmers from transitioning to RF farming. A major issue they faced was fluctuating fish prices at harvest, which often coincide with receding floodwater and an abundance of wild fish, driving market prices down. As a result, some farmers abandoned fish stocking, while others were discouraged from adopting RF farming. To mitigate this issue, farmers stored and cultured fishes in drains or ponds near their rice fields for several months, waiting for the prices to rise. However, this solution increased labor and feed costs, ultimately reducing profitability (group discussion with RF farmers, 2023). Mr. An shared his unfortunate experience from last year when the fish crop resulted in a financial loss while storing fish, because of the high costs for fish feed and labor, especically during non-flooding months. During this period, farmers had to purchase trash fish to grind to make feed, further increasing expenses (in-depth interview with a RF farmer, 2023). The local extension officer also noted that the biggest challenge of RF farming was fish marketing. As a result, he was hesitant to recommend farmers to stock fish in their rice fields. Instead, he was more comfortable with advising them to keep and culture wild fish during the flood season, while adding some small fish in the rice fields, with lower investment costs (in-depth interview with a local extension officer, 2023). It should be noted that stocked fish species are typicallly consumed locally and are sold at much lower prices than wild fish. This finding is consistent with the results of Bui and Nguyen [27], who concluded that market access significantly influences the decision to convert to new practices. Similarly, Bosma et al. [16] identified market price as a key factor affecting farmers’ decisions to adopt RF farming. The findings highlight the need for stability to facilitate the transition to RF farming; however, market prices for products and inputs remain challenging to regulate. Therefore, it is important to enhance farmer’s capacities in marketing, tentatively through establishing collective marketing cooperatives or farmer groups, to reduce exposure to market volatility.

Additionally, a lack of capital for high investment and input costs was indicated as a barrier for the R farmers in adopting RF farming (Table 3), which were also cited as problems faced by the RF farmers (Table 4). The high cost of pond and ditch construction, labor, and feed pose significant barriers for low-income farmers in adopting RF farming. This aligns with Bui and Nguyen [27], who identified high production costs as a major constraint in transitioning to organic farming. Similarly, Bosma et al. [16] emphasized that limited capital for field transformation, such as dike and trench construction, was a key obstacle for adopting RF farming in the Mekong Delta. Therefore, financial support, such as access to credits or subsidies, would be crucial in helping farmers overcome initial financial challenges and to encourage them to adopt RF farming.

4. Conclusions

Several studies show that RF farming offers a more sustainable, productive, and profitable alternative to rice monocropping. However, the adoption of RF farming in the Mekong Delta remains limited. This study identifies several factors driving famers’ adoption of RF farming. The study indicates that more experienced farmers are more likely to adopt RF farming. The findings highlight women’s more active roles in RF farming compared to rice monoculture, as they engage in various tasks across the value chain related to fish, suggesting that they should be more involved in technical, marketing, and financial management training and technology transfer to support the increased adoption of RF farming. Farm size positively influences the adoption of RF farming, indicating that farmers with larger farms have greater resources to invest in new farming practices. Additionally, suitable agro-ecological conditions including close distances between fields and homesteads and easy access to water sources were significant factors enabling farmers’ adoption of RF farming. In addition, social networks play a vital role for both the RF and R farmers by facilitating the exchange of techniques, experiences, and market information, thereby encouraging the adoption of sustainable practices. Policymakers should consider leveraging these informal networks to promote the expansion of RF farming. Technical training and support from extension officers are also key factors that motivate farmers to adopt RF farming. Economic benefits are the primary motivation driving farmers’ adoption of RF farming, as it lowers production costs and generates higher profits. Meanwhile, environmental and health concerns play a lesser role in their decision-making. Therefore, raising farmers’ awareness about both the economic advantages and long-term ecological benefits of RF farming is crucial.

However, the study also reveals several barriers to the adoption of RF farming. One significant barrier is the issue of space as, for example, fields surrounded by other fields with the high use of agrochemicals or those located far from water sources make the optimized management of the rice field challenging. Therefore, suitable agro-ecological contexts must be carefully considered when promoting the wider adoption of RF farming. The labor-intensive operation poses another challenge for RF farming, particularly for fish care during extreme weather conditions, unpredictable flood levels, and protecting against theft, which has become an increasingly serious issue. These challenges are intensified for farmers whose homes are distant from their fields, as RF farming demands constant and frequent monitoring. Collective management should be promoted to reduce the risks and burden and enable the scaling-up of RF farming. In addition, financial constraints and unstable markets are significant obstacles for low-income farmers in adopting RF farming. The high costs for pond and ditch construction, labor, and feed, along with fluctuating fish prices at harvest, discourage farmers from transitioning to RF farming. To encourage the adoption of RF farming, financial support, such as access to credit and subsidies, is essential. In addition, enhancing farmers’ capacities in marketing, particularly through collective initiatives like cooperatives or farmer groups, is essential to mitigate the risks posed by market volatility.

In summary, understanding the above factors that influence farmers’ decision-making is crucial for developing appropriate support and policies that foster the adoption of RF farming practices, ultimately promoting sustainable agriculture practices in the Mekong Delta. The main limitation of this research lies in its focus on a single case study area, which may restrict the generalizability of the findings. Future studies covering a wider range of locations across the Mekong Delta are recommended to validate and extend these results at a broader regional scale.