The effectiveness of SRP to sustainable rice production in Mekong Delta Vietnam

The effectiveness of SRP to sustainable rice production in Mekong Delta Vietnam | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The effectiveness of SRP to sustainable rice production in Mekong Delta Vietnam Do Hoang Chung, Manh Nguyen The, Nguyen Quang Tan, Mokbul Morshed Ahmad, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6200782/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 05 Jan, 2026 Read the published version in Discover Sustainability → Version 1 posted 11 You are reading this latest preprint version Abstract Rice is the daily staple food of 3.5 billion people in the world. Vietnam, providing around 16% of the world’s milled rice exports, is the fifth-largest rice producer. Despite the role of rice in Vietnam’s economy, food security, and local livelihoods, rice farmers in Mekong Delta are now amongst the most vulnerable groups affected by the negative impacts of climate change and will be unstainable rice production. Using the Sustainable Rice Platform (SRP), consists of 12 sustainability impact indicators, linked to SDGs, as the best practices case to help rice farmers produce sustainable rice production. This study provides empirical evidence on the benefits of SRP adoption and explore factors affecting SRP uptake. Surveys and FGDs were applied to collect data from 243 rice-farmers in Dong Thap province. T-test and logistic regression were applied to analyse data. Results show that farmers have positively experienced SRP adoption and farmers achieved benefits from SRP adoption such as reduced input cost and increased income. Regression showed that socioeconomic, cognitive, and farm techniques factors strongly affected farmers’ adoption of SRP. Therefore, to scale up farmers’ SRP adoption training and technical assistance, socioeconomic constraints (e.g. water use) are required. Policymakers, planners, and private actors, particularly farmers’ behaviour need to consider the factors that affecting them adopting SRP. Finally, this study highlights the potential of SRP to promote environmentally sustainable rice production and improve farmers' resilience to climate change. Farmers saving water for rice SRP sustainable rice production Mekong Delta Vietnam Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Rice is the daily staple food of 3.5 billion people in the world, accounting for 19% of total global dietary energy. Rice cultivation occurs on 160 million hectares (ha) of land, uses approximately 40% of the world’s irrigated water, and accounts for 10% of global methane emissions (IPCC 14; SRP 2017 ). About 144 million smallholder rice farmers rely on rice production for food and household income, and nearly 95% of Asian rice is traded and consumed rice (SRP 2017 ). Vietnam is the fifth-largest rice producer, providing around 16% of the world’s milled rice exports (Clauss et al., 2018 ). Most rice is exported in Vietnam’s Mekong Delta Region (MDR), including Dong Thap Province. However, the sector is facing many challenges in terms of efficiency and sustainability. Rice production has two sides - it is both affected by climate change and contributes to it because of the emissions of large amounts of CO2 equivalent (CO2 eq.). For every produced kilogram, rice requires 3,000 litres of water (IRRI 2007) and emits nearly four kg of CO2 eq, and to produce 1kg of paddy, 2.69–3.92 kg of CO2 eq. are emitted into the atmosphere (Trang et al. 2019 ). It is estimated that agricultural emissions account for 23% of total Greenhouse Gas (GHG) emissions in Vietnam, about 62.5 MT CO2 eq., The continuously irrigated paddy production is the primary contributor, emitting about 46% of the total emissions of the agricultural sector (MoNRE 2017). Despite the role of the rice industry in Vietnam’s economy, food supply, food security, and local livelihoods; rice producers in MDR are now amongst the most vulnerable groups affected by the negative impact of climate change such as drought, floods, high temperatures, abnormal rainfall, and raising sea levels as well as increased input costs. The typical triple-rice-cropping system is widespread in the MDR and produce more than 25 million Metric Tons (MT) of rice and more than 26 million MT of rice straw are generated every year. The most prevalent disposal method for rice straw is open burning, which has a negative impact on human health locally and contributes to global climate change due to the toxins generated by open and thus incomplete combustion. Similarly, many of the minerals in straw are depleted during the open burning process. Also, incorporating rice straw directly into paddy fields improves nutrient recovery but has increased diffuse methane emissions and disease and pest spread (Phuong et al. 2021 ), and uncontrolled emission of black carbon and other pollutants (Hong Phuong et al. 2022 ). It could reach an approximate amount of 34.6 million tons of CO 2 eq. per year came from the straw burned in the MDR. As a result, need to improve the sustainability of rice production is widely recognized in the Mekong Delta Region (Stuart et al. 2018 ). Farmers in MDR are confronted with many challenges. Climate change has the potential to have a severe impact on water resources, affecting agricultural and food production. Also, global temperature change may result in hotter dry seasons and wetter rainy seasons in some locations, as well as increased uncertainty and the danger of more severe and frequent floods and droughts (Tran et al. 2024 ; Tran et al. 2021 ). For example, the sea level rise, climate change impacts, population increase leading to higher rice demand, and intensification of economic development, influence the changes in cropping patterns and farm management (e.g. multiple-cropping introduction, water management, efficient use of inputs, and use of more resilient rice cultivars). To reduce negative impacts on rice farmers, many sustainable agricultural practices were issued by the Vietnamese government. For instance, replacing long-duration rice varieties with short-duration ones, helping reduce typhoon-related risks and GHG emissions time, increasing areas with mid-season water drainage, and alternating wet and dry irrigation techniques. Moreover, number of programs and policies related to sustainable rice production in MDR (e.g. increasing areas with integrated sustainable crops management practices (the “3 decreases 3 increase (3G3T)” and “1 must-do 5 reductions (1P5G)” techniques, converting inefficient rice growing models to the rice - shrimp model and reducing the rate of field burning of rice straw from 90% to less than 30% for the whole MDR) are wildly applied (NDC 2020). Sustainable Rice Platform a sustainable farm management standard for rice production is necessary to reduce the environmental burden associated with rice cultivation without jeopardizing rice production, commoditization, and global food security. The SRP is the world’s first voluntary sustainability standard for sustainable rice production (Okpiaifo et al. 2020 ; Mungkung et al. 2022 ). It consists of 41 requirements, structured under 8 themes (farm management, pre-planting, water use, nutrient management, integrated pest management, harvest and post-harvest, health and safety and labor rights) and 12 sustainability impact indicators (profitability, labor productivity, grain yield productivity, water use efficiency, nitrogen-use efficiency, phosphorus-use efficiency, biodiversity, greenhouse gas emissions, food safety, worker health and safety, child labor and youth engagement, and women empowerment) aligned with the standard and linked to Sustainable Development Goals. These allow for concrete progress toward the adoption of best practices in rice cultivation and for quantitative measurement of economic, social, and environmental impacts at the farm level (Devkota et al. 2022 ; SRP 2017 ) As a platform, SRP promotes resource efficiency and sustainability in the global rice sector through a multi-level approach from increased farmer adoption of sustainable best practices in rice production to convening a global alliance of public and private sector stakeholders linking research, policy, production, trade, and consumption (Mungkung et al. 2022 ). Some benefits include farmers saving input costs by reduced fertilizers use (100kg/ha) and efficient water drainage (saving 13.9% of water compared to conventional farming), and potential price increase for the premium quality (+ 500 VND/kg). Low GHG emissions in rice production practices such as reduced chemical fertilizer and pesticide application, or GHG emissions reducing by 50–60% can be achieved by meeting eight SRP Standard themes (Connor et al. 2022 ; Wassmann et al. 2000). Indeed, local government programs (e.g. 1M5G and 3R3G in Mekong delta) are in line with the SRP Standard requirements, resulting in reduced agrochemical application and therefore lower production costs (Connor et al. 2022 ). Moreover, SRP has adopted in many other countries such as Nigeria, Thailand, Ghana, Philippine (Okpiaifo et al. 2020 ; Mungkung et al. 2022 ). Although the adoption of SRP has produced positive impacts for rice farmers, it is still a new innovative agricultural technology for rice farmers in Mekong Delta, Vietnam. Therefore, rice value chain actors including rice farmers need to understand its practices and to get their buy-in. Moreover, to scale up SRP adoption in the Mekong Delta region much effort and attempts need to focus on policymakers, stakeholders, and particularly rice-farmers. Previous studies also conducted the factors affecting farmers adopting sustainable agricultural practices (agricultural technology adoption, climate smart agricultural techniques, and sustainable rice production). For example, age, gender, labors could affect farmers adopting sustainable agricultural practices in Vietnam (Dung & Tuan. 2024; Pham et al. 2021 ), limited input availability, lack of control over technologies, insufficient labor, high input cost, inadequate information on developed technologies, limited land access (Sanogo et al. 2023 ), and farm size, credit access, on-farm demonstration, tractor ownership, and family labor had positive influence on rice technology and statistically significant (Bilaliib Udimal et al. 2017 ). However, to the best of author’ knowledge, no specific research on factors affecting rice farmers adopting SRP in Mekong Detla is conducted. Also, previous research focusing on SRP technical or pilot in the rice field have been done (Arouna et al. 2021 ; Nguyen et al. 2022 ) but the understanding of farmers’ perception of SRP, the benefits from SRP adoption to sustainable rice production and conducting the factors affecting farmers’ adoption of SRP in MDR are necessary for scaling up SRP. Furthermore, we also agreed that problems cannot be solved solely by technical innovations, policy reforms or economic aspects. Therefore, social aspects such as farmers’ perception and behaviors, factors affecting them to adopt new technology/interventions need to be investigated. Hence, this research aims to investigate the impacts of SRP on rice-farmers and to identify the factors affecting farmers’ adoption of SRP for sustainable rice production. This research contributes to the literature in several aspects providing empirical evidence of the benefits of SRP adoption for sustainable rice production, farmers' perception of SRP, and the factors that affected farmers' adoption of SRP to scale up this standard in the future. Methodology Study area Dong Thap is one of the low-lying provinces of the Mekong Delta Region in Vietnam, within the confines of 10 0 07'- 10 0 58' North latitude and 105 0 12'- 105 0 56' East longitude, with a total area of 3,384 km 2 and a population of nearly 1.7 million people. The climate is tropical, hot, and humid, greatly influenced by seasonal monsoons. There are 2 main seasons per year: rainy and dry seasons (Table 1 . Rice crop calendar in Mekong Delta Vietnam). The average temperature of the province ranges from 26 0 C to 27 0 C, the average temperature variation is 3 0 C-4 0 C. The average annual rainfall is up to 1500 mm, and the average relative humidity for many years is 82–83% (Giao et al. 2021 ). Dong Thap’s economy is mainly composed of food production, with rice production ranking third in the country. Two districts namely Thap Muoi and Thanh Binh are the main rice area cultivation in Dong Thap and were purposively selected for data collection (Fig. 1 ). Farmers in Dong Thap were coached SPR adoption by many NGOs such as Rikolto, and GIZ. Therefore, local authorities and stakeholders could provide clear and meaningful information for our research (Dong Thap 2020 ; 2021 ). Material and data collection method This study used a mixed technique, including exploratory and explanatory components. First, we looked at the difficulties of sustainable rice production and SRP application in rice cultivation to answer the question, "How did farmers adopt SRP? And What benefits did rice growers experience after implementing SRP?" We examined farmers' socioeconomic variables (e.g., age, educational level, farming experience, attendance at training) to determine the parameters impacting SRP adoption in rice production. Therefore, we used qualitative and quantitative research methods, including questionnaires, key informant interviews, and focus group discussions (FGD). We developed the questionnaire and the checklist for data collection and interviews. A pre-test of the questionnaire was deployed to ensure clarity and avoid misunderstandings during data collection. A field research team consisting of 7 researchers collected data. We trained and guided the research team before going to the field. The time scheduled for the interviews was between 1 and 1.5 hours. Before the interview, we explained the purpose of the research and sought the respondent’s consent to participate. The checklists were used to conduct interviews with key informants. They are key experts in the SRP standard for rice farming. The first group consisted of province and local/district authorities, primarily from Dong Thap Province's Department of Agricultural and Rural Development, as well as district officers in charge of crop security, natural resources, and the environment. The second category included research institutes/universities, international agencies, local leaders, farmer cooperatives, and business players who were interested in marketing SRP rice and rice byproducts. We interviewed 24 key informants, including 12 from the provincial government, 5 from the district government, two communal leaders from My Dong and Tan Binh communes, and 5 private actors. FGDs were conducted with rice farmer groups. First, the chairman of the farmer cooperatives and commune authorities assisted in identifying essential farmers who could provide reliable information based on their knowledge and experience. We held two focus group discussions (FGDs), one in Tan Binh Farmer Cooperative with 7 female and male participants, and another in Thang Loi Farmer Cooperative with 9 mixed participants. The focus group discussions gave us more information about rice farming and farmers' acceptance of the SRP Standard and good agricultural practices in both farmer cooperatives. Then we gathered farmers' perspectives on the SRP Standard as well as good agricultural practices such as climate change impacts, organic fertilization, income, incentives, and bio-stimulants. Table 1 Rice crop calendar in Mekong Delta Vietnam Rice crop season in the Mekong Delta Sowing/Transplanting Harvesting Winter – Spring (W-S) (Dong -Xuan) Nov-Dec Mar-Apr Summer – Autumn (S-A) (He - Thu) Apr-May Jul-Aug Autumn – Winter (A-W) (Thu - Dong) * Jul-Sep Oct-Dec Source: Dong Thap Agricultural Department, 2022. * Denoted rainy season Sample size Data collection was carried out using a "multistage sampling technique". Dong Thap province was chosen because it is carrying out a sustainable rice production project supported by NGOs and the private sector (GIZ, Rikolto, Loc Troi Group, and SunRice), which has been working in Dong Thap since 2017 and is therefore familiar with the actors, rice sector, and its characteristics. Second, two districts, Thanh Binh and Thap Muoi, which have been carrying out the sustainable rice production project since 2017, were chosen as the study area. Then, in each district, we chose one farmer's cooperative for data collection with two groups of farmers (SRP adopters and non-adopters). We assume that all farmers have experience with SRP via knowledge sharing and farmer field school. Thang Loi cooperatives were in Thanh Binh district, and Tan Binh cooperatives were in Thap Muoi. We used random sampling technique for gathering data at the household level in cooperatives based on the lists from local authorities of two farmers’ cooperatives. Based on the formula (1) of Yamane (1968) cited by Manh & Ahmad ( 2021 ) with “a 95% confidence level and ± 5% margin of error,” we pre-selected 260 farmers to be interviewed using the questionnaire survey, composed of 140 members of Tan Binh commune and 120 members of Thang Loi commune in a total of 750 rice household producers in two communes. Finally, we used data from 243 respondents who completed the information to analyze. These consisted of 144 farmers who were members of farmer cooperatives (53 from Tan Binh cooperative and 91 from Thang Loi cooperative). We assumed that they adopted SRP for rice cultivation and 99 farmers who were non-members (68 from Tan Binh and 31 from Thang Loi) because they are not members of cooperatives; therefore, we assume that they did not adopt SRP. Note: “n = sample size”; “N = Total inhabitants of the research area”; “e = Level of precision, set at ± 5% at 95% of confidence”. Data analysis Analyses of qualitative data obtained from key informant interviews, focus group discussions, and the T-test and descriptive statistics analysis method were used to investigate information and data related to the socioeconomic status, societal condition, and farmers' views on rice farmers adopting SRP. The regression model was used to determine the factors that influence farmers' adoption of SRP. Finally, we utilized STATA version 15 to evaluate the data. Independent variables Table 2 shows the explanatory variables in this research Table 2 Descriptive explanatory variables No Variable name Description and measurement Mean SD Socioeconomic factors 1. Age Age of respondent (in year) 53.5 10.6 2. Experience Rice cultivation experience of the farmer (in year) 31.25 9.76 3. Education of farmers The educational level of the farmer (in year) 7.35 3.5 4. Household size Number of members in the farmer’s family (scale) 4.39 1.63 Farming techniques 5. Rice land Land size for rice cultivation of household (ha) 3.01 3.12 6. Duration of land preparation The time needed to prepare the land for the next season (days) 12.02 6.5 7. Pre-germinated blower Farmer used blower machine for seedlings (Binary 1: Yes, 0: Otherwise) 0.56 0.49 8. Pre-germinated drum Farmer used seedling drums for sowing (Binary 1: Yes, 0: Otherwise) 0.45 0.50 9. Flooding time The time of water application for rice (times) 7.99 3.02 10. Following the market price Farmers sold rice following the market price (Binary 1: Yes, 0: Otherwise) 0.93 0.26 11. Premium Farmers received a higher price when they applied SRP for rice production (Binary 1: Yes, 0: Otherwise) 0.46 0.49 12. Cooperative membership Farmer was a member of a cooperative (Binary 1: Yes, 0: Otherwise) 0.59 0.492 13. Incentive Farmer considering incentives as motivation to apply SRP (Binary 1: Yes, 0: Otherwise) 0.48 0.50 Cognitive factors 14. CC perception of rice farmers Farmers noticed climate change was happening (Binary 1: Yes, 0: Otherwise) 0.93 0.249 15. SRP perception Farmer’s perception of SRP (Binary 1: Yes, 0: Otherwise) 0.62 0.487 16. CC impacts Impacts of CC affected farmer’s adoption of SRP (Binary 1: Yes, 0: Otherwise) 0.86 0.35 17. Saving water perception Rice farmer’s perception of saving water technique (Binary 1: Yes, 0: Otherwise) 0.56 0.498 Institutional factors 18. Loan Farmer took a loan from the bank for rice cultivation (Binary 1: Yes, 0: Otherwise) 0.34 0.475 19. SRP training Farmer attended SRP training in the last 2 years (Binary 1: Yes, 0: Otherwise) 0.58 0.495 20. Poor-quality rice seed Poor quality rice seed affected farmer’s adoption of SRP (Binary 1: Yes, 0: Otherwise) 0.07 0.26 Constraint factors 21. Lack of credit Lack of credit affected farmer’s adoption of SRP (Binary 1: Yes, 0: Otherwise) 0.12 0.33 22. Lack of knowledge Lack of knowledge affected farmer’s adoption of SRP (Binary 1: Yes, 0: Otherwise) 0.24 0.43 23. Low price of rice (general rice) Low price of rice affected farmer’s adoption of SRP (Binary 1: Yes, 0: Otherwise) 0.68 0.47 24. Low SRP-rice price * Low SRP rice price affected farmer’s adoption of SRP (Binary 1: Yes, 0: Otherwise) 0.03 0.16 25. Cannot sell SRP-rice * Cannot sell SRP rice affected farmer’s adoption of SRP (Binary 1: Yes, 0: Otherwise) 0.09 0.29 26. Input price Cost of fertilizer, pesticides, seed, fungicides affected farmers’ adoption of SRP (Binary 1: Yes, 0: Otherwise) 0.84 0.37 Note: SRP-rice* denotes rice was produced when farmers applied SRP standard. Empirical logistic model We used the binary logistic model to identify the factors that affected farmers’ choices for adopting the SRP standard for rice cultivation. Socioeconomic factors and barriers influencing the choice of adoption SRP standards were investigated. The binary logistic regression model considers the relationship between a binary dependent variable (Yes = 1 indicated that rice farmers adopted SRP standard for rice cultivation, 0 (no) otherwise) and a set of independent variables (Table 2 ), whether they are binary, categories, or continuous. The logistic model is given by Manh & Ahmad ( 2021 ), and (Manh et al. 2023 ). $$Log\left( {\frac{{Pi}}{{1-Pi}}} \right)=\log (Pi)={\beta _0}+{\beta _i}{X_i}$$ 1 Where Pi is the probability of adoption of SRP for rice cultivation, and Xi is an independent variable. Therefore, the parameter βi gives the coefficients of the dependent variable, and β 0 is a constant. Results and discussion Socioeconomic demographic characteristics Table 2 shows socioeconomic data. We obtained data from 243 farms. 49.8% and 50.2% of respondents were interviewed in Thang Loi and Tan Binh, respectively. The respondents ranged in age from 28 to 85 years old. The farmers' average age was 53.5 years. The share of young farmers under 35 was only 4.9%. Only 4.1% of the farmers were women, whereas 95.9% were men. "Farmers stated that their wives stayed at home to care for the family, while agricultural operations such as rice farming were only for men... If the lady was in the field, they just removed weeds or filled gaps." … FGD with farmers in Tan binh, 2022. In terms of rice cultivation experience, respondents reported an average of 31 years, with the shortest being 8 years and the longest being 55 years. The average household size was 4.39 individuals. The average household size over the age of 18 was approximately 3.11, while the average number of elderly and children in households was around 1.02. The farmers' average education level was 7.35 years, showing that the majority did not complete secondary school. The average cultivated land size is 3.18 hectares, with 3.03 ha used for paddy. The remaining 0.15 hectare was used to cultivate fruit. Regarding the decision-makers on major matters such as buying a rice field in the farmers' family, 56.4% of respondents indicated that male farmers made the decision, 6.2% said that female farmers made the decision, and 37.4% said that there is a discussion within the family before making the decision, indicating that male members continue to hold decision-making power in the households. Therefore, it is important to have interventions to promote gender equality. Farmer’s perception of SRP. Dong Thap province has been applying the SRP since 2017. We asked rice-farmers about their perspective of SRP standard adoption in rice cultivation. The majority of farmers (61.73%) have used SRP, whereas 38.27% are unaware of it. Many international organizations, including Rikolto and GIZ, as well as the commercial sector (Loc Troi and SunRice), support SRP. However, some farmers did not experience the SRP. Unlike the "one must do five reductions" initiative, SPR has yet to be officially validated by the Vietnamese government, suggesting that SRP needs more consideration. Surprisingly, 33 farmers stated that they embraced SRP after learning from their relatives. Therefore, knowledge of SRP may spread from farmer to farmer and their families (Hua & Brown 2024 ). It gives evidence that social capital has a vital role in agricultural extension for rice farmers in terms of SRP. Data from key informant interviews in My Dong commune further confirmed that farmers may interact with one another to share rice and market knowledge, as well as learn how to use SRP through digital tools (Zalo) and farmer organizations. SRP adoption in rice production in Dong Thap province, farmers’ perspectives. Role of SRP in mechanization development. Farmers and policymakers were asked about the role of SRP in mechanization for rice cultivation. We found that in the MDR mechanization has become an indispensable requirement for rice cultivation. Local government has made great investments in developing transport and irrigation infrastructure, pumping stations, mechanization in rice production and supporting the application of scientific-technical advances. Therefore, the rate of rice-harvesting by machine reached 97%, and irrigation systems providing water to paddy fields by electric pumps reached 92%. Indeed, the annual high-quality rice field accounted for 51% of the total production land and mechanization covers almost 100% of the rice field, showing the transition to the rice industry, and gradually creating a new face for rice production when farmers adopt SRP (Dong Thap Agriculture Report 2018). According to the guidelines of SRP, the condition of paddy field is consistent and flat so that machines requirement is needed to prepare rice land. Results show that most farmers rent machines from cooperatives or privates to prepare the rice land. Since 2017, there were 1,654 combine harvesters, 50 transplanters, 975 cargo-spraying machines, 6,931 fertilizer-seeding machines, and 66,407 motorized spraying machines in this study area (Dong Thap Agriculture report 2018). We made good progress in applying new agricultural technologies, particularly in the rice sector. These included the use of harvesting machines in the whole province and the use of smartphone applications in pests and disease control. We will continue doing research to find new rice varieties that are resilient and of high quality, applying new agricultural technology and investing in agricultural infrastructure including improved irrigation systems” said Dr. Le Quoc Dien, the Deputy Director of Dong Thap Agricultural Department Role of SRP in the promotion of sustainable rice production practices In the last 15 years, several programs from the government were introduced as good agricultural practices for sustainable rice production for rice farmers, such as "3 Reduces, 3 Gains,” “1 Must Do, 5 Reductions," and "1 Must Do, 6 Reductions." Similarly, SRP as a sustainable good agricultural practice was also introduced by international non-government organizations (Rikolto, GIZ) and the private sector (Loc Troi, SunRice) in 2015 to promote sustainable rice practices. SRP was introduced by GIZ in Mekong Delta Vietnam; therefore, thousands of farmers participated in and gained benefit from these training courses (Mr. Hung, Thang Loi Cooperative 2022). The benefits include pest control information and knowledge on how to use pesticides and rice technical practices, participation in training of the Integrated Pest Management (Farmers in Thang Loi and Tan Binh Cooperatives 2022). In fact, 70.4% of the farmers, most of whom were members of cooperatives, attended SRP training. Farmers reported that SRP training provides more knowledge of how to produce rice following SRP guidance (e.g., reduced quantity of seed, fertilizer and pesticide application per hectare, and rice straw management). 58% of the farmers attended at least one SRP training. We found a significant difference whereby farmers who were members of the cooperatives had more opportunities to attend SRP training compared to farmers who did not join any cooperative. Furthermore, farmers who attended training achieved higher rice production (Ly et al. 2024 ). SRP in rice varieties and yield. To evaluate the role of SRP in selecting rice varieties, we found that farmers cultivated different rice varieties (e.g., aromatic, high-yielding, resistant to pests and diseases). Farmers were required and encouraged to use certified-quality rice varieties with a short to medium duration (90–115 days) and meet the market demand. Priority is given to the application of extremely short-term rice varieties with moderate salt tolerance, such as OM18, Dai Thom 8, ST24, ST25, and Jasmine 85. In My Dong and Tan Binh communes, the DT8 and OM 18 are the dominant varieties. Moreover, some farmers cultivated sticky rice due to receiving a higher price (around 7,500 VND-8,000 VND/kg) and being easier to sell compared to traditional rice. The average rice yield in the two communes was around 6.67 tons/ha. Farmers reported that they achieved more yield when they adopted SRP compared to non-adopted (FGDs in Tan Binh commune, agricultural officer of Thap Muoi district). Most farmers sold rice to rice-traders or millers, and less to cooperatives. In particular, rice companies only imported around 30%, and of which 60% of SRP-rice for export. Importantly, 90.5% of the farmers indicated that they do not face any problems when they sell SRP-rice. SRP in seed quantity, and land preparation To evaluate SRP's role in seed quantity, farmers were asked to answer the question, "How does SRP contribute to seed quantity use?” We found that farmers reduced the quantity of seed when they adopted SRP. There is no standard for the seed quantity needed per ha. The seed quantity also differs between direct seeding and transplant methods. To save input costs, it was recommended that rice seed should be around 80–120 kg/ha/season for the direct seeding and around 60–70 kg/ha with the transplanting machine (Dong Thap, 2021 ). However, we found that the seed rate farmers used was from 150 to 180 kg/ha/season. Farmers explained that this is because of golden snails and rat damage. Moreover, farmers reported that they reduced by 20–35% when they followed SRP guidelines compared to non-SRP. Interestingly, agricultural officers still confirmed that rice farmers used about 80–120 kg of seed per ha per season. A significant difference exists whereby farmers belonging to cooperatives that adopted SRP tend to use less seed as compared to farmers who are non-adopters of SRP (T-test, F = 11.416, p-value = 0.0001), indicating that farmers who were cooperative members used less quantity of seed. In terms of land preparation, we found that the role of SRP is important. Land preparation for rice is one of the basic practices and is a requirement of SRP adoption. Rice land needs to be carefully prepared. For example, a rice field is consistent and flat for efficient water management. To do so, the farmer cooperatives used machines to prepare paddy land with an average 2.12 times plowing frequency, and households with small sizes (0.5-1 ha) require only one time plowing. SRP in water management Water management is an important indicator of SRP application to ensure effective rice growth in the paddy field. One of the most important indicators of SRP is water management practice such as “alternate wetting and drying” (AWD), which was introduced by IRRI in the Mekong Delta in 2006 to reduce water consumption and GHG emissions. The saving-water technique was used in many provinces in the Mekong Delta. We found that rice farmers, based on their experience, have adjusted the official saving water technique (AWD) to reduce the burden, such as labor cost or time. It is called the “incomplete saving-water technique". This practice does not fully follow the AWD protocol. Farmers in cooperatives reported that they did not use “Pani-pipe” to observe the water level, and farmers did not apply water management practices in the rainy season (Nguyễn Công &Thuận, 2022). Figure 2 shows the incomplete water management practices in two communes. On two weekend days, water was delivered for rice in accordance with the schedule, indicating that the water pumping equipment was turned on Saturday and off on Sunday. Water is pumped into irrigation canals seven times and then drained (dried up) six times. Farmers stated that they can save 30 to 40% of the water required for flooding rice production (conventional rice farming) after applying incomplete saving-water technique (Mr. Bong and Mr. Hung, chairmen of Tan Binh and Thang Loi Cooperatives), our result supports to previous study of (Nguyen et al. 2022 ) SRP in fertilizer application We investigated the role of SRP in fertilizer applications by rice farmers. We discovered that fertilizer is essential in rice production, influencing yield and profitability. Different types of fertilizer were available on the market. However, most farmers employ chemical fertilizer for rice because chemical fertilizer is easy to buy. Most farmers applied single chemical fertilizers such as urea, kali, and phosphate. Moreover, different farmers used different quantities of fertilizer per hectare, depending on how and what type of fertilizer they applied, their knowledge of the different kinds of fertilizers, the stages of rice growth, and their habitual practice. The results indicated that all farmers used a single chemical fertilizer for rice cultivation. Rice farmers bought the fertilizers first and reimbursed them after harvesting. The price of fertilizer is also based on the market; in the years of conducting this study, input costs increased on average around 30% per year, leading to reduced rice farmers’ profit. “One of the most important factors that affected rice farmers in recent years was the price of fertilizers (input cost) that increased recently. We cannot control the fertilizer price because it depends on the international market.” (Mr. D; Mr. C; Dong Thap DARD 2022). We also found that the amount of fertilizer applied by farmers varied, depending on their understanding of what is needed by the plant at different stages of its growth and the condition of the soil. Most farmers who were asked about soil health were unable to answer the questions because they were unaware of the importance and relationship between soil health and rice productivity. Indeed, soil deterioration has been severe across the Delta, particularly in Dong Thap. One of the factors is intensive agricultural practices. It is the outcome of triple-rice farming systems and the extensive use of commercial fertilizers. Some farmers are already transitioning from intensive rice growing techniques to fruit gardens. The farmer indicated, "We used chemical fertilizer when I started to cultivate rice (for more than 40 years), but I did not know about soil health." Mr. B, a farmer from My Dong commune. Figure 3 shows that the average fertilizer application time was 3.33 with a standard deviation of 0.72. 67.5% of the farmers applied fertilizer 3 times, 30% of the farmers 4 times, and 1.2% of the farmers applied fertilizer from 5 to 7 times, and 1.2% of the farmers 2 times. The amount of fertilizer application depended on the soil features, soil characteristics, and rice varieties. Some rice varieties required more fertilizer than others. For example, hybrid rice requires more fertilizers than inbred rice (Huang et al. 2018 ; Jiang et al. 2015 ; Yuan et al. 2017 ). According to the guidance on fertilizer application from the local government, farmers were recommended to apply 200 kg phosphorus, 50–70 kg DAP, 150–160 kg urea, and 70–120 kg kali per ha. Indeed, farmers use fertilizer more than the government recommends. However, farmers indicated that this amount of fertilizer has been reduced much more than 5 years ago due to attending SRP training and other rice production programs (e.g., 1M5R). Furthermore, farmers tend to use compound fertilizer without reducing the urea or potassium. Farmers who have more than 5 hectares of rice applied more fertilizers than the local government’s recommendation. This is because farmers were afraid of potentially major failures, so they preferred to apply more fertilizer when they observed rice looking unhealthy. The same is true in the use of pesticide applications. SRP in promoting bio-fertilizer and bio-stimulant application Biofertilizer and biostimulant applications are another way to provide nutrition for crops, particularly rice. We found that only 17.7% of the farmers used bio-fertilizers (foliar) when rice needs more nutrition, particularly in the flowering, panicle stage, and grain filling stage. Moreover, in rainy season, rice farmers who attended SRP training used Trichoderma to transform rice straw into organic fertilizer in the field because of difficulty collecting rice straw, and it also helps farmers save the labor and cost for rice production in rainy season. Farmers stated that “we did not know about biostimulants, but we used Trichoderma to transform rice straw into organic fertilizer; we learned it from SRP training, and we saved labor costs.” Mr. L, a farmer in Tan Binh cooperative. SRP in pests and diseases management Pests and diseases can damage rice from the vegetable stage to mature time, reducing the rice yield and quality. In fact, farmers spent much money and effort to control pests and diseases, and farmers used pesticides and fungicides more than needed every season. Like fertilizer, farmers can easily buy pesticides, fungicides, and rodenticides in this area. Also, there is a diversity of pesticides on the market. In the last 5 years, the price of pesticides increased, according to agricultural officers. Farmers in Tan Binh and My Dong indicated that pesticide and fungicide prices increased in recent years. It creates hardship for rice farmers. The farmer mentioned that “the price of fertilizer and pesticides increased day by day, but the rice price was the same every year; sometimes the rice price even decreased; we cultivated rice but made no profit...” Mr. C, a farmer in Tan Binh. We found that 96.3% of farmers used pesticides to control pests in the rice field. About 39.1% of the farmers used pesticides and fungicides following the guidance on the label, and 37.9% of the farmers applied pesticides based on their experience. The rest (62.1%) followed the guidelines from SRP training. Basically, farmers know how to use pesticides and fungicides for rice. According to Mr. Hau and Mr. Thanh from the Dong Thap Agricultural Department and Rural Development, most farmers were trained how to use pesticides and fungicides via SRP training. Figure 4 showed the average of pesticides and fungicide applications was around 2.51 times less than 1.3 times compared to last year (2021). Farmers indicated that after attending SRP training, they reduced the frequency of pesticide application. However, 7% of the farmers seemed to apply more than they needed (6–7 times per season), while 3.7% of the farmers did not use pesticides (Fig. 4 ). We also found that most farmers (89.3%) frequently mixed pesticides and fungicides when they applied. SRP in rice straw management Straw management is a crucial indicator in the SRP to help farmers reduce the GHG emissions for rice cultivation. It requires, among other things, that farmers do not allow them to burn the rice straw in the field. In fact, we found that 25.5% of the farmers burned rice straw because it helps to clean the paddy field fast-to remove pests, disease, and weeds for the new planting season. Farmers believed that burning rice straw would reduce fertilizers in the next season. Indeed, burning rice straw has both negative and positive effects. On the positive side, it increases the availability of phosphorus and potassium in the short run, but at the cost of losing soil nutrition such as nitrogen, potash, and sulfur (Ahmed et al. 2015 ). As a result, when scaling up the SRP application in the future, farmers need to be trained in more knowledge of rice straw management. Rice straw management still needs to get attention from both local government and farmers. Determinant factors influence farmers’ adoption of SRP standard Identifying the factors that influence farmers’ adoption of SRP plays an important role in scaling up SRP in the future. We used a logistic model to analyze the data. Cross-sectional data in logistic model analyses frequently had two issues, including multicollinearity among independent variables and heteroscedasticity in the error term. VIF and robust variance estimator were applied to check multicollinearity and heteroscedasticity in this research, respectively. Moreover, the marginal effect (dy/dx) was also calculated for this study. The results showed that the means of VIF for all independent variables in the model are 1.829 (range from 1.091 to 4.699) less than 10, showing that multicollinearity is not an issue in this model (Manh & Ahmad 2021 ). The overall result of the logistic regression was highly significant with the values of Chi-square = 50.575, pseudo-r-square = 0.801, and prob > χ2 = 0.003. The logistic regression is significant and fits the data, indicating that these 26 explanatory variables explained 80.1% of the probability that farmers would adopt SRP for sustainable rice production. The estimated results of the model are shown in Table 3 . Table 3 Factors affecting farmers’ adoption of sustainable rice platform (n = 243) Coef. Robust Std.Err. p-value dy/dx Robust Std.Err. p-value Socioeconomic factors Age 0.568*** 0.165 0.001 0.023*** 0.005 0.000 Experience -0.32** 0.146 0.028 -0.013** 0.005 0.011 Education of farmers 0.749*** 0.186 0.000 0.030*** 0.005 0.000 Household size -0.478 0.378 0.206 -0.019 0.015 0.200 Farming techniques Rice land 0.47 0.393 0.231 0.019 0.016 0.240 Duration land preparation -0.01 0.073 0.889 -0.000 0.003 0.889 Pre-germinated blower -8.886*** 2.307 0.000 -0.353*** 0.072 0.000 Pre-germinated drum -7.598*** 2.082 0.000 -0.302*** 0.064 0.000 Flooding time 0.391*** 0.133 0.003 0.016*** 0.005 0.003 Following market price 5.526** 2.236 0.013 0.219*** 0.069 0.001 Premium -0.007** 0.003 0.017 -0.000** 0.000 0.012 Cooperative membership 15.771*** 3.943 0.000 0.626*** 0.109 0.000 Incentive -5.933*** 1.712 0.001 -0.236*** 0.051 0.000 Cognitive factors CC perception of rice farmers 5.177*** 1.792 0.004 0.206*** 0.058 0.000 SRP perception 3.528** 1.377 0.010 0.140*** 0.044 0.001 CC impacts -4.733*** 1.747 0.007 -0.188*** 0.060 0.002 Saving water perception 5.786*** 1.461 0.000 0.230*** 0.045 0.000 Institutional factors Loan 2.501* 1.332 0.060 0.099* 0.046 0.032 SRP training 3.657*** 1.342 0.006 0.145** 0.052 0.005 Poor-quality rice seed -6.677*** 2.207 0.002 -0.265*** 0.069 0.000 Constraint factors Lack of credit 0.669 1.06 0.528 0.027 0.042 0.527 Lack of knowledge -4.369*** 1.497 0.004 -0.173*** 0.057 0.002 Low price of rice (in general) 2.382* 1.367 0.081 0.095** 0.047 0.046 Low SRP rice price -16.388*** 3.908 0.000 -0.651*** 0.105 0.000 Cannot sell SRP rice -4.631** 2.13 0.030 -0.184** 0.075 0.014 Input price 4.911*** 1.858 0.008 0.195*** 0.053 0.000 Constant -35.388*** 9.909 0.000 Mean dependent var 0.695 SD dependent var 0.461 Pseudo r-squared 0.801 Number of observations 243 Chi-square 50.575 Prob > chi2 0.003 Akaike crit. (AIC) 113.386 Bayesian crit. (BIC) 207.699 *** p < .01, ** p < .05, * p < .1 Source: Author calculation (2022) Socioeconomic factors The adoption of SRP was affected by socioeconomic factors. Age and level of education were positive and statistically significantly affected farmers’ adoption of SRP, indicating that older farmers tend to adopt SRP. The reason could be older farmers attended SRP training and know how to apply SRP. One year of age increases, the probability of SRP adoption increases by 2.3%; other variables are constant. Our results contradict the previous studies of (Tho et al. 2021 ), and (Ly et al. 2024 ). Education plays a vital role for rice farmers, education positively and statistically affected farmers’ adoption of SRP. One-year education increases the probability of SRP adoption by 3%; the result is similar to the previous study (Dung & Tuan 2024 ). Interestingly, experience factors may have positive and negative effects on farmers adopting new technology (Mutyasira et al. 2018 ; Dung & Tuan 2024 ; Mariano et al. 2012 ). In this research, experience negatively affected rice farmers adopting SRP. This is because rice farmers are families with traditional rice production; they may be concerned about the risks of SRP adoption and less inclined to adopt SRP. Furthermore, this result proved that farmers who have rich experience in rice production may not affect the probability of adopting new agricultural technology, providing valid information for policymakers to build agri-policies for scaling up SRP in the future. This result contradicts the previous study of Dung & Tuan ( 2024 ). Farming techniques Adopting SRP for sustainable rice production could be affected by the times of water provided for rice (flooding time). The results show that flooding time strongly affected the process of SRP application. One percent of farmers noticed times of “flooding time” increase; the probability of adoption of SRP increases by 1.6%; other factors are constant. Following the market price factor (farmers sold rice following the market price) was positive and statistically significant for farmers’ adoption of SRP. Most farmers sold rice following the market price; farmers indicated that whatever the price was, they would sell. Farmers update rice market information frequently by smartphone or public media and can choose to sell rice to the buyer who gives them the best price. Farmers also sell as wet paddy and negotiate with buyers normally take place before the harvest. We found that following the market price factor increase of one percent, the probability of adoption of SRP increases by 21.9%. Our results are supported by previous studies (Mariano et al. 2012 ; My et al. 2018 ; Okpiaifo et al. 2020 ) Farmers who were members of the cooperative tend to apply SRP for sustainable rice production. Most of them indicate that they gained more knowledge and benefits after being cooperative members. Statistics show that this factor positively and significantly affected farmers’ adoption of SRP. One percent of farmers joining cooperatives increased; the proportion of farmers adopting SRP increased 62.6%; other factors are constants. It was similar to results in previous studies of Ly et al. ( 2024 ), and Tho et al. ( 2021 ). While premium and incentive factors negatively affected farmers’ adoption of SRP. Indeed, many farmers indicated that “incentive” was one of the factors that encouraged them to apply SRP. But if they could not sell SRP rice, receive low prices, or benefit from premium SRP rice prices, it would negatively affect their decision. Interestingly, farmers who used pre-germinated blowers and pre-generated drums for rice cultivation were less likely to adopt SRP. Regression shows that one percent of farmers used pre-germinated blowers increased; the probability of SRP adoption decreased by 35.3%; other variables are constant. It seems that farmers who used pre-germinated blowers had more burden to invest in their paddy farm; therefore, they tended to not adopt SRP. Our result contradicts the previous study of Mashi et al. ( 2022 ), and Piñeiro et al. ( 2020 ), indicating that incentives insignificantly affected farmers to adopt sustainable agricultural technologies. Moreover, this research did not find the significant effects of rice land duration and land preparation on farmers adoption of SRP. Cognitive factors Cognitive factors play an important role in scaling up SRP for farmers. The CC perception of rice farmers factors positively and significantly affected farmers adopting SRP. One percent of farmers noticed climate change is happening; the probability of SRP adoption increasing is 20.6%, with other factors remaining unchanged. Our results were also found in previous studies by Ahmed et al. ( 2022 ), and Gisi & Begho (2023). Moreover, the SRP perception factor has a positive and significant relationship with SRP adoption; farmers who notice the SRP benefits are more likely to adopt SRP. One percent of SRP perception increases; the probability of adoption of SRP increases by 14.0%; other factors do not change. Saving water, such as the AWD technique, is a vital factor for rice cultivation. This factor is a key component of SRP guidance. Therefore, farmers who noticed and applied the saving water technique tended to increase the proportion of SRP adoption by 23.0%. However, farmers who noticed climate change impacts on their paddy fields tend to reduce the adoption of SRP, indicating that farmers fear the risks when applying SRP, even though farmers noticed impacts of CC. One percent of farmers noticed the impacts of climate change on the paddy increases; the probability of adoption of SRP decreased 18.8%, with other factors being constant. Our result is not in line with the previous study; they found that when farmers noticed the impact of climate change, they tended to adopt agricultural technologies. Institutional factors Access to finance is critical in implementing agricultural innovations (Balana & Oyeyemi 2022 ; Ruzzante et al. 2021 ). Loans can assist farmers overcome financial challenges. The loan-taking component had a positive and statistically significant effect on rice farmers' adoption of SRP in the Mekong Delta; 1% of farmers took bank loans, increasing the chance of SRP adoption by 9.9%. Our findings were consistent with recent research by Sanogo et al. ( 2023 ), and Swami & Parthasarathy ( 2024 ), which indicated that loans could improve the fraction of agricultural technology uses in India and Mali. Moreover, farmers who attended SRP training are likely to apply SRP; if one percent of farmers attended SRP training, the probability of SRP adoption increases by 14.5%. This is because farmers gained more SRP knowledge and improved their knowledge of how to apply SRP from the training. Our result was supported by many previous studies of Joblaew et al. (2019), Ly et al. ( 2024 ), Mariano et al. ( 2012 ), Swami & Parthasarathy ( 2024 ), and Tho et al. ( 2021 ). Other factors that play an important role are seed quality. Absolutely, poor seed quality influenced farmers’ adoption of sustainable rice practices. Like other rice programs (e.g., 1M5R), applying SRP requires farmers to accurately follow the SRP principal guidelines, meaning that farmers must use quality rice seed (certified seed) to cultivate. Therefore, poor rice seed farmers will face many risks. Regression shows that poor quality seed factors negatively affected farmers’ adoption of SRP. If one percent of farmers used poor seed quality, the probability of SRP adoption reduces to 26.5%, with another factor constant. Constraint factors Although there are many benefits from SRP adoption for sustainable rice production, the proportion of SRP adoption in the Mekong Delta is still less. The farmers were asked to indicate the constraints factors or barriers. We found that a number of barriers (lack of knowledge, low price of rice, low SRP-rice price, farmers cannot sell SRP- rice, input cost, and no access to credit) affected rice farmers to adopt SRP. This may lead to restricted scaling up SRP standard adoption area rice in the future. Therefore, more attempts in terms of training, providing market information, and providing credit access are needed for rice farmers. Regression showed that lack of knowledge, low price of rice, low SRP-rice price, cannot sell SRP-rice negatively significantly affected farmers’ adoption of SRP, indicating that when rice farmers face these factors, the probability of adoption of SRP decreases. Furthermore, input costs (particularly fertilizer, pesticides, and fungicides) played an important role in rice production. Surprisingly, we found that input costs positively affected farmers’ adoption of SRP, indicating that as input costs increase by 1%, the probability of farmer's adoption of SRP increases by 19.5%. The reason is that when farmers spend more money on their farms, they will sell rice at a high price to get more profits to compensate for the investment cost. SRP rice can help them. Our result is in line with the results of previous studies by Alam et al. ( 2024 ), and Tran et al. ( 2020 ). Farmers tended to apply the new technologies if they encountered challenges related to the cost of inputs. Conclusion SRP can help farmers grow rice in a more sustainable manner. However, scaling up SRP presents numerous obstacles. This study examines the benefits of adopting SRP for sustainable rice production using data from 243 rice farmers in Dong Thap province. Rice farmers gained numerous benefits by implementing SRP to cultivate rice. Farmers, for example, reduced the amount of seed per hectare, cut pesticide use, and improved rice straw management. Furthermore, rice farmers decreased both the number and timing of pesticide and herbicide applications while increasing rice yields. However, it also compels rice producers to follow many of the SRP guidelines. Furthermore, farmers that joined the cooperative in Dongthap province fared well in SRP rice production, however some rice farmers did not follow the requirements strictly. For example, farmers continue to burn rice straw in open fields. This study shows that the adoption of SRP was influenced by a variety of factors, including socioeconomic status, cognitive abilities, farming techniques, institutional characteristics, and impediments. The findings of this study help to fill knowledge gaps about the social elements of rice farmers on SRP, which contributes to SDGs 1, 2, and 13. The data demonstrated that SRP should be advocated for rice producers in the Mekong Delta region to pursue sustainable rice production. To scale up SRP adoption among rice farmers, policymakers, planners, and stakeholders should consider the factors outlined in our research. Finally, there are some limitations to this research, such as the fact that we were unable to sample the entire Mekong Delta; nonetheless, this study might be replicated for other provinces in the region. Second, this study did not look at the economic differences between SRP adopters and non-adopters. Finally, this study did not examine agricultural policies that could facilitate the implementation of SRP. Declarations No support funding for this study Clinical trial number : Not applicable Declaration of Conflicting Interests: The authors declared no conflicts of interest with respect to the research, authorship, and/or publication of this article. Consent to publish : The author gives the consent to publish Consent to participate : Informed consent was obtained from all subjects involved in the study Ethics approval : This research was ethically approved by protocol of local institution (ICRA Vietnam) Data Available Declaration: The raw data supporting this study’s findings are available upon reasonable request from the author. Author contributions: All authors equally contribute in this study. References Ahmed T, Ahmad B, Ahmad W. Why do farmers burn rice residue? Examining farmers’ choices in Punjab, Pakistan. 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The SRP Standard for Sustainable Rice Cultivation. Bangkok: Sustainable Rice Platform; 2017. Wassmann, Lu Y, Neue R, H.-U., Huang C. Dynamics of Dissolved Organic Carbon and Methane Emissions in a Flooded Rice Soil. Soil Sci Soc Am J. 2000;64(6):2011–7. https://doi.org/10.2136/sssaj2000.6462011x . Ministry of Natural Resources and Environment (MONRE). (2017). Report on National GHG Inventory for 2016 of Vietnam. In the Ministry of Natural Resources and Environment. https://unfccc.int/sites/default/files/resource/Viet%20Nam_NIR2016.pdf IPCC. 2014. Climate change 2014: impacts, adaptation, and vulnerability. In: Part A: Global and Sectoral Aspects Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press Cambridge, United Kingdom and New York, NY, USA. p. 2014. Additional Declarations No competing interests reported. Supplementary Files Highlights.docx Cite Share Download PDF Status: Published Journal Publication published 05 Jan, 2026 Read the published version in Discover Sustainability → Version 1 posted Editorial decision: Revision requested 19 Jul, 2025 Reviews received at journal 15 Jun, 2025 Reviewers agreed at journal 02 Jun, 2025 Reviews received at journal 21 May, 2025 Reviews received at journal 20 May, 2025 Reviewers agreed at journal 07 May, 2025 Reviewers agreed at journal 06 May, 2025 Reviewers invited by journal 05 May, 2025 Editor assigned by journal 16 Apr, 2025 Submission checks completed at journal 13 Apr, 2025 First submitted to journal 13 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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The","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAv0lEQVRIiWNgGAWjYHACNiBmZuAHMRMKSNEi2QDSYkCKFoMDIDYxWnTbzx57XLnHOs/4/OrEDw8MGOT5xQ7g12J2Ji/d8Myz9GKzG283SwAdZjhzdgIBLQdyzCQbDhxO3Hbj7AaQlgSD24S0nH8D0bJ5xtnNP4jTcgNqywb+3m1E2nIDbEt6scQN3m0WCQYSRPjlPNgW6zz+/rObb/6osJHnlyagBQYSGCTAKiWIUw7Rwn+AeNWjYBSMglEwsgAA+mlH05TPigYAAAAASUVORK5CYII=","orcid":"","institution":"ICRAF Vietnam","correspondingAuthor":true,"prefix":"","firstName":"Manh","middleName":"Nguyen","lastName":"The","suffix":""},{"id":453228591,"identity":"a64c068d-b982-4df5-b31e-cc4cdf2641e3","order_by":2,"name":"Nguyen Quang Tan","email":"","orcid":"","institution":"ICRAF Vietnam","correspondingAuthor":false,"prefix":"","firstName":"Nguyen","middleName":"Quang","lastName":"Tan","suffix":""},{"id":453228592,"identity":"31c4ce49-53c0-4fc8-b0d0-0c69d62f9a4c","order_by":3,"name":"Mokbul Morshed Ahmad","email":"","orcid":"","institution":"Asian Institute of Technology","correspondingAuthor":false,"prefix":"","firstName":"Mokbul","middleName":"Morshed","lastName":"Ahmad","suffix":""},{"id":453228593,"identity":"d8143f2e-f41f-48a7-8dc6-cbd56f33c79e","order_by":4,"name":"Indrajit Pal","email":"","orcid":"","institution":"Asian Institute of Technology","correspondingAuthor":false,"prefix":"","firstName":"Indrajit","middleName":"","lastName":"Pal","suffix":""},{"id":453228594,"identity":"7d6aff7b-da87-4db7-ab59-4a9bd7aa819c","order_by":5,"name":"Nguyen Tien Da","email":"","orcid":"","institution":"ICRAF Vietnam","correspondingAuthor":false,"prefix":"","firstName":"Nguyen","middleName":"Tien","lastName":"Da","suffix":""}],"badges":[],"createdAt":"2025-03-11 07:08:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6200782/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6200782/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s43621-025-01986-0","type":"published","date":"2026-01-05T15:57:57+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":82357232,"identity":"6104836a-5bce-45c5-a0bc-3058c43c7735","added_by":"auto","created_at":"2025-05-09 11:21:39","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":161168,"visible":true,"origin":"","legend":"\u003cp\u003eMap of the study area (Thanh binh, and Thap Muoi districts)\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6200782/v1/3d8884f156164fc778f9ef06.png"},{"id":82355262,"identity":"5a4d55ec-3b3c-4556-afab-cf3451e47692","added_by":"auto","created_at":"2025-05-09 11:13:39","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":60341,"visible":true,"origin":"","legend":"\u003cp\u003eIncomplete water management practice (saving-water practice)\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6200782/v1/4419e960ceffc505ebc60f43.png"},{"id":82355258,"identity":"568e13c9-7032-429f-9203-6f04a7c5a64e","added_by":"auto","created_at":"2025-05-09 11:13:39","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":11530,"visible":true,"origin":"","legend":"\u003cp\u003eFrequency of farmers applying fertilizer per season.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6200782/v1/b6118c927f79cfb7e7380a80.jpg"},{"id":82355264,"identity":"6dfc1837-01e0-4f8c-a34c-bb6796a6b185","added_by":"auto","created_at":"2025-05-09 11:13:39","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":13714,"visible":true,"origin":"","legend":"\u003cp\u003eThe frequency of farmers applying pesticides per season.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6200782/v1/efe7d3659faef908f647fbdc.jpg"},{"id":100069249,"identity":"3c7a7faa-c5b2-498f-920c-8d33bc02b9de","added_by":"auto","created_at":"2026-01-12 16:11:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1681692,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6200782/v1/dbe90f19-79a4-4e79-8858-3b091981c3dc.pdf"},{"id":82355261,"identity":"1169eabf-9fe4-4f8a-a92b-179f470b2b81","added_by":"auto","created_at":"2025-05-09 11:13:39","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":15161,"visible":true,"origin":"","legend":"","description":"","filename":"Highlights.docx","url":"https://assets-eu.researchsquare.com/files/rs-6200782/v1/122e50b8e1da9a5cb4a82350.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The effectiveness of SRP to sustainable rice production in Mekong Delta Vietnam","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRice is the daily staple food of 3.5\u0026nbsp;billion people in the world, accounting for 19% of total global dietary energy. Rice cultivation occurs on 160\u0026nbsp;million hectares (ha) of land, uses approximately 40% of the world\u0026rsquo;s irrigated water, and accounts for 10% of global methane emissions (IPCC 14; SRP \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). About 144\u0026nbsp;million smallholder rice farmers rely on rice production for food and household income, and nearly 95% of Asian rice is traded and consumed rice (SRP \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Vietnam is the fifth-largest rice producer, providing around 16% of the world\u0026rsquo;s milled rice exports (Clauss et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Most rice is exported in Vietnam\u0026rsquo;s Mekong Delta Region (MDR), including Dong Thap Province. However, the sector is facing many challenges in terms of efficiency and sustainability. Rice production has two sides - it is both affected by climate change and contributes to it because of the emissions of large amounts of CO2 equivalent (CO2 eq.). For every produced kilogram, rice requires 3,000 litres of water (IRRI 2007) and emits nearly four kg of CO2 eq, and to produce 1kg of paddy, 2.69\u0026ndash;3.92 kg of CO2 eq.\u0026nbsp;are emitted into the atmosphere (Trang et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). It is estimated that agricultural emissions account for 23% of total Greenhouse Gas (GHG) emissions in Vietnam, about 62.5 MT CO2 eq., The continuously irrigated paddy production is the primary contributor, emitting about 46% of the total emissions of the agricultural sector (MoNRE 2017).\u003c/p\u003e \u003cp\u003eDespite the role of the rice industry in Vietnam\u0026rsquo;s economy, food supply, food security, and local livelihoods; rice producers in MDR are now amongst the most vulnerable groups affected by the negative impact of climate change such as drought, floods, high temperatures, abnormal rainfall, and raising sea levels as well as increased input costs. The typical triple-rice-cropping system is widespread in the MDR and produce more than 25\u0026nbsp;million Metric Tons (MT) of rice and more than 26\u0026nbsp;million MT of rice straw are generated every year. The most prevalent disposal method for rice straw is open burning, which has a negative impact on human health locally and contributes to global climate change due to the toxins generated by open and thus incomplete combustion. Similarly, many of the minerals in straw are depleted during the open burning process. Also, incorporating rice straw directly into paddy fields improves nutrient recovery but has increased diffuse methane emissions and disease and pest spread (Phuong et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and uncontrolled emission of black carbon and other pollutants (Hong Phuong et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). It could reach an approximate amount of 34.6\u0026nbsp;million tons of CO\u003csub\u003e2\u003c/sub\u003e eq.\u0026nbsp;per year came from the straw burned in the MDR. As a result, need to improve the sustainability of rice production is widely recognized in the Mekong Delta Region (Stuart et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFarmers in MDR are confronted with many challenges. Climate change has the potential to have a severe impact on water resources, affecting agricultural and food production. Also, global temperature change may result in hotter dry seasons and wetter rainy seasons in some locations, as well as increased uncertainty and the danger of more severe and frequent floods and droughts (Tran et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Tran et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). For example, the sea level rise, climate change impacts, population increase leading to higher rice demand, and intensification of economic development, influence the changes in cropping patterns and farm management (e.g. multiple-cropping introduction, water management, efficient use of inputs, and use of more resilient rice cultivars). To reduce negative impacts on rice farmers, many sustainable agricultural practices were issued by the Vietnamese government. For instance, replacing long-duration rice varieties with short-duration ones, helping reduce typhoon-related risks and GHG emissions time, increasing areas with mid-season water drainage, and alternating wet and dry irrigation techniques. Moreover, number of programs and policies related to sustainable rice production in MDR (e.g. increasing areas with integrated sustainable crops management practices (the \u0026ldquo;3 decreases 3 increase (3G3T)\u0026rdquo; and \u0026ldquo;1 must-do 5 reductions (1P5G)\u0026rdquo; techniques, converting inefficient rice growing models to the rice - shrimp model and reducing the rate of field burning of rice straw from 90% to less than 30% for the whole MDR) are wildly applied (NDC 2020).\u003c/p\u003e \u003cp\u003eSustainable Rice Platform a sustainable farm management standard for rice production is necessary to reduce the environmental burden associated with rice cultivation without jeopardizing rice production, commoditization, and global food security. The SRP is the world\u0026rsquo;s first voluntary sustainability standard for sustainable rice production (Okpiaifo et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Mungkung et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). It consists of 41 requirements, structured under 8 themes (farm management, pre-planting, water use, nutrient management, integrated pest management, harvest and post-harvest, health and safety and labor rights) and 12 sustainability impact indicators (profitability, labor productivity, grain yield productivity, water use efficiency, nitrogen-use efficiency, phosphorus-use efficiency, biodiversity, greenhouse gas emissions, food safety, worker health and safety, child labor and youth engagement, and women empowerment) aligned with the standard and linked to Sustainable Development Goals. These allow for concrete progress toward the adoption of best practices in rice cultivation and for quantitative measurement of economic, social, and environmental impacts at the farm level (Devkota et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; SRP \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2017\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eAs a platform, SRP promotes resource efficiency and sustainability in the global rice sector through a multi-level approach from increased farmer adoption of sustainable best practices in rice production to convening a global alliance of public and private sector stakeholders linking research, policy, production, trade, and consumption (Mungkung et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Some benefits include farmers saving input costs by reduced fertilizers use (100kg/ha) and efficient water drainage (saving 13.9% of water compared to conventional farming), and potential price increase for the premium quality (+\u0026thinsp;500 VND/kg). Low GHG emissions in rice production practices such as reduced chemical fertilizer and pesticide application, or GHG emissions reducing by 50\u0026ndash;60% can be achieved by meeting eight SRP Standard themes (Connor et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Wassmann et al. 2000). Indeed, local government programs (e.g. 1M5G and 3R3G in Mekong delta) are in line with the SRP Standard requirements, resulting in reduced agrochemical application and therefore lower production costs (Connor et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMoreover, SRP has adopted in many other countries such as Nigeria, Thailand, Ghana, Philippine (Okpiaifo et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Mungkung et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Although the adoption of SRP has produced positive impacts for rice farmers, it is still a new innovative agricultural technology for rice farmers in Mekong Delta, Vietnam. Therefore, rice value chain actors including rice farmers need to understand its practices and to get their buy-in. Moreover, to scale up SRP adoption in the Mekong Delta region much effort and attempts need to focus on policymakers, stakeholders, and particularly rice-farmers.\u003c/p\u003e \u003cp\u003ePrevious studies also conducted the factors affecting farmers adopting sustainable agricultural practices (agricultural technology adoption, climate smart agricultural techniques, and sustainable rice production). For example, age, gender, labors could affect farmers adopting sustainable agricultural practices in Vietnam (Dung \u0026amp; Tuan. 2024; Pham et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), limited input availability, lack of control over technologies, insufficient labor, high input cost, inadequate information on developed technologies, limited land access (Sanogo et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and farm size, credit access, on-farm demonstration, tractor ownership, and family labor had positive influence on rice technology and statistically significant (Bilaliib Udimal et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). However, to the best of author\u0026rsquo; knowledge, no specific research on factors affecting rice farmers adopting SRP in Mekong Detla is conducted. Also, previous research focusing on SRP technical or pilot in the rice field have been done (Arouna et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Nguyen et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) but the understanding of farmers\u0026rsquo; perception of SRP, the benefits from SRP adoption to sustainable rice production and conducting the factors affecting farmers\u0026rsquo; adoption of SRP in MDR are necessary for scaling up SRP. Furthermore, we also agreed that problems cannot be solved solely by technical innovations, policy reforms or economic aspects. Therefore, social aspects such as farmers\u0026rsquo; perception and behaviors, factors affecting them to adopt new technology/interventions need to be investigated. Hence, this research aims to investigate the impacts of SRP on rice-farmers and to identify the factors affecting farmers\u0026rsquo; adoption of SRP for sustainable rice production. This research contributes to the literature in several aspects providing empirical evidence of the benefits of SRP adoption for sustainable rice production, farmers' perception of SRP, and the factors that affected farmers' adoption of SRP to scale up this standard in the future.\u003c/p\u003e"},{"header":"Methodology","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy area\u003c/h2\u003e \u003cp\u003eDong Thap is one of the low-lying provinces of the Mekong Delta Region in Vietnam, within the confines of 10\u003csup\u003e0\u003c/sup\u003e 07'- 10\u003csup\u003e0\u003c/sup\u003e 58' North latitude and 105\u003csup\u003e0\u003c/sup\u003e 12'- 105\u003csup\u003e0\u003c/sup\u003e 56' East longitude, with a total area of 3,384 km\u003csup\u003e2\u003c/sup\u003e and a population of nearly 1.7\u0026nbsp;million people. The climate is tropical, hot, and humid, greatly influenced by seasonal monsoons. There are 2 main seasons per year: rainy and dry seasons (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Rice crop calendar in Mekong Delta Vietnam). The average temperature of the province ranges from 26\u003csup\u003e0\u003c/sup\u003eC to 27\u003csup\u003e0\u003c/sup\u003eC, the average temperature variation is 3\u003csup\u003e0\u003c/sup\u003eC-4\u003csup\u003e0\u003c/sup\u003eC. The average annual rainfall is up to 1500 mm, and the average relative humidity for many years is 82\u0026ndash;83% (Giao et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Dong Thap\u0026rsquo;s economy is mainly composed of food production, with rice production ranking third in the country. Two districts namely Thap Muoi and Thanh Binh are the main rice area cultivation in Dong Thap and were purposively selected for data collection (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Farmers in Dong Thap were coached SPR adoption by many NGOs such as Rikolto, and GIZ. Therefore, local authorities and stakeholders could provide clear and meaningful information for our research (Dong Thap \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMaterial and data collection method\u003c/h3\u003e\n\u003cp\u003eThis study used a mixed technique, including exploratory and explanatory components. First, we looked at the difficulties of sustainable rice production and SRP application in rice cultivation to answer the question, \"How did farmers adopt SRP? And What benefits did rice growers experience after implementing SRP?\" We examined farmers' socioeconomic variables (e.g., age, educational level, farming experience, attendance at training) to determine the parameters impacting SRP adoption in rice production. Therefore, we used qualitative and quantitative research methods, including questionnaires, key informant interviews, and focus group discussions (FGD). We developed the questionnaire and the checklist for data collection and interviews. A pre-test of the questionnaire was deployed to ensure clarity and avoid misunderstandings during data collection. A field research team consisting of 7 researchers collected data. We trained and guided the research team before going to the field. The time scheduled for the interviews was between 1 and 1.5 hours. Before the interview, we explained the purpose of the research and sought the respondent\u0026rsquo;s consent to participate.\u003c/p\u003e \u003cp\u003eThe checklists were used to conduct interviews with key informants. They are key experts in the SRP standard for rice farming. The first group consisted of province and local/district authorities, primarily from Dong Thap Province's Department of Agricultural and Rural Development, as well as district officers in charge of crop security, natural resources, and the environment. The second category included research institutes/universities, international agencies, local leaders, farmer cooperatives, and business players who were interested in marketing SRP rice and rice byproducts. We interviewed 24 key informants, including 12 from the provincial government, 5 from the district government, two communal leaders from My Dong and Tan Binh communes, and 5 private actors.\u003c/p\u003e \u003cp\u003eFGDs were conducted with rice farmer groups. First, the chairman of the farmer cooperatives and commune authorities assisted in identifying essential farmers who could provide reliable information based on their knowledge and experience. We held two focus group discussions (FGDs), one in Tan Binh Farmer Cooperative with 7 female and male participants, and another in Thang Loi Farmer Cooperative with 9 mixed participants. The focus group discussions gave us more information about rice farming and farmers' acceptance of the SRP Standard and good agricultural practices in both farmer cooperatives. Then we gathered farmers' perspectives on the SRP Standard as well as good agricultural practices such as climate change impacts, organic fertilization, income, incentives, and bio-stimulants.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRice crop calendar in Mekong Delta Vietnam\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRice crop season in the Mekong Delta\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSowing/Transplanting\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHarvesting\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWinter \u0026ndash; Spring (W-S) (Dong -Xuan)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNov-Dec\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMar-Apr\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSummer \u0026ndash; Autumn (S-A) (He - Thu)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eApr-May\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJul-Aug\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAutumn \u0026ndash; Winter (A-W) (Thu - Dong) *\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJul-Sep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOct-Dec\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eSource: Dong Thap Agricultural Department, 2022. * Denoted rainy season\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eSample size\u003c/h3\u003e\n\u003cp\u003eData collection was carried out using a \"multistage sampling technique\". Dong Thap province was chosen because it is carrying out a sustainable rice production project supported by NGOs and the private sector (GIZ, Rikolto, Loc Troi Group, and SunRice), which has been working in Dong Thap since 2017 and is therefore familiar with the actors, rice sector, and its characteristics. Second, two districts, Thanh Binh and Thap Muoi, which have been carrying out the sustainable rice production project since 2017, were chosen as the study area. Then, in each district, we chose one farmer's cooperative for data collection with two groups of farmers (SRP adopters and non-adopters).\u003c/p\u003e \u003cp\u003eWe assume that all farmers have experience with SRP via knowledge sharing and farmer field school. Thang Loi cooperatives were in Thanh Binh district, and Tan Binh cooperatives were in Thap Muoi. We used random sampling technique for gathering data at the household level in cooperatives based on the lists from local authorities of two farmers\u0026rsquo; cooperatives. Based on the formula (1) of Yamane (1968) cited by Manh \u0026amp; Ahmad (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) with \u0026ldquo;a 95% confidence level and \u0026plusmn;\u0026thinsp;5% margin of error,\u0026rdquo; we pre-selected 260 farmers to be interviewed using the questionnaire survey, composed of 140 members of Tan Binh commune and 120 members of Thang Loi commune in a total of 750 rice household producers in two communes. Finally, we used data from 243 respondents who completed the information to analyze. These consisted of 144 farmers who were members of farmer cooperatives (53 from Tan Binh cooperative and 91 from Thang Loi cooperative). We assumed that they adopted SRP for rice cultivation and 99 farmers who were non-members (68 from Tan Binh and 31 from Thang Loi) because they are not members of cooperatives; therefore, we assume that they did not adopt SRP.\u003c/p\u003e \u003cp\u003e\u003cimg src=\"data:image/png;base64,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\"\u003e\u003c/p\u003e\n\u003cp\u003eNote: \u0026ldquo;n\u0026thinsp;=\u0026thinsp;sample size\u0026rdquo;; \u0026ldquo;N\u0026thinsp;=\u0026thinsp;Total inhabitants of the research area\u0026rdquo;; \u0026ldquo;e\u0026thinsp;=\u0026thinsp;Level of precision, set at \u0026plusmn;\u0026thinsp;5% at 95% of confidence\u0026rdquo;.\u003c/p\u003e \u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eAnalyses of qualitative data obtained from key informant interviews, focus group discussions, and the T-test and descriptive statistics analysis method were used to investigate information and data related to the socioeconomic status, societal condition, and farmers' views on rice farmers adopting SRP. The regression model was used to determine the factors that influence farmers' adoption of SRP. Finally, we utilized STATA version 15 to evaluate the data.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eIndependent variables\u003c/h3\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the explanatory variables in this research\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive explanatory variables\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVariable name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDescription and measurement\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eSocioeconomic factors\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAge of respondent (in year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eExperience\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRice cultivation experience of the farmer (in year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEducation of farmers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe educational level of the farmer (in year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHousehold size\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber of members in the farmer\u0026rsquo;s family (scale)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFarming techniques\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRice land\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLand size for rice cultivation of household (ha)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDuration of land preparation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe time needed to prepare the land for the next season (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePre-germinated blower\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFarmer used blower machine for seedlings (Binary 1: Yes, 0: Otherwise)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePre-germinated drum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFarmer used seedling drums for sowing (Binary 1: Yes, 0: Otherwise)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFlooding time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe time of water application for rice (times)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFollowing the market price\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFarmers sold rice following the market price (Binary 1: Yes, 0: Otherwise)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePremium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFarmers received a higher price when they applied SRP for rice production (Binary 1: Yes, 0: Otherwise)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCooperative membership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFarmer was a member of a cooperative (Binary 1: Yes, 0: Otherwise)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.492\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIncentive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFarmer considering incentives as motivation to apply SRP (Binary 1: Yes, 0: Otherwise)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCognitive factors\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCC perception of rice farmers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFarmers noticed climate change was happening (Binary 1: Yes, 0: Otherwise)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.249\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSRP perception\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFarmer\u0026rsquo;s perception of SRP (Binary 1: Yes, 0: Otherwise)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.487\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCC impacts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eImpacts of CC affected farmer\u0026rsquo;s adoption of SRP (Binary 1: Yes, 0: Otherwise)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSaving water perception\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRice farmer\u0026rsquo;s perception of saving water technique (Binary 1: Yes, 0: Otherwise)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.498\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInstitutional factors\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLoan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFarmer took a loan from the bank for rice cultivation (Binary 1: Yes, 0: Otherwise)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.475\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSRP training\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFarmer attended SRP training in the last 2 years (Binary 1: Yes, 0: Otherwise)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.495\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePoor-quality rice seed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePoor quality rice seed affected farmer\u0026rsquo;s adoption of SRP (Binary 1: Yes, 0: Otherwise)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eConstraint factors\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLack of credit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLack of credit affected farmer\u0026rsquo;s adoption of SRP (Binary 1: Yes, 0: Otherwise)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLack of knowledge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLack of knowledge affected farmer\u0026rsquo;s adoption of SRP (Binary 1: Yes, 0: Otherwise)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow price of rice (general rice)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLow price of rice affected farmer\u0026rsquo;s adoption of SRP (Binary 1: Yes, 0: Otherwise)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow SRP-rice price\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLow SRP rice price affected farmer\u0026rsquo;s adoption of SRP (Binary 1: Yes, 0: Otherwise)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCannot sell SRP-rice\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCannot sell SRP rice affected farmer\u0026rsquo;s adoption of SRP (Binary 1: Yes, 0: Otherwise)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e26.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInput price\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCost of fertilizer, pesticides, seed, fungicides affected farmers\u0026rsquo; adoption of SRP (Binary 1: Yes, 0: Otherwise)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNote: SRP-rice* denotes rice was produced when farmers applied SRP standard.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eEmpirical logistic model\u003c/h2\u003e \u003cp\u003eWe used the binary logistic model to identify the factors that affected farmers\u0026rsquo; choices for adopting the SRP standard for rice cultivation. Socioeconomic factors and barriers influencing the choice of adoption SRP standards were investigated. The binary logistic regression model considers the relationship between a binary dependent variable (Yes\u0026thinsp;=\u0026thinsp;1 indicated that rice farmers adopted SRP standard for rice cultivation, 0 (no) otherwise) and a set of independent variables (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), whether they are binary, categories, or continuous. The logistic model is given by Manh \u0026amp; Ahmad (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and (Manh et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$Log\\left( {\\frac{{Pi}}{{1-Pi}}} \\right)=\\log (Pi)={\\beta _0}+{\\beta _i}{X_i}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere \u003cem\u003ePi\u003c/em\u003e is the probability of adoption of SRP for rice cultivation, and \u003cem\u003eXi\u003c/em\u003e is an independent variable. Therefore, the parameter \u003cem\u003eβi\u003c/em\u003e gives the coefficients of the dependent variable, and \u003cem\u003eβ\u003c/em\u003e\u003csub\u003e\u003cem\u003e0\u003c/em\u003e\u003c/sub\u003e is a constant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results and discussion","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n\u003ch2\u003eSocioeconomic demographic characteristics\u003c/h2\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e shows socioeconomic data. We obtained data from 243 farms. 49.8% and 50.2% of respondents were interviewed in Thang Loi and Tan Binh, respectively. The respondents ranged in age from 28 to 85 years old. The farmers' average age was 53.5 years. The share of young farmers under 35 was only 4.9%. Only 4.1% of the farmers were women, whereas 95.9% were men.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\"Farmers stated that their wives stayed at home to care for the family, while agricultural operations such as rice farming were only for men... If the lady was in the field, they just removed weeds or filled gaps.\" \u0026hellip;\u003c/em\u003eFGD with farmers in Tan binh, 2022.\u003c/p\u003e\n\u003cp\u003eIn terms of rice cultivation experience, respondents reported an average of 31 years, with the shortest being 8 years and the longest being 55 years. The average household size was 4.39 individuals. The average household size over the age of 18 was approximately 3.11, while the average number of elderly and children in households was around 1.02. The farmers' average education level was 7.35 years, showing that the majority did not complete secondary school. The average cultivated land size is 3.18 hectares, with 3.03 ha used for paddy. The remaining 0.15 hectare was used to cultivate fruit. Regarding the decision-makers on major matters such as buying a rice field in the farmers' family, 56.4% of respondents indicated that male farmers made the decision, 6.2% said that female farmers made the decision, and 37.4% said that there is a discussion within the family before making the decision, indicating that male members continue to hold decision-making power in the households. Therefore, it is important to have interventions to promote gender equality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFarmer\u0026rsquo;s perception of SRP.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDong Thap province has been applying the SRP since 2017. We asked rice-farmers about their perspective of SRP standard adoption in rice cultivation. The majority of farmers (61.73%) have used SRP, whereas 38.27% are unaware of it. Many international organizations, including Rikolto and GIZ, as well as the commercial sector (Loc Troi and SunRice), support SRP. However, some farmers did not experience the SRP. Unlike the \"one must do five reductions\" initiative, SPR has yet to be officially validated by the Vietnamese government, suggesting that SRP needs more consideration. Surprisingly, 33 farmers stated that they embraced SRP after learning from their relatives. Therefore, knowledge of SRP may spread from farmer to farmer and their families (Hua \u0026amp; Brown \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e). It gives evidence that social capital has a vital role in agricultural extension for rice farmers in terms of SRP. Data from key informant interviews in My Dong commune further confirmed that farmers may interact with one another to share rice and market knowledge, as well as learn how to use SRP through digital tools (Zalo) and farmer organizations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSRP adoption in rice production in Dong Thap province, farmers\u0026rsquo; perspectives.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRole of SRP in mechanization development.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFarmers and policymakers were asked about the role of SRP in mechanization for rice cultivation. We found that in the MDR mechanization has become an indispensable requirement for rice cultivation. Local government has made great investments in developing transport and irrigation infrastructure, pumping stations, mechanization in rice production and supporting the application of scientific-technical advances. Therefore, the rate of rice-harvesting by machine reached 97%, and irrigation systems providing water to paddy fields by electric pumps reached 92%. Indeed, the annual high-quality rice field accounted for 51% of the total production land and mechanization covers almost 100% of the rice field, showing the transition to the rice industry, and gradually creating a new face for rice production when farmers adopt SRP (Dong Thap Agriculture Report 2018). According to the guidelines of SRP, the condition of paddy field is consistent and flat so that machines requirement is needed to prepare rice land. Results show that most farmers rent machines from cooperatives or privates to prepare the rice land. Since 2017, there were 1,654 combine harvesters, 50 transplanters, 975 cargo-spraying machines, 6,931 fertilizer-seeding machines, and 66,407 motorized spraying machines in this study area (Dong Thap Agriculture report 2018).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eWe made good progress in applying new agricultural technologies, particularly in the rice sector. These included the use of harvesting machines in the whole province and the use of smartphone applications in pests and disease control. We will continue doing research to find new rice varieties that are resilient and of high quality, applying new agricultural technology and investing in agricultural infrastructure including improved irrigation systems\u0026rdquo;\u003c/em\u003e said Dr. Le Quoc Dien, the Deputy Director of Dong Thap Agricultural Department\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n\u003ch2\u003eRole of SRP in the promotion of sustainable rice production practices\u003c/h2\u003e\n\u003cp\u003eIn the last 15 years, several programs from the government were introduced as good agricultural practices for sustainable rice production for rice farmers, such as \"3 Reduces, 3 Gains,\u0026rdquo; \u0026ldquo;1 Must Do, 5 Reductions,\" and \"1 Must Do, 6 Reductions.\" Similarly, SRP as a sustainable good agricultural practice was also introduced by international non-government organizations (Rikolto, GIZ) and the private sector (Loc Troi, SunRice) in 2015 to promote sustainable rice practices. \u003cem\u003eSRP was introduced by GIZ in Mekong Delta Vietnam; therefore, thousands of farmers participated in and gained benefit from these training courses (Mr. Hung, Thang Loi Cooperative 2022).\u003c/em\u003e The benefits include pest control information and knowledge on how to use pesticides and rice technical practices, participation in training of the Integrated Pest Management (Farmers in Thang Loi and Tan Binh Cooperatives 2022). In fact, 70.4% of the farmers, most of whom were members of cooperatives, attended SRP training. Farmers reported that SRP training provides more knowledge of how to produce rice following SRP guidance (e.g., reduced quantity of seed, fertilizer and pesticide application per hectare, and rice straw management). 58% of the farmers attended at least one SRP training. We found a significant difference whereby farmers who were members of the cooperatives had more opportunities to attend SRP training compared to farmers who did not join any cooperative. Furthermore, farmers who attended training achieved higher rice production (Ly et al. \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSRP in rice varieties and yield.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo evaluate the role of SRP in selecting rice varieties, we found that farmers cultivated different rice varieties (e.g., aromatic, high-yielding, resistant to pests and diseases). Farmers were required and encouraged to use certified-quality rice varieties with a short to medium duration (90\u0026ndash;115 days) and meet the market demand. Priority is given to the application of extremely short-term rice varieties with moderate salt tolerance, such as OM18, Dai Thom 8, ST24, ST25, and Jasmine 85. In My Dong and Tan Binh communes, the DT8 and OM 18 are the dominant varieties. Moreover, some farmers cultivated sticky rice due to receiving a higher price (around 7,500 VND-8,000 VND/kg) and being easier to sell compared to traditional rice. The average rice yield in the two communes was around 6.67 tons/ha. Farmers reported that they achieved more yield when they adopted SRP compared to non-adopted (FGDs in Tan Binh commune, agricultural officer of Thap Muoi district). Most farmers sold rice to rice-traders or millers, and less to cooperatives. In particular, rice companies only imported around 30%, and of which 60% of SRP-rice for export. Importantly, 90.5% of the farmers indicated that they do not face any problems when they sell SRP-rice.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n\u003ch2\u003eSRP in seed quantity, and land preparation\u003c/h2\u003e\n\u003cp\u003eTo evaluate SRP's role in seed quantity, farmers were asked to answer the question, \"How does SRP contribute to seed quantity use?\u0026rdquo; We found that farmers reduced the quantity of seed when they adopted SRP. There is no standard for the seed quantity needed per ha. The seed quantity also differs between direct seeding and transplant methods. To save input costs, it was recommended that rice seed should be around 80\u0026ndash;120 kg/ha/season for the direct seeding and around 60\u0026ndash;70 kg/ha with the transplanting machine (Dong Thap, \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, we found that the seed rate farmers used was from 150 to 180 kg/ha/season. Farmers explained that this is because of golden snails and rat damage. Moreover, farmers reported that they reduced by 20\u0026ndash;35% when they followed SRP guidelines compared to non-SRP. Interestingly, agricultural officers still confirmed that rice farmers used about 80\u0026ndash;120 kg of seed per ha per season. A significant difference exists whereby farmers belonging to cooperatives that adopted SRP tend to use less seed as compared to farmers who are non-adopters of SRP (T-test, F\u0026thinsp;=\u0026thinsp;11.416, p-value\u0026thinsp;=\u0026thinsp;0.0001), indicating that farmers who were cooperative members used less quantity of seed.\u003c/p\u003e\n\u003cp\u003eIn terms of land preparation, we found that the role of SRP is important. Land preparation for rice is one of the basic practices and is a requirement of SRP adoption. Rice land needs to be carefully prepared. For example, a rice field is consistent and flat for efficient water management. To do so, the farmer cooperatives used machines to prepare paddy land with an average 2.12 times plowing frequency, and households with small sizes (0.5-1 ha) require only one time plowing.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n\u003ch2\u003eSRP in water management\u003c/h2\u003e\n\u003cp\u003eWater management is an important indicator of SRP application to ensure effective rice growth in the paddy field. One of the most important indicators of SRP is water management practice such as \u0026ldquo;alternate wetting and drying\u0026rdquo; (AWD), which was introduced by IRRI in the Mekong Delta in 2006 to reduce water consumption and GHG emissions. The saving-water technique was used in many provinces in the Mekong Delta. We found that rice farmers, based on their experience, have adjusted the official saving water technique (AWD) to reduce the burden, such as labor cost or time. It is called the \u0026ldquo;incomplete saving-water technique\". This practice does not fully follow the AWD protocol. Farmers in cooperatives reported that they did not use \u0026ldquo;Pani-pipe\u0026rdquo; to observe the water level, and farmers did not apply water management practices in the rainy season (Nguyễn C\u0026ocirc;ng \u0026amp;Thuận, 2022).\u003c/p\u003e\n\u003cp\u003eFigure 2 shows the incomplete water management practices in two communes. On two weekend days, water was delivered for rice in accordance with the schedule, indicating that the water pumping equipment was turned on Saturday and off on Sunday. Water is pumped into irrigation canals seven times and then drained (dried up) six times. Farmers stated that they can save 30 to 40% of the water required for flooding rice production (conventional rice farming) after\u003c/p\u003e\n\u003cp\u003eapplying incomplete saving-water technique (Mr. Bong and Mr. Hung, chairmen of Tan Binh and Thang Loi Cooperatives), our result supports to previous study of (Nguyen et al. \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n\u003ch2\u003eSRP in fertilizer application\u003c/h2\u003e\n\u003cp\u003eWe investigated the role of SRP in fertilizer applications by rice farmers. We discovered that fertilizer is essential in rice production, influencing yield and profitability. Different types of fertilizer were available on the market. However, most farmers employ chemical fertilizer for rice because chemical fertilizer is easy to buy. Most farmers applied single chemical fertilizers such as urea, kali, and phosphate. Moreover, different farmers used different quantities of fertilizer per hectare, depending on how and what type of fertilizer they applied, their knowledge of the different kinds of fertilizers, the stages of rice growth, and their habitual practice. The results indicated that all farmers used a single chemical fertilizer for rice cultivation. Rice farmers bought the fertilizers first and reimbursed them after harvesting. The price of fertilizer is also based on the market; in the years of conducting this study, input costs increased on average around 30% per year, leading to reduced rice farmers\u0026rsquo; profit. \u003cem\u003e\u0026ldquo;One of the most important factors that affected rice farmers in recent years was the price of fertilizers (input cost) that increased recently. We cannot control the fertilizer price because it depends on the international market.\u0026rdquo;\u003c/em\u003e (Mr. D; Mr. C; Dong Thap DARD 2022).\u003c/p\u003e\n\u003cp\u003eWe also found that the amount of fertilizer applied by farmers varied, depending on their understanding of what is needed by the plant at different stages of its growth and the condition of the soil. Most farmers who were asked about soil health were unable to answer the questions because they were unaware of the importance and relationship between soil health and rice productivity. Indeed, soil deterioration has been severe across the Delta, particularly in Dong Thap. One of the factors is intensive agricultural practices. It is the outcome of triple-rice farming systems and the extensive use of commercial fertilizers. Some farmers are already transitioning from intensive rice growing techniques to fruit gardens. The farmer indicated, \u003cem\u003e\"We used chemical fertilizer when I started to cultivate rice (for more than 40 years), but I did not know about soil health.\"\u003c/em\u003e Mr. B, a farmer from My Dong commune.\u003c/p\u003e\n\u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e shows that the average fertilizer application time was 3.33 with a standard deviation of 0.72. 67.5% of the farmers applied fertilizer 3 times, 30% of the farmers 4 times, and 1.2% of the farmers applied fertilizer from 5 to 7 times, and 1.2% of the farmers 2 times. The amount of fertilizer application depended on the soil features, soil characteristics, and rice varieties. Some rice varieties required more fertilizer than others. For example, hybrid rice requires more fertilizers than inbred rice (Huang et al. \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e; Jiang et al. \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e; Yuan et al. \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e). According to the guidance on fertilizer application from the local government, farmers were recommended to apply 200 kg phosphorus, 50\u0026ndash;70 kg DAP, 150\u0026ndash;160 kg urea, and 70\u0026ndash;120 kg kali per ha. Indeed, farmers use fertilizer more than the government recommends. However, farmers indicated that this amount of fertilizer has been reduced much more than 5 years ago due to attending SRP training and other rice production programs (e.g., 1M5R). Furthermore, farmers tend to use compound fertilizer without reducing the urea or potassium. Farmers who have more than 5 hectares of rice applied more fertilizers than the local government\u0026rsquo;s recommendation. This is because farmers were afraid of potentially major failures, so they preferred to apply more fertilizer when they observed rice looking unhealthy. The same is true in the use of pesticide applications.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n\u003ch2\u003eSRP in promoting bio-fertilizer and bio-stimulant application\u003c/h2\u003e\n\u003cp\u003eBiofertilizer and biostimulant applications are another way to provide nutrition for crops, particularly rice. We found that only 17.7% of the farmers used bio-fertilizers (foliar) when rice needs more nutrition, particularly in the flowering, panicle stage, and grain filling stage. Moreover, in rainy season, rice farmers who attended SRP training used \u003cem\u003eTrichoderma\u003c/em\u003e to transform rice straw into organic fertilizer in the field because of difficulty collecting rice straw, and it also helps farmers save the labor and cost for rice production in rainy season. Farmers stated that \u003cem\u003e\u0026ldquo;we did not know about biostimulants, but we used Trichoderma to transform rice straw into organic fertilizer; we learned it from SRP training, and we saved labor costs.\u0026rdquo;\u003c/em\u003e Mr. L, a farmer in Tan Binh cooperative.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n\u003ch2\u003eSRP in pests and diseases management\u003c/h2\u003e\n\u003cp\u003ePests and diseases can damage rice from the vegetable stage to mature time, reducing the rice yield and quality. In fact, farmers spent much money and effort to control pests and diseases, and farmers used pesticides and fungicides more than needed every season. Like fertilizer, farmers can easily buy pesticides, fungicides, and rodenticides in this area. Also, there is a diversity of pesticides on the market. In the last 5 years, the price of pesticides increased, according to agricultural officers. Farmers in Tan Binh and My Dong indicated that pesticide and fungicide prices increased in recent years. It creates hardship for rice farmers. The farmer mentioned that \u003cem\u003e\u0026ldquo;the price of fertilizer and pesticides increased day by day, but the rice price was the same every year; sometimes the rice price even decreased; we cultivated rice but made no profit...\u0026rdquo;\u003c/em\u003e Mr. C, a farmer in Tan Binh. We found that 96.3% of farmers used pesticides to control pests in the rice field. About 39.1% of the farmers used pesticides and fungicides following the guidance on the label, and 37.9% of the farmers applied pesticides based on their experience. The rest (62.1%) followed the guidelines from SRP training. Basically, farmers know how to use pesticides and fungicides for rice. According to Mr. Hau and Mr. Thanh from the Dong Thap Agricultural Department and Rural Development, most farmers were trained how to use pesticides and fungicides via SRP training.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFigure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e showed the average of pesticides and fungicide applications was around 2.51 times less than 1.3 times compared to last year (2021). Farmers indicated that after attending SRP training, they reduced the frequency of pesticide application. However, 7% of the farmers seemed to apply more than they needed (6\u0026ndash;7 times per season), while 3.7% of the farmers did not use pesticides (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). We also found that most farmers (89.3%) frequently mixed pesticides and fungicides when they applied.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n\u003ch2\u003eSRP in rice straw management\u003c/h2\u003e\n\u003cp\u003eStraw management is a crucial indicator in the SRP to help farmers reduce the GHG emissions for rice cultivation. It requires, among other things, that farmers do not allow them to burn the rice straw in the field. In fact, we found that 25.5% of the farmers burned rice straw because it helps to clean the paddy field fast-to remove pests, disease, and weeds for the new planting season. Farmers believed that burning rice straw would reduce fertilizers in the next season. Indeed, burning rice straw has both negative and positive effects. On the positive side, it increases the availability of phosphorus and potassium in the short run, but at the cost of losing soil nutrition such as nitrogen, potash, and sulfur (Ahmed et al. \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e). As a result, when scaling up the SRP application in the future, farmers need to be trained in more knowledge of rice straw management. Rice straw management still needs to get attention from both local government and farmers.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\n\u003ch2\u003eDeterminant factors influence farmers\u0026rsquo; adoption of SRP standard\u003c/h2\u003e\n\u003cp\u003eIdentifying the factors that influence farmers\u0026rsquo; adoption of SRP plays an important role in scaling up SRP in the future. We used a logistic model to analyze the data. Cross-sectional data in logistic model analyses frequently had two issues, including multicollinearity among independent variables and heteroscedasticity in the error term. VIF and robust variance estimator were applied to check multicollinearity and heteroscedasticity in this research, respectively. Moreover, the marginal effect (dy/dx) was also calculated for this study. The results showed that the means of VIF for all independent variables in the model are 1.829 (range from 1.091 to 4.699) less than 10, showing that multicollinearity is not an issue in this model (Manh \u0026amp; Ahmad \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eThe overall result of the logistic regression was highly significant with the values of Chi-square\u0026thinsp;=\u0026thinsp;50.575, pseudo-r-square\u0026thinsp;=\u0026thinsp;0.801, and prob\u0026thinsp;\u0026gt;\u0026thinsp;\u0026chi;2\u0026thinsp;=\u0026thinsp;0.003. The logistic regression is significant and fits the data, indicating that these 26 explanatory variables explained 80.1% of the probability that farmers would adopt SRP for sustainable rice production. The estimated results of the model are shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eFactors affecting farmers\u0026rsquo; adoption of sustainable rice platform (n\u0026thinsp;=\u0026thinsp;243)\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eCoef.\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eRobust Std.Err.\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003ep-value\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003edy/dx\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eRobust\u003c/p\u003e\n\u003cp\u003eStd.Err.\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003ep-value\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eSocioeconomic factors\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAge\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.568***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.165\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.023***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.005\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eExperience\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.32**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.146\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.028\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.013**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.005\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.011\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEducation of farmers\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.749***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.186\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.030***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.005\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHousehold size\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.478\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.378\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.206\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.019\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.015\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.200\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eFarming techniques\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRice land\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.47\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.393\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.231\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.019\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.016\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.240\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDuration land preparation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.01\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.073\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.889\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.003\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.889\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePre-germinated blower\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-8.886***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.307\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.353***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.072\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePre-germinated drum\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-7.598***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.082\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.302***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.064\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFlooding time\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.391***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.133\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.003\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.016***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.005\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.003\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFollowing market price\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.526**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.236\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.013\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.219***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.069\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePremium\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.007**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.003\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.017\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.000**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.012\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCooperative membership\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15.771***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.943\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.626***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.109\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIncentive\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-5.933***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.712\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.236***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.051\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eCognitive factors\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCC perception of rice farmers\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.177***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.792\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.004\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.206***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.058\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSRP perception\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.528**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.377\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.010\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.140***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.044\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCC impacts\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-4.733***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.747\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.007\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.188***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.060\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.002\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSaving water perception\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.786***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.461\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.230***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.045\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eInstitutional factors\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLoan\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.501*\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.332\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.060\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.099*\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.046\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.032\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSRP training\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.657***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.342\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.006\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.145**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.052\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.005\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePoor-quality rice seed\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-6.677***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.207\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.002\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.265***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.069\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eConstraint factors\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLack of credit\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.669\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.06\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.528\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.027\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.042\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.527\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLack of knowledge\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-4.369***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.497\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.004\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.173***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.057\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.002\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLow price of rice (in general)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.382*\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.367\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.081\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.095**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.047\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.046\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLow SRP rice price\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-16.388***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.908\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.651***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.105\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCannot sell SRP rice\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-4.631**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.030\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.184**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.075\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.014\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eInput price\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.911***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.858\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.008\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.195***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.053\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eConstant\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-35.388***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9.909\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMean dependent var\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.695\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSD dependent var\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.461\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePseudo r-squared\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.801\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNumber of observations\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e243\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eChi-square\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e50.575\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eProb\u0026thinsp;\u0026gt;\u0026thinsp;chi2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.003\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAkaike crit. (AIC)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e113.386\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBayesian crit. (BIC)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e207.699\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003e*** p\u0026thinsp;\u0026lt;\u0026thinsp;.01, ** p\u0026thinsp;\u0026lt;\u0026thinsp;.05, * p\u0026thinsp;\u0026lt;\u0026thinsp;.1\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"7\"\u003eSource: Author calculation (2022)\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\n\u003ch2\u003eSocioeconomic factors\u003c/h2\u003e\n\u003cp\u003eThe adoption of SRP was affected by socioeconomic factors. Age and level of education were positive and statistically significantly affected farmers\u0026rsquo; adoption of SRP, indicating that older farmers tend to adopt SRP. The reason could be older farmers attended SRP training and know how to apply SRP. One year of age increases, the probability of SRP adoption increases by 2.3%; other variables are constant. Our results contradict the previous studies of (Tho et al. \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e), and (Ly et al. \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e). Education plays a vital role for rice farmers, education positively and statistically affected farmers\u0026rsquo; adoption of SRP. One-year education increases the probability of SRP adoption by 3%; the result is similar to the previous study (Dung \u0026amp; Tuan \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e). Interestingly, experience factors may have positive and negative effects on farmers adopting new technology (Mutyasira et al. \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e; Dung \u0026amp; Tuan \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e; Mariano et al. \u003cspan class=\"CitationRef\"\u003e2012\u003c/span\u003e). In this research, experience negatively affected rice farmers adopting SRP. This is because rice farmers are families with traditional rice production; they may be concerned about the risks of SRP adoption and less inclined to adopt SRP. Furthermore, this result proved that farmers who have rich experience in rice production may not affect the probability of adopting new agricultural technology, providing valid information for policymakers to build agri-policies for scaling up SRP in the future. This result contradicts the previous study of Dung \u0026amp; Tuan (\u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\n\u003ch2\u003eFarming techniques\u003c/h2\u003e\n\u003cp\u003eAdopting SRP for sustainable rice production could be affected by the times of water provided for rice (flooding time). The results show that flooding time strongly affected the process of SRP application. One percent of farmers noticed times of \u0026ldquo;flooding time\u0026rdquo; increase; the probability of adoption of SRP increases by 1.6%; other factors are constant.\u003c/p\u003e\n\u003cp\u003eFollowing the market price factor (farmers sold rice following the market price) was positive and statistically significant for farmers\u0026rsquo; adoption of SRP. Most farmers sold rice following the market price; farmers indicated that whatever the price was, they would sell. Farmers update rice market information frequently by smartphone or public media and can choose to sell rice to the buyer who gives them the best price. Farmers also sell as wet paddy and negotiate with buyers normally take place before the harvest. We found that following the market price factor increase of one percent, the probability of adoption of SRP increases by 21.9%. Our results are supported by previous studies (Mariano et al. \u003cspan class=\"CitationRef\"\u003e2012\u003c/span\u003e; My et al. \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e; Okpiaifo et al. \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e\n\u003cp\u003eFarmers who were members of the cooperative tend to apply SRP for sustainable rice production. Most of them indicate that they gained more knowledge and benefits after being cooperative members. Statistics show that this factor positively and significantly affected farmers\u0026rsquo; adoption of SRP. One percent of farmers joining cooperatives increased; the proportion of farmers adopting SRP increased 62.6%; other factors are constants. It was similar to results in previous studies of Ly et al. (\u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), and Tho et al. (\u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). While premium and incentive factors negatively affected farmers\u0026rsquo; adoption of SRP. Indeed, many farmers indicated that \u0026ldquo;incentive\u0026rdquo; was one of the factors that encouraged them to apply SRP. But if they could not sell SRP rice, receive low prices, or benefit from premium SRP rice prices, it would negatively affect their decision.\u003c/p\u003e\n\u003cp\u003eInterestingly, farmers who used pre-germinated blowers and pre-generated drums for rice cultivation were less likely to adopt SRP. Regression shows that one percent of farmers used pre-germinated blowers increased; the probability of SRP adoption decreased by 35.3%; other variables are constant. It seems that farmers who used pre-germinated blowers had more burden to invest in their paddy farm; therefore, they tended to not adopt SRP. Our result contradicts the previous study of Mashi et al. (\u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e), and Pi\u0026ntilde;eiro et al. (\u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e), indicating that incentives insignificantly affected farmers to adopt sustainable agricultural technologies. Moreover, this research did not find the significant effects of rice land duration and land preparation on farmers adoption of SRP.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\n\u003ch2\u003eCognitive factors\u003c/h2\u003e\n\u003cp\u003eCognitive factors play an important role in scaling up SRP for farmers. The CC perception of rice farmers factors positively and significantly affected farmers adopting SRP. One percent of farmers noticed climate change is happening; the probability of SRP adoption increasing is 20.6%, with other factors remaining unchanged. Our results were also found in previous studies by Ahmed et al. (\u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e), and Gisi \u0026amp; Begho (2023). Moreover, the SRP perception factor has a positive and significant relationship with SRP adoption; farmers who notice the SRP benefits are more likely to adopt SRP. One percent of SRP perception increases; the probability of adoption of SRP increases by 14.0%; other factors do not change. Saving water, such as the AWD technique, is a vital factor for rice cultivation. This factor is a key component of SRP guidance. Therefore, farmers who noticed and applied the saving water technique tended to increase the proportion of SRP adoption by 23.0%. However, farmers who noticed climate change impacts on their paddy fields tend to reduce the adoption of SRP, indicating that farmers fear the risks when applying SRP, even though farmers noticed impacts of CC. One percent of farmers noticed the impacts of climate change on the paddy increases; the probability of adoption of SRP decreased 18.8%, with other factors being constant. Our result is not in line with the previous study; they found that when farmers noticed the impact of climate change, they tended to adopt agricultural technologies.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\n\u003ch2\u003eInstitutional factors\u003c/h2\u003e\n\u003cp\u003eAccess to finance is critical in implementing agricultural innovations (Balana \u0026amp; Oyeyemi \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e; Ruzzante et al. \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). Loans can assist farmers overcome financial challenges. The loan-taking component had a positive and statistically significant effect on rice farmers' adoption of SRP in the Mekong Delta; 1% of farmers took bank loans, increasing the chance of SRP adoption by 9.9%. Our findings were consistent with recent research by Sanogo et al. (\u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e), and Swami \u0026amp; Parthasarathy (\u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), which indicated that loans could improve the fraction of agricultural technology uses in India and Mali.\u003c/p\u003e\n\u003cp\u003eMoreover, farmers who attended SRP training are likely to apply SRP; if one percent of farmers attended SRP training, the probability of SRP adoption increases by 14.5%. This is because farmers gained more SRP knowledge and improved their knowledge of how to apply SRP from the training. Our result was supported by many previous studies of Joblaew et al. (2019), Ly et al. (\u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), Mariano et al. (\u003cspan class=\"CitationRef\"\u003e2012\u003c/span\u003e), Swami \u0026amp; Parthasarathy (\u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), and Tho et al. (\u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eOther factors that play an important role are seed quality. Absolutely, poor seed quality influenced farmers\u0026rsquo; adoption of sustainable rice practices. Like other rice programs (e.g., 1M5R), applying SRP requires farmers to accurately follow the SRP principal guidelines, meaning that farmers must use quality rice seed (certified seed) to cultivate. Therefore, poor rice seed farmers will face many risks. Regression shows that poor quality seed factors negatively affected farmers\u0026rsquo; adoption of SRP. If one percent of farmers used poor seed quality, the probability of SRP adoption reduces to 26.5%, with another factor constant.\u003c/p\u003e\n\u003cdiv id=\"Sec23\" class=\"Section3\"\u003e\n\u003ch2\u003eConstraint factors\u003c/h2\u003e\n\u003cp\u003eAlthough there are many benefits from SRP adoption for sustainable rice production, the proportion of SRP adoption in the Mekong Delta is still less. The farmers were asked to indicate the constraints factors or barriers. We found that a number of barriers (lack of knowledge, low price of rice, low SRP-rice price, farmers cannot sell SRP- rice, input cost, and no access to credit) affected rice farmers to adopt SRP. This may lead to restricted scaling up SRP standard adoption area rice in the future. Therefore, more attempts in terms of training, providing market information, and providing credit access are needed for rice farmers. Regression showed that lack of knowledge, low price of rice, low SRP-rice price, cannot sell SRP-rice negatively significantly affected farmers\u0026rsquo; adoption of SRP, indicating that when rice farmers face these factors, the probability of adoption of SRP decreases.\u003c/p\u003e\n\u003cp\u003eFurthermore, input costs (particularly fertilizer, pesticides, and fungicides) played an important role in rice production. Surprisingly, we found that input costs positively affected farmers\u0026rsquo; adoption of SRP, indicating that as input costs increase by 1%, the probability of farmer's adoption of SRP increases by 19.5%. The reason is that when farmers spend more money on their farms, they will sell rice at a high price to get more profits to compensate for the investment cost. SRP rice can help them. Our result is in line with the results of previous studies by Alam et al. (\u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), and Tran et al. (\u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). Farmers tended to apply the new technologies if they encountered challenges related to the cost of inputs.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eSRP can help farmers grow rice in a more sustainable manner. However, scaling up SRP presents numerous obstacles. This study examines the benefits of adopting SRP for sustainable rice production using data from 243 rice farmers in Dong Thap province. Rice farmers gained numerous benefits by implementing SRP to cultivate rice. Farmers, for example, reduced the amount of seed per hectare, cut pesticide use, and improved rice straw management. Furthermore, rice farmers decreased both the number and timing of pesticide and herbicide applications while increasing rice yields. However, it also compels rice producers to follow many of the SRP guidelines. Furthermore, farmers that joined the cooperative in Dongthap province fared well in SRP rice production, however some rice farmers did not follow the requirements strictly. For example, farmers continue to burn rice straw in open fields. This study shows that the adoption of SRP was influenced by a variety of factors, including socioeconomic status, cognitive abilities, farming techniques, institutional characteristics, and impediments. The findings of this study help to fill knowledge gaps about the social elements of rice farmers on SRP, which contributes to SDGs 1, 2, and 13. The data demonstrated that SRP should be advocated for rice producers in the Mekong Delta region to pursue sustainable rice production. To scale up SRP adoption among rice farmers, policymakers, planners, and stakeholders should consider the factors outlined in our research. Finally, there are some limitations to this research, such as the fact that we were unable to sample the entire Mekong Delta; nonetheless, this study might be replicated for other provinces in the region. Second, this study did not look at the economic differences between SRP adopters and non-adopters. Finally, this study did not examine agricultural policies that could facilitate the implementation of SRP.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eNo support funding for this study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e: Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of Conflicting Interests:\u0026nbsp;\u003c/strong\u003eThe authors declared no conflicts of interest with respect to the research, authorship, and/or publication of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publish\u003c/strong\u003e: The author gives the consent to publish\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e: Informed consent was obtained from all subjects involved in the study\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e: This research was ethically approved by protocol of local institution (ICRA Vietnam)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Available Declaration:\u003c/strong\u003e The raw data supporting this study’s findings are available upon reasonable request from the author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u003c/strong\u003e All authors equally contribute in this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAhmed T, Ahmad B, Ahmad W. 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Cambridge University Press Cambridge, United Kingdom and New York, NY, USA. p. 2014.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-sustainability","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"disu","sideBox":"Learn more about [Discover Sustainability](https://www.springer.com/43621)","snPcode":"","submissionUrl":"","title":"Discover Sustainability","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Farmers, saving water for rice, SRP, sustainable rice production, Mekong Delta, Vietnam","lastPublishedDoi":"10.21203/rs.3.rs-6200782/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6200782/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eRice is the daily staple food of 3.5\u0026nbsp;billion people in the world. Vietnam, providing around 16% of the world\u0026rsquo;s milled rice exports, is the fifth-largest rice producer. Despite the role of rice in Vietnam\u0026rsquo;s economy, food security, and local livelihoods, rice farmers in Mekong Delta are now amongst the most vulnerable groups affected by the negative impacts of climate change and will be unstainable rice production. Using the Sustainable Rice Platform (SRP), consists of 12 sustainability impact indicators, linked to SDGs, as the best practices case to help rice farmers produce sustainable rice production. This study provides empirical evidence on the benefits of SRP adoption and explore factors affecting SRP uptake. Surveys and FGDs were applied to collect data from 243 rice-farmers in Dong Thap province. T-test and logistic regression were applied to analyse data. Results show that farmers have positively experienced SRP adoption and farmers achieved benefits from SRP adoption such as reduced input cost and increased income. Regression showed that socioeconomic, cognitive, and farm techniques factors strongly affected farmers\u0026rsquo; adoption of SRP. Therefore, to scale up farmers\u0026rsquo; SRP adoption training and technical assistance, socioeconomic constraints (e.g. water use) are required. Policymakers, planners, and private actors, particularly farmers\u0026rsquo; behaviour need to consider the factors that affecting them adopting SRP. Finally, this study highlights the potential of SRP to promote environmentally sustainable rice production and improve farmers' resilience to climate change.\u003c/p\u003e","manuscriptTitle":"The effectiveness of SRP to sustainable rice production in Mekong Delta Vietnam","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-09 11:13:34","doi":"10.21203/rs.3.rs-6200782/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-07-19T12:33:17+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-16T03:07:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"310653533504098996660447108348496247033","date":"2025-06-02T12:07:59+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-21T08:43:33+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-20T11:17:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"179774859308441150954665684187403765450","date":"2025-05-07T10:29:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"140929840666397449701256998232237783097","date":"2025-05-06T12:55:21+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-05T10:49:53+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-16T10:20:18+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-13T14:24:19+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Sustainability","date":"2025-04-13T14:23:10+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-sustainability","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"disu","sideBox":"Learn more about [Discover Sustainability](https://www.springer.com/43621)","snPcode":"","submissionUrl":"","title":"Discover Sustainability","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"90ab4615-53bd-4d92-92ae-c83c2ce19b5c","owner":[],"postedDate":"May 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-01-12T16:02:38+00:00","versionOfRecord":{"articleIdentity":"rs-6200782","link":"https://doi.org/10.1007/s43621-025-01986-0","journal":{"identity":"discover-sustainability","isVorOnly":false,"title":"Discover Sustainability"},"publishedOn":"2026-01-05 15:57:57","publishedOnDateReadable":"January 5th, 2026"},"versionCreatedAt":"2025-05-09 11:13:34","video":"","vorDoi":"10.1007/s43621-025-01986-0","vorDoiUrl":"https://doi.org/10.1007/s43621-025-01986-0","workflowStages":[]},"version":"v1","identity":"rs-6200782","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6200782","identity":"rs-6200782","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}