Exploring ways to scale direct-seeded rice in Sta. Cruz, Zambales: a Living Labs Approach

While it offers a host of advantages, such as significantly reducing labor costs and methane emissions, direct-seeded rice has failed to gain traction in the Philippines. Only 43% of farmers prefer DSR, particularly during the dry season. Employing the Living Labs Approach, this study set out to unpack ways to scale DSR in Sta. Cruz, Zambales. Living Labs is an approach that values co-creation and intensive stakeholder engagement in creating usable technologies or strategies for intended users. Sta. Cruz was chosen as the research site as it has evidence of farmers employing DSR as a crop establishment method. The Collective Approach to Technology Adoption served as the main theoretical framework for this research. Multiple methods, including in-depth interviews, surveys, and policy brokering, were employed, along with capacity-building activities, to address the research questions posed by this study. High interest among locals; assistance from various stakeholders, both within and outside Sta. Cruz; transdisciplinarity and strong support from local executives, as evidenced by their passage of a local ordinance supporting wider DSR promotion in the town, contributed to the DSR scaling efforts.

Introduction

The difficulty in finding farmworkers, rising labor and other input costs, and concerns about climate change compel the rice sector to explore alternative methods of cultivation (Pandey and Velasco, 2002; Savari et al., 2025). Direct-seeding is known to have addressed all of these challenges. In the literature, it is known to be the preferred mode of rice crop establishment in exporting countries such as Vietnam (Van Hung et al., 2024). With the discourse now turning to the creation of carbon markets, DSR appears to be a promising technology for earning carbon credits.

Despite these advantages, it is perplexing that direct seeding has not gained significant traction in most rice-producing provinces in the Philippines, where only 43% of farmers prefer DSR, particularly during the dry season. Most of the adopters came from Iloilo, Antique, Capiz, Palawan, Aurora, and Sultan Kudarat (PhilRice, 2023). This is the scenario, even though issues above persist in some of the poorest rice-producing regions.

Hence, this research seeks to look into the phenomenon of low DSR uptake in the Philippines by examining the case of Sta. Cruz, Zambales, through a project funded by the Food and Agriculture Organization. For 2 years, a transdisciplinary team of PhilRice experts implemented a project to explore how DSR could be scaled in the town. The team was composed of agronomists, crop modelers, weed experts, training management specialists, economists, development communicators, sociologists, engineers, and community development experts. The project looked into the policy, entrepreneurship, agronomic, and mainstreaming aspects of DSR. The municipality of Sta. Cruz was chosen for evidence of DSR use in crop establishment and for its proximity. Proximity was an important criterion because, during project implementation, there were still occasional lockdowns that restricted mobility. Hence, the team chose a site that could be visited frequently.

The overarching research question of this study was: How do we scale DSR in Sta. Cruz, Zambales? When we say scaling, we mean: (1) an increase in the number of hectares employing DSR; (2) evidence of support to scale; (3) the presence of legislative support to ensure that scaling efforts continue. The specific research questions were the following: (1) What are the constraints and opportunities to increase the uptake of DSR; (2) Is there a business for machine service provision for DSR?; (3) How does DSR compare with other crop establishment methods?; and (4) What are the indications of DSR uptake in the community?

Literature review

There is strong consensus in the literature that DSR is a much more environmentally friendly method of rice crop establishment (Bwire et al., 2024; Darikandeh et al., 2025; Dey et al., 2024). The literature emphasizes that direct-seeded rice is key to reducing methane emissions in rice (although some studies suggest that it might increase Nitrous oxide, for instance, see Susilawati et al., 2019), reducing water requirement, improving soil health in paddy fields, and reducing overall labor costs (Jeke et al., 2025; Kaur and Singh, 2017; Mwakyusa et al., 2024; Shekhawat et al., 2020). DSR is seen as the sustainable future of rice cultivation (Singh et al., 2024).

DSR seems to be a favored way of crop establishment in South Asia, with a report that 95% (Kaur and Singh, 2017) of the area devoted to rice in Sri Lanka is DSR (Hai Van et al., 2025). Vietnam, a rice-exporting country, appears to have benefited from DSR in reducing its overall rice production costs.

Despite its advantages, many issues have been reported in the literature regarding the cultivation of DSR. Among these issues are high weed infestation, risk of weedy rice evolution, increased soil-borne pathogens, nutrient disorders, poor crop establishment, blast incidence (Kaur and Singh, 2017), and bird infestation in the Philippines.

On the flip side, in the technological alley of DSR, scholars have advanced insights into alleviating the disadvantages of DSR practice. Among these insights are integration of weed management approaches that are collectively projected to reduce herbicide use by up to 50%; genomics-assisted improvements in rice varieties to address disease-related issues such as blast; and development of transgenic herbicide-resistant rice (Kashiwar et al., 2016; Shekhawat et al., 2020).

There are not many studies in the literature that examine the scaling of DSR in the Philippines. In other countries such as Sri Lanka and Vietnam, DSR appears to have already scaled (Hai Van et al., 2025; Kaur and Singh, 2017). Likewise, in terms of study types, the global literature seems to have focused on the technological aspects of DSR, such as how to breed rice varieties for DSR, improving the characteristics of existing varieties for DSR, nutrient-crop interaction, and water management efficiency. We did not find studies examining the social dimensions of DSR, which may be because scaling DSR is no longer of interest in other countries. Additionally, there is a dearth of policy-related studies on DSR scaling. In terms of mechanized DSR, studies in Southeast Asia, particularly Vietnam and Cambodia, examine its economic feasibility and potential to reduce emissions (Oyinbo et al., 2024; Van Hung et al., 2024). None of these studies, however, explored the potential of rice-farming communities to provide machine services to facilitate DSR scaling and provide additional income to farmers’ associations.

Theoretical framework

The scaling of agricultural technologies has been a long-standing subject of discourse. It remains a challenge that technologies, despite passing expert reviews and multi-location tests, are not adopted by their intended users. This outcome represents a significant setback for technology developers and a waste of resources for funding agencies, whether public or private. The Technology Acceptance Model (TAM) is among the most popular models of technology adoption. This theory, however, is criticized for its simplistic assumption of how technologies scale, i.e., perceived ease of use and perceived relevance. It is common knowledge that many technologies are perceived as valuable and easy to use, yet are not adopted by the intended users. For this work, we are applying the unified theory of technology adoption by Dissanayake et al. (2022). While not infallible, this theory has robust explanatory power, as it summarizes insights from 18 known theories of technology scaling (Figure 1).

Figure 1

Figure 1. Unified approach in looking at technology adoption in the agricultural sector (Dissanayake et al., 2022).

This theory advanced four key factors that affect technology adoption. These are factors related to (1) technology; (2) personal attributes; (3) social factors; (4) economic factors. An example of a technology-related factor is the ease of use of the technology in question, a key feature of the Technology Acceptance Model. An example of a factor relating to personal attributes is self-efficacy. Social factors relate to facilitating conditions, such as the availability of support structures that promote adoption. Economic factors boil down to the affordability of the technology. These four key findings form the foundation of the Unified Approach to Technology Adoption in the agricultural sector.

This framework is insightful, especially with particular reference to its emphasis on “facilitating conditions.” The environment in which any technology exists certainly affects its potential and actual uptake. From a sociotechnical standpoint, the recognition of subjective norms in this theoretical framework is laudable. The literature provides sufficient evidence that subjective norms influence farmers’ acceptance of technology within their communities or ethnic groups (Crudeli et al., 2022). The emphasis on intent, which later translates into action or not, is an important aspect of this framework. This is drawn from studies in social psychology, recognizing the many considerations a farmer or any decision-maker must factor into technology adoption decisions.

In general, this framework can capture the complexities of technology adoption in the agriculture sector [see the work of Woltering et al. (2019), for an interesting take on scaling as a facilitator of societal change]. This is a welcome addition to the wealth of frameworks available, especially since it seeks to synthesize insights from years of research on technology adoption. Capturing complexity is important, as the social world—the innovation system—is far from linear and straightforward.

Drawing on the theoretical framework outlined above, Figure 2 summarizes the state of play of the variables used in this study to explain how DSR scaling may unfold. We theorize that there are constraints and opportunities. Constraints can take the form of institutional bottlenecks, difficulties with the technology (e.g., a mechanized DSR machine), or farmers’ capacity to use it. Opportunities may include funding to purchase machines, networking opportunities for collaboration, or a law or local ordinance that supports the massive scaling of DSR. These constraints and opportunities are well within the four key factors outlined in Figure 1 for technology adoption.

Figure 2

Figure 2. Conceptual framework.

An important sub-factor under constraints and opportunities is the farmers’ entrepreneurial capacity to become service providers for the machine. This is a sub-factor we added, drawn from the work of one of the team members on the site, who highlighted that machine service provision could be key to scaling DSR in the area.

Given that DSR is a technical intervention, there must be technical prerequisites for scaling. In Figure 1, this concerns technology. Once all this is present, scaling will only take place if mainstreaming strategies are in place. Mainstreaming can take the form of reinforcement mechanisms such as social media posts, a radio program, or publications. Mainstreaming, as shown in Figure 1, will help create “facilitating conditions” for scaling.

Methodology

Living Labs as a methodological approach

In this research, we used Living Labs as our key research methodology (Gardezi et al., 2024). Living Labs originated in the information technology discipline, with evidence of conceptualization dating back to the 1970s. Over the years, Living Labs have evolved for use in other disciplines and sectors, including agriculture. The World Bank has recognized and is funding projects that use Living Labs as a key methodological approach.

There are many definitions and governing principles of Living Labs. Suffice it to say, amid these sometimes divergent views on what it is and what it is not, years of practice have yielded some key commonalities (see Følstad, 2008; Leminen et al., 2012). Among these commonalities is the value Living Labs place on co-creation in technology development. This means that members of the community actively participate in developing an artifact. The second is the emphasis on the research context: the intervention must occur in a natural environment. Thirdly, which relates to the first two, is the emphasis on experimentation. This means that stakeholders go through an iterative process to develop a technology or intervention that will be useful to them. Fourth, other scholars emphasize that in a Living Labs design, there is emphasis on the public-private partnerships or multi-stakeholder participation in general. Fifth, in a Living Labs approach, a multi-method approach is the gold standard, meaning using methods from disciplines such as sociology, engineering, economics, and others.

There are some discussions in the literature on how the Living Labs Approach differs from the Participatory Action Research. At the risk of being simplistic, the Living Labs is a broader approach that utilizes PAR principles, especially co-creation and some participatory techniques, to realize its goals. In terms of goals, PAR emphasizes social change through solutions developed with community members. Living Labs, on the other hand, focus on developing usable technologies for key stakeholders.

It should also be emphasized that the discourse on Living Labs has evolved. In the past, there were notions of “social shaping,” i.e., the idea that members of the community determine the trajectory of technological development (Ballon and Schuurman, 2015). Over the years, the discourse shifted to “mutual shaping,” i.e., the technology and the members of the community are shaped mutually by their interactions (Ballon and Schuurman, 2015).

Our Living Labs have the following components (Figure 3): harvesting insights, roll out of capacity enhancement activities, conducting Farmer Field Schools/experiments, and mainstreaming activities. The harvesting of insights component was conducted during the Inception meeting and the Participatory Needs and Opportunities Assessment (PNOA).

Figure 3

Figure 3. The Living Labs Approach in scaling DSR.

The Inception meeting was attended by stakeholders such as researchers who did some work on DSR in the past, farmers from other communities, and local officials. This meeting provided a productive exchange of ideas from various stakeholders. The PNOA was conducted at the project site using focus groups, in-depth, and key informant interviews among farmers and key informants to understand more deeply the development context surrounding DSR.

After the PNOA, capacity enhancement modules, such as those on how to operate the multi-purpose machine that will be used in the project, and on entrepreneurship to assist farmers in being a mechanization service provider, were rolled out. Insights on the content were likewise derived from the PNOA. The research team, in collaboration with the local farmers and agriculture officials, also conducted farmer field schools and experiments to come up with a crop management guide for DSR. After which, a number of capacity enhancements happened. Side by side with all these activities, the communication and policy team members were doing mainstreaming efforts through the conduct of Palay-Aralan, social media engagements, and policy brokering initiatives. Plenty of listening sessions were conducted throughout the project duration to ensure that the implementers and the members of the community were on the same page as far as project implementation was concerned.

Research sites

This research was conducted in the barangays (villages) of Bangcol and Guisguis in Sta. Cruz, Zambales. During the PNOA, the farmers in the area noted that it was the first time that a project of this kind was being conducted in their respective villages. In both sites, farmers complained that their once-arable lands were turned into mining-affected soils; hence, it would take a lifetime before rice cultivation could be made profitable again in their town. Mining for Nickel in the town started in 2005, specifically in Sitio Acoje, Barangay Lucapon South. Among the impacts of mining in the rice communities reported during the data collection were a reduction in the volume of water, soil and water contamination, yield reduction in rice, and issues on food safety. Key informants also noted that large-scale mining has, thus far, converted agricultural lands to mining areas.

There were many women farmers as male farmers shifted to mining owing to higher cash payments. Mining, while more dangerous, gives them an average of PhP 500 daily income. For context, income from rice is seasonal and highly dependent on overall yield and prevailing prices toward the end of the cropping season.

Most farmers in Bangcol practice DSR because their farms are mostly rainfed. In Guisguis, farmers alternate DSR and TPR because they have a stable supply of water. While DSR is perhaps the oldest crop establishment method in rice, it only gained massive interest in Sta. Cruz in 2018, because farmers felt the pinch of rising costs of inputs and the difficulty in finding farm workers.

Research participants

The main research participants were the farmers on-site, that is, 30 per site. They were selected based on two criteria: having farmed rice for a minimum of 10 years and serving as the primary farm decision-maker. The main research participants provided data for research question 1.

For research question 3, the participants were the main research participants, but the data just came from farmer-cooperators only given that the data obtained were results of field experiments. There were 5 cooperators in Bangcol and 2 in Guisguis. The setup included two demonstration sites that served as learning fields for the farmer-participants. A farmer-cooperator served as the lead in managing the site. The farmer-cooperators were chosen based on the availability of the resources that can be used for the experiments, such as land and the overall leadership potential.

A number of key informants were tapped in this study to shed light on various aspects of the project. Most of them participated in the Inception Meeting and, as necessary, on separate occasions during project implementation. Key informants were DSR researchers, representatives from other LGUs that implemented or are implementing DSR, and farmers from other towns (e.g., those from Infanta, Pangasinan) that have experience employing DSR. For the survey respondents, the information on the respondents is presented in the next section.

Methods

Different methods were used in this research, as shown in Table 1. For research question 1, we gathered insights from key stakeholders involved in the rice sector’s transition to direct seeding. Given the constraints of the COVID−19 pandemic, the study was conducted through an online survey distributed to a targeted sample of 489 individuals. These respondents were identified using available contact lists from various regional and municipal agricultural offices and key stakeholder groups, including the Department of Agriculture - Regional Field Offices (DA-RFOs), Provincial and Municipal Agriculturists, Agricultural Extension Workers, Chairpersons of Agriculture and Fishery Councils, rice researchers, and farmer leaders.

Table 1

Table 1. Methodological matrix.

Due to the absence of a comprehensive sampling frame, the sample was non-random and based on available lists, including individuals with a direct role in rice research, development, and extension, particularly those involved in transitioning from transplanting to direct seeding.

Table 2 provides a detailed breakdown of the number of emails sent, responses received, and response rate for each stakeholder group. The overall response rate was 44%, consistent with typical online survey response rates, especially during the pandemic, when many stakeholders were working remotely or facing other restrictions.

Table 2

Table 2. Salient information on the survey conducted.

The Inception meeting also generated insights for this research question. In responding to research question 2, we made a sample profitability analysis to demonstrate the business case for the machine service provision. Analysis is shown for service areas of 60, 80, and 100 hectares (see the results section for more details). For research question 3, we conducted a Farmer Field School during which several experiments were conducted. There, several plots were prepared to compare farmers’ practices and the best management practices (drum seeder and precision seeder). Several agronomic parameters were also recorded, such as plant height, productive tillers, and field grains. A series of data collection events was conducted to record the data needed throughout this study. For research question 4, we examined indicators of DSR uptake at the level of participants’ knowledge gains, as well as several indicators of stakeholder interest on the ground. Examples of interest include purchasing machines, requesting more training programs, or seeking legislative support. To assess the gain in knowledge, we collected the participants’ pre- and post-test scores and conducted significance tests.

Ethics

All in-depth interview participants signed a consent form outlining their rights as research participants, including the right to withdraw. They were also informed of the use of data, and that they will be anonymized in data presentation. Other research participants were likewise informed of their rights to participate in this research. We also note that this project was extensively reviewed by representatives from the Food and Agriculture Organization and the Philippine government, specifically the Department of Agriculture in the Philippines. Furthermore, the overall conduct of this activity was shown during the Inception meeting, with researchers, key officials present to ensure that the method was robust and that ethical safeguards were in place.

Results

In this section we present the results of the study, following the sequence of the questions asked. Each section also builds on each other to form a cohesive story exploring ways to scale DSR.

Constraints and opportunities in increasing the uptake of DSR

The top issues noted by the respondents pertaining to difficulties in increasing DSR uptake were pests (n = 56), weeds (n = 49), high seed requirement (n = 39), and water unavailability (n = 29) (Table 3). As regards pests, the respondents noted that DSR is prone to infestation by Golden Apple Snails (GAS), rodents, and birds. GAS is a usual problem in areas with drainage issues, while birds are usually a problem immediately after broadcasting the seeds. Weeds are a problem, especially in areas with no stable water supply. The respondents reported issues on how to manage weeds in their rice field effectively. There are also mentions of the evolution of weedy rice. The high seed requirement proved to be an important issue for DSR. The respondents noted that, compared with TPR, DSR requires about 60 to 80 kg/ha of seeds, whereas TPR requires only 40 kg/ha. Several rice diseases likewise emerged with reference to the practice of DSR.

Table 3

Table 3. Constraints in adopting DSR.

On a far second are weather-related concerns. The respondents noted that wet DSR proves challenging when it rains hard because the seeds get washed away easily. For dry direct seeding, the main issue is weeds due to the delay in the onset of rainfall. This issue is even more pronounced in recent years as farmers could no longer predict the onset of rain, making it difficult for them to plan accordingly. When seeds are washed away, farmers buy seeds again and replant, which means additional cost, and not to mention the time that is lost in the process.

The respondents reported that DSR is not promoted as widely as TPR, resulting in low DSR knowledge. On the contrary, there are numerous training programs on TPR as it is being promoted using the PalayCheck platform and in many programs by the Philippine government on rice agriculture. Machines for TPR, such as the mechanical transplanter, are also being distributed by the Philippine Center for Mechanization and Development (PHilMech).

Inadequacy of seeds supplied to farmers through the Rice Competitiveness Enhancement Fund (RCEF) also emerged in the survey. The context of this is that farmers only receive 40 kg of certified seeds per hectare. Farmers feel that they receive far less than what they need considering that their usual seeding rate is about 60–80 kg per hectare, with some reporting even higher seeding rates of 180 kg per hectare.

In relation to lack of skills on DSR is the finding that farmers simply prefer TPR. This, again, may have something to do with the massive support that has been extended to TPR in terms of training programs and overall research and development in the Philippines. DSR is also not massively promoted. There are mentions of extension workers not receiving tangible support to promote DSR. The respondents also noted that there is simply a lack of support technologies for DSR. For instance, they reported that, to their knowledge, there are no hybrid varieties developed for DSR. To a few respondents, they reported that DSR is simply just not the right method of crop establishment in their area. Lastly, a few respondents reported that there is no available workforce to work in the farm as the usual people who help in rice farming activities are already dependent on the cash that they receive from the 4Ps program (cash assistance) of the national government.

In terms of opportunities in scaling DSR, at least two key factors could be mentioned. The first was the support of the Masagana Rice Industry Development Programme (MRIDP), the major national rice program of the Department of Agriculture. MRIDP pushes for the promotion of direct seeding at the national level. The second was the realization of the rising cost of inputs, especially fertilizer and labor. Against the backdrop of the data collection was the onset of the Ukraine-Russia War that resulted in the skyrocketing of fertilizer prices. Additionally, the locals lamented that looking for farmworkers has been quite a challenge in recent years.

Establishing the business case for machine service provision

A Training Manual on Machine Service Provision for Dry Direct Seeding was developed by the team for associations interested in venturing into the agricultural machine service provision business. This module details the nitty-gritty of operating a service-based enterprise using dry direct seeding machines, specifically the Multi-purpose Seeder and Multi-purpose Reduced-till Planter.

The module highlights the importance of careful planning, resource allocation, and sound management strategies, including proper execution of services. Importantly, it introduces the economic dimension of machine service provision by showcasing how dry direct seeding machines technologies can serve as an additional source of income for cooperatives and farmer-entrepreneurs.

To reinforce this business opportunity, the module walks participants through cost and return analyses, break-even computations, and business plan development. These exercises help participants assess the financial viability of operating a machine service enterprise, offering them the tools to make data-driven decisions.

Below is an example of profitability analysis (Table 4) to illustrate the potential earnings from offering DDS machine services, focusing on the MP seeder:

• Assumptions:

• Acquisition cost, MPS: PhP90,000

• Life span: 5 years

• Salvage value: 10% of the acquisition cost

• Custom service fee: PhP1300 per ha

• Field capacity: 4 h per ha

• Field capacity (ha/day): 2 hectares per day

• Fuel consumption: 6 liters per hectare

• Price of diesel: PhP55.00 per liter

• Wage per day: PhP500.00

Table 4

Table 4. Profitability analysis, custom hiring of multipurpose seeder (MPS).

In this example, the table compares profitability across three distinct scenarios, representing potential areas in hectares (60, 80, 100) that the FCA could offer for the MP seeder’s custom hire. The gross returns are derived from the total service area covered and the custom service fee charged per hectare. The returns increase in proportion to the size of the service area despite the reduction in the service fee.

Costs are divided into cash costs (fuel, labor, and repair) and non-cash costs (depreciation). Fuel costs are calculated based on fuel consumption per hectare, with fuel priced at PhP55/kg. Labor cost is PhP500 per day. Depreciation accounts for the wear and tear on the machine computed using a straight-line method (Acquisition cost – Salvage value divided by the life span in number of years).

Net returns are determined by subtracting total costs from the gross returns, representing the actual income left after accounting for all expenses. The net-profit-cost ratio indicates how much profit the FCA earns for every peso spent.

The profitability analysis demonstrates that the FCA can generate favorable income by providing custom services from the MP seeder and making machine service provision a profitable agribusiness venture, particularly in areas facing labor shortages and rising transplanting costs. Across the various service area scenarios, the custom service provision remains profitable, as evidenced by positive net returns and high net profit cost ratios. Notably, the FCA will generate more profits as service areas increase; however, in terms of net profit-to-cost ratio, 60 hectares and a service fee of PhP 1,400 per hectare offer a higher return on investment at PhP 0.64 for every peso invested. In addition, the MPS machine can be custom hired for direct seeding of corn and mungbean, which can provide the farmer organization with additional income.

Technical comparison between DSR and farmers’ practice

Below, we show the comparative costs of the Farmers’ Practice and Best Management Practice setups at the two research sites. In Bangcol, the data came from the demonstration sites using the plastic drum seeder for DSR (Table 5). It appears that, across all the parameters tested, only “materials” proved significant, although the total cost was significant as well.

Table 5

Table 5. Actual costs (PhP) in employing farmers’ practice and best management practice (Plastic Drum seeder) in Bangcol.

In Guisguis (Table 6), the demonstration was on the use of a precision seeder for DSR. The table below shows that Farmer’s Practice is way better than the Best Management Practice (or in this case the use of Precision Seeder), with the cost difference of close to PhP 10,000. We could not establish if this result is significant as we only had two farmer-cooperators in the site; hence, the number of data entries is insufficient for a statistical test.

Table 6

Table 6. Actual costs (PhP) in employing farmers’ practice and best management practice (Precision Seeder) in Guisguis.

In terms of nutrient management, we conducted focus group discussions in each site to know the nutrient status of their soil. We found that all farmers were underapplying nutrients for their rice at the wrong time. In a hectare of ricefield, they only apply 1 bag of complete fertilizer (14–14-14 NPK) and 1 bag of urea (46–0-0 NPK) at 15–20 DAS interval, with additional application of 1 kg/ha foliar fertilizer at 30–35 DAS or when the rice plants are nearing their reproductive stages. Taking off from one of these gaps, we conducted simultaneous soil samplings in each of farmers’ ricefields. Soil samples collected were subjected to the process of Minus-One Element Technique (MOET).

These data were collected in collaboration with the farmers on-site; hence, it formed an important part of knowledge co-creation on DSR. Insights from these data were factored into the development of the PalayCheck for DSR. PalayCheck is an integrated crop management system for rice. In short, the PalayCheck for DSR was co-developed with the farmers in Sta. Cruz, Zambales, with the experts from DA-PhilRice serving as catalysts of the process. Note that these tables are shown to appreciate the process of involving farmers in knowledge co-creation on DSR (Tables 7, 8).

Table 7

Table 7. Soil deficiencies and nutrient recommendation based on minus-one element techniques (MOET) in farmers’ fields of Brgy. Bangcol, Sta. Cruz, Zambales.

Table 8

Table 8. Soil deficiencies and nutrient recommendations based on minus-one element techniques (MOET) in farmers’ fields of Brgy. Guisguis, Sta. Cruz, Zambales.

The tables below show the yield comparisons between the plots—Farmers’ practice and Best Management Practice. They are both from field experiments conducted under the project’s auspices. In Bangcol, the farmer-cooperators who employed manual wet direct-seeding reported yields exceeding 1 t/ha. Those who used manual transplanting showed that Farmer’s Practice was better than the Best Management Practice. The 1 t/ha yield increase meets the standard set forth by PhilRice for all its field-level experiments as reflected in its Strategic Plan. On the other hand, in Guisguis, both farmer-cooperators, regardless of the crop establishment method used, reported yield increments. The yield increment for manual wet-direct seeding is almost 2 t/ha, compared to 1 t/ha for manual transplanting (Tables 9, 10).

Table 9

Table 9. Yield comparison of techno demo (plastic drum seeder) and farmer’s practice in Brgy. Bangcol (2022WS).

Table 10

Table 10. Yield comparison of techno demo (plastic drum seeder) and farmer’s practice in Brgy. Guisguis (2022WS).

Indications of DSR uptake in the community

In this section, we report on indications of DSR uptake in Sta. Cruz. These are gains in knowledge, enactment of a local ordinance, purchase of new machines, and an increase in the area planted to DSR. The gain in knowledge is an important indicator, as DSR has many technical aspects. Below, we present the participants’ knowledge gains from the training programs conducted under the project’s auspices.

Table 11 shows the increase in knowledge of the training participants on direct-seeded rice: 16 members of the Guisguis-PAO Farmers Association and the Bangcol Farmers Association. Eight staff members of the local government unit (municipal and provincial levels) of Sta. Cruz also participated in the activity, held on May 4–5, 2022, in Barangay Guisguis. The training evaluation results show a 19.55% gain in knowledge (GIK) for participants.

Table 11

Table 11. Pre- and post-test scores and %GIK results for the participants.

In this training, there is a significant difference between participants’ pre- and post-test scores (p < 0.001). The participants’ average post-test score increased by about 2.44 points compared to their pre-test score.

Table 12 shows the participants’ knowledge gain from a season-long training on mechanized DSR. It was attended by 37 farmers (21 men, 16 women) from Sta. Cruz, Zambales and Infanta, Pangasinan. PhilRice staff were tapped as resource persons, while LGU personnel assisted in facilitating the conduct of training sessions, including fieldwork. At the end of the training course, the farmers achieved a 54.7% GIK (Table 12).

Table 12

Table 12. Pre-and Post-test scores and %GIK result of the participants.

This season-long training on mechanized DSR resulted in a significant increase in participants’ knowledge (p < 0.001). The participants’ post-test scores increased by about 9.324 points compared to their pre-test scores.

In interventions conducted at the ground level, it is important to identify indicators of interest at the local executive level. The support of local executives suggests the sustainability of the intervention in Sta. Cruz. The team lobbied to the newly minted officials of the local legislative council to enact legislation supporting broader promotion of DSR. The Sangguniang Bayan (the local legislative council) followed the recommendation after a dialogue with the team members. Hence, a local ordinance championing the wider uptake of DSR in Sta. Cruz has been enacted. This ordinance is noteworthy for the PhP 100,000 seed fund it includes. For context, it is common in the Philippines for pieces of legislation to lack adequate funding; hence, they are unimplementable.

Two years after the project terminated in Sta. Cruz, the town has invested in purchasing two units of the Multi-Purpose Seeder for distribution to farmers’ associations. This purchase means the LGU has increased its spending on DSR, as a unit of the Multi-purpose seeder costs about PhP 50,000-60,000.00. They were convinced the machine would improve their DSR practice. From the Municipal Agriculture Office of Sta. Cruz, the number of hectares that employ DSR as their crop establishment appears to be increasing (Table 13). For example, the area employing direct seeding almost doubled from 2024 to 2025, i.e., from 305 ha to 678 ha.

Table 13

Table 13. Area employing direct seeding in Sta. Cruz, Zambales.

Likewise, 2 years after the project was terminated, the local executives have supported the conduct of training programs on mechanized dry direct-seeded rice, and a technical briefing on the PalayCheck System (an integrated crop management system for rice).

Discussion

From the results above, it appears that there are similarities in the constraints raised by the farmer-participants with those in the literature (Padala et al., 2024). For example, a global meta-analysis of literature shows that weeds are among the key issues in DSR, and that overall, DSR’s outcome is dependent on “location, cropping history, clay content of the site, rainfall, weather, irrigation techniques, and micronutrient foliar sprays” (Bhatt et al., 2023). The literature emphasizes proper weed, fertilizer, and water management practices to address DSR challenges (Chaudhary et al., 2023).

Mechanized DSR appears to be the future of DSR, as it seeks to address key issues of labor and efficiency (Aravindakshan et al., 2024; Van Hung et al., 2024; Xiwen et al., 2023). In this study, there was a deliberate effort to demonstrate mechanized DSR using the precision seeder and the Multi-purpose seeder; however, farmers raised concerns about the lack of skills and training in mechanized DSR during the Participatory Needs and Opportunities Assessment at the start of the project. Additionally, there are several issues unique to the sites, such as inadequate seed supplies for farmers, insufficient promotion, and a shortage of workforce. The literature is silent on these issues. As regards the seeds supplied, at the time of data collection, the National government was running a seed distribution program that gave farmers 40 kg/ha of seeds. Farmers at the research sites feel this is inadequate, as the practice in DSR is 60 kg/ha or higher. They think that by distributing 40 kg/ha of seeds, the government is promoting transplanting. Lack of promotion and lack of workforce also did not figure prominently in the literature. The promotion aspect is understandable because DSR, as previously mentioned, may already be a dominant practice in other countries, such as Sri Lanka, where 95% of the ricefields are planted to DSR. The workforce issue not emerging prominently is surprising, given that globally, farmers are aging and young people are generally disinterested in farming.

It should also be reported that the literature is silent on machine service provision, which this current study has espoused, with a few exceptions, such as the case in Bihar, India. In the study by Brown et al. (2021), they highlighted that the limited number of fee-for-hire service providers is among the key issues in scaling DSR in India. We advance that pursuing machine service provision is a relevant and important move for the Philippines and comparable areas with workforce and labor cost issues. As shown above, the profitability analysis indicates a strong business case for pursuing machine service provision. We advance that the move to push for machine service provision adds an element of novelty in this study. We should report that studies have vouched for the advantages of using machines for direct-seeded rice, such as Sansen et al. (2019) in Thailand and Andriatsiorimanana et al. (2024) in Madagascar. In general, the discourse on mechanized DSR, especially machine service provision, does not seem to resonate quite loudly outside of Asia.

When it comes to the technical advantages of DSR over farmers’ practice, the results need some explaining. As shown above, for the plastic drum seeder, the only significant parameter was “materials”; all other parameters were insignificant, although the total cost was significant. This needs some explaining, as the key advantage of DSR is in labor cost. It should be noted that the figures reflect the cost for a small area of the demonstration farm. If computed on a per-hectare basis, the cost difference will be bigger. Also, under this project, labor was paid for by the project. In reality, as reported in the constraints section, finding farm laborers has become a key issue in recent years. Hence, with mechanized DSR, the advantage will be more pronounced. Another figure worth looking into is the cost difference, which is roughly PhP 3,000. While this difference is statistically insignificant, we argue that it actually is significant for smallholder farmers. For context, farmers in the Philippines borrow money to finance their ventures. Also, a family of five among rice-farming households in the Philippines has roughly P30,000 in monthly income, according to the 2022 Rice-based Farm Households Survey of PhilRice. This means that the difference in labor cost as reflected in the table below already constitutes 10% of their monthly income. Hence, it makes sense to argue that the PhP 3,000 difference should be significant in real terms. The same could not be said if a precision seeder is used for DSR.

Overall, when yield is factored in, the technology demonstration shows that the outcomes lean toward DSR at both sites. Statistically, however, this result is insignificant, although it meets the 1 t/ha yield increment set forth by PhilRice for its field experiments. This result is consistent with the literature, which suggests that DSR does not significantly outperform other crop establishment methods.

As regards indications of DSR uptake, many indicators could be cited. These are of interest to the locals, as shown by increased knowledge, support from local executives (as evidenced by the enactment of a local ordinance in support of DSR), and the purchase of additional units of the Multi-Purpose seeder. Seen from a rural development perspective, these outcomes indicate community ownership of the intervention, organic support from local stakeholders, and evidence of a bottom-up development approach.

Overall, there remain aspects of DSR that need to be ironed out for its uptake to be solid and unequivocal. For example, the numbers on the technical advantages of DSR over farmers’ practice need some firming up. While explanations can be provided in favor of DSR, as shown above, it would be more compelling if future studies could substantiate those advantages, especially for labor.

In hindsight, this paper has shown that there are good reasons to believe that DSR may indeed be worth pushing for as the preferred mode of crop establishment, especially in areas where it is suited. This paper also highlights several aspects of scaling that emerged from the community, owing to its members’ involvement in exploring DSR’s scaling efforts. Hence, this paper goes beyond technical outcomes in cost, nutrient management, and yield to focus on the process of scaling.

Explaining the outcome of scaling efforts using the combined Living Labs Approach and the Unified Approach to Technology Adoption

In this section, we reflect on how the combined Living Labs Approach and the Unified Approach to Technology Adoption may help explain the scaling that happened in Sta. Cruz. Figure 4 below shows the key principles of the Living Labs Approach: co-creation in technology development, the natural environment, and experimentation. In the same figure, we show the aspects of the Unified Approach to Technology Adoption that helped realize the principles of the Living Labs Approach. Below, we detail how integrating the Living Labs Approach and the Unified Approach to Technology Adoption may help explain DSR’s scaling.

Figure 4

Figure 4. Theoretical integration of the living labs approach and the Collective Approach to Technology Adoption.

Co-creation increased the likelihood of scaling DSR

The local farmers were heavily involved in the overall design of the project, particularly in developing mechanisms to scale DSR. This was demonstrated in various instances throughout the project, including during the inception meeting, PNOA, and spot checks by the project team. The farmers had plenty of opportunities to share insights and interact with the experts, which, together, resulted in the complementation of efforts and wisdom on how DSR might scale in the town.

During the inception meeting, an aspect of the theory that emerged was “external influence,” in which representatives from other LGUs with experience implementing DSR in their respective towns shared their experiences. Hence, these insights sharpened the implementation in Sta. Cruz, in the sense that potential pitfalls were forewarned and success enablers noted. The insights from researchers who had previously worked on DSR were the same. Perhaps, one aspect of the project that should be highlighted is transdisciplinarity. By onboarding multiple experts and having them interact with farmers and other important stakeholders in the town, the Project provided the “facilitating conditions” to optimize “external influences,” thereby contributing to a favorable outcome—co-creation in the technology development process. In this whole process, instead of treating farmers’ knowledge as inferior in some ways or not scientific, it was treated as a form of knowledge that was never inferior to any other form.

Paying attention to the natural environment is key to enhancing DSR uptake

One of the key strengths of this project was its deliberate effort to understand the nuances in the development context. With the social science researchers on board, they set out to explore the various social elements that were getting in the way or enabling (at some point) the scaling of DSR. This was shown, for instance, in doing scoping work with Infanta, Pangasinan, the neighboring town of Sta. Cruz, Zambales, to understand the dynamics in DSR uptake. It was also in these social studies that the issue of mining emerged. Later, the team learned that the mining issue was creating negative vibrations toward anything related to farming. The team collected insights such as “it will take a lifetime before the once-arable lands become productive once again,” as they are now mining-affected soils. The mining situation has led farmers to believe that agriculture is a dying industry in their town; hence, they are reluctant to any attempt to revive it through technology or practices like the DSR.

Cognizant of this situation, the team employed interpersonal communication techniques (as denoted in the theory) to explain to the farmers what the technology could offer. This was shown in the way the experts explained during the training programs and during the Farmers’ Field School (please refer to the succeeding subsection for more information). Additionally, the team reached out to the members of the Sanggunian Bayan (the local legislative council) to discuss the situation in the town regarding the overall reception to the technology and to farming itself. We argue that, through this dialogue, the town officials were convinced to enact local legislation to support the broader promotion of DSR. We emphasize that this is not local legislation for its own sake—it was more than a piece of paper, as the local legislative council allocated P100,000 as a seed fund for this purpose. For context, it is common in the Philippines for local legislation to be enacted without clear funding sources. From a rural community perspective, this act is a strong indication of interest and sincerity in pushing for the scaling of DSR. The approved DSR policy was implemented in the Municipality of Sta. Cruz, Zambales, through capacity enhancement initiatives, including training on mechanized dry direct-seeded rice and technical briefing on the PalayCheck System for farmers in rainfed areas. In support of this, the LGU also distributed MP seeders to farmers’ associations.

This level of engagement by the LGU attests to the creation of a “facilitating condition” for DSR uptake. By being involved, the LGU also helped address issues relating to “institutions,” specifically by providing a seed fund, which, in theory, pertains to “availability of capital resources.”

Experimentation helped address farmers’ doubts

This project set up Farmer Field Schools in Sta. Cruz to demonstrate the different ways DSR can be done, for example, manually or with machines. This move is not new. It is being faithful to an adage in doing agricultural extension: to see is to believe. From there, the farmers interacted with agronomists, weed science experts, and rice machine experts to develop a technology package for their town on DSR. The farmers were a part of the process every step of the way. Going back to the framework, this level of farmer-expert interaction contributed to addressing “self-efficacy” issues on the side of the farmers. On the other hand, this is also consistent with the “mutual shaping” discourse in the evolution of the Living Labs Approach. As earlier alluded to, it is not just the social aspects that are shaping the technology; the technology and the practice are shaping the social environment as well. In those experimental series, it was shown that there is a form of DSR that might work for their context, which, in the framework, pertains to “compatibility.” Throughout the project implementation, as previously mentioned, the locals expressed gratitude to the team, as it was, according to them, the first time a project of this kind and scale was conducted in their villages. During those instances, the locals realized how valuable and easy to implement DSR is, which, in theory, refers to perceived usefulness and perceived ease of use.

Conclusion

While doing these quick checks relative to the integration of Living Labs and the Unified Approach to Technology Adoption, a critical look at the context might reveal something that could blow these favorable outcomes away. Returning to the development context, the farmers reported that much of the once-arable land for rice cultivation is now affected by mining. Many lament that it might take a lifetime for rice farming to be profitable again, sans changes in their development context. Hence, this is worth pondering and perhaps highlights the robustness of the Living Labs as a methodological approach, with its emphasis on ‘real-life’ settings. Perhaps the key learning from this study is that scaling is primarily a function of the development context. This work shows that the team may have achieved some success in promoting the use of DSR, but these technological interventions are at the mercy of the prevailing development context in the area. If anything, the team also pushed for something that might influence the scaling trajectory of DSR in the area: the local ordinance—but this, too, rests on the political climate, now and in the future, in the town.

There are several reasons this research is novel. First, this is the first research in Asia’s rice-growing countries to scrutinize the scaling of DSR at this level. Usually, scaling studies focus solely on economic aspects. This current study did so much more, guided by the Unified Approach to Technology Adoption and the Living Labs Approach, to include the wider bureaucracy, the ‘real-life setting’, and others. Second, and related to the first, this is the first study to combine the Living Labs Approach and the Unified Approach to Technology Adoption in a scaling study of agricultural technologies. We found that these two complement each other and recommend incorporating insights from them into future studies. Third, this study demonstrates how transdisciplinarity can help expose salient aspects of technology scaling that are often glossed over within the usual discipline-specific silos of scaling studies.

Recommendations

We close this paper by highlighting some recommendations that may influence scaling efforts of agricultural technologies:

• Pay attention to the development context, the ‘real-life’ setting. We learned from this work that scaling technologies is hardly a function of a technology’s quality alone. The various elements in the social system – from supportive stakeholders to broken bureaucracies to favorable or unfavorable reception to technologies – project implementers must pay attention to the tug-of-war among these elements. Fixing attention to just one of them and forgetting the rest will never be helpful.

• Ensure that intended users co-create the technology and the process. Perhaps this is a key element in any hints of success in scaling DSR in Sta. Cruz. The farmers were involved in almost every aspect, with several listening sessions in between to ensure that the implementers and the intended users were on the same page. Toward the end of the project, the farmers were re-energized by the prospect of a cheaper way to establish crops and by the possibility of making some money through custom service provision.

• Seal commitment of the local executives, but work harder prior to asking for it. In this project, we saw strong interest among farmers — it never waned over the course of 2 years, with different team members alternating to visit the site. This, however, we attribute to the prior work done by some of our team members on the site. Prior to this current project, some of our team members had managed to show something on the multi-purpose seeder. This, we argue, had significantly helped win over the locals’ trust. This current project benefited from the previous one. Hence, it proved easy to win the support of the local executives. While a cliché, it is indeed true that trust is earned through consistency; there are no shortcuts to winning over local stakeholders’ support.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

Ethical approval was not required for the studies involving humans because PhilRice, the implementing agency does not have an Ethics Committee yet. This project, however, was reviewed internally at PhilRice and by FAO during an Inception Meeting, and by the Department of Agriculture in the Philippines prior to its conduct. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

Author contributions

JM: Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Supervision, Visualization, Writing – original draft, Writing – review & editing. EQ: Conceptualization, Funding acquisition, Resources, Writing – review & editing. KB: Funding acquisition, Resources, Supervision, Writing – review & editing. ACo: Conceptualization, Methodology, Project administration, Validation, Writing – review & editing. AM: Conceptualization, Formal analysis, Project administration, Writing – review & editing. EB: Conceptualization, Methodology, Project administration, Supervision, Writing – review & editing. DD: Conceptualization, Formal analysis, Investigation, Project administration, Writing – review & editing. MA: Investigation, Project administration, Supervision, Writing – review & editing. ACa: Formal analysis, Supervision, Writing – review & editing. DE: Project administration, Supervision, Writing – review & editing.

Funding

The author(s) declare that financial support was received for the research and/or publication of this article. This research received funding from the Food and Agriculture Organization and Department of Agriculture-Philippine Rice Research Institute.

Acknowledgments

The research team extends its gratitude to the Food and Agriculture Organization for funding this research and development project. The partners on the ground, particularly the staff of the Municipal Agriculture Office and the farmer-cooperators in the barangays of Bangcol and Guisguis of Sta. Cruz, Zambales, is also recognized. We also thank Mr. Warren Cacho for the statistical support.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The authors declare that no Gen AI was used in the creation of this manuscript.

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