Impact of Farmer Field School Palaycheck In The Irrigated Rice Areas In The Philippines

Transcription

1 Philippine Journal of Crop Science (PJCS) December 2015, 40 (3):30-42 Copyright 2015, Crop Science Society of the Philippines Full Paper Impact of Farmer Field School Palaycheck In The Irrigated Rice Areas In The Philippines Alice B. Mataia *, Resi O. Olivares, Rowena G. Manalili, Ronell B. Malasa, Aileen C. Litonjua, Guadalupe O. Redondo, Rhemilyn Z. Relado, Suenie Jane Paran and Charis Mae A. Tolentino Philippine Rice Research Institute, Maligaya, Science City of Muñoz, Nueva Ecija 3119, Philippines. * Corresponding author, ab.mataia@philrice.gov.ph The Farmer Field School-PalayCheck (FFSP) is a knowledge and learning-based approach that aims to improve yield and income of farmers through the adoption of PalayCheck platform, a dynamic rice crop management system that presents the best key technology and management practices as key checks. It was implemented in by the Philippine Rice Research Institute (PhilRice) in support to the 100% rice self-sufficiency target of the government. The FFSP was operationalized through the deployment of Rice Self-Sufficiency Officers (RSOs) in 24 provinces with yields below 4 t ha -1 in irrigated areas. This study assessed the impacts of the FFSP using the 2009 two season baseline and seasonal monitoring survey data. Impacts of the project were measured using descriptive statistics, costs and returns analysis, and frontier production function adopting the before and after project evaluation approach. Results showed positive impacts of the project in relative to More farmers adopted different combinations of the 8 key checks with 18% completely adopting, resulting in an improved technology adoption, management practices and technical efficiency scores of farmers. Adoption of key checks increased yield by 9% (0.33 t ha -1 ), and reduced per unit production cost by 2.82% (PhP0.23 kg -1 ), which translates to a notable increase in net income by 25% (PhP3,907 ha -1 ) and returns to investment by 18%. Total rice areas covered by the project generated an incremental palay output of 3,457 t with 0.022% share to domestic total production in. The FFSP is a good extension approach for capacitating farmers and has the potential to shift the yield from low to high level. The following are recommended to achieve significant impact: enhance TE level of farmers; establish more field demonstrations to facilitate PalayCheck dissemination and diffusion; expansion of areas to cover more farmers; and periodic monitoring and feedback for its sustainability and improve implementation. Keywords: farmer field school, impact assessment, integrated crop management technologies, palay check, productivity, rice self-sufficiency INTRODUCTION Rice food security and self-sufficiency has been a development goal and policy objective of the Philippine government (PhilRice ). The country is consistently rice food secure even if total rice production perpetually lagged behind total rice consumption due to the country s dependence on the global rice market. However, the global rice price spikes in 2008 placed the country s rice food security at risk (DA 2012). This served as a wakeup call for the government not to totally rely on the global market, but to consider seriously its long policy objective of pursuing and attaining rice self-sufficiency by end of 2013 and maintain it through 2016 (DA-BAR 2011). Inspired by the 1 t ha -1 yield increase due to PalayCheck system (DA 2008; Lemerle ), the Philippine Rice Research Institute (PhilRice) promoted it nationwide in using the Farmer Field School (FFS) extension approach in support to the attainment of the rice self-sufficiency goal of the government. PalayCheck is a rice Integrated Crop Management System for irrigated lowland rice farming (Yabes 2008). It integrates and balances relevant technology and crop management options with farmers' learning to improve productivity and profitability in an environment-friendly manner (Cruz et al. 2005). It prescribes that technology recommendations for yield improvement be developed and transferred to farmers as a holistic and integrated package and not by component (PhilRice 2007). PalayCheck covers the principal areas of crop management such as seed quality, land preparation, crop establishment, nutrient management, pest management, water management, and harvest management. It encourages farmers to manage their rice crop according to targets by measuring crop performance and analyzing results, and it provides standards in the form of Key Checks that guide farmers on what to achieve, guide on how to assess the Key Checks, and provide recommendations on how to achieve the Key Checks. In such way, PalayCheck will help farmers learn their experiences while improving their crop management practices (Castaňeda 2007). The Farmer s Field School (FFS) was adopted by PhilRice as a good extension system to facilitate adoption of PalayCheck. According to Balisacan et AB Mataia et al.

2 al.(2006) extension contributes 15% of the total increase in rice yield. Likewise, FFS is a popular education and extension approach worldwide, which use experiential learning and a group approach to facilitate farmers in making decisions, solving problems, and learning new techniques (Pontius et al. 2000; IFRI 2002). The Farmer Field School PalayCheck (FFSP) is envisioned to improve yield and income of farmers through access and availability of PalayCheck technology. It is also viewed that this knowledge and learning based approach is more effective and sustainable than the traditional extension method, which is directive (Yabes et al. 2008). The Farmer Field School-PalayCheck approach was operationalized through the deployment of Rice Self- Sufficiency Officers (RSOs) in the target rice producing provinces. The RSOs together with farmer innovators (FIs), engaged in the establishment of variety trial plots in farmers fields to determine the most suitable variety in the areas, and to identify location-specific technologies anchored on the PalayCheck platform. This also serves as the training fields for participating farmers (PFs) in the FFSP. The RSOs also lead the FFSP to capacitate PFs by promoting the integrated crop management technologies such as PalayCheck. Each RSO is required to set-up at least four sites of FFSP per year. After training the farmers for two cropping seasons, they are required to establish four more sites in another area where they will begin training new set of farmers. The FFSP was mobilized in irrigated areas where rice yield is below 4 t ha -1. A total of 24 provinces with 165 sites of FFSP were established by RSOs during its first year of implementation in. Against that background, the study assessed the actual impact of the Farmer Field School-PalayCheck (FFSP) system after its two seasons implementation in 24 provinces. Specifically, the study determined the farm level and patterns of PalayCheck technology adoption and impact on yield; assessed the immediate changes of FFS- PalayCheck on farmers crop management practices and technology adoption, input use and production cost; assessed the actual impacts of FFS- PalayCheck on farmers yield, income, technical efficiency score of farmers, and total rice output; determined farmers perceptions on the effectiveness of the FFS-PalayCheck ; and formulated sets of policy recommendations to facilitate diffusion and sustainability of the FFS-PalayCheck system. MATERIALS AND METHODS Data Sources The study used baseline and two-seasons monitoring survey data gathered by the staff from the Socioeconomic Division (SED) of PhilRice. The baseline survey consisted of 2009 dry and wet season rice production input and output data collected prior to the FFS- PalayCheck implementation in 24 rice producing provinces in the Philippines. The two-season monitoring survey included the dry and wet season rice production data of the FFS-PalayCheck intervention. The specific data and information collected included Table 1. Province Distribution of sample farmers per province, Philippines, Number of Sample Farmer Innovator* Participating Farmer** Abra Agusan del Norte Aklan Albay Antique Apayao Aurora Bulacan Cagayan Camarines Sur Capiz Compostella Valley Davao del Norte Ilocos Norte Iloilo Isabela Negros Occidental North Cotabato Nueva Ecija South Cotabato Sultan Kudarat Surigao del Norte Zamboanga del Norte Zamboanga Sibugay TOTAL *Farmer Innovators (FIs) - are those farmers that allowed a portion of their rice farms as trial/learning fields for rice varieties and PalayCheck technologies; **Participating (PFs) are those farmers that are trained on PalayCheck technologies together with the FIs and at the same time observers of the demonstration field or learning field. farmers socioeconomic and farm profile, and key impact indicators such as: crop management practices and technology adoption, yield level, input use and costs, palay price, and rice income. perceptions on FFSP project and performance of RSOs was also gathered. The panel sample farmers covered 1,606 farmers selected from the total 3,665 farmers who participated in the FFS-PalayCheck from 165 FFS-PalayCheck sites in 24 provinces (Table 1). From each site, the 3 FIs were automatically drawn, and 9 PFs were chosen using simple random sampling technique, which translated to a total of 12 farmers per site. For site with less than 12 farmers, a complete enumeration was employed. The sample provinces consist of: Abra, Apayao, Ilocos Norte, Cagayan, Isabela, Aurora, Bulacan, Nueva Ecija, Albay, Camarines Sur, Aklan, Antique, Capiz, Negros Occidental, Agusan del Norte, Compostela Valley, Davao Norte, North Cotabato, South Cotabato, Sultan Kudarat, Surigao del Norte, Zamboanga del Norte and Zamboanga Sibugay (Figure 1). Impact of farmer field school-palaycheck 31

3 Figure 2. Simple comparisons of yield: before and after the project intervention. Figure 1. Location of the FFS-PalayCheck sites, Philippines Data Analysis To measure the impacts of the FFS-PalayCheck after two cropping season implementation, the approach before and after project intervention was adopted by comparing what happened before and after the program (Khandker et al. ). Figure 2 illustrates the before and after project evaluation approach. The before case refers to prior implementation of the FFS -PalayCheck, while after scenario corresponds to what has been observed after two-season implementation by adopting the PalayCheck platform and applying the feature of farmer field school (FFS) approach. The estimated impact of the project is the difference of the before and after outcome. The before and after scenario used panel data that included the baseline data which measure the outcome before the intervention, and the monitoring data that measure the outcome after two-season implementations of the project. The following comparative analyses were employed in assessing the actual impact of the Farmer Field School - PalayCheck : Level and patterns of PalayCheck adoption. The level and extent of adoption was estimated based on the number of farmers who tried and who did not try the key checks. Adoption level was clustered into: 1) adoption of individual key check, 2) multi-key check adoption, and 3) full adoption of the 8 key checks. The key checks adoption per season of the FFS- PalayCheck operation was also determined to evaluate the patterns of key check adoption. The impact on yield of the number of key checks achieved was also examined. Comparative analysis. To measure the impacts of the FFS-PalayCheck by adopting PalayCheck technology, the results of the dry and wet seasons project interventions were compared with 2009 dry and wet seasons baseline survey data. The following socioeconomic indicators, as bases for the comparative analysis include changes in: 1) crop management practices and technology adoption, 2) input use, 3) production costs, 4) net income, and 5) technical efficiency (TE) scores of farmers. Total Rice Supply. The impact of the FFS- PalayCheck by adopting the PalayCheck technology on total rice supply and self-sufficiency level was estimated by the incremental yield and total rice area in the FFS-PalayCheck sites. The additional total rice production was the contribution of the project to the total rice output and rice sufficiency level at the national scale. Technical Efficiency. To determine if technical knowledge of farmers improved through attending farmer field school on PalayCheck, the technical efficiency (TE) level of farmers was investigated. Differences in TE level were determined by comparing the before and after project scenario. RESULTS AND DISCUSSION Socioeconomic Profile of Rice Table 2 describes the profile of farmer participants in the FFS-PalayCheck. Farmer participants were still on their productive years with mean age of 50 yr old, have 5 household members, and have at least one member working in the farm. Male dominates the total participants because most male farmers are the rice farm operators. This indicates the patriarchal structure of Philippine household. Majority of the participants have long years of experience in rice farming, averaging 22 yr, while almost all have formal education with high percentage of farmers with secondary and college education. This suggests that more educated farmers are into rice farming and are assumed to be more receptive to technology AB Mataia et al. 32

4 Table 2. Socioeconomic profile of sample rice farmers, Philippines Parameters Farmer Participating Innovators Age Household size No. of household working in the farm Farming experience Male : Female 83% : 17% 64% : 36% 69% : 31% Educational Attainment n % n % n % No formal schooling Elementary High School College Vocational/Others Post-graduate Household Income Composition PhP % % % PhP PhP Share Share Share Rice Farming 211, , , Non-rice farming 31, , ,021 9 Non-agriculture 64, , , Total 307, , , Subsistence Characteristics Poverty Incidence (< poverty threshold) 37.63% 58.05% 53.08% Food Poor (<food threshold) 28.79% 44.23% 40.47% innovation. The socio-demographic profile of the sample farmers conforms with the general characteristics of farmers described by the Bureau of Agricultural Statistics (BAS 2013). The main source of income of the sample farmers was rice farming with 45% share to the total household income. were also engaged in other farming and non-farming activities to supplement their income from rice farming. Income from non-farming has significant share of 37% of the household total income, which are derived from employment, remittances abroad, business and others. The importance of other sources of income for the rice farm households were also reported in earlier studies (Estudillo and Otsuka 1999; Castillo 2006). Using the official poverty and food threshold level in the rural areas, 53% of the farmers were considered poor, while 40% were regarded as food poor, implying that poverty incidence is still high in the rice farming areas. This result corroborates the results of Casiwan (2006) and PSA (2014) that poverty in the rice farming sector is still widespread, with around 40% of rice farmers considered poor. The socioeconomic characteristics of both groups of farmers were equally the same, except that FIs were more financially secure since their income was 69% higher than their counterparts. Moreover, incidence of poor and food poor were lesser compared to PFs, which can be explained by the amount of their total household income portfolio. In terms of human capital, there were more FIs with college degrees compared to PFs. Characteristics of Rice Farms Operated by Farmer participants cultivated an average rice area of 1.67 ha, suggesting they were relatively small scale. Rice areas range 0.1 to 13 ha, implying the large variability of rice area cultivated by farmers. Around 60% of the farmers own the rice land. Two-thirds (65%) of the farms is serviced by NIS/CIS, 25% by STW/SFR/SWIP/Pump, and 10% depend on rainfall. In terms of water availability, 66% of the farms received sufficient irrigation water, while others experienced insufficient and/or excessive water. The soil types were considered good for rice growing, with 39% clay and 31% was loam. Infrastructure was poor, with 53% of the road network from farm to market center classified as earth road, making transport of inputs and outputs more costly (Table 3). Adoption of the PalayCheck Technology and Impact on Yield The PalayCheck technology is a holistic and integrated package of component technologies consisting of eight key checks. One of the objectives of FFS-PalayCheck is to facilitate and increase adoption of the key checks to improve yields (Yabes et al. 2008). Adoption rate of the eight key checks at the farm level was determined during the two-cropping season intervention of the FFS-PalayCheck. Level and Patterns of Adoption of Key Checks The adoption of key checks ranged 50-94%, which suggests the high receptiveness of farmers on the Impact of farmer field school-palaycheck 33

5 Table 3. Characteristics of rice farm operated by sample farmers, Philippines Parameters Total Rice Farm Area Rice land ownership Source of Irrigation Farmer Innovators Participating NIS/CIS % % % STW/SFR/ SWIP/Pump 97 25% % % Rainfall 24 6% % % Water Availability Sufficient % % % Insufficient 96 24% % % Excessive 15 4% 41 3% 56 3% Others 2 1% 14 1% 16 1% Road Structure Concrete % % % Asphalt 25 6% 59 5% 84 5% Earth % % % Others 17 4% 48 4% 65 4% Soil Texture Clayey % % % Loamy % % % Sandy 39 10% % % Silty 8 2% 24 2% 32 2% Others 70 18% % % potential of the technology (Table 4). The high adoption rate can also be due to the economic merits (productivity and profitability) of the PalayCheck technology. Across season, there was an increase in the rate of adoption of the key checks from its initial dry season implementation relative to its second season implementation in wet season. Among farmers, FIs had higher adoption rate relative to PFs. This is because FIs are engaged as farmer-partner in the demonstration field where they learned by doing the PalayCheck technology. This finding is supported by the study of Paris et al. (2008), wherein a technology is better adapted if the adopter is actually involved in all the stages of the research process rather than just being involved as observer of on-farm experiments. Among key checks, the least adopted was Key Check 1 (KC1) - use of high quality seeds of a recommended variety, which conforms with the finding of Castaňeda (2007). Many sample farmers still prefer to plant the common or popular varieties in the areas, particularly farmers home saved seeds (good/farmer s seed). Constraints to adoption of KC 1 could be due to high price of quality seed (Malasa and Launio 2015), and the lack of available quality seed of the preferred variety (Floyd et al. 1999). The most adopted was the Key Check 8 (KC 8) cut and thresh the palay at the right time. are already familiar and knowledgeable of KC 8 because it is generally practiced. Moreover, it is relatively easier to manage and does not require much time, skill, and financial cost. Key Checks and Yield The PalayCheck is a rice integrated crop management system consisting of several factors and management practices that are interdependent and interrelated. To have a significant impact on increasing yield, PalayCheck must be transferred to farmers as a holistic and integrated package of technology since this technology is based on the principle that as number of key checks adoption increased, yields also improved (Castaňeda 2008; and Manalo and Cruz ). with the most number of key checks achieved had higher yields relative to those who adopted less number of key checks (Table 5). During the project implementation, the number of key checks achieved improved from DS to WS cropping, suggesting the potential of FFSP in helping farmers learn and recognize the need to adopt best farming practices. In addition, this can be attributed to the improved knowledge of farmers on the yield potential of the key checks. Based on the results, there was a shift on the number of key checks adopted, i.e. the percentage of farmers that adopted less than five checks declined, while the percentage of farmers that achieved higher total number of key ckecks (6 8 checks) inreased. As per farmer classification, more FIs achieved a total of 6-8 key checks compared to PFs. This can be ascribed to the involvement of FIs in the demonstration/learning field and personally experiencing the key checks practices. Impacts of the Farmer Field School - PalayCheck Farmer Field School - PalayCheck is expected to increase the total rice supply and net rice farm income through improvement in rice yield, and reduction of production costs through adoption of the key checks, respectively. The measurement of impact was done through comparison of the before and after scenario using descriptive statistics, costs and returns analysis, and stochastic frontier production function. Analysis was done at the national level and farmer classification. Impact on Technical Efficiency Level. The FFS-PalayCheck project was intended to enhance the technical efficiency of farmers. To measure the possibilities of technical gains, the Cobb- Douglas stochastic frontier was used in estimating the farm level technical efficiency (TE) of farmers. The Cobb-Douglas stochastic frontier model is specified as: n lny i = β 0 + Σ β ij ln X ij + v i - u i j=1 where: Y i is yield in kg ha -1 of the i farmers; X ij is a vector of a set of inputs used by farmers I; and vi - u is an error term. AB Mataia et al. 34

6 Table 4. Patterns of keycheck adoption, DS and WS project implementation, Philippines Key Checks Number 1 - Used of high quality seeds of a recommended Variety 2 - No high and low soil spots after a fallow period 3 - Practiced synchronous planting after a fallow period 4 - Sufficient number of healthy seedlings 5 - Sufficient nutrients at tillering to early panicle initiation, and flowering 6 - Avoid excessive water or drought stress that could affect the growth and yield of the crop 7 - No significant yield loss due to pests 8 - Cut and threshed the crop at the right time Number of keychecks attained Pattern of Keychecks Adoption DS FIs WS DS WS PFs Percent of Adopted PFs The technical efficiency of farmers was determined using the equation: ^ TEi = exp(- u i ) = exp (- E(u i ε i )) FIs FIs PFs Yield level (t ha -1 ) by no. of key checks attained Table 5. Pattern of keychecks adoption, yield level and number of keychecks attained, by season, and farmer class, Philippines, Based on the estimates of the stochastic frontier production function, the TE scores of farmers that participated in the FFS-PalayCheck prior to the implementation of the project ranged 0.01%-0.97%, with a mean of 51.2%. This indicates a large variability in the farmers TE scores. The range of TE scores imply that an average farmer in the sample provinces could save 47.2% (1[51.17/96.99]) of costs, and the Table 6. Mean and percentage distribution of technical efficiency score of sample farmers, Philippines TE Score FIs 2009 Baseline Data PFs Project Implementation FIs PFs > > > Mean TE Minimum TE Maximum TE FIs = Farmer Innovators; PFs = Participating most technically-inefficient may attain 98.95% cost saving (i1-[1.03/96.99]). Similar trend was also observed after a year of project implementation. TE score was 55.3% with 8% improvement compared to the mean TE score prior to the project implementation. This can be attributed to farmers participation in the FFS-PalayCheck whose technical capacity might have been enhanced. Among farmer classification, TE scores also increased, i.e. 9% on FIs and 8% on PFs. Overall, the mean TE score after two season implementation of the FFS-PalayCheck was 55.3% (Table 6). This implies that about 45% of palay output is lost due to the inefficient use of resources. produced only 55% of the maximum attainable output for given input level. Hence, the need to enhance the farmers TE particularly on the efficient use of production inputs. used more seeding rate on hectare basis, and farmers have not optimized their NPK fertilizer application. The actual impact of the project on the technical gains of farmers was determined by the percentage distribution of farmers by TE scores before and after the project implementation. The percentage of farmers with mean TE scores of less than 40% declined from 27.6% to 22%. Similar trend was observed on the percentage of farmers with mean TE scores between 41 to 60%, indicating a shift from low to high mean TE scores. Similarly, the percentage of farmers with mean TE scores from 61 to 80% and from 81 to 100% increased in compared with the 2009 baseline data, which suggests that the FFS-PalayCheck had been quite effective on enhancing the ability of farmers to adopt some of the recommended best farming practices. This was also observed for both farmer groups (FIs and PFs) as shown in Table 6. Impact on Crop Management Practices and Input Use. The knowledge gained and adoption of the key checks is expected to change the crop management practices of farmers particularly on the use of recommended technologies and their applications. In this section, the technology adoption and input utilization of farmers are presented, particularly the assessment of the project impact at the farm level after its twoseason operation. Impact of farmer field school-palaycheck 35

7 Adoption of Quality Seed and Seeding Rate. Prior to project intervention, about 65% of the farmers were already using quality seeds such as hybrid, registered and certified. The high adoption rate of quality seeds can be partly due to the government seed subsidy program where a portion of the seeds used by the farmers were provided by the Department of Agriculture (DA) and Local Government Units (LGUs). Within two seasons of implementation, adoption of certified and hybrid seed increased by 9 and 3%, respectively. Adoption of good seeds increased by 19%, while farmers seed adopters declined by 4%, which can be attributed to farmers practice of seed replacement (Table 7). Based on the study of Diaz et al. (1994) on seed management of farmers in Central Luzon, farmers replaced their seeds every year and every 2 years to maintain its quality. There was a possibility that some of the farmers who planted certified seed in 2009 opted to reuse their seeds in, which resulted in an increase in the adoption of good seed. Overall, the increased adoption of quality seeds suggests that some farmers became more receptive on Key Check 1 (KC1) use of high quality seed recommended in the areas. However, some farmers were also constrained by the high price of quality seed and unavailability of preferred rice variety, hence 36% of them planted their home- saved seeds. Among farmer groups, there were more PFs who shifted to adopting quality seed relative to their counterparts. Comparison of before and after project intervention shows that seeding rate on the average declined by 4% i.e. from 88 to 85 kg ha -1. Across crop establishment methods, farmers used 60 kg ha -1 on transplanting, while112 kg ha -1 on direct seeding which was lower than the national average (Malasa and Launio 2015). This indicates that while sample farmers did not adopt exactly the recommended seeding rate, they were able to reduce their seed use. The seeding rate however, is still higher than the recommended seed use per ha, hence the need to study farmers risk tolerance on seeding rate (Pandey et al. 2000). Among farmer groups, a decline in seed use was higher for FIs (-10%) compared to PFs (-2%), which can be explained by the direct exposure of FIs to the PalayCheck demonstration field. The FIs have direct contact with RSOs since they work together in the demonstration field, enabling them to learn the technology through experience. According to Ortiz (2005), participatory research has usually been perceived to bring more benefits for the final users of technologies who are involved in the research process. Rice Variety Adoption. decision-making behavior in choosing rice variety to be planted is dependent on the ability of the variety to produce consistent high yield and tolerance againts pests/ diseases/weeds (Launio et al. 2008). Comparison of variety planted by farmers before and after project implementation shows that farmers adoption of rice variety did not change to a large extent. PSB Rc82 remained the top favorite even after the project implementation followed by PSB Rc18 and PSB Rc10, mainly because of their proven yield advantage, agronomic performance and short maturity as in the case of PSB Rc10. Other varieties also became popular to farmers in such as NSIC Rc160, NSIC Rc158, NSIC Rc152. These varieties were the best performers tested in the demonstration trials conducted during the two-season project implementation. Fertilizer and Pesticide Rate Application. Two of the critical key checks in the PalayCheck technology are Key Check 5 (KC5) and Key Check 7 (KC7) which refer to nutrient management, and pest management, respectively. Table 7 shows the change in fertilizer and pesticide application of sample farmers before and after the project intervention. There was no observed change on total NPK application prior and after the project implementation, but a substitution on the quantity of nutrient application rate was observed. Nitrogen application rate declined by 5% (from 59 to 56 kg ha -1 ), while there was an increase in phosphorus and potassium application rates by 8 and 10%, respectively. Similar trend was observed on FIs and PFs. The shift in nutrient application rates although insignificant can be partly explained by the introduction of MOET and LCC during the project implementation as diagnostic tools for determining soil nutrient limitations. Sample farmers appreciated greatly the importance of MOET as they were able to learn the nutrient limitations of their rice fields, as well as the amount of nutrients required. The project distributed MOET to farmer participants, thus the significant increase in MOET users from 15% in 2009 to 70% in. In general, the total pesticide application rate (a.i. kg ha -1 ) decreased by 11% during the project operation compared to its prior implementation. There was also a decrease in pesticide application rate among farmer groups. Similar trend was also observed on types of pesticides, except for molluscicide application rate which increased by 7% (Table 7). Herbicide application rate declined considerably by 24%, which can be partly accounted for the high adoption rate of Key Check 2 (KC2) no low and high soil spots after a fallow period. This is a result of a thorough land preparation since a properly-leveled field allows more uniform water distribution and requires less water, hence possible reduction in weed incidence. The decrease in the overall pesticide rate application can also be partly attributed to the adoption of Key Check 7 (KC7) avoid yield loss due to pest, wherein farmers were trained on how, and when to apply appropriate pesticide. Change in Labor Use. Labor use (md ha -1 ) declined by 8% after the implementation of the FFS-PalayCheck and comparable observation was obtained among groups of farmers. This can be partially attributed to the adoption of Key Check 7 (KC 7). As shown in Table 7, pesticide application rate in a.i. kg ha -1 decreased by 11%, which consequently reduced labor use. AB Mataia et al. 36

8 Table 7. Technology adoption and input use, before and after the project implementation, Philippines Item Before Project: 2009 After Project: Estimated Impact FIs PFs FIs PFs FIs PFs Adoption Rate by Seed Class Hybrid Registered Certified Good Seed Farmer's Seed Ave. seeding rate (kg ha -1 ) Average Fertilizer Rate Application N application rate (kg ha -1 ) P application rate (kg ha -1 ) K application rate (kg ha -1 ) Total NPK (kg ha -1 ) Average Pesticide Rate Application Insecticide (a.i. kg ha -1 ) Herbicide (a.i. kg ha -1 ) Molluscicide (a.i. ha -1 ) Fungicide (a.i. kg ha -1 ) Rodenticide (a.i. kg ha -1 ) Total Ai (kg ha -1 ) Labor Use (md ha -1 ) MOET Users Impacts on Rice Yield. Table 8 shows the comparison of yield level before and after project intervention. Generally, yield increased by 9% or an equivalent of 0.33 t ha -1 due to project intervention This was observed consistently across farmer groups. Thus, the PalayCheck system has the potential of increasing rice productivity. Similarly, Castaňeda (2007) reported 16% yield advantage in PalayCheck farmer adopters versus non-adopters in 2005 WS. Across seasons, yields were considerably higher by 16% (0.59 t ha -1 ) during wet season compared to only a 1% increase during the dry season. The low yield improvement during dry season was due to the drought spell that occurred in some sample provinces. This reduced the total domestic palay production in the Philippines by 10.24% or an equivalent of 0.75 M t during Jan-Jun relative to 2009 of the same semester (BAS 2011). In addition, the shift in distribution of sample farmers given the yield level was determined before and after project intervention (Figure 2). There was a declined from 29 to 23% in the number of farmers producing below 3 t ha -1, while from 52 to 49% for those producing medium yield level (>3 to 5 t ha -1 ). In contrast, farmers producing more than 5 t ha -1 increased from 20 to 28%, indicating the potential of the FFS-PalayCheck system to shift the yield level of farmers from low to high. The adoption of some of the key checks, improvement in crop management practices (increase adoption of quality and good seed, appropriate amount of NPK and active ingredient application), and technology adoption (high adopters of MOET) might have contributed to the yield improvement of farmers. Table 9 shows the differences in technology adoption of sample farmers that have attained yield above 5 t ha -1 and below 3 t ha -1. High yielding farmers have an average rice area (1.99 ha) larger than their low yielding farmer counterparts (1.43 ha). Likewise, 74% of their cultivated rice land is within easy access to irrigation facilities relative to only 54% of the low yielding farmers. Compared with low yielding farmers, greater percentage of high yielding farmers were more receptive of the new technologies, such as adoption of high quality seed (hybrid and certified seed) and MOET. In addition, they applied more NPK and were relatively efficient in the use of inputs as observed by the low seeding and pesticide application rates. Our results indicate that adoption of new technologies and appropriate inputs due to the FFS-PalayCheck improved rice yield. decision to adopt a new innovation is also often influenced by their financial capacity and level of education. The high yielding farmers had bigger per capita income per year, and a big percentage attained college level or completed university education relative to the low yielding farmers. Impact of farmer field school-palaycheck 37

9 Table 8. Change in yield, before and after FFS-PalayCheck implementation Philippines Farmer Classification Farmer Innovators (FIs) Participating (PFs) Jan-Jun, 2009 Before: 2009 After: Estimated Impacts Jul-Dec, 2009 Seasons Jan-Jun, Jul-Dec, Seasons Jan-Jun, Jul-Dec, Seasons Table 9. Technology adoption of sample farmers by yield level Philippines Parameters Low Yield (< 3.0 t ha -1 ) High Yield (> 5.0 t ha -1 ) Below Above Figure 3. Distribution in the number of sample farmers by yield level, before and after FFS-PalayCheck implementation Philippines Impacts on Production Costs and Net Income The FFS-PalayCheck system aims to increase productivity and profitability of rice production by simply learning and doing the best farming practices. Its implementation is expected to enhance the welfare of rice farmers through increased net profit as a result of increase in yield, attributed to improvements in farm management practices. Change in costs of production. Production costs before and after the project increased by 5.5%, which can be attributed to additional labor costs incurred for harvester and thresher. Payments for these operations were based on sharing arrangement or percentage basis relative to gross harvest. However, on a per unit cost, the cost of producing a kilogram of palay decreased by 2.82% or equivalent to PhP0.23 kg -1, which resulted in an increase in cost efficiency. Among farmer groups, FIs were more cost efficient than PFs. The per unit cost incurred by FIs on producing a kilogram of palay was only PhP7.46 compared with PFs at PhP8.21. The per unit cost declined from 2009 to were 4% on FIs and 2% on PFs (Table 10). Change in Net Income. Net income was computed as the difference between gross returns and total Age With college level/ college graduate Per capita income (P yr -1 ) 14,462 34,408 High quality seed users Average rice area (ha) Farms serviced by NIS/CIS Performed MOET Users of hybrid (NSIC Rc 132H) 1 5 Seeding rate (kg ha -1 ) NPK application rates (NPK kg ha -1 ) Pesticides use (ai kg ha -1 ) Labor use (man-day ha -1 ) production costs. Based from the results in Table 11, net income considerably increased by around 25% (PhP3,907 ha -1 ) in. This can be attributed to the increase in yield, increase in palay price, and reduction in per unit cost. The high net income translated to a net profit-cost ratio of 0.60, an increase of 18% from This means a farmer received a return of PhP0.60 per peso invested in rice production in compared to only PhP0.51 in Among farmer groups, FIs have bigger net income in (PhP4,644 ha -1 ) compared to PFs (PhP3,699 ha -1 ). Correspondingly, net percentage increment on net profit-cost ratio was higher by 1.60%. Similarly, Castaňeda (2007) also reported an estimated positive difference of 36% in the net income of PalayCheck and non- PalayCheck farmers. Impact on Domestic Total Rice Supply During the first year of operation of the project (), there were 165 FFS-PalayCheck sites established with a total of 3,665 farmer-participants (an average of 22 farmer-participants per FFS-PalayCheck in 24 provinces). Given the total rice areas (5,402 ha) cultivated by the total farmer-participants and the corresponding yield growth, the total incremental palay output achieved was 3,457 t, which is equivalent to 0.022% share to the total palay production in 201 AB Mataia et al. 38

10 Table 10. Comparison of production costs, before and after project implementation, Philippines Items Before: 2009 After: Estimated Impact % Change Seeds 1, , * Fertilizer 4, , * Pesticides 1, , * Fuel and Oil , Labor Costs Hired Labor 11, , , Permanent labor 1, , * Imputed labor (O,F,E) 3, , Other Costs Irrigation fee/cost Interest payments Food expenses Transportation costs Land tax / rental value 2, , Machine & animal rental Other Costs Total Costs 31, , , Cost per kg Table 11. Costs and returns, before and after FFS- PalayCheck implementation, Philippines, Items Before: 2009 After: Estimated Impact % Change Yield (kg ha -1 ) 3,812 4, Price (P kg -1 ) Gross Returns (PhP ha -1 ) Total Production Cost Net Profit (PhP ha -1 ) Net Profit-Cost Ratio *1% level of significance 47,188 52,818 5, * 31,330 33,053 1, ,857 19,764 3, * (Table 13). This result suggests that the project did not contribute markedly to the total domestic palay supply despite the average yield increment of 9% because of the small number of farmers and areas covered. The impact on the total palay supply would have been more significant if more provinces and more farmers were included in the project. Assessment of the Farmer Field School- PalayCheck Qualitative data were also gathered to solicit information from farmer-participants on the effectiveness of the FFS-PalayCheck in capacitating farmers, and in facilitating the dissemination of the PalayCheck technology. In this section, farmers were asked about their perceptions on the effectiveness of the project to impart knowledge, their likes and dislikes on the project, and on school curriculum especially on the topics discussed. Moreover, farmers were asked on how they rate the performance of the Rice Self- Sufficiency Officers (RSO) in the implementation of Table 12. Incremental palay output after the project implementation, Philippines, Rice areas cultivated (ha) Yield (t ha -1 ) Before: 2009 After: Increment 5,402 5,402 0 Dry Season Wet Season Palay Production (t) Dry Season 21,338 21, Wet Season 19,879 23,067 3,187 Total 41,217 44,675 3,457 the project and what suggestions they can recommend to improve the performance of the Farmer Field School- PalayCheck. The Farmer Field School-PalayCheck used several strategies in its implementation and in conveying of knowledge to farmer-participants. The strategies employed include: field day, cross visit, field demonstration, conduct of lecture, and agro-ecological system analysis (AESA). On the scale 1-10, where 10 is the highest, farmers were asked to rate which among the strategies they considered were successfully implemented and most effective in conveying knowledge. Field demonstration was highly rated (a score of ) both in communicating knowledge and in its implementation. This suggests that the field demonstration strategy is a viable educational delivery method because it shows and tells farmers exactly what the key checks are and how these will fit under their local conditions. On the other hand, cross-visit and lectures were only rated satisfactory by farmers (Figure 4). Impact of farmer field school-palaycheck 39

11 Figure 4. assessment of the strategies used in the FFS-PalayCheck Figure 5. rating on the performance of RSOs by province The FFS-PalayCheck consists also of classroom lectures, which discussed the PalayCheck principles from which the key checks, and technology recommendations are developed, and how the key checks are associated. It also explains the integration of all aspects of PalayCheck management and the assessment of key checks at different growth stages of the rice crop. Willingness to learn new innovations or new technologies motivates farmers to attend lectures. Around 50% appreciated all the topics studied, where rice variety and selection was the most favorite followed by pest management, land preparation, nutrient management, and water management. Very few farmers also expressed disappointment on the lack of commitment of fellow farmers, resulting in putting off some of the project s schedule activities. Figure 5 presents farmers rating on the performance of the RSOs in implementing the project. The RSOs served as researcher cum extensionist in the respective province assigned to them. They served as researcher in the field demonstration, and led the FFS- PalayCheck in capacitating farmers by promoting the integrated crop management technologies such as the PalayCheck. On a scale of 1-10, farmers rated exemplary the RSOs with an overall score of They understood that RSOs performed their best in implementing all the activities related to the project despite the numerous workload they assumed. Two-thirds of the farmer-participants seemed satisfied on how the project was implemented, while around 30% recommended some suggestions to improve its implementation, namely: a continuation of the project for sustainability of the FFS-PalayCheck so that more farmers will be trained on the technology, encourage more and active participation of farmers, subsidize price of certified seeds, and a regular review of old topics to refresh/retool farmers. CONCLUSION AND RECOMMENDATIONS The project showed positive impacts in compared to its implementation in The Farmer Field School-PalayCheck facilitates the adoption of the key checks where 18% of the farmers completely adopted the 8 key checks and majority with different combinations of the key checks. Adoption of the individual key checks from the project 1 st season operation improved from 53-85% to 63-88% in its 2 nd season implementation. The adoption of some of the key checks resulted in a 8% increase in the technical efficiency level of farmers from 51.2 to 55.3%, which translated to a significant improvement in crop management practices, technology adoption (such as MOET), and efficient use of inputs particularly pesticides. In addition, yield increased by 9% (0.33 t ha -1 ) while per unit production cost reduced by 2.82% (PhP0.23 kg -1 ), which translated to a growth in net income by a considerable 25% (PhP3,907 ha -1 ), and an 18% returns on investment. A major reduction in costs was observed among material inputs such as seeds, fertilizer, and pesticides. Similarly, the total rice areas covered by the project generated an incremental palay output of 3,457 t with 0.022% share to total domestic production in. Significant impact of the project was observed among FIs from PalayCheck technology field demonstrations. The field/technology demonstration was also rated the most effective strategy in imparting knowledge to farmers. Moreover, the establishment of technology demonstration as technology showcase is an effective means of showing and telling farmers exactly what the key checks are, and how these will fit under their local conditions. Overall, the project has been effective in achieving its objectives but greater impacts could be realized given AB Mataia et al. 40

12 the following recommendations: 1) the mean TE scores of farmers are still relatively low at 55.29% compared with the farmers mean TE scores (66-73%) in (Castaneda2009). The mean TE indicates that around 45% of palay output is lost due to inefficient use of resources. can save cost by 57% if they are technically efficient hence, there is a need to enhance more the technical knowledge of farmers on the appropriate and efficient use of inputs particularly on the recommended seeding rate, fertilizer rate, and time of application; 2) the field demonstration was rated the most effective strategy in imparting knowledge to farmers because they experienced the best key checks practices. More demonstration farms should be established in multilocations in major rice producing provinces in the country to showcase the benefits of the PalayCheck technology for widespread adoption of farmers. Modules in the PalayCheck must give emphasis on key checks with very low adoption such as Key Checks KC1, KC6, and KC7; 3) the project s contribution to domestic total palay output was estimated to an insignificant (0.022%) only. The contribution could have been remarkable if more FFS-PalayCheck have been established, and more areas and farmers were included and trained on the PalayCheck technology; and 4) periodic monitoring of the implementation of the FFS-PalayCheck must be conducted to improve and sustain its implementation. ACKNOWLEDGMENT This work was a derivative of the project on Monitoring and Evaluation (M&E) of the Socioeconomic Impacts of the Location-Specific Technology Development (LSTD) on PalayCheck, which was funded by the Philippine Rice Research Institute (PhilRice). The authors would also like to acknowledge some staffs from the Socioeconomics Division of PhilRice who were part of the M&E team during the implementation of the project. The technical assistance provided particularly in the conduct of the baseline and monitoring surveys in their respective assigned provinces is highly appreciated. LITERATURE CITED Agricultural Technology Adoption Initiative (n.d.). A Spectrum of adoption constraints March, Anderson JR, Herdt RW Reflection on impact assessment. In: Methods for diagnosing research system constraints and assessing the impacts of agricultural research. Echeverria RG, editor. The Hauge (Netherlands): International Service for National Agricultural Research. 8 May, Balisacan AM, Sebastian LS, Alpuerto VB Securing rice, reducing poverty: challenges and policy directions. Southeast Asian Regional Center for Graduate Study and Research in Agriculture (SEARCA), Philippine Rice Research Institute (PhilRice), and Department of Agriculture-Bureau of Agricultural Research (DA-BAR). Los Baños: SEARCA, p. [BAS] Bureau of Agricultural Statistics Socioeconomic characteristics of farmers in the Philippines. BAS, Quezon City. Casiwan CB, Cabling JM, Nievera MR, Mataia AB, Dawe DC Rice farmers are better off than many other farmers. In: Why does the Philippines import rice? Meeting the challenge of trade liberalization. Dawe DC, Moya PF, Casiwan CB, editors. Manila (Philippines): International Rice Research Institute, and Science City of Muňoz (Philippines): Philippine Rice Research Institute. 31 p. Castaňeda AC An evaluation of the potential impact of PalayCheck system for the Philippine rice industry. [MS Thesis] School of Economics, Quezon City (Philippines): University of the Philippines Diliman. (Available at UP School of Economics Library). 134 p. Castaňeda AC Changes in technical efficiency of rice farmers. Terminal Report. Science City of Munoz (Philippines): Philippine Rice Research Institute. 22 p. Castillo GT Rice in our Life: A review of Philippine studies. Angelo King Institute for Economic and Business Studies, De La Salle University, Manila, Philippines and Philippine Rice Research Institute, Science City of Muñoz, Nueva Ecija, Philippines. 182 p. [DA] Department of Agriculture Food staples sufficiency program (Enhancing agricultural productivity and global competitiveness ). DA, Ouezon City, Philippines. [DA] Department of Agriculture Philippine Rice Self-sufficiency Master Plan, 2009-: Focusing on Increasing Provincial Productivity. [DA-BAR] Department of Agriculture Bureau of Agriculture Research In search of food: DA s food staples sufficiency program March, [DA-BAS] Department of Agriculture Bureau of Agricultural Statistics Palay: volume of Impact of farmer field school-palaycheck 41