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African Crop Science Journal, Vol. 10. No. 3, 2002, pp. 271-280 AN ASSESSMENT OF THE INTEGRATED PEST MANAGEMENT COLLABORATIVE RESEARCH SUPPORT PROJECT’S (IPM CRSP) ACTIVITIES IN UGANDA: IMPACT ON FARMERS’ AWARENESS AND KNOWLEDGE OF IPM SKILLS J. M. Erbaugh1, J. Donnermeyer1 , P. Kibwika3 and S. Kyamanywa4 1 Department
of Human and Community Resource Development, The Ohio State University, 113
Agricultural Administration Bldg., Columbus, Ohio 43210 (Received 15 October, 2001; accepted 2 July, 2002) Code Number: cs02027 ABSTRACT The IPM CRSP (Integrated Pest Management Collaborative Research Support Program) has been applying a farmer participatory IPM strategy at on-farm research sites in eastern Uganda since 1995. Following five years of project implementation an evaluation of project impacts was conducted using a stratified random sample of 200 small- scale farmers. The main purpose of this study was to evaluate the impact of project (IPM CRSP) activities on IPM knowledge and awareness change using comparison groups composed of project participants and non-participants. A summated ratings scale consisting of four attributes was developed to measure knowledge of IPM and individual indices were developed to measure crop specific pest management knowledge. Results indicate that more active participation increased knowledge of IPM skills and knowledge, provided preliminary support for the project’s participatory research and extension approach. However, diffusion of knowledge was limited and project beneficiaries were slightly more socioeconomically advantaged. Several recommendations are made for increasing the number of farmer participants and improving the evaluation process. Key Words: Beneficiaries, diffusion, evaluation, on-farm, participatory approach RÉSUMÉ Les IPM CRSP était entrain d’appliquer une stratégie participative à des sites de recherches à l’est de l’Ouganda depuis 1995. Après cinq ans de réalisation du projet, une évaluation de son l’impact était conduite utilisant un échantillonnage stratifié au hasard et 200 petits fermiers. Le but principal de cette étude était d’évaluer l’impact des activités du projet (IPM CRSP) sur la connaissance des IPM et le changement de conscience en comparant des groupes des participants et non participants au projet. Une échelle de classement sommative, avec quatre attributs, était développée pour mesurer la connaisance sur les IPM et des indices individuels étaient développés pour mesurer la connaissance spécifique sur la gestion des pestes. Les résultats indiquent que la participation active augmente la connaissance technique des IPM, si un support préliminaire est assuré dans l’approche de la recherche participative et l’extension. Cependant, la dissémination de connaissances était limitée et les bénéficiaires du projet étaient un peu avantagés sur le plan socio-économique. Plusieures recommendations étaient faites pour augmenter le nombre des fermiers participants et améliorer le processus d’évaluation. Mots Clés: Bénéficiaires, dissémination, evaluation, sur fermes, approche participative INTRODUCTION Attempts to develop and disseminate integrated pest management (IPM) systems and practices have been pursued in developing countries for over two decades. Despite these efforts, the application of IPM, particularly among small-scale farmers, has been limited (Maxwell, 1996; Morse and Buhler, 1997; Yudelman et al., 1998). A range of factors including weak links between research scientists and farmers and the use of top-down technology transfer programs have constrained the successful development and adaptation of IPM technologies to meet the specific needs of resource poor farmers (M’Boob, 1993; Dent, 1995; Douglah & Sicilima, 1997). Increasing farmer participation in the development and implementation of IPM programs has emerged as a strategy for overcoming these constraints (Yudelman et al., 1998). Different paradigms have guided IPM program implementation since its inception, resulting in myriad definitions and approaches that emphasize different research and extension strategies (Yuldeman et al., 1998; Ehler and Bottrell, 2000). The traditional approach was to develop pest and disease management alternatives in order to reduce or eliminate the use of chemical pesticides. This approach evolved in response to environmental concerns about the abuse or overuse of chemical pesticides associated with intensive-input agricultural systems in developed countries. The role of extension was to directly transfer and disseminate these alternative technologies and practices to farmers. Alternative approaches have evolved for small-scale farming systems in sub-Saharan Africa which are characterised by the absence or minimal use of production inputs, including chemical pesticides. These newer approaches seek to combine indigenous farmer knowledge with scientific knowledge of cropping systems and pests to develop site specific IPM systems. Variously labeled as ecological or sustainable IPM (Pimbert, 1991; Schwab, 1995; Mangan and Mangan, 1998), these approaches are often described as being knowledge intensive (Morse and Buhler, 1997) because they require enhanced knowledge and understanding of biological factors and ecological interactions for their successful implementation by small farmers (Dent, 1995). Since information and knowledge transfer between farmers and scientists is an important objective, ecological IPM programs are increasingly linked to participatory research and extension approaches (Norton et al., 1999). The IPM CRSP (Collaborative Research Support Project) has been applying a farmer participatory IPM strategy at on-farm research sites in eastern Uganda since 1995. Farmer participation at each stage of the research process provided the nexus for an emerging synthesis of both ecological and traditional approaches. Evaluating the impact of traditional IPM programs has generally relied upon monitoring reductions in pesticide use and assessing new technology profitability among farmers in developed countries (Ehler and Bottrell, 2000). However, the main purpose of this study was to evaluate the impact of project (IPM CRSP) activities on IPM knowledge and awareness change among small-scale farmers in eastern Uganda. Formative evaluations like the one attempted in this study are useful for examining programmatic effects and suggesting program modifications. METHODOLOGY Evaluation approach. The analysis of project impacts roughly follows the hierarchical target/outcome structure suggested in the Targeting Outcomes of Programs (TOP) outlined by Bennett and Rockwell (1995). Their model involves seven stages to guide both program development and assess program performance. The seven stages include: (1) conditions; (2) practices; (3) knowledge, attitudes, skills, and aspirations (KASA); (4) reactions; (5) participation; (6) activities; and (7) resources. Program development begins with Stage 1 (assessment of conditions) and progresses through the remaining 6 stages. However, evaluation or program performance, proceeds in the opposite direction. The most elementary evaluation level would be an assessment of resources (Stage 7), and the most advanced evaluation would be to examine changes in conditions (Stage 1). This evaluation is conducted at the third stage, or KASA. The TOP model assumes that changes in knowledge, attitudes, skills, and aspirations (KASA) lead to changes in practices, that in turn, create the desired change. Increased knowledge and awareness are generally considered prerequisites to the adoption of new practices and technologies, including IPM (Dent, 1995; Rogers, 1995). The IPM CRSP designed specific program activities to present subject matter that would lead to change in knowledge, attitudes, skills and aspirations among farmers in eastern Uganda. Thus, increased project involvement and exposure is presumed to be associated with increased KASA, and this should lead to adoption of targeted practices (i.e., stage 2), and, ultimately, to enhanced social, economic and environmental conditions (i.e., stage 1). Population and sample. A multi-stage sampling procedure was used to select eight villages in two districts in eastern Uganda. In each district, 4 sub-counties were selected, with two of these being sub-counties where the IPM CRSP had active programs and two others where the CRSP had not previously been active. The selection of sub-counties where the IPM CRSP had not been active was based on geographical proximity and agro-ecological similarity to those where the IPM CRSP had been active. Villages in each sub-county were then purposively selected: two were selected near NGOs that had worked with the IPM CRSP. In sub-counties where the IPM CRSP had not been active, villages were selected near an identified, active farmer NGO. Lists of farmers for each village were obtained from government officials. A systematic random sample of 25 farmers was selected from each village, totaling 100 interviews from each district, and 200 completed questionnaires in all. Data collection and instrumentation. The evaluation instrument was developed through the iterative process of farmer participation with scientists and extension agents. Farmer knowledge and knowledge gaps of on-farm ecological relationships, priority pests and diseases, and pest management practices, suggested questions for assessing knowledge and awareness change. Added to the instrument was a series of questions that required farmers to identify pests and diseases from enlarged photos and answer specific questions about pest and disease management practices. A one-day enumerator training workshop was held prior to field testing the instrument. Field enumerators were selected based on their familiarity with local languages, survey methodology and past experience with IPM CRSP activities in Uganda. A pre-test of the instrument was conducted by teams of enumerators in their respective districts with five different farmers. Minor revisions to the instrument were made and a final instrument completed, copied and distributed to field coordinators. All questionnaires were conducted by personal interviews by one of the eight enumerators. Female enumerators, two for each district, were instructed to interview female farmers knowledgeable of the farm operation when possible. Enumerators, both male and female, were instructed to follow the systematic selection process described above. Each enumerator completed 25 questionnaires. Comparison group identification. An important objective of the sampling procedure was to have comparison groups composed of project participants and non-participants. Participation was established by asking respondents if they had participated, in two or more IPM CRSP activities. Participation in the IPM CRSP was regarded to be a trichotomous variable with (0) indicating no participation (N=142), (1) participation in 1 or 2 activities (N=34), and (2) participation in three or more activities (N=24). For some analyses, the participation variable was made dichotomous yielding non-participants (N=142), and participants (N=58). Of the 58 participants, 51 were from sub-counties where the IPM CRSP had active programs. The remaining 7 were coded as participants because they had traveled to and participated in various IPM CRSP-related demonstrations and seminars. Group comparability. In order to attribute outcomes to project activities, it is necessary to assess the degree of comparability of the two groups. Since the inception of the project, a great deal of additional effort has been made to include both male and female farmers and to ensure that project beneficiaries were not necessarily from socio-economically advantaged segments of local communities. Using a T-test of mean differences, the two groups were compared on the basis of socio-economic criteria including sex, age, years of education, farm income, and acres in crops. Sex was a dummy variable with women coded (0) and men (1). Age and years of education were considered continuous variables. Education was measured by the number of years of formal education completed. Farm income was operationalised by asking farmers to approximate their annual farm income in Ugandan Shillings (Ug. Shs.), using seven categories ranging from less than 50,000 to more than 500,000 Ugandan Shillings, coded 0-6. Crop acreage was the amount of land in production at the time of the interview. Crop acreage was used instead of total farm size because it more accurately reflected each household’s resource capacity for putting land into production. IPM knowledge. The project did not begin with a rigid predetermined definition of IPM, because local and contextual pest management experience were not known. Since IPM is a multi-dimensional concept (Dent, 1995), it was decided to let important dimensions emerge from participatory activities. Early activities established that most farmers preferred to use, and many were frequently using, synthetic pesticides; many farmers were unaware of alternatives to pesticides for managing pests; farmers were unaware of many crop diseases and small insects; and were generally unaware of beneficial insects. In recognition of farmers’ preference for using pesticides it was decided to retain and promote “IPM” as a brand name for pest management alternatives to sole reliance on chemical pesticides. Each of these knowledge attributes or dimensions were considered fundamental to a strong working knowledge of IPM. Through program activities, the IPM CRSP attempted to increase the knowledge and awareness of these dimensions. A dichotomous measure of a multi-dimensional concept was considered inappropriate; thus a summated rating scale consisting of these four attributes was devised to measure farmers knowledge of IPM. The coefficient of reliability for the knowledge of IPM scale was .72, indicating an acceptable level of reliability (Nunnally, 1978). The first item requested interviewers to evaluate farmers’ ability to define these dimensions or attributes of IPM on 0-2 scale, where 0 indicated an inability to define IPM; 1, indicated a partial definition of IPM; and, 2, indicated a more complete definition. Partial and more complete definitions were scored if farmers mentioned one or more of the attributes of IPM including, reducing use of pesticides or using them selectively, using alternative practices besides pesticides to control pests, or protecting beneficial organisms. The second item asked farmers if they were aware of any harmful effects from using pesticides, and was coded 0 if they were unaware; and 1-3 if they were aware of potential harmful impacts from using pesticides. A third item asked farmers if they could name any beneficial insects, with a no response coded 0, naming one insect coded 1, and naming more than 1 insect coded 2. The fourth item asked farmers if they knew other practices to control pests and diseases besides using pesticides, with a no (0) response indicating that they were not aware of other means to control pests besides using pesticides and the mentioning of alternative control methods coded 1-3. Alternative control methods mentioned included crop rotation, fallowing, increasing plant populations, roguing diseased plants, hand-removal of pest species, using homemade concoctions, use of locally available bio-rational products, and use of resistant or tolerant varieties. Knowledge of crop specific pests, diseases and management alternatives. The initial participatory assessment (PA) established priority crops and pest and diseases. In Iganga district the priority crops selected by farmers were maize, beans, and groundnuts; for Kumi District the priority crops were sorghum, groundnuts and cowpea. Following the PA, IPM CRSP activities focused on developing knowledge and awareness of priority pests and diseases, and, pest management alternatives. In order to assess knowledge accrual impact from IPM CRSP activities a set of test questions were developed for each crop. Since pest and disease identification was an early activity of the IPM CRSP, some questions pertained to enlarged photos of specific pests, diseases, or plant damage. Other questions required specific answers about a resistant variety, post-harvest storage techniques, disease vectors, or control practices. Responses to these questions were coded either 0 for not-known, or 1 if the farmer knew the answer or could identify the pest or disease. These responses were then combined to form an index of pest management knowledge for each crop. Data analysis. To test the effects of various levels of participation in IPM CRSP activities on knowledge of IPM, one-way analysis of variance test was used. The simple hypothesis that guided this analysis was that increased participation in IPM CRSP activities would be associated with more knowledge of IPM. The impact of project participation on knowledge of crop specific pests, diseases and knowledge items was assessed using a t-test for equality of means. The hypothesis here was that there would be significant differences of crop specific knowledge between those who had and had not participated in the project. FINDINGS Group comparability. Comparisons of non-participants and participants on key socio-economic variables provide some indication that programmatic activities may be reaching older, larger and wealthier farmers (Table 1), although mean differences were not dramatically large even for those that were statistically significant. Additional T-tests of mean differences were conducted on the 100 participants (n=58) and non participants (n=42) from sub-counties where the IPM CRSP had active programs. The results were found to be similar. Compared to non participants, participants were farmers with more acres in crops and more farm income. Within these IPM CRSP targeted sub-counties, participants were also more likely to be female and had higher levels of education. However, the difference in age was not statistically significant. Knowledge of IPM. Table 2 presents the mean IPM Knowledge scores by the three different levels of IPM participation. The majority of respondents (71%) have not participated in IPM CRSP activities. This is not surprising considering that half the villages in the sample were deliberately selected because they had not participated in IPM CRSP activities. The hypothesis tested is that participation in IPM CRSP activities had a positive impact on knowledge of IPM. Overall, those who participated in more IPM activities have greater knowledge of IPM than those who have not participated. An analysis of variance (ANOVA) of these results is presented in Table 2. As participation increases mean scores went up dramatically and significantly, indicating that those who participated in more IPM activities have greater knowledge of IPM than those who have not participated. Knowledge of crop specific pests, diseases and management alternatives. For each of the priority crops, a set of questions was developed to test farmers’ knowledge of pest management. Since priority crops differed by district, the sample size for each district was 100, except for cowpea, beans, and groundnuts in Iganga, where not all farmers were growing these crops. The level of IPM CRSP participation was reduced to two levels: non-participation and participation. A t-test was used to compare means between the two different levels of project participation on a summated ratings scale of crop specific pest management knowledge (Table 3). For each crop specific knowledge scale, a statistically significant difference was found. In every case, mean scores were higher among farmers who had participated in IPM CRSP activities. Maize pests and diseases. Table 4 presents specific questions that pertain to maize pests and disease infestation and response distributions for each question. Sampled farmers in Iganga were best able to identify maize streak disease and least knowledgeable about the stalk borer parasitoid (Cotesia Flavipes) that the IPM CRSP had released at research sites. Despite being able to recognize maize streak, fewer farmers knew that the variety, Longe-1, developed and released some 12 years ago, carried streak resistance. In general, farmers displayed little knowledge of beneficial insects such as the stalk borer parasitoid despite releases conducted by scientists in the fields of participating farmers. Bean pests. Table 5 presents the specific questions that pertain to pest attack on beans and response distributions for each question. Sampled farmers in Iganga were best able to identify the damage to the plant caused by bean fly (Ophiomyia sp.) and least knowledgeable about earthing-up as a practice for controlling bean fly damage. Farmers originally attributed plant damage caused by the bean fly to plant stress caused by drought. Farmer field monitoring of pests latter determined the bean fly to be the priority pest responsible for yield loss. As a result, the project has made considerable efforts to develop two controls: application of a seed dressing and earthing-up. More farmers were aware of the former than the latter. Two explanations for this finding would be that project activities had emphasized seed treatment as a control more than earthing-up; or, that farmers noticed that seed treatment required less labor and provided better control than did the practice of earthing-up. Sorghum production constraint. Table 6 presents the specific questions that pertain to sorghum production constraint and response distributions for each question. Most sampled farmers in Kumi were able to identify the parasitic weed (Striga) probably because of its widespread distribution throughout the district. Farmers’ were least knowledgeable about the stalk borer parasitoid (Cotesia Flavipes) that the IPM CRSP had released at research sites. That farmers in Kumi were less familiar with the stalk borer parasitoid than farmers in Iganga may be attributable to the variation in importance of the crop for both districts. Test items for sorghum are less able to differentiate between non-participating and participating farmers than other crop specific tests. This is partially attributable to the questions pertaining to striga, in which most farmers demonstrated a high degree of knowledge and awareness. Striga is quite visible and widespread throughout the district and has received much research and extension attention over the years. Cowpea pests and disease infestation. Table 7 presents the specific questions that pertain to cowpea pests and diseases and response distributions for each question. Most sampled farmers in Kumi were able to identify the cowpea aphid and blister beetles, and least able to identify a second disease of cowpea, this despite the common occurrence of 4 main diseases throughout the district. Participating farmers were perhaps better able to identify a second disease because of 2 years of on-farm trials that emphasised disease identification and control (Adipala et al., 1998). Cowpea is one of the crops in Kumi that is consistently sprayed with synthetic pesticides, however, that 66% of the farmers were aware of the correct timing for pesticide application was a surprise finding. Prior evidence had indicated that many farmers sprayed cowpeas indiscriminately and more frequently. Groundnuts and diseases. Table 8 presents the specific questions that pertain to groundnuts pests and diseases and response distributions for each question by district (Iganga N = 77; Kumi N = 100). Farmers in both Iganga and Kumi were best able to identify groundnut rosette disease and least able to identify another non-chemical method to control aphids. Alternative controls are increasing plant population in order to deter infestation by the main insect vector, aphids, of groundnut rosette disease; and using the resistant variety Igola-1. Kumi farmers were more aware that Igola-1 was a resistant variety. Kumi non-participants and participants had higher mean scores on test items. This may be caused by a one year delay in starting groundnut activities in Iganga or by the greater centrality of groundnuts to the farming systems in Kumi. CONCLUSIONS Examining the results of farmer participation on knowledge of IPM and knowledge and awareness of crop specific pest management demonstrates that participation, and thus, IPM CRSP activities, are having the desired impact. The results indicate that more active farmer participation increases knowledge of IPM. This provides some preliminary support for the participatory research and extension approach being used by the project. Whether this will lead to the adoption of new practices, reduce pesticide usage, and enhance economic and environmental impacts will be the subject of future analyses. However, the analysis provides evidence that the number of project beneficiaries were small and more socio-economically advantaged. Altogether, only 58 (29%) of the farmers sampled had participated in project activities, despite nearly 5 years of project activity and purposively sampling villages located near research sites. An important reason why more farmers have not participated was the emphasis placed on using a participatory approach. Activities such as participatory assessments, farmer field monitoring, on-farm trials and field evaluations were generally limited to small groups of farmers in order to maintain program quality and to remain within project budgetary parameters. Others have noted that participatory programs are more demanding than conventional on-station, on-farm approaches and, as a result, have encountered similar difficulties in trying to expand participation (Roling and van de Fliert, 1994; Douglah and Sicilima, 1997). The project made concerted attempts to ensure equal access to project activities even going to the extent of working with NGOs with exclusive female membership and conducting farmer open days. This helps explain why female participation was higher in IPM CRSP active sub-counties. Efforts to be more inclusive of poorer farmers may have been confounded by the noted phenomenon that attendees at training programs are often the more aggressively innovative farmers, that is, those with better education, larger acreage, and higher farm income (Dent, 1995; Rogers, 1995; Haug, 1999). Participatory agricultural research (PAR) programs may not be a remedy for reaching the most marginalised in society and the conduct of agricultural research, even PAR, may self-select for those with the capacity to innovate and accept risks. Addressing the needs of the poorest of the poor, although a desirable objective will always be difficult, particularly when the majority of farmers in a targeted community are small and resource poor. Implications. To reach a broader audience the project will need to implement more activities that focus on dissemination, such as demonstration trials with farmer associations or developing training programs for extension agents. Already, a discovery and experiential learning-based IPM training module has been developed for extension agents to use with groups of farmers over the course of a single growing season. Additionally, in keeping with the participatory precept that knowledge is contextual, a new evaluation instrument has been constructed for use in the field with farmers. Future assessments will examine the relationship between IPM knowledge and awareness change an adoption of pest management technologies. ACKNOWLEDGEMENTS This paper was supported by the IPM CRSP which is funded by the U.S. Agency for International Development (USAID) under Agreement No. LAG-4196-G-00-5001-00 to Virginia Tech. Additional support was provided by the International Programs in Agriculture Office at The Ohio State University. REFERENCES
©2002, African Crop Science Society The following images related to this document are available:Photo images[cs02027t4.jpg] [cs02027t6.jpg] [cs02027t8.jpg] [cs02027t1.jpg] [cs02027t3.jpg] [cs02027t2.jpg] [cs02027t5.jpg] [cs02027t7.jpg] |
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