PERCEPTION OF ARABLE FARMERS ON THE VIABILITY OF PRECISION AGRICULTURE PRACTICES IN IDO LOCAL GOVERNMENT OF OYO STATE

This study was conducted to determine the perception of arable farmers on the viability of precision agriculture practices in Ido Local Government of Oyo state. Objectives of the study were to, ascertain their awareness with some specific Precision Agriculture Practices (PAP), assess their ability to adopt the Precision Agriculture Practices (PAP) if available, determine the knowledge of potential benefit of the Precision Agriculture Practices (PAP) and determine their perception towards the validity of Precision Agriculture Practices (PAP). Multi stage sampling technique was used to select 150 respondents. Data for this study was analyzed using descriptive statistics such as frequency count, mean and percentages while the inferential statistics such as Factor analysis, Cluster Analysis and the structural equation modeling was used to test the hypotheses. The study also examines the socio-economic characteristics of the participants using numerical data. The findings of the study revealed that the majority of agricultural workers, specifically 60%, were male with an average age of 45 and an average of 20 years of experience in the industry. The data also showed that 70% of the individuals had received primary education, whereas only 15% had pursued secondary education. In terms of knowledge of precision farming techniques, the study found that 55% were familiar with soil testing, while only 25% were knowledgeable about the use of drones in agriculture. The study also analyzed the perception of potential benefits associated with PAP. Findings showed that 65% of farmers recognized economic advantages, such as increased yields and reduced input costs, while 30% acknowledged environmental benefits like decreased use of chemicals. However, 25% expressed concerns about the practicality of implementing these methods due to perceived high costs and complexity. Inferential statistics were used to test the study's hypotheses. The first hypothesis, suggesting no significant difference in farmers' perceptions of precision agriculture practices, was evaluated using factor analysis. The analysis revealed a KMO value of 0.72, indicating sufficient sampling, and a significant Bartlett's test of sphericity (p < 0.05), supporting the factorability of the data. Four factors were identified, explaining 65% of the variance in farmers' perceptions. The second hypothesis, stating that farmers' knowledge of benefits, familiarity, and ability to practice precision agriculture have no significant influence on their perception, was tested using structural equation modeling (SEM). The results showed a significant positive relationship between farmers' knowledge of benefits and their perception of PAP (β = 0.45, p < 0.01). Familiarity with precision agriculture practices also significantly influenced perception (β = 0.35, p < 0.05), while the ability to implement these practices had a weaker but still significant impact (β = 0.25, p < 0.05). Cluster analysis revealed three distinct groups of farmers based on their perceptions of precision agriculture. The first cluster, comprising 30% of respondents, demonstrated high familiarity and positive perception of PAP, indicating readiness to adopt new practices. The second cluster, representing 50% of farmers, showed moderate familiarity and a neutral perception, suggesting potential for increased adoption with appropriate support. The final cluster, accounting for 20% of respondents, had low knowledge and held negative views about precision agriculture, which creates significant obstacles to its adoption. This underscores the need to address farmers' perceptions to promote the uptake of precision agriculture practices. The study recommends targeted educational programs and support systems to improve farmers' understanding and capabilities in relation to precision agriculture. By closing these knowledge gaps, stakeholders can help promote the adoption of practices that ultimately enhance agricultural productivity and sustainability in the area.