Accuracy of Indigenous Knowledge for Predicting Farming Seasons among Crop Farmers in Ogun State, Nigeria

Abstract

This study assessed the accuracy of indigenous knowledge for predicting farming seasons among crop farmers in Ogun State by employing a cross-sectional survey research design. A multistage sampling procedure was used to select 250 crop farmers from the four extension zones in Ogun State. Additionally, two key informant interviews (KII) and one focus group discussion (FGD) were held in each farming community. Quantitative data were obtained using an interview schedule, while qualitative data were obtained using checklists for KII and FGD. Quantitative data were subjected to frequency counts, percentages, means, standard deviations, and thematic analysis. Results revealed that 55.6% and 51.2% of the farmers cultivated annual crops and were not involved in livestock rearing, respectively. The incidence of the dry season was predicted mostly by the dropping of leaves from the fig tree (73.2%), almond leaves (70.4%) and sprouting of the Lantana plant (61.6%). Heavy budding of the acacia tree (70.0%), sprouting of Aloe ferax in the mountain (70.8%), and development of young leaves and grasses in the field (76.0%) were some of the indicators used in predicting the rainy season. Some translational meanings derived from the qualitative data are that the appearance of rainbirds and chameleons predicts the onset of the rainy season. At the same time, the defoliation of almond trees and African teaks indicates the start of the dry season. Furthermore, farmers' predictions of farming seasons were relatively consistent with science-based climate information. The study concluded that indigenous knowledge indicators are relatively accurate in predicting farming seasons compared to science-based climate information.