Ogunwande, I. and Akinrinola, O.O.

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The paper examined the effect of nomadic activities on the productivity of arable crop farmers in Oyo State, Nigeria. A total of 175 respondents were interviewed using structured questionnaire and interview schedule to collect the data used. Analytical tools used were descriptive statistics, probit model, and ordinary least square multiple regression. Descriptive statistics result showed the highest value for farm size (2.1-5.0) hectares (65.1%), Age (21-60) as 73.2%, married (77.1%), educated farmers (98.1%) and primary occupation (59.4%) among others. Farm size, extension contacts, work-hour, kraal proximity, and nearness to nomadic route were probit variables which significantly influenced nomadic invasion among farmers. Multiple regression result for output determinants showed that farm size, quantity of planting materials, number of extension contacts positively affected the output of both farmers with invasion experience and otherwise while the output of non-nomadic experience farmers were further positively affected by work-hours, education and labour while pooled data showed that farm output of all farmers were positively influenced by farm size, planting materials, and extension contacts while about 97% of respondents responded that low yield and high cost remained the prominent resultant effect of cattle invasion among farmers in the study area. Hypothesis tested showed that the relationship between farm output and number of monthly nomadic invasion was significant at 1% level suggesting that quantity of farm output is inversely related to number of cattle invasion of farms. It was therefore recommended that government should provide cattle ranch for farmers, educate the young and old Fulani herdsmen on the need for peaceful co-existence of Nigerians; and, law on the grazing reserve should be amended and improved upon among others. It was nevertheless concluded that farm invasion evidently led to a colossal loss of lives and crops. Key words: Nomadic invasion, farmers, herdsmen, probit, multiple regression