25 pages., The study adopted survey research design. The population of the study consisted 1200 respondents comprising (staff of the Zamfara State Agricultural Development Project, FADAMA III Project, IFAD, Animal rearers and Farmers). Instruments of data collection used for the study were the questionnaire, interview and discussions. One thousand two hundred questionnaires were distributed to respondents and only 988 (82.2%) were dully returned and found usable. The results of the responses were interpreted using simple percentage and frequency tables. The findings of the study include, that 95% of Zamfara State population are farmers, Maru and Gusau Local Government Areas recorded the highest farmers’ population. It was also discovered that there was a high rate of awareness of climate change information in the State with Radio, Television, extension services as major sources of climate change information in the State. It was also discovered that farmers in the State utilize climate change information like taking decisions on what and when to plant, planting improved crop varieties among others. There is also the challenges of reduction in annual rainfall, deforestation, insect-pests attack, high temperature among others. Recommendations were made for intensified awareness campaign on climate change, increased budgetary allocation to the agricultural sector for more mitigation and adaptation capacity for the farmers.
Via online issue. 2 pages., Describes recent experience in which a packing house fire resulted in lower fed cattle prices and higher values of choice boxed beef cutout values - resulting in frustration and anger in cattle country.
Available online at www.centmapress.org, Results showed that the producers had seen a positive improvement in sales following acquisition of the regional food quality label, although they had not noticed greater interest in their products during campaigns to support awareness of the label.
29 pages, Agent-based models are important tools for simulating farmers’ behaviour in response to changing environmental, economic or institutional conditions and policies. This article introduces an agent-based modelling approach that combines behavioural factors with standard bio-economic modelling of agricultural production. More specifically, our framework integrates the cumulative prospect theory and social interactions with constrained optimisation decisions in agricultural production. We apply our modelling approach to an exemplary bio-economic model on the assessment of weed control decisions. Results show the effects of heterogeneous farm decision-making and social networks on mechanical weed control and herbicide use. This framework provides a generic and conceptually sound approach to improve the scope for representing farmers’ decision-making and allows the simulation of their decisions and recent advances in behavioural economics to be aligned with existing bio-economic models of agricultural systems.
