climate variability

The impact of climate variability on agricultural food crop production and output: the case of some selected communities in Offinso South District of Ghana

Published on: 20th December, 2022

In Ghana, there is evidence of the direct influence of climate change on the environment, such as rising temperatures, variable rainfall, and precipitation. These manifestations affect various facets of Ghana socio-economic structure especially with its high reliance on sectors that are particularly sensitive to climate change like agriculture. In the settlements of Bonsua and Amoawi in the Offinso South District, the study concentrated on the influence of climate change variables on food crop production and how farmers are adapting to the various climate change measures. Out of the total of 650 staple food crop farmers in the dorminated selected communities namely, Amoawi and Bonsua, 160 farmers were chosen for the study using systematic random sampling. The study included both primary and secondary data. Descriptive cross sectional survey was employed for the study. The data collection instrument employed was Structured and semi-structured interviews. SPSS was used to analyse the data. The data collected for the study were analysed using both descriptive and inferential analytical tools. Findings from the study indicate that climate change is a challenge to food crop production since agriculture activity in the two communities are mostly rain feed (97.5%). The majority of the crops grown in the two areas are climate change vulnerable. Another study finding reveals that most respondents have modified their coping mechanisms such as such as growing different crop varieties, early and late planting, irrigation and soil conservation to deal with how climate change is affecting agriculture. Therefore, the study suggests that both government and non-governmental organizations should support farmers in building irrigation systems to continuously irrigate their food crops during the dry season, increasing their farm productivity.
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