Rainfall Variability and Food Crop Vulnerability in Ndu Sub-Division, North West Region of Cameroon


  •  Chiarity Zetem Chiambah    
  •  Cordelia G. Kometa    

Abstract

Little scientific evidence exists in the context of climate variability and food crop production in Ndu. This study seeks to assess the impact of rainfall variability on food crop vulnerability in Ndu Sub-Division. The primary data were gotten through field surveys. A total of 200 farmers were sampled and questionnaires were administered to them. Descriptive and inferential statistical techniques were employed to analyze the data. Results were presented in tables and climographs. Formulated hypotheses were tested using the least square regression model to establish the extent of exposure and sensitivity of rainfall variability on food crop production. The Pearson Product Moment Correlation Coefficient was used to describe the trends of variations in rainfall. Statistically, rainfall accounted for 19.5% of variability in maize production while 50.87% accounted for variability in beans production. Furthermore, 30.1% accounted for variations in potatoes production. From these statistics it was then concluded that rainfall variability minimally affects maize and beans but had a significant effect on maize production in Ndu. The research study also revealed that rainfall shows a decreasing trend. The study recommended, amongst others the need for farmers to adopt more sustainable agricultural practices and the increased use of more resistant crop species that can withstand exposure and sensitivity to rainfall variability. The study concluded that a bottom-up approach should be employed in order to improve on the adaptive capacities of the agricultural sector in Ndu.



This work is licensed under a Creative Commons Attribution 4.0 License.
  • ISSN(Print): 1916-9779
  • ISSN(Online): 1916-9787
  • Started: 2009
  • Frequency: quarterly

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(The data was calculated based on Google Scholar Citations)

Google-based Impact Factor (2018): 11.90

h-index (January 2018): 17

i10-index (January 2018): 36

h5-index (January 2018): 13

h5-median(January 2018): 15

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