Crop Yield Prediction Using Solar Activity
Journal Title: IOSR Journal of Applied Physics (IOSR-JAP) - Year 2018, Vol 10, Issue 6
Abstract
The yields of tuber crops were predicted in this work. Parametric analysis was carried out to obtain historical coefficients for solar activity index and crop yield data, using observed yields with time, Sunspot Number, and cultivated area as input variables. Multiple polynomial regression of 2nd degree was used to model the yields of yam and cassava in Benue State-Nigeria. The model explained 73.9 % of yield variance for yam and 69.9% of yield variance for cassava, and it showed increment in yields for two years (2018 and 2019) for both crops, corresponding to minimum solar activity. The model was testedfor accuracy using Willmottβs dvalue,and the accuracy test gave π. ππ for yam and π. ππ for cassava on a scale of 0.0 to 1.0. In addition to this, the model was validated using observable data and a good agreement was found between the observed and the predicted yields.
Authors and Affiliations
C. A. Chile,, G. D. Ihongo,, B. A. Ikyo.
Keywords
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- EP ID EP423856
- DOI 10.9790/4861-1006013543
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