Spatial Analysis
     Now that all constraints and factors have been identified and isolated the analysis can now begin.  This is a weighted linear combination multi-criteria evaluation, so all factors have been weighed according to their importance in affecting wheat production.  I could not find sources that identified the which factors were the most important for production, so I decided the weigh them using intuition.  In the preparatory steps for this analysis I isolated the maximum and minimum values for the parameters for successful wheat production.  Of course, there will not likely be one area which has all of the best characteristics for wheat.  The weighted MCE will trade-off negative factors with positive ones, coming up with the best locations according to the weight placed on the factors.  A cartogram leading to the MCE can be viewed here.

  • Once all the factors were identified and entered as a new pairwise comparison file, weight was added to each factor.
  • The most important factors I identified were:
    •                 1)  Precipitation
                    2)  Proximity to Waterbodies
                    3)  Wind
                    4)  Population Density
                    5)  Temperature
                    6)  Local Vegetation Type
                    7)  Slope

                                                 The weights of each factor are automatically calculated (above) after I input the weight of the factors
                                                 two at a time (below).
     

                                                The final result of this analysis are shown below.  The most suitable growing areas occur on a northwest
                                                  to southeast axis, centered over the equator.
     
     

                                                                          So which countries are best candidates for starting up an agribusiness?
                                                                          Ironically some of the war ravaged countries, such as Sierra Leone, have the
                                                                          best opportunity to help the continent's hunger pains.
     

         This analysis has shown areas of Africa suitable for massive wheat production.  Seven factors and two constraints were used with the weighted MCE to find areas most suitable, which is important because agribusiness is a costly venture.  Efficiency and productivity are functions of suitable land, suitable climate and local markets.  The value of wheat on the world market is quite low.  Canadian farmers in the early 1980's were getting around $11/bushel, whereas today the market price is around $4.  In fact, presently most of Africa's grain comes from places like Canada and the United States, so it would be unlikely that African agribusiness would export grain.  The costs of malnutrition can are associated with high costs of transporting and storing wheat from around the world.  To mitigate this, African governments that have the agricultural potential should sponsor agribusiness so hunger could be dealt with.
     

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