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The purpose of this study was to investigate the predictability of the consistency of blended porridges based on the volume fractions of separate porridges made from orange-fleshed sweet potato, cowpea, dehulled soybean, dehulled sorghum and maize flour (dehulled, commercial and germinated). Accurate predictions could be made for 13 of the 21 blends investigated. The consistency of porridge consisting of mixtures of cowpea with orange-fleshed sweet potato, and cowpea with dehulled soybean was lower than expected, and was attributed to the different size distributions of the swollen flour particles. Blends containing germinated maize showed significantly lower consistency than expected in both porridges with starchy continuous phase and porridges with proteinaceous continuous phase. It was thus concluded that both amylolytic and proteolytic activity are of importance in the ameliorating effects of germinated maize.
In this paper, regression function estimation from independent and
identically distributed data is considered. We establish strong
pointwise consistency of the famous Nadaraya-Watson estimator under weaker
conditions which permit to apply kernels with unbounded support and even not
integrable ones and provide a general approach for constructing strongly
consistent kernel estimates of regression functions.