Modeling and Optimization of some optical properties of cowpea seeds for
Automation Sensing Operations.
Artificial intelligent and automation are the modern trends to
industrial development. The objective of this study is to determine,
model and optimize some optical properties of bulk cowpea grains
varieties relevant for automation. Three varieties with five moisture
levels were used. Colour properties were determined using chroma meter
while the absorbance and transmittance properties were determined using
spectrophotometer. Direct reflection property was calculated using
Beer-Lambert equation. Quartic model was found to be the best for colour
properties while quadratic model for absorbance and reflection
properties. Quadratic model was not sufficient enough to describe the
transmittance property. All models developed were found to be
significant at p < 0.05 and were also confirmed. Optimal
values for selecting sensors to identify, classify or sort cowpea seeds
using the optical properties studied were developed.