In the post "Linear Combinations to improve correlation" we selected three wavelengths where normally we found overtones for Protein, Fat and Fiber (Cellulose), and we found a linear combination of these three wavelengths to improve the correlation with the Protein constituent.
In this one we continue with the study of this data set. We have not just the Protein constituent, we have the values for Moisture, Fiber and Fat as well in the "Y" matrix and we want to check the inter-correlation between the constituents.
In the case we have NA values for some sample we won´t get the correlation value, and this is the case, so we remove first the samples with NA values and calculate the correlation between the constituents:
We see how we find a high negative correlation between Fiber and Protein, but this is normal in the case of soy meal.
But do we have high correlation between the absorbance of the wavelengths we associate with Protein and Fiber.
#1022nm datapoint 87 Protein or Oil
#1008nm datapoint 80 Oil or Water
# 996nm Oil or Water
# 902nm datapoint 27 Cellulose
# 964nm datapoint 58 CH2 Oil