We employ a wide range of advanced techniques from benchtop to handheld devices for modeling different phyisical, chemical and compositional parameters of food.
 
We use advanced statistical machine learning methods such as Principal component analysis (PCA) to visualiza patterns in the the experimental samples,
 
Linear Discriminant Analysis (LDA), to classify or group samples according to parameters of interest e.g expired, non-expire, close to expiry or ripe, unripe,  semi-ripe etc.
 
Partial Least Squares Regression) to predict the the concentration/presence of chemical components.
 
Contact: +233555183680