Determination of honey adulteration with beet sugar and corn syrup using infrared spectroscopy and genetic-algorithm-based multivariate calibration.

Published in: Journal of the science of food and agriculture (2018)

The fact that the models were generated with several honey samples coming from various different botanical and geographical origins, quite successful results were obtained for the detection of adulterated honey samples with a simple Fourier transform infrared spectroscopy technique. Having a genetic algorithm for variable selection helped to build somewhat better models with GILS compared with PLS. © 2018 Society of Chemical Industry.

Keyphrases

machine learning
deep learning
genome wide
copy number
neural network
dna methylation
gene expression
label free
molecularly imprinted
loop mediated isothermal amplification
real time pcr