At this point in our series dealing with linearity, we have determined that the data under investigation do indeed show a statistically significant amount of nonlinearity, and we have developed a way of characterizing that nonlinearity. Our task now is to come up with a way to quantify the amount of nonlinearity, independent of the scale of either variable, and even independent of the data itself.
New Study on Edible Oil Analysis Integrates FT-NIR and Machine Learning
January 14th 2025A new study published in Food Control introduces an approach for assessing antioxidant levels in edible oils using artificial intelligence and spectroscopy, offering significant potential for improving food quality control.