Computer vision systems have become typical tools of increasing importance to control manufacturing processes and product quality in a non-destructive manner in food industrial processing. During the past several years, we have heard about how hyperspectral imaging, joined with chemometrics, could offer a set of possibilities that may help to increase the control of the final quality assessment in production lines. This chapter will not review the main applications of HSI and chemometrics for food quality assessment, since this has already been extensively covered in several reviews. Instead, we will discuss the application and feasibility of the main chemometric techniques applied to different foodstuffs. The reader will be provided with a detailed overview of how to use chemometrics in hyperspectral data, along with a critical discussion on their respective advantages and potential pitfalls. The examples that we will use for this purpose are the detection of water in cheese, classification of bitterness in almonds in a set of samples, detection and classification of contaminants in cheese, and hydration of chickpeas during soaking.

Text in English