Editing Chemometrics (section)

=== Chemometrics and Food Science ===
Over the past decade, multivariate statistical techniques originally developed for analytical chemistry have become widely utilized in food science and technology. Chemometrics is particularly valuable when dealing with large and complex datasets, encompassing diverse sample types, numbers, and responses. These techniques support the authentication of geographical origins, farming systems, and the detection of adulteration in high-value food commodities. <ref name=":0">{{Cite journal |last=Granato |first=Daniel |last2=Putnik |first2=Predrag |last3=Kovačević |first3=Danijela Bursać |last4=Santos |first4=Jânio Sousa |last5=Calado |first5=Verônica |last6=Rocha |first6=Ramon Silva |last7=Cruz |first7=Adriano Gomes Da |last8=Jarvis |first8=Basil |last9=Rodionova |first9=Oxana Ye |last10=Pomerantsev |first10=Alexey |date=2018 |title=Trends in Chemometrics: Food Authentication, Microbiology, and Effects of Processing |url=https://ift.onlinelibrary.wiley.com/doi/10.1111/1541-4337.12341 |journal=Comprehensive Reviews in Food Science and Food Safety |language=en |volume=17 |issue=3 |pages=663–677 |doi=10.1111/1541-4337.12341 |issn=1541-4337|url-access=subscription }}</ref>

Overall, chemometrics is an essential tool for addressing complex, multifactorial challenges in food science through a holistic approach. Governmental bodies and industries responsible for food quality monitoring, raw material assessment, and process optimization should incorporate chemometrics, particularly when working with high-dimensional data. To assist users in selecting the most suitable tools, this article outlines practical applications and evaluates the advantages and limitations of commonly used chemometric methods. <ref name=":0" />