Page 45 - FoodFocusThailand No.246 October 2026

STRONG
STRONG QC & QA QC & QA

FROM TESTING TO PREDICTION:

NON-DESTRUCTIVE TECHNOLOGIES

FOR SMARTER NUTRITIONAL ANALYSIS

Traditional nutritional analysis methods, known as wet chemistry methods, such as Kjeldahl, Soxhlet,
and Lane-Eynon, are standard methods that provide accurate results and are internationally recognized.
However, these methods have several limitations, including sample destruction, lengthy analysis times,
chemical consumption, and reliance on skilled personnel and specialized equipment. As a result, they are
not well suited for rapid and continuous nutritional monitoring on the production line. These challenges
have driven the development of non-destructive analytical techniques, bringing nutritional assessment
closer to real-time measurement.

When Light and Wavelengths Become Tools Near-Infrared Spectroscopy:
for Nutritional Analysis The Pioneer with the Widest Practical Use
One major group of non-destructive testing (NDT) technologies Near-Infrared Spectroscopy (NIR) uses light at
uses electromagnetic radiation at different wavelengths to measure wavelengths of approximately 760–2,500 nanometers,
how food samples absorb, reflect, or scatter light. This approach, either passing through or reflecting from a food
known as spectroscopy, generates spectral data that can be sample. Different chemical bonds in molecules,
combined with statistical models and artificial intelligence to estimate such as C-H, O-H, and N-H, are associated with
or predict the chemical composition and quality characteristics of the major components of food, including proteins,
food without destroying the sample. fats, and carbohydrates, and absorb light at specific
This article explores three key technologies: Near-Infrared wavelengths. By processing the resulting signals
Spectroscopy (NIR), Hyperspectral Imaging (HSI), and Raman using chemometrics, the levels of nutrients can be
Spectroscopy. All are increasingly used in food analysis and estimated.
quality control. HSI also combines spectral information with spatial NIR is fast, requires little sample preparation,
information, allowing differences in composition to be analyzed uses no chemicals or reagents, and can measure
across different areas of a food sample. several parameters at the same time. In research

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