Year: 2025
Type: article
Abstract: Food fraud is a new term worldwide and can involve many different stages of the production process. It affects safety, quality, consumer acceptance, and profitability. Food fraud assessment methods need to be very precise and reliable. Most animal-origin foods, including milk, dairy products, meat and meat products, eggs, fish, and fisheries goods, are vulnerable to food fraud. Identifying any adulteration in them is essential to stop unfair competition and protect consumer rights. Due to financial benefits, meat and meat products are vulnerable to various forms of adulteration. The meat business is transitioning from laborious and time-consuming analytical procedures to quick, non-invasive, non-destructive, repeatable, and trustworthy analytical technologies. This reviews precision analytical methods like near-infrared (NIR) spectroscopy and machine learning algorithms, linear regression, principal component analysis, etc., for detecting food fraud in meat and meat products.
Source: Food Nutrition Chemistry
DOI: 10.18686/fnc333
Authors: Prantic Kumar Goswami, A. M. M. Nurul Alam, Jahan Ara Monti, M. A. Hashem, M. A. K. Azad
Language: English
Subfield: Analytical Chemistry
Field: Chemistry
Domain: Physical Sciences
SDG: Zero hunger
Open Access status: diamond
OpenAlex ID: W4410136248