Classical and emerging non-destructive technologies for safety and quality evaluation of cereals: A review of recent applications

Background: Cereals are globally consumed as staple food, providing essential nutrients to the consumers. The emerging problems associated with cereals are mycotoxin outbreaks and adulteration in both the cereals and their products. Both classical and emerging techniques are extensively exploited to tackle such problems. However classical methods still face more limitations as compared to emerging nondestructive methods. Scope and methods: High-performance liquid chromatography, gas chromatography and enzyme-linked immunosorbent assays, are classical methods employed for assessing the quality and safety parameters of cereal foods, with limitations of offline, time consuming and destructiveness. On the other hand, emerging nondestructive methodologies like hyperspectral imaging, fluorescence spectroscopy, near infrared spectroscopy and Fourier transform infrared spectroscopy have been introduced as promising techniques for the assessment of fungal contamination, quality discrimination and adulteration detection in cereals and cereal products. This review highlights the most recent applications of enlisted classical and emerging approaches, their working principles and advances in determining various safety and quality attributes of cereals and their products. Besides, challenges and future trends, their advantages and limitations are also elucidated. Key findings and conclusions: Classical methods have been exploited for safety and quality measurement of cereal foods with relatively low efficiency, as compared to emerging nondestructive techniques. Classical methods suffer from disadvantages of destructiveness, thus they cannot be used for on-line monitoring, detection and evaluation. Emerging approaches are reliable with accurate, fast and non-invasive nature of investigations for the authentication of safety and quality attributes of cereal grains and their products during storage and processing. These innovative technologies can overcome the complexity, troubles, destructibility and slowness associated with classical analytical tools.