Milk and milk products, meat, fish and poultry as well as other animal derived foods occupy a pronounced position in human nutrition. Unfortunately, fraud in the food industry is common, resulting in negative economic consequences for customers as well as significant threats to human health and the external environment. As a result, it is critical to develop analytical tools that can quickly detect fraud and validate the authenticity of such products. Authentication of a food product is the process of ensuring that the product matches the assertions on the label and complies with rules. Conventionally, various comprehensive and targeted approaches like molecular, chemical, protein based, and chromatographic techniques are being utilized for identifying the species, origin, peculiar ingredients and the kind of processing method used to produce the particular product. Despite being very accurate and unimpeachable, these techniques ruin the structure of food, are labor intensive, complicated, and can be employed on laboratory scale. Hence the need of hour is to identify alternative, modern instrumentation techniques which can help in overcoming the majority of the limitations offered by traditional methods. Spectroscopy is a quick, low cost, rapid, non-destructive, and emerging approach for verifying authenticity of animal origin foods. In this review authors will envisage the latest spectroscopic techniques being used for detection of fraud or adulteration in meat, fish, poultry, egg, and dairy products. Latest literature pertaining to emerging techniques including their advantages and limitations in comparison to different other commonly used analytical tools will be comprehensively reviewed. Challenges and future prospects of evolving advanced spectroscopic techniques will also be descanted.

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Pasta is a cereal based, ready to cook, staple food, known for its affordable price, easy cooking, preferable sensory appeal and better storage stability, but its popularity is now growing as a healthy food worldwide. It is generally made from durum wheat semolina. Pasta made from gluten containing cereals creates problem for celiac patients.Hence, current study was undertaken (i) to prepare gluten free pasta from optimized levels of brown rice, amaranth flour, flaxseed flour and whey protein concentrate (WPC-70) and, (ii) to compare sensorial quality of gluten free pasta vis-a-vis available market samples of pasta to avoid market failure using fuzzy logic soft computing tool.Sensory evaluation was performed by a trained panel of sixteen judges. 'In general' ranking of pasta samples and their quality attributes was determined in linguistic term as (in decreasing order): Sample 4 (very good)> Sample 2 (very good)>Sample 3 (good)>Sample 1 (satisfactory) and Texture (highly important)>Flavor (highly important)> Appearance (important)>Color (important), respectively. However, exact ranking of pasta samples was obtained on the basis of maximum similarity value through fuzzy logic as shown in descending order: Sample 4 'very good'> Sample 2 'very good'>Sample 1 'good'>Sample 3 'good'. Gluten free pasta meets consumer's preference in terms of 'good' sensorial quality as revealed by fuzzy logic; contains higher dietary fibre, minerals and superior milk proteins than traditional pasta made from durum wheat. Therefore, it can be considered as a better and nutritional choice for celiac patients and general consumers.

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