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Vol. 10, Issue 11 (2021)

Development of medium fat plant-based mayonnaise using chickpea (Cicer arietinum) and green gram (Vigna radiata) and sensory evaluation using fuzzy logic

Author(s):
Kadam Mayur Raghunath, Bhosale Yuvraj Khasherao and Akalya Shanmugam
Abstract:
Mayonnaise and salad dressing have gained massive popularity among the young population worldwide. The legumes are good sources of protein and can be used as an egg replacer in mayonnaise. This study focuses on developing healthy mayonnaise options from green gram and chickpea to make it an entirely plant-based product. The chickpea and green gram were soaked for 12 hrs and cooked at 100 °C for 20 min, and after grinding, the extract was used to prepare mayonnaise in addition with chilli-mint paste. The physicochemical analysis has shown no significant difference among moisture, fat, carbohydrates, and ash. The significant difference was seen in protein content of green gram mayonnaise (4.14 ± 0.1%) and chickpea mayonnaise (3.62±0.27%). Similarly, crude fiber content was 6.33±0.12% in the chickpea mayonnaise and 3.9±0.1% green gram mayonnaise. Chickpea mayonnaise has shown high shear-thinning properties than green gram mayonnaise. The sensory evaluation revealed that mayonnaise made with chickpea was more accepted in terms of colour, appearance, and texture. At the same time, green gram flavoured mayonnaise was preferred for taste and, mouthfeel. The best sample was chosen by using fuzzy logic in which all samples were compared with commercial sample and consumer expectations for ideal mayonnaise and developed sample were found acceptable.
Pages: 896-901  |  962 Views  818 Downloads


The Pharma Innovation Journal
How to cite this article:
Kadam Mayur Raghunath, Bhosale Yuvraj Khasherao, Akalya Shanmugam. Development of medium fat plant-based mayonnaise using chickpea (Cicer arietinum) and green gram (Vigna radiata) and sensory evaluation using fuzzy logic. Pharma Innovation 2021;10(11):896-901.

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