326 Indian J. Dairy Sci. 68(4), 2015 Abstract In the present investigation, sensory scores of four screened market samples of Kheer Mohan were evaluated and ranked for their quality attributes employing fuzzy logic. A panel of sixteen judges performed the sensory evaluation of Kheer Mohan samples. Both ranking and desirable quality characteristics of the samples 'in general' were analyzed with fuzzy logic. Among the screened samples, products from Gangapur city were ranked as the most preferred samples. The quality attributes which affected the acceptability of samples were found to be flavor, body & texture, colour & appearance and juiciness & sweetness in descending order of their significance. Flavor, body and texture of Kheer Mohan were considered as the most vital quality attributes and were rated under the category "very good" by the sensory panel. Strong as well as weak attributes with respect to their impact on product quality, were also determined. Keywords : Sensory evaluation, Fuzzy logic, chhana, Kheer Mohan, modelling Introduction India is the global leader in milk production with the annual production of 127.8 million tonnes during year 2011-12 and it is expected to reach the value of 133 million tonnes in year 2012-13 (Srivastava, 2013). Conversion of the surplus milk into indigenous sweets has played a vital role in economic, social, religious and nutritional well-being (by preserving natural nutritional potent of milk and shelf life enhancement) of the nation's consumers since time immemorial. More than half of the annual milk production is being utilized mainly by unorganized sector for the production of such indigenous products having estimated market size and annual growth of Rs. 1,00,000 crores and Rs. 5,000 crores respectively (Patil, 2013). Moreover, conversion of milk into such indigenous sweet meats results in addition of 200% value to the original milk when compared with its conversion into western dairy products which adds only 50% value to it (Aneja et al., 2002). Basically, chhana and khoa are the two base/filler materials for a number of chhana and khoa based sweets. Around 7% of India's total milk production is used to produce six lakh tonnes of khoa on annual basis (Rajarajan et al., 2007). Sahu and Das (2007) reported that about 6% of the total milk production is converted to chhana through coagulation. Sahu and Das (2009) also reported market volume of chhana based sweets in India is about 1 million tonnes with a value of Rs. 7,00,000 crores. These indigenous products are mainly produced using the processes like heat and acid coagulation, heat desiccation and fermentation and can be classified into two major groups i.e. popular indigenous products and regional/underutilized indigenous products. Kheer Mohan is a chhana based sweet meat highly popular in eastern Rajasthan. Till date, production of Kheer Mohan is mainly region-specific and to make its presence all over the country, more efforts are needed. The first step of such an effort is product characterization, which has already been reported (Meena et al., 2014). Total impression created by any food stuff in the minds of consumers usually determines its sensorial quality (Giusti et al., 2008; Reinoso et al., 2008). Although humans are well equipped with five different integral senses yet, they can only evaluate aroma, taste, color and appearance followed by body and texture of a particular food item. The course of sensory evaluation, which decides the acceptance or rejection of any foodstuff, is usually characterized by imprecision, inaccuracy and ambiguous repeatability. Moreover, during sensory RESEARCH ARTICLE Fuzzy logic (Similarity Analysis) modelling for sensory evaluation of market samples of Kheer Mohan Ganga Sahay Meena, Vijay Kumar Gupta, Yogesh Khetra, Raghu H V and P T Parmar Received : 14 August 2014 / Accepted : 14 January 2015 Ganga Sahay Meena () , Vijay Kumar Gupta, Yogesh Khetra Dairy Technology Division Raghu HV and P T. Parmar Dairy Microbiology Division ICAR-National Dairy Research Institute,Karnal -132001 Ganga Sahay Meena Email-gsiitkgp@gmail.com