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β-Carotene-rich sweet potato curd: production, nutritional and proximate composition
- Mohapatra, Samaptika, Panda, Smita H., Sahoo, Santosh K., Sivakumar, Paramasivan Sethuraman, Ray, Ramesh C.
- International journal of food science & technology 2007 v.42 no.11 pp. 1305-1314
- Lactobacillus delbrueckii subsp. bulgaricus, Lactococcus lactis subsp. lactis, antioxidants, beta-carotene, beverages, color, consumer preferences, dietary fiber, fermentation, fermented foods, hedonic scales, lactic acid, milk, milk curds, minerals, nutrients, pH, pigments, plate count, principal component analysis, proximate composition, starch, sweet potatoes, sweetness, texture, titratable acidity
- Sweet potato (SP) is an important root crop grown all over the world and consumed as a vegetable, boiled, baked or often fermented into food and beverages. A curd-like product was prepared by fermenting boiled β-carotene-rich SP puree and cow milk with curd (starter) culture (Lactobacillus bulgaricus, Streptococcus lactis, Streptococcus diacetilactis, etc.). There were not much variation in pH (3.6-3.9), titratable acidity (10-11.8 g kg⁻¹ curd) and lactic acid (LA) (7.9-5.3 g kg⁻¹ curd) contents in SP curd consisting different concentration of SP puree. However, curd with 12-16% SP puree was most preferred by a consumer's panellist. The addition of SP puree (12-16%) made the curd quite firm and imparted flavour, body/texture, minerals, nutrients, antidiabetic substances, β-carotene pigments (antioxidant), dietary fibres and starch (carbohydrate source). The LA bacterial counts in the curd after 18 h of fermentation having 8% and 16% SP were 7 x 10⁷ and 14 x 10⁷ (CFU mL⁻¹), respectively. The consumer evaluation scores ranged from 7 to 8 (in a hedonic scale of 1-9), from moderate liking to very much liking of the SP curd, taking into consideration the sensory attributes such as colour, texture, flavour, sweetness, appearance, etc. Principal component analysis (PCA) reduced the fourteen original analytical (proximate) variables to four independent components (factors), which accounted for 97% of the total variations. Similarly, PCA analysis reduced the seven original sensory attributes to three independent components that accounted for 70% of the total variations.