Swapna K.S.,Dairy Science College |
Rao K.J.,National Dairy Research Institute
Journal of Food Science and Technology | Year: 2015
In view of their growing importance in human nutrition, incorporation of oats and cheese during the manufacture of short-dough type biscuits was studied. Rolled oats were incorporated at 25, 35 and 45 % of refined wheat flour in short-dough type biscuit formulation. Cheddar and processed cheese were used for flavouring purpose at three levels each, viz. 30, 40 and 50 % on flour basis. The dough exhibited less firmness on oats incorporation as indicated by lower firmness value (21.73 N) as against 25.05 N for control dough measured by Texture Analyser. Addition of cheese to the 25 % oat incorporated dough further reduced its firmness and altered its viscoelastic characteristics. Baking conditions for the oats and cheese incorporated biscuits were optimized as 165 °C for 25–27 min. Sensory evaluation results revealed that the biscuit made from 25 % oat incorporated dough scored highest in most of the sensory attributes including overall acceptability. Cheddar cheese and processed cheese levels were optimized at 30 and 40 % in oats-incorporated dough based on the sensory analysis of biscuits prepared from the dough samples. The moisture and β- glucan contents were 3.93 % and 0.62 %; 4.32 % and 0.60 % for cheddar cheese and processed cheese added biscuits, respectively. The spread ratios were higher in cheese incorporated biscuits than in oat incorporated biscuits. It was concluded that good quality cheese flavoured biscuits can be prepared by incorporating rolled oats in biscuit formulation along with cheddar or processed cheese. © 2015 Association of Food Scientists & Technologists (India)
Sharma A.K.,National Dairy Research Institute |
Sawhney I.K.,National Dairy Research Institute |
Lal M.,Dairy Science College
Drying Technology | Year: 2014
Soft computing-based intelligent models have been proposed to predict moisture sorption isotherms in milk and pearl millet-based weaning food, "fortified Nutrimix," at four temperatures, 15, 25, 35, and 45°C over the water activity range 0.11-0.97. Connectionist and adaptive neuro-fuzzy inference system (ANFIS) models were investigated. A back-propagation algorithm with Bayesian regularization/Levenberg-Marquardt optimization mechanisms was employed to develop connectionist models. The ANFIS model was based on the Sugeno-type fuzzy inference system. In addition, several empirical models were explored for fitting the sorption data. The soft computing models, in particular, ANFIS, outperformed the conventional sorption models for predicting isotherms in Nutrimix. © 2014 Copyright Taylor & Francis Group, LLC.
Latha K.V.A.,University of Agricultural Sciences, Dharwad |
Bhat A.R.S.,University of Agricultural Sciences, Dharwad |
Achoth L.,Dairy Science College
International Journal of Agricultural and Statistical Sciences | Year: 2012
Decomposition models are models that are helpful in the agricultural and non-agricultural sectors where segregation of component elements is important. In agricultural research institutions of various countries, composition models have been applied to study the contribution of component elements in the change of crops output. And this research is limited to the component analysis of crop research, more importantly identification and measurement of component elements in the change of crop production, identification and quantification of sources of variance in crop production over space and time, decomposition of output with the introduction of new technology in the farming system. This study deals with Hazell peter (1982) model on changes in important cereal production. This model is a time tested model which decomposes variance of production into direct effects and indirect effects, it has unique feature in that the variance of production is decomposed into ten components. The analysis has been done at State level data. Production variability has been measured in two time periods. The data used here were obtained by the department of Economics and Statistics, Bangalore. The researcher has developed a programme in MS-Excel package for Peter Hazell's Decomposition Analysis, which is used friendly. This decomposition models not only help in agriculture sector, but also in non-agricultural sectors to find out the key factors of instability in production.
Giri A.,National Dairy Research Institute |
Rao H.G.R.,University of Veterinary and Animal Sciences |
Ramesh V.,Dairy Science College
International Journal of Dairy Technology | Year: 2013
In 50% sugar replaced with 0.05% stevia-added Kulfi, whey protein concentrate (WPC) at 0, 2, 3 and 4% levels were separately incorporated. Increase in WPC level resulted in significant (P < 0.05) decrease in freezing point, melting rate, hardness and moisture percentage and significant (P < 0.05) increase in specific gravity, protein percentage and total calorie content in the product. Among 0, 2, 3 and 4% WPC-added Kulfi, 3% WPC-added Kulfi was adjudged as best by a panel of judges. Above 3% WPC addition, the product was very soft and possessed undesirable whey flavour. © 2012 Society of Dairy Technology.
Schober Y.,Justus Liebig University |
Yoo S.H.,Konkuk University |
Paik H.-D.,Konkuk University |
Park E.J.,Kyungnam University |
And 4 more authors.
Milchwissenschaft | Year: 2012
This investigation was carried out to evaluate the extent of bioactive peptides that can be obtained from proteolytic enzymes, including alcalase, flavorzyme, neutrase, and protamax. For this purpose, whey protein concentrate (WPC) was hydrolyzed, spray-dried, and subjected to mass spectrometric analysis. In addition, offline-electrospray-ionizationmass spectrometry (ESI/MS) measurements and offline-matrix-assisted laser desorption/ionization mass spectrometry (MALDI/MS) measurements were compared to determine analytical adequacy. Samples treated with alcalase for 3 hours produced various bioactive peptides, suggesting the possible application of this method to functional food preparations. Comparison of both ionization methods indicated ESI/MS as suitable for the identification of peptides from whey protein hydrolysates.