Modeling thermal conductivity, specific heat, and density of milk: A neural network approach

The accurate determination of thermophysical properties of milk is very important for design, simulation, optimization, and control of food processing such as evaporation, heat exchanging, spray drying, and so forth. Generally, polynomial methods are used for prediction of these properties based on empirical correlation to experimental data. Artificial neural networks are better Suited for processing noisy and extensive knowledge indexing. This article proposed the application of neural networks for prediction of specific heat, thermal conductivity, and density of milk with temperature ranged from 2.0 to 71.0degreesC, 72.0 to 92.0% of water content (w/w), and 1.350 to 7.822% of fat content (w/w). Artificial neural networks presented a better prediction capability of specific heat, thermal conductivity, and density of milk than polynomial modeling. It showed a reasonable alternative to empirical modeling for thermophysical properties of foods.

Isoflavone-supplemented soy yoghurt associated with resistive physical exercise increase bone mineral density of ovariectomized rats

Objective: To determine the effects produced by the ingestion of a fermented soy product (soy yoghurt), supplemented with isoflavones and associated with a resistive exercise program, on the bone metabolism of mature ovariectomized (Ovx) and sham-ovariectomized (sham-Ovx) rats.Methods: A total of 56 rats were used. They were divided into 2 sedentary control groups, the Ovx control group (C-Ovx) and the sham-Ovx control group (C-Sovx), each with 7 sedentary animals, and 2 treated groups, Ovx and sham-Ovx, with 21 animals each. These two treated groups were subdivided into three subgroups of seven animals each, which received the following treatments: consuming the soy yoghurt + sedentary, only subjected to resistive exercise, and consuming the soy yoghurt + resistive exercise. Both the program of resistive exercise and the consumption of soy yoghurt (at 3 mL/(kg body weight day)) continued for 12 weeks. The soy yoghurt was supplemented with isoflavones at 50 mg/100 g of product. The animals were sacrificed and their right-side femurs and tibias removed and assessed for bone mineral density (BMD). The alkaline phosphatase activity (AP) was determined in the blood serum.Results: There was a significant increase in both femur and tibia BMD values and in serum alkaline phosphatase activity in all the treated subgroups, compared with the control groups (p < 0.05).Conclusion: the ingestion of the soy yoghurt supplemented with isoflavones was capable of preventing a loss of bone mass in Ovx rats and of increasing bone mass in sham rats, whilst the resistive exercise program was effective in augmenting the bone mass in sham and Ovx rats. (c) 2007 Elsevier B.V.. All rights reserved.

Genetic and environmental effects over milk production of buffalo cows in Brazil

The objective of this paper was to evaluate the relevance of environmental and genetics effects on milk production of buffalo cows in Brazil. The data were based on the Buffalo Genetic Improvement Program - PROMEBUL, using information of 1,911 cows (107 Jafarabadi, 101 Mediterranean, 1,056 Mu/Tab and 647 crossbred females) with parturition between 1982 and 2003. The mathematic model for evaluating milk production included the fixed effects of herd, parturition year (1982 to 2003) and month (January to December), calf's sex (male or female), genetic group (Jafarabadi, Mediterranean, Murrah, and crossbreed), number of milking (one or two), lactation order (1 to 12) and duration of lactation (as a linear effect). The mean milk production in herds was 1,590.36 +/- 609.25 kg. All sources of variation were significant (P<0.05) for the studied characteristics, except calf's sex. The mean milk production per genetic group was 1,651.4; 1,592.2; 1,578.3 and 1,135.5 kg, for Murrah, Mediterranean, Crossbred and Jafarabadi, respectively. The duration of lactation was the most important source of variation over milk production, followed by the year of parturition, herd, parturition order, genetic group and month of parturition.

Genetic parameters estimate for milk and mozzarella cheese yield, fat and protein percentage in dairy buffaloes in Brazil

The aim of this study was analyze the (co)variance components and genetic and phenotypic relationships in the following traits: accumulated milk yield at 270 days (MY270,), observed until 305 days of lactation; accumulated milk yield at 270 days (MY270/A) and at 305 days (MY305), observed until 335 days of lactation; mozzarella cheese yield (MCY) and fat (FP) and protein (PP) percentage, observed until 335 days of lactation. The (co)variance components were estimated by Restricted Maximum Likelihood methodology in analyses single, two and three-traits using animal models. Heritability estimated for MY270, MY270/A, MY305, MCY, FP and PP were 0.22; 0.24, 0.25, 0.14, 0.29 and 0.40 respectively. The genetic correlations between MCY and the variables MY270, MY270/A, MY305, PP and FP was: 0.85; 1.00; 0.89; 0.14 and 0.06, respectively. This way, the selection for the production of milk in long period should increase MCY. However, in the search of animals that produce milk with quality, the genetic parameters suggest that another index should be composed allying these studied traits.

Correlation between acidic ninhydrin and HPLC methods to evaluate fraudulent addition of whey in milk

The acidic ninhydrin spectrophotometric method (ANSM) for quantitative determination of free and bound sialic acid of milk glycoprotein has been proved to be fast and efficient for routine detection of fraudulent addition of rennet whey to fluid milk. In this research the ANSM was compared with the high performance liquid chromatography (HPLC) method, internationally recommended for caseinomacropeptide (CMP) determination, which besides its high accuracy is more sophisticated and requires trained personnel. For several sample conditions (raw milk and milk with variable added amounts of rennet cheese whey), the methods showed an excellent linear correlation, with r = 0.981 when milk was deproteinized with a 120 g.L-1 final concentration of trichloroacetic acid (TCA) concentration. The best correlations could be seen with final concentrations of 100 g.L-1 and 80 g.L-1 TCA; respectively, r = 0.992 and 0.993.

Influence of temperature and water and fat contents on the thermophysical properties of milk

Heat capacity, thermal conductivity, and density of whole milk, skimmed milk, and partially skimmed milk were determined at concentrations varying from (72.0 to 92.0) mass % water content and from (0.1 to 7.8) mass % fat content, at temperatures ranging from (275.15 to 344.15) K. Heat capacity and thermal conductivity varied from (3.4 to 4.1) J(.)g(-) K-1.(-1) and from (0.5 to 0.6) W(.)m(-1) K-1.(-1), respectively. Density varied from (1011.8 to 1049.5) kg(.)m(-3). Polynomial functions were used to model the dependence of the properties upon the studied variables. A linear relationship was obtained for all the properties. In the tested range, water content exhibited a greater influence on the properties, while fat content showed a smaller influence.

Genetic parameters of milk, fat, and protein yields in the first three lactations, using an animal model and restricted maximum likelihood

Milk, fat, and protein yields of Holstein cows from the States of New York and California in the United States were used to estimate (co)variances among yields in the first three lactations, using an animal model and a derivative-free restricted maximum likelihood (REML) algorithm, and to verify if yields in different lactations are the same trait. The data were split in 20 samples, 10 from each state, with means of 5463 and 5543 cows per sample from California and New York. Mean heritability estimates for milk, fat, and protein yields for California data were, respectively, 0.34, 0.35, and 0.40 for first; 0.31, 0.33, and 0.39 for second; and 0.28, 0.31, and 0.37 for third lactations. For New York data, estimates were 0.35, 0.40, and 0.34 for first; 0.34, 0.44, and 0.38 for second; and 0.32, 0.43, and 0.38 for third lactations. Means of estimates of genetic correlations between first and second, first and third, and second and third lactations for California data were 0.86, 0.77, and 0.96 for milk; 0.89, 0.84, and 0.97 for fat; and 0.90, 0.84, and 0.97 for protein yields. Mean estimates for New York data were 0.87, 0.81, and 0.97 for milk; 0.91, 0.86, and 0.98 for fat; and 0.88, 0.82, and 0.98 for protein yields. Environmental correlations varied from 0.30 to 0.50 and were larger between second and third lactations. Phenotypic correlations were similar for both states and varied from 0.52 to 0.66 for milk, fat and protein yields. These estimates are consistent with previous estimates obtained with animal models. Yields in different lactations are not statistically the same trait but for selection programs such yields can be modelled as the same trait because of the high genetic correlations.

Effects of soy protein and resistance exercise on body composition and blood lipids in postmenopausal women

Objective: To assess the effect of soy protein and progressive resistance training on body composition and lipids in postmenopausal women.Design: In a controlled trial, 46 postmenopausal women were randomized to one of four groups: 25 g of soy protein (SP, n = 10), 25 g of soy protein plus resistance exercise (SPE, n = 14), 25 g of maltodextrine (placebo) (PL, n = 11), or placebo plus resistance exercise (PLE, n = 11). Progressive resistance training was held three times a week for 16 weeks and included 8 exercises (3 series of 8-12 repetitions). At baseline and after 16 weeks, body mass index, waist circumference (WC), body fat, muscle mass and serum lipid levels were measured. To confirm isoflavone absorption, urinary concentrations were determined. The t-test of Student and ANOVA were used in the statistical analysis.Results: Subjects were classified as overweight and showed android fat distribution: Urinary isoflavone excretion indicated compliance to soy protein treatment. After 16 weeks of intervention, both SPE and PLE groups showed a significant increase of 1.3 kg in muscle mass and reduction in WC of -1.4 and -2.1 cm, respectively (p < 0.05). Significant decreases in the mean values of total cholesterol and LDL (-29.0 and -24.0 mg/dL, p < 0.001 and p < 0.006, respectively) were observed in the users of soy protein alone (SP).Conclusions: Soy protein supplementation did not influence the indicators of body composition. However, it exerted possible favorable effects on lipid profile in postmenopausal women. The increase in muscle mass and reduction in abdominal fat were correlated with resistance training. (c) 2006 Elsevier B.V.. All rights reserved.