Analysis of organochlorine pesticides in plain milk using direct injection on an ISRP column, with column switching

A simple and rapid procedure for extraction and separation from aldrin, DDT, endrin, heptachloro- and methoxychloro-organochlorine pesticides in raw milk has been developed by direct injection into an HPLC system without pretreatment of the samples, using an ISRP column.

Isolation of Candida spp. from mastitic bovine milk in Brazil

The purpose of this study was to isolate yeast (Candida) from the quarter milk of cow udders from 37 dairy farms in Brazil and to identify the different species involved in mastitis. The samples were collected between October 2002 and February 2003. Two-hundred-and-sixty milk samples from cows with clinical and subclinical mastitis were examined. Milk samples were plated onto Blood agar, Mac Conkey agar and Sabouraud dextrose agar. Forty-five (17.3%) samples were positive for the genus Candida. The Candida species isolated were C. krusei (44.5%), C. rugosa (24.5%), C. albicans (8.9%), C. guilliermondii (8.9%), and others (13.2%). We also isolated Escherichia coli (26.5%), coagulase-positive Staphylococcus (25.0%), Streptococcus spp. (8.1%), Enterobacter spp. (8.1%), and other fungi (8.1%), among others.

On-line extraction and determination of carbofuran in raw milk by direct HPLC injection on an ISRP column

A method has been developed for extraction and determination of carbofuran in milk. The method involved direct injection of raw milk on to a human serum albumin dimethyloctyl-silica gel (HSA-Cs) column and the use of 80:20 (v/v) 0.01 M phosphate buffer pH 5.5 - acetonitrile as mobile phase. UV spectrophotometric detection was performed at 220 nm. Identification was based on retention time. Quantification was performed by automatic peak-area determination and was calibrated by use of an external standard.

Rehydration and shrinkage behaviour of dried pineapple

The shrinking behavior, apparent densities and rehydration indexes of fresh and osmotically pre-treated pineapple slices during air-drying were obtained. The air drying velocity varied from 1.5 to 2.5 m/s and the air temperature from 40 to 70 degreesC. By means of automatic control, it was possible to obtain drying curves under conditions of constant product temperature. Volumetric shrinkage of fresh samples was temperature independent for drying at high air velocities but, at lower velocities, increased with decreasing drying temperature. Osmotically pre-treating the material resulted in reduced shrinkage, as well as drying with product temperature controlled, due to lower drying times needed that led to shorter high temperature exposition. Moisture dependence of apparent density was highly non-linear and could be fitted by an empirical model. Fresh sample rehydration indexes were higher than osmosed ones and increased with increasing temperature, except for pre-treated samples dried at 70 degreesC, probably due to superficial sugar caramelization, which reduced surface water permeability.

Genetic parameters for milk yield, age at first calving and interval between first and second calving in milk buffaloes

Genetic parameters for the relation between the traits of milk yield (MY), age at first calving (AFC) and interval between first and second calving (IBFSC) were estimated in milk buffaloes of the Murrah breed. In the study, data of 1578 buffaloes at first lactation, with calvings from 1974 to 2006 were analyzed. The MTDFREML system was used in the analyses with models for the MY, IBFSC traits which included the fixed effects of herd-year-season of calving, linear and quadratic terms of calving age as covariate and the random animal effects and error. The model for AFC consisted of the herd-year-season fixed effects of calving and the random effects of animal and error. Heritability estimates MY, AFC and IBFSC traits were 0.20, 0.07 and 0.14, respectively. Genetic and phenotypic correlations between the traits were: MY and AFC = -0.12 and -0.15, MY and IBFSC = 0.07 and 0.30, AFC and IBFSC = 0.35 and 0.37, respectively. Genetic correlation between MY and AFC traits showed desirable negative association, suggesting that the daughters of the bulls with high breeding value for MY could be physiological maturity to a precocious age. Genetic correlation between MY and IBFSC showed that the selection of the animals that increased milk yield is also those that tend to intervals of bigger calving.

Buffalos milk yield analysis using random regression models

Data comprising 1,719 milk yield records from 357 females (predominantly Murrah breed), daughters of 110 sires, with births from 1974 to 2004, obtained from the Programa de Melhoramento Genetic de Bubalinos (PROMEBUL) and from records of EMBRAPA Amazonia Oriental - EAO herd, located in Belem, Para, Brazil, were used to compare random regression models for estimating variance components and predicting breeding values of the sires. The data were analyzed by different models using the Legendre's polynomial functions from second to fourth orders. The random regression models included the effects of herd-year, month of parity date of the control; regression coefficients for age of females (in order to describe the fixed part of the lactation curve) and random regression coefficients related to the direct genetic and permanent environment effects. The comparisons among the models were based on the Akaike Infromation Criterion. The random effects regression model using third order Legendre's polynomials with four classes of the environmental effect were the one that best described the additive genetic variation in milk yield. The heritability estimates varied from 0.08 to 0.40. The genetic correlation between milk yields in younger ages was close to the unit, but in older ages it was low.

Glass transitions for freeze-dried and air-dried tomato

Glass transition temperatures of freeze-dried tomato conditioned at various water activities at 25 C were determined by differential scanning calorimetry (DSC). Air-dried tomato with and without osmotic pre-treatment in sucrose/NaCl solutions was also analyzed. Thermograms corresponding to the low water activity domain (0.11 less than or equal to a(w) less than or equal to 0.75) revealed the existence of two glass transitions, which were attributed to separated phases formed by sugars and water and other natural macromolecules present in the vegetable. Both transitions were plasticized by water and experimental data could be well correlated by the Gordon-Taylor equation in the low-temperature domain, and by the Kwei model in the high-temperature domain. For higher water activities, the low-temperature glass transition curve exhibited a discontinuity, with suddenly increased glass transition temperatures approaching a constant value that corresponds to the T-g of the maximally freeze-concentrated amorphous matrix. The unfreezable water content was determined through the melting enthalpy dependence on the moisture content. (C) 2002 Elsevier B.V. Ltd. All rights reserved.

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.

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.