جستجوی مقالات مرتبط با کلیدواژه « شیرخام » در نشریات گروه « کشاورزی »

Milk and dairy products, due to their high nutritional value and consumption by all ages, are an important part of the human diet in many parts of the world. Nitrate and heavy metals contamination of milk is a danger to humans that is much more common in childhood. The Lenjan county in the southwest of Isfahan province and different industries, such as Esfahan Steel Company and Mobarakeh Steel Company, are located around the region. In addition, because of the intensive agricultural activities in this region, dairy products, including raw milk, could be exposed to nitrate and heavy metals pollution. The objective of this study is to investigate the concentration of lead, nitrate, and nitrite in the raw milk of livestock in the Lenjan region. Raw milk sampling was performed in polyethylene containers from 30 farms including industrial, semi-industrial, and traditional units situated in the different parts of the county. Furthermore, eight samples of raw and pasteurized milk from a dairy processing company in the region were collected in four different working days. The vanadium trichloride reduction and graphite furnace atomic absorption methods were used to measure the nitrate and lead concentrations of the samples, respectively. The results demonstrated that the concentration range of nitrate was 0-12.6 with a mean of 1.41 mg/kg; nitrite was 0-3.3 with a mean of 0.11 mg/kg; and lead was 0.006-0.387 with a mean of 0.03 mg/kg. Nitrite and nitrate levels of the samples were less than the standard of Codex (1 and 10 mg/kg, respectively). Moreover, the amount of lead in 16.7% of the samples was higher than the world standard (0.002 mg/kg). The risk assessment of lead and nitrate for humans through the consumption of raw milk was in the safety range. Risk factors (THQ) for lead, nitrate, and nitrite were 0.14, 0.01, and 0.0, respectively. However, monitoring of various contaminants in dairy products in the areas, which are at high risk of contamination, seems to be necessary.

Nowadays, it has demonstrated that viruses can be transmitted by water and foods. Therefore, it causes the research to develop for detecting different viruses in water and foods. Among foods, milk can transfer potentially pathogenic viruses. On the other hand, to achieve every method for recovery and extraction of viruses in raw milk it needs to know about impact of milk components on viruses. Artificial neural network (ANN) and Adaptive Nero Fuzzy Inference System (ANFIS) can help to estimate recovery efficiency of viruses in raw milk. The objective of this study was to evaluate the application of ANN and Adaptive Nero Fuzzy Inference System (ANFIS) to predict the impact of milk components on recovery and extraction of viral RNA in raw milk. Therefore, to run the model the amount of milk components (casein, whey protein, fat and lactose) and viral RNA extraction were as the input and the output of the network respectively. Also, to evaluate the efficiency of the network for the prediction, variables such as training, validating and test subsets as well as the hidden layers, transfer functions, learning rules and the hidden neurons were used. Based on the results, the best models in ANN were linear sigmoid transfer function, levenberg learning rule (r: 0.919) and linear sigmoid transfer function, levenberg learning rule (r: 0.956) for spiked model solution and (spiked – non spiked) model solution respectively and in Adaptive Nero Fuzzy Inference System (ANFIS) the best model were membership function Gaussian, Adaptive Nero Fuzzy Inference System (ANFIS) model TSK, linear tanh axon transfer functions and momentum learning rule (r: 0.879) and membership function Gaussian, Adaptive Nero Fuzzy Inference System (ANFIS) model TSK, linear axon transfer function, and step learning rule (r: 0.889) for spiked model solution and (spiked – non spiked) model solution respectively.

Milk is considered a nutritious food because it contains several important nutrients including proteinsand vitamins. Conversely, it can be a vehicle for several pathogenic bacteria such as Staphylococcusaureus. In this study, 123 milk samples of 123 cows from four farms of different geographic locations inQom were collected from March until November 2011. The samples were cultured on Blood agar andbacteria were identified by standard methods. On the basis of cultural and biochemical properties, 26Staphylococcus aureus isolates obtained from 123 milk samples. Among a 26 isolates, 9 isolates (7.31%)were positive coagulase and 12 isolates (9.75%) were positive DNAase.Milk is considered a nutritious food because it contains several important nutrients including proteinsand vitamins. Conversely, it can be a vehicle for several pathogenic bacteria such as Staphylococcusaureus. In this study, 123 milk samples of 123 cows from four farms of different geographic locations inQom were collected from March until November 2011. The samples were cultured on Blood agar andbacteria were identified by standard methods. On the basis of cultural and biochemical properties, 26Staphylococcus aureus isolates obtained from 123 milk samples. Among a 26 isolates, 9 isolates (7.31%)were positive coagulase and 12 isolates (9.75%) were positive DNAase.

In order to study the residual of antibiotics in raw milk of dairy products from one factory, this research carried out in 2008.The number of samples included 7,1&3 from three groups of raw milk collecting, semi industrial &industrial farms,respectively. The expriment was conducted in the groups and regular replications in the intervals of one week. Total samples (i.e167 samples) were analysed by the method of Copan test. The correlation between depended & independent variables were analyzed by Kruskal Wallis test. The results of 103 test were negative and 64 test were positive.The number of samples in the 3 mentions groups were 61,9&97 and the number of positive samples were 2,1&61 (i.e 3.3%,11.1%&62.9%) respectively.The results of this research indicated that antibiotic residual from the samples of industrial farms were superior than two other groups, and the semi industrial farms were superior than the first group.