saeed esmaeilkhanian

Animal husbandry, as one of the important sub-sectors of the agricultural sector, requires the formulation of a strategic plan at the regional level. The purpose of the research is the necessity of scientific planning for the improvement and development of livestock production, in line with the optimal use of the existing capabilities and capacities of Sistan region. The data collection tool was a questionnaire, Data analysis was done in the descriptive statistics section in Excel software, and then multi-indicator decision making technique and gray method were used to estimate other results. The results of the study showed that the index of reducing the vulnerability caused by natural disasters through capacity building and water resources management has the greatest effect in determining the index of the vision, goals and strategies of sustainable development of the industry. The index of preventing severe market fluctuations has the most effective variable to improve the capacity of the existing economic activities of the industry. In addition, the results showed that in order to meet the energy and protein needs of this livestock population, about 1288274 tons of dry matter, 171666 tons of raw protein and 2430870955 megacalories of metabolizable energy are needed, and about 209 thousand tons of dry matter (33% protein and 1.41% energy) are needed annually. Metabolizable) is deficient.Based on the type of strategy obtained, Zahak and Hamon cities should include aggressive strategy, Hirmand and Nimroz cities, change direction strategy, and Zabul city should include diversity strategy in the work plan.

The aim of this study was to investigate the effects of adding betaine to diets of Ross and Arian strains that received drinking water with total concentration of TDS. 720 single-day broiler chicks, Ross and Arian strains were distributed in 12 experimental units for six weeks. The experiment was conducted in a completely randomized design with factorial arrangement (2 × 2 × 3) containing two levels of additive betaine (0 and 0.2% diet) and three levels of TDS (400, 2000 and 3500 mg / l) with four replicates and 15 chicks in Every repetition was done on the seventh day. . With the increase in TDS water content, the body weight of the chicks decreased, and the conversion factor of food and water consumption increased. Additive betaine had a significant effect on the increase in weight and water consumption during the durability period. The percent mortality and moisture content of the waste was higher in treated water with higher TDS. The amount of moisture was reduced by the addition of betaine. The effect of adding betaine and increasing TDS on the concentration of sodium chloride in chicks was significant at 28 days of age (P <0.05). By increasing TDS in drinking water, the BHMT enzyme gene expression in the liver of the chicks also decreased in the Arian strain relative to the Ross strain. The gene expression increased with the addition of betaine to the ration of chicks.

In this study, direct methylation was compared with two conventional extraction methods (Soxhlet and Folch) in terms of extraction yield, the stability of configuration of fatty acids chemical structures and their effect on saturated and unsaturated fatty acids profile. Also, by evaluating and comparing fat extraction methods for fish, egg yolk and milk samples, the efficiency of these methods was determined according to the sample tissue. After extraction and esterification procedures, fatty acids were determined by gas chromatography method. The statistical method of ANOVA using GLM technique was applied to compare the mean of data. The fatty acid profile was subjected to analysis similarities based on cluster analysis to check how the methods would affect the fatty acid profile and to evaluate how much differences are between the methods. The obtained results indicated that the Soxhlet had the lowest efficiency for the extraction of fatty acids, especially in a sample of dry milk, but it was the highest precision compared with the Folch and direct methylation methods. It was also found that the methods have different ability to extract fatty acids based on their unsaturation degree. In general, extraction methods, in addition to affecting the fatty acid profile, have a different effect rate, depending on the sample tissue. Therefore, in order to select an effective method for extracting fat, it is necessary to consider the sample tissue.

Precise prediction of milk yield is essential for management and modeling of farmer’s income in analysis of cost-benefit. Such that, accurate prediction of future records can decrease recording time. Early estimation of bull breeding value using partly records of parity can lower generation interval and increase selection intensity and genetic progress. Linear model is the most commonly used modeling method in research on different field of science. Artificial Neural Network (ANN) is based on artificial intelligent that uses working principles of human brain. Ease of application and power to model complex functions and relationships is factor of wide use of Artificial Neural Network. Revolutionized use of artificial neural network modeling in different aspects of science in the last two decades, is indication of successful application of this powerful technique to solve wide range of problems in different scientific issues. Therefore, object of current research is prediction milk yield of different parity milk production of dairy cattle using production of first recorded parity and artificial neural networks modeling. Furthermore, results of artificial neural network model compared with linear model. In current research, two sequential records of 2460 dairy cattle of a herd were investigated. Pedigree of used data set contained 2517 individuals. Data divided into two sub data of training and testing, to fitting Artificial Neural Network model. Artificial Network model learned the relationship between output and inputs of training data set. Adequacy parameters of the model investigated using model predicted outputs of testing data set and original outputs of the data. Network structure with the beast adequacy parameters were used for Artificial Neural Network model. Finally, linear model was fitted and compared with artificial neural network model. The best structure of Neural Network had 8 inputs, 4 neuron at first hidden layer, 2 neuron at second hidden layer and output of milk production that inputs were breeding value of average milk yield of first recorded parity, parity, sire group, age at first registered parturition, number of records for each parity and mean, minimum and maximum of recorded days in milk for each parity. The used artificial neural network model, predicted the parity milk production with RMSE and R2 of 7.94 and 0.625, respectively. R2 and RMSE of considered linear model was 0.39 and 26.63, respectively. The applied model of artificial neural network appropriately predicted the subsequent parity production using precedent parity data. This research indicated that use of artificial network model can be beneficial for decreasing recording period for dairy cattle genetic evaluation specially in sire evaluation and will decrease generation interval. The results showed that incomplete data can be used for genetic evaluation using artificial neural network model. Comparison of the results with past reports indicated that use of effective inputs for milk production can increase accuracy and precision of the ANN model.