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The development of sustainable animal husbandry plays an important role in establishing food security, improving welfare, increasing the income of rural households, improving productivity, creating job opportunities, creating links with other economic sectors, and rural development. In Iran, the issue of sustainable development of the animal husbandry industry and creating sustainability is one of the most important issues of the country because the animal husbandry industry is one of the most important sub-sectors of the agricultural industry, which produces the most important basic food of the country, i.e., red meat. The main goal of this research is to identify and prioritize the obstacles and problems of sustainable animal husbandry development in Guilan province. The development of the agriculture and animal husbandry industry is necessary to access a sufficient amount of food and energy and to cover the ever-increasing demand due to the increase in the population. Guilan province has a suitable capacity for the development of animal husbandry activities. Paying attention to the existing research gaps, by summarizing findings in this field, using the opinion of animal husbandry industry experts, and the application of the multi-indicator decision-making model, this study identified the obstacles and problems for the development of sustainable animal husbandry in Guilan province.

Various criteria have been introduced in previous research as key factors for the sustainable development of animal husbandry, the most important of which included structural, institutional, economic, cultural, social, environmental, macro goals and strategies, the process and cycles of providing inputs, and selling livestock products. The decision tree was drawn using the findings of similar studies and the opinions of provincial experts in this industry. The data collection tool is a questionnaire for pairwise comparisons of decision tree criteria and sub-criteria. To determine the weight of the criteria and sub-criteria included in the decision tree, the opinions of 10 experts in this field in Guilan province were collected and analyzed using the Fuzzy Hierarchy Process (FAHP). Fuzzy set theory is a mathematical theory designed to model the ambiguity of processes related to human knowledge. The decision maker can freely choose the range of desired values. Also, the uncertain judgment of the expert can be expressed by a fuzzy number. In this method, fuzzy numbers are used for the pairwise comparison of options, and the decision maker can express the pairwise comparisons of the elements of each level in the form of triangular fuzzy numbers. The decision tree for this research has five main criteria including institutional, environmental, social and cultural, structural, and economic factors, and 31 different sub-criteria. FAHP is a systematic method that uses the concepts of fuzzy set theory and hierarchical structure analysis. The calculated weights are a suitable basis for prioritizing the main obstacles and problems in the sustainable animal husbandry industry development of Guilan province. Modeling and obtaining the results were done in the MATLAB software.

The results of the research showed that from the point of view of experts, institutional and economic obstacles with the weights of 29.71% and 19.23%, respectively, are considered to be the most important obstacles to the development of sustainable animal husbandry in Guilan province. On the other hand, the sub-criteria of low attention to the animal husbandry sector in the provincial policies from the institutional criterion, the inappropriateness of the materials used, considering the weather conditions from the environmental criterion, the low status and job position of animal husbandry from the social and cultural criterion, the lack of high-yielding breeds consistent with the conditions of the region from the structural criterion, and the lack of adequate insurance coverage from the economic criterion have the highest rank among the sub-criteria.

The obtained results indicated the high level of obstacles and problems for the development of sustainable animal husbandry in Guilan province, which requires the attention of policymakers and the development of a policy package that fits the priorities determined in this study.

This study aimed to compare different methods of genomic evaluation using the criteria of correlation (ρ), regression (β), mean square error (MSE), and selection effectiveness (SE). For this purpose, nine different scenarios were designed based on different levels of heritability (0.1, 0.3, and 0.5) and different numbers of QTLs (20, 200, and 1000). To simulate different scenarios, five generations with a size of 1000 animals were simulated, of which the first two generations were considered as the reference population and the next three generations as the validation population. For each animal, a genome of 500 centimorgans with a marker density of 10000 SNP consisting of five chromosomes was simulated. Genomic breeding values were predicted using three statistical methods GBLUP, Bayes A, and Bayes B. The results showed that with increasing generation interval from the reference population, the accuracy of genomic breeding values decreased for three statistical methods, although Bayesian methods performed better in terms of continuity of accuracy. Based on the criteria of correlation, regression, and selection effectiveness, with increasing the levels of heritability, improved accuracy was observed, but the criterion of mean squares error showed the opposite trend. Bayesian methods performed better in low QTLs, but differences in different genomic evaluation methods were minimized in high QTLs. The results of selection effectiveness in comparison with the accuracy of genomic breeding value showed that accuracy can’t always be a suitable criterion for determining the superior method of genomic evaluation.

This experiment carried out to determine the nutritional value of 18 sorghum forage varieties and to introduce superior cultivars using multicriteria decision-making technology. They sow in early June and harvested in mid-November. Random samples were taken from the center of each experimental plot in a way that ten plants were cut from 10 cm above soil. These samples were cut into 3 to 5 cm pieces, eachcultivar had three samples, in total 54 samples were collected. Yield and nutrient contents such as, crude protein, crude ash, ADF, NDF, water-soluble carbohydrates, starch and lignin measured in the experimental cultivars. The metabolizable energy of sorghum cultivars estimated by gas test method using the amount of gas produced in 24 hours and the amount of crude protein contained in it. Sorghumcultivars ranked based on 11 integrated traits. Among the domestic cultivars, Spidfeed ranked fifth among all varieties, followed by KFS-18 ranked seven and pegah ranked 10th and KFS-2 ranked 12th with moderate quantitative and qualitative performance. Overall, based on the results of the multi-criteria decision-making method, it was found that the top three sorghum cultivars are Siloking, FGCSI12 and PHFS-27, respectively, which are recommended for sorghum forage production and silage for dairy farmers.

This study was carried out to investigate different data transformation methods on homogeneity and heterogeneity of variance components. Data included 305-day lactation records for protein yield from the first three lactations of Iranian Holstein cows collected from 1983 to 2014 by the Animal Breeding Center and Promotion of Animal Products of Iran. Data included 141670 records for 1st lactation, 115395 records for 2nd lactation and 82529 records for 3rd lactation. Records were categorized to 3 classes according to the average of herd-year production. For testing the heterogeneity of variance components Bartlet test was used and it was significant among all three lactations. A pre-correction method and two different data transformation methods including Box-Cox and Square root were used to correct for heterogeneity of variance. Genetic parameter and heritability estimates were estimated by VCE program, under an animal model. Spearman correlations and proportion of animals selected before and after data transformation were also estimated. Application of the Visscher adjustment method resulted in slightly higher heritabilities, which may be due to the more accurate estimation of additive genetic effects when heterogeneity is considered. Heterogeneity of variance had a significant effect on re-ranking and selection of 5% top sires and 1% of top dams. Pre-correction, Box-Cox and Square root method caused a proportion of 4%, 19% and 10% of top sires and 10%, 21% and 7% of top dams, respectively, to be excluded from selection when compared to the homogenous variance scenario. The results of this research indicate that the variance between different levels of herd-year production is not homogeneous and may influence the ranking and genetic evaluation of top cows.