m. b. montazer torbati

In many countries of the world, the camel has played an important role in the lives of people in arid and semi-arid regions in terms of providing milk and meat products. Based on phenotypic characteristics, the camel has been adapted to the deserts from physiological, anatomical, and behavioral points of view. Due to limited water resources, the south Khorasan province of Iran has not been an appropriate geographical region for a great number of agricultural products. Weighing plays an important role in the management of camel breeding to adjust the nutritional needs and also the annual evaluation of the animals. One of the main challenges of camel breeding is the difficulty of recording and the lack of records due to the wild nature and also the large size, especially in adults. Due to the many difficulties and risks, camel breeders usually use various potential alternative tools such as apparent estimation or weighing tape to estimate the weight of camels at different ages. For farm animals, significant correlations between body measurements and body weight can be used as a tool to estimate the weight of animals through a mathematical equation. The main objective of this study was to compare the accuracy of artificial neural network (ANN) and multiple linear regression model (MLR) in estimating the body weight of a humped camel.
In the present study, the data of a total number of 177 one-humped camels in four groups  (including 1. 63 adult female Pakistani camels aged between 9 and 12 years, 2. 21 adult female Baluchi camels aged between 9 and 12 years, 3. 93 male and female camels less than 2 years of age of Pakistani and Baluchi breeds, and 4. total camels) collected at the South Khorasan camel breeding station in 2019 were used. Morphological characteristics of camels include: neck length, neck girth, hand length, foot length, shoulder height to the ground, hump height to the ground, hip height to the ground, chest girth, chest width, abdomen girth, hip width, tail length, breast height, and breast girth were measured. After measuring the body dimensions, the evaluated camels were weighed using a 1000 kg digital scale. To estimate the weight of camels from their body dimensions, the data were analyzed using the MLR model and ANN with the nnet package in R software. For ANN analysis, 80% of the data were considered for network training and 20% for testing. The accuracy of MLR and ANN for camel body weight estimation was compared using the coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE).
The results of the MLR model showed that body dimensions of shoulder height to the ground, chest girth, abdominal girth, neck girth, and hand length had a significant effect on body weight (P<0.05). In the ANN model, chest girth, abdominal girth, and shoulder height to the ground were the most important variables in estimating the body weight of camels of the whole population. The MLR and ANN models had acceptable accuracy in weight estimation. However, compared to the MLR model, the ANN model had a higher R2 and a lower error in estimating the weight of camels. In the first group, R2 and RMSE were found to be 0.996 and 6.852, respectively, for ANN while the corresponding values were 0.979 and 22.955, respectively, for MLR.  In the second group, R2 and RMSE were found to be 0.995 and 3.525, respectively, for ANN while the corresponding values were 0.989 and 5.377, respectively, for MLR.  In the third group, R2 and RMSE were found to be 0.896 and 13.959, respectively, for ANN while the corresponding values were 0.849 and 17.549, respectively, for MLR. In the fourth group, R2 and RMSE were found to be 0.929 and 20.248, respectively, for ANN while the corresponding values were 0.903 and 38.505, respectively, for MLR. The results showed that ANN is more accurate compared to MLR in predicting the body weight of camels. 
In terms of goodness of fit (including R2 and RMSE), the results of the present research suggest that both MLR and ANN methods have high acceptable accuracy for predicting body weight in camels. ANN was more suitable compared to MLR, suggesting that it could be used to predict camel body weight. Furthermore, grouping the camels by age and breed could also lead to higher precision and lower prediction error.

 In dairy cows, milk yield changes over the lactation period. Lactation curve modelling could be of importance from nutritional management and genetic selection point of view. The trajectory shape of the lactation curve has inclining and declining slopes which determine total amount of milk yield during the lactation. A great number of linear and nonlinear mathematical models have been so far utilized to describe the shape of the lactation curve in dairy cows. Among the models, mechanistic functions are considered to be more accurate than empirical models in terms of taking account of biological mechanisms undertaken in mammary gland to produce milk. To our knowledge, no research has been carried out to use a complex mechanistic model for describing the lactation curve of Iranian dairy cows. Based on this, the present research aimed to apply a five-parameter nonlinear mechanistic model for mathematical description of the shape of the lactation curve in Iranian first-parity dairy cows.

Animal Breeding Centre of Iran provided the data used in this research. Initial data in separate files were merged and edited by the SPSS software. Final data comprised 5596039 milk test day records from 821153 first-parity cows distributed in 579 herds of 26 provinces over the country. The cows were the progeny of 7957 sires and 530394 dams and calved between 1996 and 2020. The cows were categorized into two groups based on the age of first calving: <=25 or >25 months. Also, two groups of cows were created based on the proportion of Holstein gene inheritance: <100% (grade cows) or 100% (pure Holstein cows). A five-parameter nonlinear mechanistic model was applied to mathematically describe the shape of the lactation curve. The fitted mechanistic model had five parameters including MSmax (maximum milk secretion potential of the lactation), GR (relative proliferation rate of secretory cell number during early lactation), MSLmax (maximum secretion loss), NOD (proportion of parenchyma cell dead at parturition), and DR (relative decline rate in cell number) which their estimates were obtained for different seasons and ages of calving, as well as different genotypes (grade and pure Holstein) using NLIN procedure of the SAS software. Based on the estimated parameters of the model in each year of calving, phenotypic trends were calculated using the SPSS software.

The results indicated that Iranian first-parity dairy cows reach to peak of milk production during the third month of the lactation curve. Based on standard deviation as well as coefficient of variation (CV) of milk test day milk records, maximum variation was observed in the last month of the lactation period. The findings also indicated that cows calved in autumn had the greatest MSmax and GR while cows calved in spring and summer had the lowest magnitude for these parameters (P<0.05). The minimum magnitude of MSLmax and NOD were detected for the cows calved in summer (P<0.05). Regarding the DR parameter of the model, cows calved in spring were observed to have a minimum value. Maximum MSmax, Gr, and DR values ​​were determined for cows calving up to 25 months of age, while maximum MSLmax and NOD values ​​were observed for cows of later ages (P<0.05). Compared to pure Holstein cows, grade cows had higher MSLmax and NOD values, but other parameters were found to be greater in the pure Holstein cows (P<0.05), suggesting that the maximum milk secretion potential during lactation in pure Holstein cows is expected to be higher than that of grade cows. Annual phenotypic change trends were found to be 0.376 kg/year (R2=0.9), 0.00009869 (R2=071), -0.146 kg/year (R2=0.59), -0.011 (R2=0.85), and 0.001 (R2=0.85) for MSmax, GR, MSLmax, NOD, and DR, respectively (P<0.0001).     

This study found that the parameters of the mechanistic model fitted to the milk test day records of Iranian primiparous dairy cows are significantly influenced by the age and season of calving as well as the genotype of the cow. Cows calving in summer are expected to have more persistency. Moreover, pure Holsteins are more persistent than grade cows. Positive and negative annual trends have been detected for MSmax and MSLmax parameters, respectively, during 1996-2020 indicating a favorable increase in maximum milk secretion potential of the lactation and also a favorable decrease in maximum secretion loss over that period.

The main aim of the present research was the genetic analysis of the first lactation milk yield trait and evaluation of the impact of selection for milk on the phenotype of age at first calving in Iranian dairy cows using quantile regression. Lactation milk records of 327190 first parity cows (progeny of 5260 sires and 235172 dams) in 637 herds (in 15 provinces) and calved between 2007 and 2015 were utilized. Genetic analysis was carried out with the use of an animal model. In the model, fixed effects of the province, herd, year and month of calving, covariates of lactation length, age at first calving, percentage of Holstein gene, as well as the random effect of the cow were included. The model was fitted on the data using the DMU package. Regression of age at first calving on predicted breeding value was fitted through a quantile regression model. The findings revealed that the heritability of lactation milk yield was equal to 0.276. Annual genetic gain in grade and Holstein purebred were found to be 17.352 (R2=0.913) and 23.398 (R2=0.962) Kg, respectively (P<0.0001). All estimated regression coefficients were negative in different percentiles of age at first calving and ranged between -0.0009 and -0.0344 (month per Kg) which indicates that the influence of genetic potential of cows for milk yield on different parts of calving age distribution is not the same.

The central melanocortin system appears to be an important mediator of the actions of both leptin and insulin, which are key elements in the control of energy balance. Proopiomelanocortin (POMC) is a complex precursor protein that is proteolytically cleaved to a variety of biologically active and important neuroendocrine peptides. The POMC gene is expressed mainly in the anterior and intermediate lobes of the pituitary and in the arcuate nucleus of the hypothalamus, and at a lower level also in a wide variety of peripheral tissues and of brain regions in mammals. It produces many biologically active peptides via a series of enzymatic steps in tissue-specific manners, which have important roles in the regulation of appetite, sexual behavior, the movement of melanin produced from melanocytes in skin and the production of endogenous opioid peptides with widespread actions in the brain. In chicken, the POMC gene consisted of three exons and two introns and its protein has 251 amino acid residues with nine proteolytic cleavage sites, suggesting that it could be processed to give rise to all members of the melanocortin family, including adrenocorticotropic hormone and alpha-, beta- and gamma-melanocyte-stimulating hormones, as well as the other POMC-derived peptides.
Considerable evidence has been collected indicating that POMC mutations are associated with obesity.

Blood samples were collected in EDTA vials from one hundred Ross and sixty Cobb broiler chicks, stored at -20 and their DNA was extracted using the modified salting-out chloroform method. Polymerase chain reaction (PCR) was carried out by specific primer pairs to amplify a 444bp fragment from a part of exon two of the Pro-Opiomelanocortin gene. The pattern of all samples was determined through single stranded conformation polymorphism (SSCP) analyses by Acrylamide gel using silver nitrate staining.
The associations between polymorphisms (patterns) and the growth traits (live and carcass weight, and the weight of breast, thigh, back and neck, wings, liver, heart, bursa of Fabricius, pancreas, paraventricular, gizzard and spleen) were evaluated using the GLM procedure of the SAS software.

The extraction or genomic DNA and amplification of 444bp fragment of Pro-Opiomelanocortin gene were successfully done and it was polymorph in both strains. Two different patterns were found in Ross strain, E and F patterns with the frequencies of 0.56 and 0.44, respectively. Four different patterns were found in Cobb strain, A, B, C and D patterns with the frequencies of 0.63, 0.09, 0.14 and 0.14, respectively. There was no significant association between the patterns and the growth traits. In Ross strain, the effect of genotype (pattern) tend o be significant for carcass weight (p value = 0.054) and the chickens with F pattern have more carcass weight than those with pattern E. In Cobb strain, chickens with B pattern tend to have better slaughter yields compared to other patterns. Our results revealed that Cobb strain has more diversity in the studied fragment of POMC gene than Ross strain.

Energy homeostasis and body weight (BW) are regulated by coordinated actions of multiple genes. For significant economically traits, improvements in BW can be achieved through mass selection whereas feed conversion is relatively more difficult to improve. Gene polymorphisms can be used for improvement of the production traits by genetic selection, if the allelic association with the traits be determined. The variable associations of the identified polymorphisms may be a result of the differences in the population characteristics,
sex, or both, indicating that the selection criteria may influence the production trait associations. This should be taken into consideration while selecting for the desired production traits. Additional studies are required to expand the genetic and physiological aspects involved in feed intake, digestion, and metabolism. The genomic diversity also has important implications in the evolutionary dynamics of species. Investigations of polymorphisms are useful for better understanding of the gene function, and those associated with commercially significant production traits have a potential for usage as molecular markers for selection programs. In summary, the identified polymorphisms and their associations with the traits of economic importance in the present study provides greater insight into the role POMC gene involved in energy balance in poultry and points toward the
potential application of the findings for the enhancement of production traits by marker assisted selection.

By studying lipid and lipoprotein concentrations changes in the pregnant camels, methods can be found to reduce fertility problems and enhance reproduction efficiency in the species Bactrian camels.
This experiment was carried out to evaluate the effect of age, sex and pregnancy on serum lipid and lipoproteins in two humped Camels.
blood samples were collected from the jugular veins of 20 healthy camels according to their age (4 years), sex and pregnancy. Serum concentrations of total cholesterol (TC), triglyceride (TG), total lipid (TL), LDL-cholesterol, HDL-cholesterol and VLDL-cholesterol were evaluated.
The concentrations of TG, HDL-cholesterol, LDL-cholesterol and VLDL-cholesterol in different age groups was significantly different (P Probably activation of sexual hormones during the puberty and hormonal interactions in the hypothalamus – pituitary - Gonadal axis (HPG) is the main reason for this phenomenon.