Fifty Years of Research on Camelids and the Contribution of Genetics and Genomics: A Scientometrics Evaluation

The population and importance of camels in human life have improved in recent years. As genetics and genomics are becoming a more comprehensive section of life sciences, studying genetic/genomic aspects of the camelid nutrition, milk production, reproduction, immunity, disease and racing ability has become common in recent years. This study was conducted based on text mining and scientometrics techniques. To employ relevant information from Web of Science (WoS), a search strategy was developed to retrieve the “genetics or genomics” and words/phrases related to “camelids”. The statistical population of this study included 3830 publications over a period of 50 years (1971–2020). A total of 3830 publications were retrieved that included 3269 research articles (85.35% of the publications) and 224 review articles (5.85% of the publications). The most frequent subject groups were “Veterinary Sciences” including 862 publications. In total, articles on camelid genomics were published in 1345 journals. Moreover, 127 countries contributed to these 3830 publications, with the USA being the leading country both in number of publications and international collaboration. During the 1971–2010 time period, the phrases “MERS-CoV” and “coronavirus” did not exist in the literature at all, while in the last decade, with 140 and 63 times (5.36% and 2.41%, respectively), they were the most frequent keywords. In general, the most important topics studied from the perspective of camelid genomics have been population genetics and pathogens and their diagnosis, as well as camelid immunity. Future studies should pay special attention to the specificity of camelid genomics for hosting the coronavirus. Furthermore, the special structure of humoral immunity in camels makes this section attractive in immunogenetics research

Using Nonlinear Growth Models to Fit the Egg Production Curve in Khazak Hen

Introduction: The egg production curve is defined graphically as the relationship between the number of eggs and laying time, which indicates the biological efficiency of a hen and can be effective in the selection and nutritional management of laying hens. Egg production is an essential section of the poultry industry. Appropriate mathematical models accurately represent the production phases of the hen and provide a valuable tool for biological comparisons and interpretations. Also, egg production curves help predict egg production, determine the appropriate age for poultry culling, and economic decisions. Sigmoid growth models are often used to describe size over time in plants, animals, and humans. In laying hens, the shape of the cumulative egg production curve is similar to the growth curve. Therefore, different growth models may be used to model the cumulative egg production curve. Khazak hen is one of the native birds of the Sistan region (Iran), and natural selection has adapted this bird to the conditions of Sistan over the years. The body of this chicken is small, and has low growth and is mainly kept for egg production. Since laying patterns is different in populations. Thus, the use of an appropriate model to describe the specific laying pattern of each population is necessary. Therefore, this study was conducted to investigate growth models to describe the cumulative egg production and weight of eggs and select the best model for the Khazak hen.Materials and Methods: The present study was conducted in the Research Center of Domestic Animals (RCDA), the Research institute of Zabol, Zabol (Iran). Khazak pullets are identified using foot-banded numbers before they start laying. During the experiment, all birds had access to water and feed ad libitum. The egg production was recorded daily for each hen separately. Based on daily records, the weekly egg production of each bird was calculated and then used the calculation of the cumulative egg production. A total of 365 pellet egg production records were used to analyze the production curve from the first to the fortieth week of laying. Five growth models (Gompertz, Logistics, Richards, Lopez, and Weibull) were fitted on cumulative egg production and weight records. The goodness of fit criteria, including Akaike information criterion (AIC), mean square error (MSE), Bayesian information criterion (BIC), and adjusted coefficient of determination ( ), were used to compare the growth models and to select the best model. All models were fitted on egg production records using the nlme package in R software, and the parameters of each model were estimated. After fitting the models, the cumulative production values for different ages were predicted by the models and were compared with the actual values over 40 weeks.Results and Discussion: Based on the goodness of fit criteria, the Lopez mod had the highest  value and lowest values of AIC, BIC, and MSE for cumulative egg production. While the Weibull model was the best model than other models to describe cumulative egg weight in terms of the goodness of fit criteria. The Gompertz and Logistic models overestimated initial production and underestimated the final production compared with other models. Estimates of time and production at the inflection points using Lopez and Weibull models were close to actual values of cumulative egg production and weight, respectively. Also, prediction of cumulative egg production and egg weight in different weeks using Lopez and Weibull models was accurately, respectively. In literature, various models were reported as the best model to describe the egg production curve, which indicates that the appropriate model specific to each breed should be used to evaluate its curve. The overestimation and underestimation of initial and final production using Logistic models were reported in other research that was similar to our findings. The important application of egg production models in poultry is to estimate the economic and genetic value by predicting total egg production from some records, which can be a suitable tool for biological comparisons and interpretations.Conclusion: The results of the present study, showed that the Lopez and Weibull models were the best models to describe the cumulative egg production and egg weight based on four good fit criteria, respectively. Therefore, these models can be used to describe the cumulative egg production and egg weight in Khazak hens. The application of these growth models can be useful to nutritional management and breeding programs to improve and change cumulative egg production and egg weight

Mathematical Modeling of Egg Production Curve in Khazak Indigenous Hens

The number of eggs produced in a given period (egg production rate) is an important trait in layers that change over time and can be presented as a curve. This study aimed to fit the weekly egg production data of Khazak indigenous hens using non-linear regression models and to select an appropriate model for describing the egg production curve for this bird. Biweekly egg production of 144 laying hens over 52 weeks of egg production was used to evaluate the egg production curve. Seven non-linear models (Gamma, McNally, Compartmental II, Nelder, Yang, Lokhorst, and Narushin-Takma) were fitted to egg production data. The four goodness fit criteria (Akaike’ s information criterion, Mean square error, Log Likelihood, and Bayesian information criterion) were used to compare the models. The results of the goodness of fit criteria showed that the Narushin-Takma and Yang models were the best and worst models, respectively, for describing the egg production curve of Khazak hens. The time and egg production at the peak with the Narushin-Takma model was similar to the actual values, and this model was significantly better than other studied models. The correlation between actual and predicted egg production indicated that the Narushin-Takma model could accurately predict the egg production of this breed. As a result, the Narushin-Takma model can be used to predict the egg production curve of Khazak hens in breeding programs and nutritional management

Comparison of Different Non-Linear Models for Describing Plasma Lysozyme Activity in Quail

Lysozyme activity is one of the nonspecific immunity parameters measured by changing the amount of adsorption at different times. The objective of the present study was to compare five non-linear models including Gompertz, Richards, Logistic, Lopez, and Weilbull to describe the cumulative plasma lysozyme activity in quails. In total 1364 plasma samples (1004 females and 360 males) were collected and the cumulative lysozyme activity was calculated by turbidimetric method assay in Micrococcus luteus. The goodness-of-fit of models was compared according to different criteria of Maximum log-likelihood, Akaike information criterion, Mean square error, and Bayesian information criterion. The results showed that the Gompertz model was the best model for describing of decreasing cumulative pattern of lysozyme activity in female and male quails and provided satisfactory predictions of lysozyme activity at different times (30, 60, 90, 120, 150, 180, 210, 240, 270, 300 seconds). The parameters of all models were higher in females than males except for the k parameter which was greater in the males. Male quails had higher values for time and lysozyme activity than females at inflection points, whereas the absolute growth rate in 30, 150, and 300 seconds was predicted higher in female quails. In conclusion, the Gompertz model can be used accurately to evaluate cumulative lysozyme activity patterns in both sexes of quails

Evaluation of Non- linear Growth Curves Models for Native Slow-growing Khazak Chickens

Native poultry is a valuable genetic source with high resistance against diseases providing an important subject for breeding programs. The non-linear mathematical modeling of the growth pattern may partly explain the relationship between requirements and body weight to precise feeding that plays a vital role in the animal enterprises. A study was conducted to compare five non-linear models including Gompertz, Richards, Lopez, Logistic, and Von Bertalanffy describing the growth curve of Khazak native chickens. A total of 120 Khazak chickens (male and female) were individually weighed from 0 to 29 weeks under the same condition. The models were fitted on body weight data set and then evaluated by goodness-of-fit criteriaincluding root mean square error (RMSE), Bayesian information criterion (BIC), Akaike information criterion (AIC), and adjusted coefficient of determination (R2Adj). Based on goodness-of-fit criteria, Lopez model was the most suitable one for describing the growth curves in female and male chickens. The effect of sex was significantly important on curve parameters in all models (P< 0.05). The highest and lowest initial weight (W0) parameter was estimated by Logistic and Richards models, respectively, however, the other parameters of the growth curves were higher in Lopez model compared to others. Male chickens had higher values for age (ti), and weight (wi) at inflection point than females. Using an appropriate model to describe the growth curve in native Khazak chickens could increase the accuracy of selection for rapid growth at early stages of age

Radiographic evaluation of the mental foramen in a selected Iranian population

<b>Background: </b> Information on the position of the mental foramen is important for dental surgeons. Variations in its position can be a cause of complications during local anesthesia or surgical procedures. The usual position of the mental foramen in an Iranian population has not been previously reported. <b> Aims:</b> The purpose of this study was to determine the most common location of the mental foramen in an Iranian population. We also analyzed gender differences and the symmetry of location within individuals. <b> Materials and Methods</b> : 400 panoramic radiographs were evaluated with regard to the location and symmetry of the mental foramina in male and female subjects. <b> Results</b> : We found that the mental foramen was located between the first and second premolars in 47.2&#x0025; of patients and in line with the second premolar in 46&#x0025;. In 49.2&#x0025; of males, the mental foramen was in line with the second premolar. In 50.9&#x0025; of females it was between the first and second premolars. It was symmetrical in 85.7&#x0025;. <b> Conclusions</b> : Based on this study it appears that the most common position of mental foramen is either between the two premolars or in line with the second premolar. This is in concordance with previous studies

Genetic and Phonotypic Trends for Somatic Cell Score and Determination of Effective Environmental Factors on this Trait in Iranian Holstein Cows

The aim of this study was to estimate the genetic and phonotypic trends of Somatic Cell Score in Iranian Holstein cows. Also, the environmental factors affecting this trait are investigated. A total of 375351 test day records of somatic cells take from 54374 animals between year 2002 and 2007 were used in this study. The breeding values were estimated by fitting animal model in ASREML software. Genetic and phonotypic trends were estimated by regression of phonotype and breeding value means on year of calving. SAS software was used for estimation of genetic, phonotypic trends and effect of environmental factors. The heritability, genetic and phonotypic trends for Somatic Cell Score were 0.082 ± 0.009, 0.013 ± 0.002 and -0.224 ± 0.103, respectively. The genetic trend was significant and different from zero but phonotypic trends were not significant. Effects of herd, year, interactions between herd and year, herd and season, year and season of calving were also significant however the effects of season of calving were not

Estimate of Inbreeding Coefficient and Its Effects on Reproductive Traits of Dairy Herds in Isfahan Province

This study was carried out to study the inbreeding coefficient and its effect on reproductive performance of dairy cows (age at first calving, calving interval and open days) in Isfahan province. Records of 31,977 (primiparous cows), 36,982 and 51,423 (multiparous cows) for age at first calving, calving interval and open days were used, respectively. The inbreeding coefficients of animals were calculated using pedigree information of 78,425 females and 8,056 males, which were born from 1963 to 2009. The overall mean and maximum inbreeding coefficients in Holstein cows were 2.33% and 31.30%, respectively. The results showed that 57,234 animals were inbred with 3.57% inbreeding coefficient. Regression coefficients on inbreeding coefficient for age at first calving, calving interval and open days were 0.589±0.21, 1.08±0.15 and 0.27±12, respectively. Estimated inbreeding indicated significantly negative effect on the reproductive traits in different parturition periods. The results revealed that the average inbreeding trend was increased in the dairy herds. The increased inbreeding was due to close mating systems between the candidates, and it showed negative effects on the reproductive traits in Isfahan dairy herds