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Improved feed efficiency (FE) is one of the most important achievements in animal breeding programs. The present investigation aimed to determine the phenotypic correlations of residual feed intake (RFI) breeding value with some traits in growing Japanese quail. A total of 48 birds (24 males and 24 females) were selected from 220 quail chicks divided into three classes based on breeding values (BV) for RFI including low (LBV; n = 16), medium (MBV; n = 16), and high-BV (HBV; n = 16) were used to test FE. The effects of three groups of BV on the studied traits including carcass traits, meat quality, humoral immunity, and bone properties were evaluated. The BV for RFI was positively correlated with feed conversion ratio (FCR) and feed intake (FI) but not with metabolic BW (MBW 0.75 ). Live body weight, carcass, breast, and thigh weight in the LBV-RFI group were significantly greater than those in the HBV-RFI group. The BV for RFI had a negative correlation with live body weight and thigh weight. Our findings suggested that the selection of LBV-RFI quails may be useful to increase live body weight without any adverse impact on meat quality and bone properties, and live body weight can be implemented in breeding programs as an indirect selection indicator for improvement of FE in quails., (© 2023. The Author(s), under exclusive licence to Springer Nature B.V.)

Early growth traits in quails are considered as the growth performances before the inflection point which are genetically different from body weights (BW) at later stages. Moreover, in addition to growth performance, humoral immunity is moderately heritable and is considered in some breeding programs. However, estimating the direct genetic, particularly the maternal genetic correlations between growth and immunity in quail, are not studied sufficiently, which were the aims of the present study. The quails' BW were recorded at hatch (BW0) to 25 d of age with a 5-d interval and body weight gains (BWG) were measured as average growth performance of the birds in a 5-d period. Antibody titer against Newcastle disease virus (IgN) was measured through the hemagglutination inhibition (HI) test. For titration of anti-SRBC antibodies (IgY and IgM), a hemagglutination microtiter assay was used. In general, growth records in 4,181 birds and humoral immune responses in 1,023 birds were assigned to the study. The genetic parameters were estimated by single-trait analysis via Gibb's sampling. After finding the best model for each trait, multi-trait analysis was done to estimate the direct and maternal genetic correlations. Direct heritabilities (h 2 ) were estimated to be moderate for BW (0.481-0.551) and BWG (0.524-0.557), while h 2 for immune responses were low (0.035-0.079). Maternal environmental effect (c 2 ) was only significant for BW0, BW5, and BWG0-5. Maternal heritabilities (m 2 ) for BW and BWG were all lower than corresponding h 2 , ranging from 0.072 (BW25) to 0.098 (BW0). The m 2 for IgN (0.098) was more than 2.5 times greater than h 2 (0.040) for this trait. Direct (r a ) and maternal (r m ) genetic correlations between IgN-BW, IgY-BW, and IgY-BWG were negative, while ra and rm for IgM-BW, IgN-BWG, and IgM-BWG were positive. The r a between humoral immune responses were low to moderate and rm was significant only for IgY-IgM (0.339). Given positive genetic correlations in BWG-IgN and BWG-IgM as well as positive genetic correlations between both IgN and IgM with IgY, it is suggested that including the BWG in the breeding programs would directly result in the improvement of the birds' growth performance. It would also contribute indirectly to the improvement of the birds' humoral immune responses., (Copyright © 2022. Published by Elsevier Inc.)

In most countries, ostrich farming is considered a developing branch of the efficient poultry industry. The profitability of ostrich farm requires specific consideration of productions features such as the female fertility, egg production, hatchability, and growth performance. Hence, this study aimed to fit nonlinear functions to describe the ostrich egg production pattern to achieve the most appropriate and recommendable mathematical function for future studies. For this purpose, 14,507 daily records of 184 female ostriches in 5 production seasons (periods) during 2016 to 2021 were used. Five nonlinear functions including Incomplete gamma (Wood function), Corrected gamma (McNally), nonlinear Logistic (Yang), Logistic (Nelder), and Lokhorst were fitted for modeling the egg production curve in ostrich. The goodness of fit criteria's including Mean Square Error (MSE), Likelihood Ratio Test (LRT), Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC) were used to evaluate and selection of the best function. The results indicated that the Wood and the McNally functions with a slight difference in all fitting criteria were the best-fitted functions and the Yang function with the highest values of MSE, LRT, AIC, BIC, were the most inappropriate function to describe the ostrich egg production curve. The McNally and the Wood can be recommended as appropriate functions to describe egg production during 5 production seasons in the studied ostrich flock., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Minimizing bird mortality in the commercial quail breeding industry is important from an economic and welfare perspective. Genetic and non-genetic factors can influence on the cumulative survival of the birds (CS). Accordingly, this study aimed to investigate non-genetic factors on CSs (cumulative survival of the birds from hatch to 5 (CS 1 ), 10 (CS 2 ), 15 (CS 3 ), 20 (CS 4 ), 25 (CS 5 ), 30 (CS 6 ), 35 (CS 7 ), 40 (CS 8 ), and 45 (CS 9 ) days of age), and estimation of the genetic parameters for CSs in crossbred population of quail. Data set included 1794 records from crossbred chicks hatched from 70 sires and 72 dams. The fixed effects were analyzed using an animal model by ASReml software, and all traits were analyzed using Bayesian method via Gibbs sampling by fitting of 6 threshold animal models including the direct genetic effect, the maternal permanent environmental effect, and the maternal genetic effect. The best fitted model for each trait was selected based on the deviance information criteria. Hatch number, the month of hatch, and combination of chickens showed a significant effect on CSs, but the sex of chickens does not have a significant effect on CSs. However, females have higher survival than males (except for CS 1 ). With the best model, the highest and lowest direct heritability was estimated for CS 5 (0.386) and CS 3 (0.250), respectively. The maternal genetic effect was significant for CS 1 , CS 2 , CS 3 , and CS 4 traits, but the maternal permanent environmental effect was significant only for CS 1 . The range of maternal heritability for CS 1 to CS 4 traits was estimated from 0.064 to 0.111, and ratio of the permanent environmental variance to phenotypic variance for CS 1 was 0.021. The result showed that increasing of the birds' survival could be performed by correcting non-genetic factors and genetic selection for CSs considering the maternal genetic effects in younger ages. HIGHLIGHTS: • In the commercial quail breeding industry, the bird mortality is important from an economic and welfare perspective. • Improving quail survival can be achieved by controlling the genetic and non-genetic factors affecting on survival, so knowledge of these factors is necessary. • The combination of crossbred chickens had a significant effect on cumulative survival traits. • The Cumulative survival traits in the crossbred population had relatively high genetic diversity, so genetic selection for these traits could be effective., (© 2022. The Author(s), under exclusive licence to Springer Nature B.V.)

To have a better contribution to the poultry production community, the Poultry Science Association founded journals including Poultry Science (PS) at 1921. Now, after 100 yr of publishing, PS ranks between the top 10 journals in the category of "agriculture, dairy, and animal science". One hundred years after publishing the first paper in PS, the poultry industry has been completely revolutionized. Hence, it will be interesting to establish scientometrics study of the PS development during the last century. Therefore, based on findings of the current study, among countries/authors' collaborations, future research fronts, and possibility of hot topics in the coming years may be predictable. Accordingly, a total of 22,451 articles were retrieved. For content analyses, according to the PS categorization for subject areas, 14 different subject areas were developed, including "behavior, breeding and quantitative genetics, education and extension, health and welfare, immunology, management and environment, metabolism and nutrition, microbiology and virology, modeling, molecular biology, physiology and anatomy, production, products, processing and marketing, and reproduction". Considering the 100-yr of PS, the most frequent subject area was "nutrition and metabolism" (14,109 articles), and "modeling" (1,114 articles) attracted less scholarly attention. However, considering the last decade (2011-2020), the most important subject area was "molecular biology" (1,420 of 2,466 articles; 57.58%), followed by "modeling" (544 of 1,144 articles; 48.88%). Moreover, the most frequent poultry species/strains were broilers (retrieved in 6,156 articles), followed by laying hens, turkeys, and quail. Considering collaboration of countries and researchers, it can be said that a total number of 108 countries contributed to PS, with the most prolific country being United States (with 9,421 articles; 43.16%), followed by China, Canada, the Netherlands, and Japan. Among the authors, Harms RH (287 articles), and Siegel PB (208) were the most prolific authors, and Siegel PB and Dunnington EA (71 articles) had more collaborations. To study keyword trends, including 3 time periods broilers was the central co-occurrent keyword, while the importance of chickens and turkeys declined during the time. Salmonella spp. was a constant representative of poultry microbiology during 100 yr. While "nutrition and metabolism" was the most important subject area, nutrition-related keywords (major items) were not concentrated and co-occurred with a variety of keywords from different subject areas. While "molecular biology" ranked first over the past decade, the importance of "nutrition and metabolism" should not be ignored. In fact, in recent years, molecular basis of the nutrition has been studied. In big-data era and due to developing the molecular biology technologies, it seems that using mathematical modeling and computational methodologies will increase and probably remains as one of the most attractive research areas for scientists at least in the upcoming future decades., Competing Interests: DISCLOSURES The authors have no conflict of interest., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Carcass yield of meat-type quails is strongly correlated with the weight of the birds at slaughter (slaughter weight [SW]; body weight at 45 D of age). Moreover, prediction of superior animals for SW at the earlier stages of the rearing period is favorable for producers. Therefore, the aim of the present study was to predict and optimize SW of Japanese quails based on their early growth performances, sex, and egg weight as predictors through artificial neural network (ANN) modeling. To construct the ANN model a feed-forward multilayer perceptron neural network structure was used. Moreover, sensitivity analysis was used to arrange the predictors in the ANN model(s) according to their predictive importance too. In addition, the optimization process was conducted to determine the optimum values for the input variables to yield maximum SW. The best-fitted network on input data to predict SW in Japanese quails was determined with 7 neurons in the input layer, 11 neurons in the hidden layer, and one neuron in the output layer. The coefficient of determination (R 2 ) was 0.9404, 0.9359, and 0.9223 for training, validation, and testing phases, respectively. For the corresponding phases, SEM were also 51.8854, 52.2764, and 55.2572, respectively. According to sensitivity analysis, the most important input variable for prediction of SW was body weight at 20 D of age (BW20), whereas the less important input variables were weight of the birds at hatch and body weight at 5 D of age. The results of the neural network optimization indicated that all the input variables, except for BW20, were very similar but slightly higher than mean values (μ for each input variable). The results of this study suggest that the ANN provides a practical approach to predict the final body weight (SW) of Japanese quails based on early performances. Moreover, phenotypic selection for higher values of early growth traits did not ensure the achievement of maximum SW, except for BW20., (Copyright © 2019. Published by Elsevier Inc.)

Non-additive genetic effects are important to increase the accuracy of estimating genetic parameters for growth traits. The aim of this study was to estimate genetic parameters and variance components, specially dominance and epistasis genetic effects, for growth traits (birth weight (BW), weaning weight (WW), 3 (W3), 6 (W6), 9 (W9), and 12 (W12) month weight) in Adani goats. Analyses were carried out using Bayesian method via Gibbs sampler animal model by fitting of 18 different models. All fixed effects (sex, type of birth, age of dam, and year) showed significant effects on BW, WW, W3, and W6, whereas the type of birth and age of dam were not significant on W9 and W12. With the best model, direct heritability estimates were 0.347, 0.178, 0.158, 0.359, 0.278, and 0.281 for BW, WW, W3, W6, W9, and W12 traits, respectively. Maternal permanent environmental effect was significant for BW and WW, but maternal genetic effect was significant only for W3. Dominance and epitasis effects were significant almost for all traits and as a proportion of phenotypic variance were ranged from 0.115 to 0.258 and 0.107 to 0.218, respectively. The range of accuracy of breeding values estimated for growth traits with appropriate evaluation models was from 0.521 to 0.652, 0.616 to 0.694, and 0.548 to 0.684 for the all animals, 10% of the best males and 50% of the best females, respectively. When dominance and epistasis effects added to models, the error variance was reduced and the accuracy of estimated breeding values increased. The accuracy of the best model showed a significant difference with the accuracy of other models (p < 0.01). The result of the present study suggests that non-additive genetic effects should be in genetic evaluation models for goat growth traits because of its effect on accuracy of estimated breeding values.