Eggshell translucency: its relationship with specific gravity and eggshell color and its influence on broiler egg weight loss, hatchability, and embryonic mortalities

Eggshell quality is among the most important factors affecting hatchability in broiler breeders, and therefore several methods for its assessment are available in the poultry industry. Among them, eggshell translucency has received special attention in recent years due to its connection with ultrastructural disorganization of the shell layers. However, there is very limited data on the impact of translucency on hatching eggs and on the possible links between this trait and specific gravity (SG) or shell color. Thus, our study investigated associations and interactions between eggshell translucency, SG, and color on incubation parameters of eggs from the same breeding flock (Ross 308AP, 51 wk of age). To this end, light and dark eggs within 5 different SG categories (≥1.065, 1.070, 1.075, 1.080, and ≤1.085) were selected from 15,976 eggs, graded into 3 translucency scores, and later incubated to evaluate egg weight loss, hatchability and embryonic mortalities. In general, translucency scores were evenly distributed within SG categories (χ2 [8, N = 1,138] = 13.67, P = 0.090) and color (χ2 [2, N = 1,138] = 4.93, P = 0.084). No interactions between eggshell translucency and SG or between translucency and color were found for the analyzed variables. An interaction was observed between SG and eggshell color for the variable egg weight loss, where the light-shelled eggs, in most SG categories lost more weight throughout incubation than dark eggs. Eggshell translucency affected egg weight loss, hatchability, and embryonic mortality on 11 to 18 d of incubation, with highly translucent eggs showing the worst results. At the same time, eggs with SG lower than 1.070 displayed the greatest weight loss, lowest hatchability, and highest contamination. We found no influence of eggshell color on weight loss or hatchability, but light-shelled eggs exhibited higher late embryonic mortality. Together, these data suggest that despite its effects on certain hatching parameters, shell translucency bears no relationship to SG or color.

Genetic improvement of duration of fertility in chickens and its commercial application for extending insemination intervals

The growth rate of chickens has made remarkable progress in recent decades through continuous breeding efforts. However, this advancement has also led to a decline in fertility among commercially bred chickens. Therefore, it is crucial to understand and improve factors that influence fertility to ensure the continued success of the industry. Here, we conduct a 3-generation selection experiment within 2 purebred female lines, with the aim of increasing the duration of fertility (DF). Duration of fertility refers to the length of time hens remain capable of producing fertilized eggs and is a crucial factor that directly impacts chick output. The results showed that significant genetic progress was achieved in embryo survival rates and the fertility duration day during both the peak and late laying periods. Moreover, after 3 generations of selective breeding, the disparities in embryo survival and chick health rates from setting eggs between 8-d and 5-d insemination intervals in the grandparent stock were significantly reduced. The rates decreased from 1.83% and 2.39 to 0.72% and 0.33%, respectively. Surprisingly, the hatching performances of hens with an 8-d interval were comparable to those hens that had not undergone genetic selection for DF and had a 5-d interval. We further discussed the possibility of extending the insemination interval to 8 d in parent stock for commercial practices. The parental populations exhibited remarkable performance in terms of percentages of embryo survival and healthy chicks from the setting eggs, with rates exceeding 94 and 90%, respectively. Thus, it can be inferred that an extended insemination interval is feasible by genetic selection for DF. These findings will provide valuable insights into the efficacy of genetic selection in enhancing DF and its practical application in commercial breeding programs.

Fast growing broiler production from genetically different pure lines in Turkey. 1. Parental traits: growth, feed intake, reproduction, and hatching traits

The aim of the present study was to reveal the trends in age-related growth, feed intake, reproduction, and hatchability traits in 5 pure line (PL) breeders (3 dam [A1: slow-feathering, A2: fast-feathering, A3: slow-feathering] and 2 sire [B1: fast-feathering, B2: fast-feathering]) and their reciprocal two-way cross parent stock (PS) breeders (6 female [A1♂ × A2♀; A1♂ × A3♀; A2♂ × A1♀; A2♂ × A3♀; A3♂ × A1♀; A3♂ × A2♀] and 2 male [B1♂ × B2♀; B2♂ × B1♀]) and to identify heterotic effects in two-way cross PS combinations showing superiority over PL breeders. In the rearing period, 60 females and 15 males in the each PL group, 120 females in each female PS and 120 males in each male PS breeders, and 40 females and 5 males were used in each PL and PS genotype in the laying period. Body weight (BW), average daily feed intake (ADFI), reproductive traits (age at first egg [AFE], age at sexual maturity [ASM], egg number, weekly and total %Lay, egg weight, egg mass), hatching traits (fertility, hatchability of fertile [HOF] and set [HOS] and embryonic mortality), and heterosis (%) values for some traits were assesed. Both males and females of PLs and PSs had different BW at 4 and 8 weeks of age (P < 0.01), but had similar BW from 12 to 24 weeks of age. The A2, B1, and B2 hens had a higher BW (nearly 4000 g) than the others at 31 weeks of age (P < 0.01), and B2 hens showed a BW of more than 5000 g at 64 weeks (P < 0.001). Weekly ADFI per female in rearing, laying, and overall period was not different between groups. The A1 (179 days), A3 (183 days), two-way cross (from 175.5 to 185.5 days) hens started laying at a similar age and earlier than B1 (184 days), A2 (192 days), and B2 (194 days) hens. From AFE to 64 weeks, %Lay was the highest in the A1 line (69.7%), lowest in the B1 (45.3%) and B2 (48.8%) line, and between 56.9 and 64.8% in PS breeder hens. The PS eggs tended to have higher fertility, HOF, and HOS, and less embryonic mortality compared to PL eggs. Negative and low heterosis for AFE was observed in PS eggs, while positive heterosis for fertility, HOF, and HOS was generally observed in four-way hybrid eggs. The highest heterosis for the 64-week cumulative egg number was observed in A3 × A2 hens. Our study results show that mating of B1 × B2 males with A3 × A2 females seems more favorable in terms of higher egg or chick production. However, more knowledge is also needed for the overall efficiency of each PS, including the final performance of its hybrids.

Applicability of single-step genomic evaluation with a random regression model for reproductive traits in turkeys (Meleagris gallopavo)

Fertility and hatchability are economically important traits due to their effect on poult output coming from the turkey hatchery. Traditionally, fertility is recorded as the number of fertile eggs set in the incubator (FERT), defined at a time point during incubation by the identification of a developing embryo. Hatchability is recorded as either the number of fertile eggs that hatched (hatch of fertile, HOF) or the number hatched from all the eggs set (hatch of set, HOS). These traits are collected throughout the productive life of the bird and are conventionally cumulated, resulting in each bird having a single record per trait. Genetic evaluations of these traits have been estimated using pedigree relationships. However, the longitudinal nature of the traits and the availability of genomic information have renewed interest in using random regression (RR) to capture the differences in repeatedly recorded traits, as well as in the incorporation of genomic relationships. Therefore, the objectives of this study were: 1) to compare the applicability of a RR model with a cumulative model (CUM) using both pedigree and genomic information for genetic evaluation of FERT, HOF, and HOS and 2) to estimate and compare predictability from the models. For this study, a total of 63,935 biweekly FERT, HOF, and HOS records from 7,211 hens mated to 1,524 toms were available for a maternal turkey line. In total, 4,832 animals had genotypic records, and pedigree information on 11,191 animals was available. Estimated heritability from the CUM model using pedigree information was 0.11 ± 0.02, 0.24 ± 0.02, and 0.24 ± 0.02 for FERT, HOF, and HOS, respectively. With random regression using pedigree relationships, heritability estimates were in the range of 0.04–0.09, 0.11–0.17, and 0.09–0.18 for FERT, HOF, and HOS, respectively. The incorporation of genomic information increased the heritability by an average of 28 and 23% for CUM and RR models, respectively. In addition, the incorporation of genomic information caused predictability to increase by approximately 11 and 7% for HOF and HOS, respectively; however, a decrease in predictability of about 12% was observed for FERT. Our findings suggest that RR models using pedigree and genomic relationships simultaneously will achieve a higher predictability than the traditional CUM model.

Synergy Between Dietary Quercetin and Vitamin E Supplementation in Aged Hen’s Diet Improves Hatching Traits, Embryo Quality, and Antioxidant Capacity of Chicks Hatched From Eggs Subjected to Prolonged Storage

The current study aims to investigate the effects of the synergy between quercetin and vitamin E in aged hen’s diet on hatchability and antioxidant levels of the embryo and newly hatched chicks from prolonged storage eggs. A total of 400 breeder laying hens of 65 weeks of age were selected and randomly divided into 4 groups. Birds were fed a basal diet alone (Control), and basal diets supplemented with quercetin (Q) (0.4 g/kg) and vitamin E (VE) (0.2 g/kg) alone and their combination (0.4 g/kg Q + 0.2 g/kg VE) for 14 weeks, respectively, to determine their effects on yolk antioxidant status, fertility, embryonic mortality, hatchability, antioxidant status of embryonic tissues, as well as the antioxidant status of the newly hatched chicks. The results showed that the hen’s dietary Q + VE increased the yolk weight, as well as increased the antioxidant status of the egg yolk (p < 0.05). Compared with the control group, the supplementation of Q + VE significantly increased the hatchability of set-fertile eggs and decreased early embryonic mortality in eggs stored for 7 and 14 days, respectively (p < 0.05), and also improved the antioxidant capacity of the embryos obtained from eggs stored for 14 days (before incubation) (p < 0.05). Moreover, Q + VE increased the levels of SOD, GSH-Px, T-AOC, T-SOD, and CAT in the liver, heart, and pectoral muscle of the embryo, 1-day-old and 14-day-old chicks (p < 0.05), as well as upregulated the antioxidant related genes (GPx-1, GPx-2, GPx-4, DIO-1, and SOD-1) in the liver of the embryo, 1-day-old and 14-day-old chicks hatched from 14-days storage eggs (p < 0.05). Meanwhile, the MDA levels were decreased by the Q + VE in the embryo and post-hatched chicks (p < 0.05). In conclusion, these findings suggested that maternal dietary Q + VE exerts beneficial synergistic effects on the antioxidant capacity of the egg yolk, embryo, and chicks during prolong egg storage, therefore, Q + VE could be used as a dietary measure to enhance hatchability and chick quality in poultry production.

Predicting hatchability of layer breeders and identifying effects of animal related and environmental factors

In this study, a data driven approach was used by applying linear regression and machine learning methods to understand animal related and environmental factors affecting hatchability. Data was obtained from a parent stock and grand-parent stock hatchery, including 1,737 batches of eggs incubated in the years 2010-2018. Animal related factors taken into consideration were strain (white vs. brown strain), breeder age, and egg weight uniformity at the start of incubation, whereas environmental factors considered were length of egg storage before incubation, egg weight loss during incubation and season. Effects of these factors on hatchability were analyzed with 3 different models: a linear regression (LR) model, a random forest (RF) model and a gradient boosting machine (GBM) model. In part one of the study, hatchability was predicted and the performance of the models in terms of coefficient of determination (R²) and root mean square error (RMSE) was compared. The ensemble machine learning models (RF: R² = 0.35, RMSE = 8.41; GBM: R² = 0.31, RMSE = 8.67) appeared to be superior than the LR model (R² = 0.27, RMSE = 8.92) as indicated by the higher R² and lower RMSE. In part 2 of the study, effects of these factors on hatchability were investigated more into detail. Hatchability was affected by strain, breeder age, egg weight uniformity, length of egg storage and season, but egg weight loss didn't have a significant effect on hatchability. Additionally, four 2-way interactions (breeder age × egg weight uniformity, breeder age × length of egg storage, breeder age × strain, season × strain) were significant on hatchability. It can be concluded that hatchability of parent stock and grand-parent stock layer breeders is affected by several animal related and environmental factors, but the size of the predicted effects varies between the methods used. In this study, 3 models were used to predict hatchability and to analyze effects of animal related and environmental factors on hatchability. This opens new horizons for future studies on hatchery data by taking the advantage of applying machine learning methods, that can fit complex datasets better than LR and applying statistical analysis.

Modeling genetic components of hatch of fertile in broiler breeders

Reproductive efficiency such as fertility and hatch of fertile (HoF) are of economic importance and concern to breeding companies becaue of their effects on chick output. Similar to other traits of economic importance in poultry breeding, the rate of response for HoF is largely dependent on the use of an appropriate model for evaluating the trait. Therefore, the objectives of this study were to estimate genetic parameters from cumulative, repeatability, fixed regression, random regression, and multitrait models for HoF from a pure-line broiler breeder. The data available for this study consisted of weekly HoF records from 11,729 hens with a total pedigree record of 38,260. Estimates of heritability from the various models ranged from 0.04 to 0.22 with the highest estimate obtained from the cumulative model and the lowest from the repeatability model. Responses to selection estimated for the different models ranged from 0.03 to 0.08% gain per year of the phenotypic mean. In general, the cumulative and the repeatability models underestimated response to selection. The multitrait and random regression models gave similar results for response to selection at 0.08 percentage change in phenotypic mean. In conclusion, the cumulative model is not optimal for modeling HoF, and likewise, the repeatability model. The random regression and multitrait models should be considered instead as they offered a higher response to selection. However, if a multitrait analysis is to be considered, it is recommended to split up the production period in such a way as to avoid computational constraints due to overparameterization.

Estimation of additive genetic, dominance, and mate sire variances for fertility traits in Thai native (Pradu Hang Dam) chickens

The objective of this study was to compare the appropriate models used to estimate the value of genetic parameters in fertility traits: fertility (FER), hatchability of fertile eggs (HOF), and hatchability of eggs set (HOS) in Thai native (Pradu Hang Dam) chickens. Data were collected for each fertility trait from 3435 test-week records from 715 hens, 158 mate sires, and 972 pedigree animals. Three random regression models were analyzed: model 1 (M1: A + PE) was adjusted by using additive genetic and permanent environmental effects. Model 2 (M2: A + PE + D) was adjusted by using the dominance effect. Finally, model 3 (M3: A + MS + PE + D) was adjusted by using the mate sire effect. The results found the low heritability of FER (M1 to M3), HOF (M1 to M3), and HOS (M1 to M3) ranged from 0.031-0.040, 0.037-0.066, and 0.040-0.059, respectively. Adjustment for the dominance and mate sire effects in M3 reduced the upward bias in heritability and improved the accuracy of variance component estimates compared to M1 and M2. In conclusion, the genetic evaluation for FER, HOF, and HOS can include the dominance and MS effects to increase the accuracy of evaluation of breeding values and plan for mate selection in breeding programs.

Breed and feed affect amino acid contents of egg yolk and eggshell color in chickens

Genetic and environmental factors regulate hen egg traits. To demonstrate the possibility of producing designer eggs through genetic and environmental factors, we investigated the effects of breed and feed on egg traits using 2 chicken breeds, Rhode Island Red (RIR) and Australorp (AUS), and 2 feeds, mixed feed and fermented feed. A total of 40 eggs were collected at 33 wk of age (0 mo under mixed feed) and 1, 1.5, and 2 mo after switching to fermented feed. Two-way ANOVA mixed design was used to evaluate 10 egg traits: weight, length of the long axis, length of the short axis, eggshell weight, yolk weight, albumen weight, eggshell thickness, eggshell lightness, redness, and yellowness, and 19 yolk amino acids. The results revealed significant breed effects on eggshell redness and yellowness, with higher values of these traits in RIR eggs compared with AUS eggs. There was a significant effect of feed on eggshell lightness, with a lighter color observed under fermented feed compared with mixed feed. Significant effects of breed and breed × feed were found for yolk cysteine content. Eggs from AUS had a higher yolk cysteine content than those from RIR. The cysteine content in AUS eggs increased gradually after starting fermented feed, although RIR remained relatively constant over time. These findings suggest that it is possible to produce designer eggs with enriched components, including yolk amino acids, by adjusting both genetic and environmental factors. This represents a first step in understanding the mechanisms underlying the production of value-added eggs in chickens.

Metabolomics Approach Reveals the Effects of Breed and Feed on the Composition of Chicken Eggs

Chicken eggs provide essential nutrients to consumers around the world. Although both genetic and environmental factors influence the quality of eggs, it is unclear how these factors affect the egg traits including egg metabolites. In this study, we investigated breed and feed effects on 10 egg traits, using two breeds (Rhode Island Red and Australorp) and two feed conditions (mixed feed and fermented feed). We also used gas chromatography-mass spectrometry (GC-MS/MS) to analyze 138 yolk and 132 albumen metabolites. Significant breed effects were found on yolk weight, eggshell weight, eggshell colors, and one albumen metabolite (ribitol). Three yolk metabolites (erythritol, threitol, and urea) and 12 albumen metabolites (erythritol, threitol, ribitol, linoleic acid, isoleucine, dihydrouracil, 4-hydroxyphenyllactic acid, alanine, glycine, N-butyrylglycine, pyruvic acid, and valine) were significantly altered by feed, and a significant interaction between breed and feed was discovered in one albumen metabolite (N-butyrylglycine). Yolk and albumin had higher levels of sugar alcohols when hens were fed a fermented diet, which indicates that sugar alcohol content can be transferred from diet into eggs. Linoleic acid was also enriched in albumen under fermented feed conditions. This study shows that yolk and albumen metabolites will be affected by breed and feed, which is the first step towards manipulating genetic and environmental factors to create "designer eggs."

Causal phenotypic networks for egg traits in an F2 chicken population

Traditional single-trait genetic analyses, such as quantitative trait locus (QTL) and genome-wide association studies (GWAS), have been used to understand genotype-phenotype relationships for egg traits in chickens. Even though these techniques can detect potential genes of major effect, they cannot reveal cryptic causal relationships among QTLs and phenotypes. Thus, to better understand the relationships involving multiple genes and phenotypes of interest, other data analysis techniques must be used. Here, we utilized a QTL-directed dependency graph (QDG) mapping approach for a joint analysis of chicken egg traits, so that functional relationships and potential causal effects between them could be investigated. The QDG mapping identified a total of 17 QTLs affecting 24 egg traits that formed three independent networks of phenotypic trait groups (eggshell color, egg production, and size and weight of egg components), clearly distinguishing direct and indirect effects of QTLs towards correlated traits. For example, the network of size and weight of egg components contained 13 QTLs and 18 traits that are densely connected to each other. This indicates complex relationships between genotype and phenotype involving both direct and indirect effects of QTLs on the studied traits. Most of the QTLs were commonly identified by both the traditional (single-trait) mapping and the QDG approach. The network analysis, however, offers additional insight regarding the source and characterization of pleiotropy affecting egg traits. As such, the QDG analysis provides a substantial step forward, revealing cryptic relationships among QTLs and phenotypes, especially regarding direct and indirect QTL effects as well as potential causal relationships between traits, which can be used, for example, to optimize management practices and breeding strategies for the improvement of the traits.

Organic and inorganic selenium in Aseel chicken diets: Effect on hatching traits

A study was conducted to evaluate the effect of dietary selenium (Se) sources (organic and inorganic Se at 0.30 ppm and basal diet at 0 ppm level of supplemented Se) on hatching traits in four varieties of Aseel chicken, Lakha, Mushki, Peshawari, and Mianwali. In total, 84 adult molted hens (50 wk old), 21 from each variety, were randomly assigned to 12 treatment groups in a 3 (Se diets) × 4 (Aseel varieties) factorial arrangement under a randomized complete block design. Each treatment was replicated 7 times with individual hens in each. Settable egg, fertility, hatch of fertile eggs, hatchability, A-grade chick, and embryonic mortality parameters were evaluated. The results indicated that the birds fed an organic Se supplemented diet had greater (P < 0.05) settable eggs, fertility, hatch of fertile eggs, hatchability, and A-grade chicks and reduced embryonic mortality than those fed inorganic or no Se. Among varieties, Mushki had lower (P < 0.05) fertility, hatch of fertile eggs, hatchability, and A-grade chicks than rest of three varieties. Interaction of Se sources and varieties indicated that dietary organic Se supplementation improved (P < 0.05) hatch of fertile eggs in Peshawari and Mianwali, whereas hatchability only in Peshawari variety and reduced embryonic mortality in Mianwali. It was concluded that dietary supplementation of organic Se could be used to improve hatching traits as well as reduce embryonic mortality in native Aseel chicken.

Accuracy of genomic prediction using an evenly spaced, low-density single nucleotide polymorphism panel in broiler chickens

One approach for cost-effective implementation of genomic selection is to genotype training individuals with a high-density (HD) panel and selection candidates with an evenly spaced, low-density (ELD) panel. The purpose of this study was to evaluate the extent to which the ELD approach reduces the accuracy of genomic estimated breeding values (GEBV) in a broiler line, in which 1,091 breeders from 3 generations were used for training and 160 progeny of the third generation for validation. All birds were genotyped with an Illumina Infinium platform HD panel that included 20,541 segregating markers. Two subsets of HD markers, with 377 (ELD-1) or 766 (ELD-2) markers, were selected as ELD panels. The ELD-1 panel was genotyped using KBiosciences KASPar SNP genotyping chemistry, whereas the ELD-2 panel was simulated by adding markers from the HD panel to the ELD-1 panel. The training data set was used for 2 traits: BW at 35 d on both sexes and hen house production (HHP) between wk 28 and 54. Methods Bayes-A, -B, -C and genomic best linear unbiased prediction were used to estimate HD-marker effects. Two scenarios were used: (1) the 160 progeny were ELD-genotyped, and (2) the 160 progeny and their dams (117 birds) were ELD-genotyped. The missing HD genotypes in ELD-genotyped birds were imputed by a Gibbs sampler, capitalizing on linkage within families. In scenario (1), the correlation of GEBV for BW (HHP) of the 160 progeny based on observed HD versus imputed genotypes was greater than 0.94 (0.98) with the ELD-1 panel and greater than 0.97 (0.99) with the ELD-2 panel. In scenario (2), the correlation of GEBV for BW (HHP) was greater than 0.92 (0.96) with the ELD-1 panel and greater than 0.95 (0.98) with the ELD-2 panel. Hence, in a pedigreed population, genomic selection can be implemented by genotyping selection candidates with about 400 ELD markers with less than 6% loss in accuracy. This leads to substantial savings in genotyping costs, with little sacrifice in accuracy.