The breeding goal in dairy cattle is to increase lifetime profit per animal. Profit is a function of production and the time that a cow remains in herd. Thus, profit can only be recorded when a cow is culled, and breeding value of more profitable aniUnauthenticated Download Date | 5/13/18 1:11 AM

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1. A study was conducted to study direct dominance genetic and maternal effects on genetic evaluation of production traits in dual-purpose chickens. The data set consisted of records of body weight and egg production of 49 749 Mazandaran fowls from 19 consecutive generations. Based on combinations of different random effects, including direct additive and dominance genetic and maternal additive genetic and environmental effects, 8 different models were compared. 2. Inclusion of a maternal genetic effect in the models noticeably improved goodness of fit for all traits. Direct dominance genetic effect did not have noticeable effects on goodness of fit but simultaneous inclusion of both direct dominance and maternal additive genetic effects improved fitting criteria and accuracies of genetic parameter estimates for hatching body weight and egg production traits. 3. Estimates of heritability (h) for body weights at hatch, 8 weeks and 12 weeks of age (BW0, BW8 and BW12, respectively), age at sexual maturity (ASM), average egg weights at 28-32 weeks of laying period (AEW), egg number (EN) and egg production intensity (EI) were 0.08, 0.21, 0.22, 0.22, 0.21, 0.09 and 0.10, respectively. For BW0, BW8, BW12, ASM, AEW, EN and EI, proportion of dominance genetic to total phenotypic variance (d) were 0.06, 0.08, 0.01, 0.06, 0.06, 0.08 and 0.07 and maternal heritability estimates (m) were 0.05, 0.04, 0.03, 0.13, 0.21, 0.07 and 0.03, respectively. Negligible coefficients of maternal environmental effect (c) from 0.01 to 0.08 were estimated for all traits, other than BW0, which had an estimate of 0.30. 4. Breeding values (BVs) estimated for body weights at early ages (BW0 and BW8) were considerably affected by components of the models, but almost similar BVs were estimated by different models for higher age body weight (BW12) and egg production traits (ASM, AEW, EN and EI). Generally, it could be concluded that inclusion of maternal effects (both genetic and environmental) and, to a lesser extent, direct dominance genetic effect would improve the accuracy of genetic evaluation for early age body weights in dual-purpose chickens.

The aim of this study was to compare genetic (co)variance components and prediction accuracies of breeding values from genomic random regression models (gRRM) and pedigree-based random regression models (pRRM), both defined with or without an additional environmental gradient. The used gradient was a temperaturehumidity index (THI), considered in statistical models to investigate possible genotype by environment (G×E) interactions. Data included 106,505 test-day records for milk yield (MY) and 106,274 test-day records for somatic cell score (SCS) from 12,331 genotyped Holstein Friesian daughters of 522 genotyped sires. After single nucleotide polymorphism quality control, all genotyped animals had 40,468 single nucleotide polymorphism markers. Test-day traits from recording years 2010 to 2015 were merged with temperature and humidity data from the nearest weather station. In this regard, 58 large-scale farms from the German federal states of Berlin-Brandenburg and Mecklenburg-West Pomerania were allocated to 31 weather stations. For models with a THI gradient, additive genetic variances and heritabilities for MY showed larger fluctuations in dependency of DIM and THI than for SCS. For both traits, heritabilities were smaller from the gRRM compared with estimates from the pRRM. Milk yield showed considerably larger G×E interactions than SCS. In genomic models including a THI gradient, genetic correlations between different DIM × THI combinations ranged from 0.26 to 0.94 for MY. For SCS, the lowest genetic correlation was 0.78, estimated between SCS from the last DIM class and the highest THI class. In addition, for THI × THI combinations, genetic correlations were smaller for MY compared with SCS. A 5-fold cross-validation was used to assess prediction accuracies from 4 different models. The 4 different models were gRRM and pRRM, both modeled with or without G×E interactions. Prediction accuracy was the correlation between breeding values for the prediction data set (i.e., excluding the phenotypic records from this data set) with respective breeding values considering all phenotypic information. Prediction accuracies for sires and for their daughters were largest for the gRRM considering G×E interactions. Such modeling with 2 covariates, DIM and THI, also allowed accurate predictions of genetic values at specific DIM. In comparison with a pRRM, the effect of a gRRM with G×E interactions on gain in prediction accuracies was stronger for daughters than for sires. In conclusion, we found stronger effect of THI alterations on genetic parameter estimates for MY than for SCS. Hence, gRRM considering THI especially contributed to gain in prediction accuracies for MY.

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Samples of 3 varieties of full-fat canola seed (FFCS), Okapi, Opera, and SLM046, were obtained from a local oilseed company, and chemical composition and mineral content of the 3 varieties were determined. Crude protein content of the canola seed ranged from 19.5 to 21.4%, with an average of 20.36 ± 0.85%. Ether extract of the canola seed ranged from 47.3 to 50.4%, with an average of 48.77 ± 0.92%. Composition of the main fatty acids in the oil was determined by gas chromatography. The saturated fatty acid content of Okapi and SLM046 (including palmitic and stearic acids) was very low compared with the unsaturated fatty acid content, and oleic acid (C18:1n-9 cis) constituted the highest proportion of fatty acids (52.56%) in SLM046 (with an average content of 35.84%). Canola seed is rich in C18:3n-3 fatty acids, and the oil of canola seed is an excellent source of α-linolenic acid (8 to 12%). The calcium content of Okapi, Opera, and SLM046 was 1.05, 0.97, and 0.7%, respectively. The average Mg content of canola seed was 0.14 ± 0.007%. Iron content ranged from 45.2 to 51.7 mg/kg in the 3 varieties of FFCS. Zinc content of Okapi, Opera, and SLM046 was 11.1, 17.6, and 13.7 mg/ kg, respectively. Mean content of Mn was 35.57 ± 0.57 mg/kg, and that of Cu was 11.97 ± 0.42 mg/kg in the FFCS samples. The effects of variety, enzyme addition, and thermal processing on the ME of ground FFCS were investigated in a TME n assay with adult roosters. Ground FFCS samples were heated at 120°C for approximately 3 h in an electric oven. A currently available commercial multienzyme was added to the 3 raw varieties of FFCS at an inclusion level of 0.5%. The average TME n content of ground FFCS was 5,495 kcal/kg, and a significant difference was found between the 3 varieties of canola seed (P < 0.05). The TME n content of ground FFCS was not affected by thermal processing or multienzyme supplementation.

The objective of the present study was to estimate the heritability and to assess the existence of maternal effects for economic traits in Iranian native fowl. Variance components were estimated for body weight at hatch (BW 0 ), 8 (BW 8 ) and 12 (BW 12 ) weeks of age, age at sexual maturity and weight at sexual maturity, egg number and average egg weight at 28th, 30th and 32nd weeks using restricted maximum likelihood method and six animal models. The best model was determined using the Akaike information criterion for each trait. For age at sexual maturity, the basic model consisting of direct genetic effects was superior. For weight at sexual maturity and egg number, a model consisting of maternal permanent environmental effects in addition to direct genetic effects was the best. For average egg weight at 28th, 30th and 32nd weeks, the model with direct and maternal genetic effects assuming no covariance between them was the best. For BW 0 , BW 8 and BW 12 , the model including maternal genetic and permanent environmental effects in addition to direct genetic effects was the most appropriate. The estimates of direct heritability ranged from 0.05 (BW 0 ) to 0.35 (weight at sexual maturity). Direct genetic variance and heritability were overestimated if maternal effects were ignored in the statistical model for all traits except ASM. The results indicated that the evaluation of direct and maternal genetic and phenotypic trends based on the best model for each trait was carried out. Maternal genetic trends for BW 0 , BW 8 , BW 12 and average egg weight at 28th, 30th and 32nd weeks were significantly positive. Present results indicated favourable effects of the performed breeding program for all traits except BW 0 , during generations.

Applying a multiple trait random regression (MT-RR) in national level and for whole test day records of a country is a great advance in animal breeding context. Having reliable (co) variance components is a critical step in applying multiple traits genetic evaluation especially in developing countries. Genetic parameters of milk, fat and protein yields were estimated for Iranian Holstein dairy cows. Data included 276 692 test day (TD) production traits records collected of 30 705 primiparous cows belonging to 619 sires. An animal multi-trait random regression model was employed in the analyses using the restricted maximum likelihood (REML) method. The model included herd-test-date, age-season of calving (by applying a fixed regression for each subclass of this effect) and year of calving as fixed effects and random regression (RR) coefficients for additive genetic (AG) and permanent environmental (PE) effects. Obtained results showed that daily heritabilities ranged from 0.10 to 0.21 for milk, from 0.05 to 0.08 for fat and from 0.08 to 0.18 for protein yield. Estimated heritability for 305-d milk, fat and protein yields were 0.25, 0.20 and 0.25, respectively. Correlations between individual test day records within traits were high for adjacent tests (nearly 1) and decreased as the interval between tests increased. Correlations between yields of milk, fat and protein on a given test day are also high and greater during late lactation than during early or mid-lactation. Genetic correlations between 305-d yield traits ranged from 0.75 to 0.92. The largest genetic correlation, as well as permanent environmental correlation, was observed between milk and protein yield.