Small Ruminant Research
ISSN : 0921-4488
Published by: Elsevier BV (10.1016)
Total articles ≅ 6,147
Latest articles in this journal
Small Ruminant Research, Volume 200; doi:10.1016/j.smallrumres.2021.106400
The effects of including thyme, celery or their mixture (as an alternative to salinomycin ionophore) on nutrient utilization and animal performance were evaluated using Barki lambs. Fifty-five lambs weighing 18.5 ± 1.1 kg and about 90 ± 5 days old were stratified into 5 treatment groups and fed: (1) a control diet of concentrates and maize fodder (600:400 on dry matter basis), or the control diet supplemented with (2) 15 g of thyme, (3) 15 g of celery, (4) 15 g of thyme and celery mixture, or (5) 1 g of salinomycin/lamb daily for 288 days. Additives significantly increased (P<0.05) both maize and total intakes, while thyme and thyme-celery significantly increased nutrient digestibility (P<0.05) compared with the control treatment. Celery, thyme-celery and salinomycin treatments decreased (P<0.05) serum cholesterol. Celery increased (P<0.05) final body weight, weight gain and average daily gain without affecting shrunk liveweight, hot carcass weight or dressing percent. Thyme-celery mix increased fat thickness of the rib cuts (P<0.001), while thyme, thyme-celery and celery treatments increased (P<0.01) the longissimus muscle area. Salinomycin, celery and thyme treatments increased (P<0.05) the lean proportion and decreased the fat proportion. Thyme, celery and thyme-celery treatments decreased (P<0.001) protein of meat, while thyme and thyme-celery treatments increased (P<0.01) carcass water holding capacity. Salinomycin, thyme and celery treatments decreased (P<0.01) meat brightness score, while celery treatment increased (P<0.05) redness of meat without affecting yellowness, chroma or hue of meat. Overall, results in the present study showed that these natural additives had similar effects to salinomycin, but further studies are necessary to validate the results and their mechanism of action.
Small Ruminant Research, Volume 202; doi:10.1016/j.smallrumres.2021.106465
The impact of selection of sheep for reproduction on meat traits are not evident, while genetic parameters for meat traits is absent for South African pure breeds. Quantitative and qualitative meat traits were therefore studied in progeny of two Merino selection lines that were divergently selected for number of lambs weaned per ewe joined (NLW) since 1986. The historic divergent selection resulted in two lines (High (H) and Low (L)) differing widely for NLW. Slaughter data were recorded during the routine slaughter of surplus 14-month-old ram and ewe hoggets from these lines and assessed for selection line and sex. Single-trait heritability estimates were derived for meat traits by average information restricted maximum likelihood methods. Depending on the trait, data were available for between 340 and 576 animals that were recorded between 2015 and 2018. Hoggets from the H line were heavier than their L line contemporaries, with a slightly lower ultimate pH after 48 h in the cooler and slightly darker meat. H line ewes had, on average, redder meat than the other selection line x sex groups. Single-trait heritability estimates amounted to 0.44 ± 0.16 for slaughter weight, 0.63 ± 0.15 for carcass weight, 0.34 ± 0.15 for dressing percentage, 0.25 ± 0.11 for fat depth at the 13th rib, 0.29 ± 0.11 for fat depth at the rump, 0.12 ± 0.11 for ultimate pH, 0.32 ± 0.12 for lightness, 0.11 ± 0.09 for redness, 0.04 ± 0.06 for yellowness, 0.05 ± 0.08 for cooking loss and 0.06 ± 0.07 for drip loss. Parameter estimates for initial pH and shear force of the meat went to the boundary of parameter space and were not estimable. It was concluded that selection for NLW did not compromise any of the meat traits and that most quantitative meat traits were heritable and variable, making selection for improvement of these traits feasible. Additional research is indicated on the qualitative meat traits studied.
Small Ruminant Research; doi:10.1016/j.smallrumres.2021.106489
This study aimed to infer the causal effects of birth weight on growth curve traits as well as, assessment of causal relationships among the growth curve traits in Lori-Bakhtiari sheep using structural equation modeling. The body weight-age records were collected from birth to 390 days of age from 1995 to 2012 in Shooli Breeding Station of Lori-Bakhtiari sheep, Shahr-e Kord, Iran. Initially, five non-linear models including Brody, Logistic, Negative exponential, Gompertz and von Bertalanffy were fitted on 22,546 body weight-age records for determining the best model describing the growth curve. Among the tested non-linear growth models, Brody model showed the best goodness of fit. Then, data on growth curve traits of 3,168 lambs from 217 rams and 1,211 ewes were considered for genetic evaluation of growth curve traits including asymptotic weight (A), integration constant related to initial animal weight (b), and maturation rate (k).The causal effect of birth weight (BW) on growth curve traits under two models including standard multivariate model (SMM) and fully recursive model (FRM) were fitted via a Bayesian approach. The posterior means of heritability for the growth curve traits were similar under both SMM and FRM, while the posterior means of genetic correlations among the traits were statistically different under both SMM and FRM. Structural coefficients related to causal effects of BW on b, k and A, were statistically significant with values -0.19, 0.01and 12.58, respectively. Therefore, considering the causal effects of BW on growth curve traits is essential for accurate genetic analysis of growth curve traits of Lori-Bakhtiari sheep.
Small Ruminant Research; doi:10.1016/j.smallrumres.2021.106487
A meta-analysis was conducted to develop and evaluate new empirical predictive models for drinking water intake (DWI) of growing lambs. A large dataset containing 213 experimental diets from 47 experiments published in 44 peer-reviewed papers was built. Selected explanatory variables were grouped into animal (bodyweight initial (BWi); body weight final (BWf); average daily gain (ADG); feed conversion ratio (FCR); nitrogen intake (Nint), diet composition (dry matter; ash; crude protein (CP); neutral detergent fiber; forage), dry matter intake (DMI) and total digestible nutrient (TDN) and/or total digestible nutrient intake (TDNI) inputs. To develop predictive models, the dataset (peer-reviewed papers) was randomly divided into two subsets for statistical analyses. The first data subset was used to develop equations to predict DWI (27 peer-review papers; 28 experiments; 139 experimental diets), and the second data subset was used to assess the adequacy of the predictive models (17 peer-review papers; 19 experiments; 74 experimental diets). Ash was the main diet input affecting DWI in growing lambs, while FCR affected DWI more than ADG and Nint among the animal inputs. For growing lambs, the use of predictor variables associated with energy requirements improved the accuracy of the models when compared to those which used DMI. Among the developed models, the complete ones, which include diet and animal input, present better predictive quality. The use of the Diet + Animal Ib Model is recommended for the prediction of DWI in growing lambs.
Small Ruminant Research; doi:10.1016/j.smallrumres.2021.106485
The present study was undertaken to estimate (co)variance components and genetic parameters of important growth and wool traits in Harnali sheep using data records of 1862 lambs born to 144 sires and 591 dams for the period from 1998 to 2018. Six univariate animal models including or ignoring maternal genetic and permanent environmental effects were fitted to birth weight (BWT), weaning weight (WWT), 6 months weight (6WT), 12 months weight (YWT), first clip greasy fleece weight (FGFW) and annual greasy fleece weight (AGFW) and further compared using likelihood ratio test. It was observed that the model including direct additive genetic and maternal additive genetic effect without taking covariance between them into account was the most suitable for BWT and WWT. For remaining traits, only direct additive genetic effect model was found to be most appropriate. The estimates of heritability under the best model for BWT, WWT, 6WT, YWT, FGFW and AGFW were 0.23, 0.10, 0.18, 0.11, 0.08 and 0.31, respectively. The maternal influence accounted for 8% of variation for BWT and WWT which indicated importance of maternal effect during preweaning period. The genetic and phenotypic correlations of 6WT with other traits were positive and ranged medium to moderate. Therefore, it was concluded that medium genetic variability of 6WT and its potential ability for improving other traits should be exploited to achieve genetic improvement in Harnali sheep.
Small Ruminant Research; doi:10.1016/j.smallrumres.2021.106464
This study aimed to evaluate if a short-term nutritional supplementation has any stimulatory effects on liver function and metabolic status in sheep. The experiment was carried out using 30 Dorset×Han crossbred ewes (age, 9 ± 0.6 months; weight, 36.58 ± 2.56 kg) allocated into two treatments, the control group (AD group: DE 11.72 MJ/d; DP 79.71 g/d) and the nutritional supplementation group (HE group: DE18.75 MJ/d; DP 108.44 g/d), respectively. Experiment lasted 20 days, including 10 d for adaption. Blood samples of these ewes were collected to detect the concentrations of glucose, insulin, leptin, and cholesterol. Then, liver samples of these animals were collected to explore the genome-wide transcriptome analysis. Results showed that the weight gain was significantly increased in the nutritional supplementation group, compared with those in the control group (p = 1.27e-03). The concentrations of glucose, insulin, leptin, and cholesterol were also influenced, compared with the AD groups, higher glucose concentrations ranging from 0.10 to 1.11 mmol/L were observed in the HE groups. The concentrations of insulin and leptin varied over time and they were higher in HE groups. The cholesterol concentration was lower in the HE groups. Furthermore, 622 differentially expressed genes (DEGs) were identified between different treatments. Of these, 271 genes were down regulated while 351 genes were up regulated. qRT-PCR analysis of 10 randomly selected genes were consistent with the sequencing results. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways revealed these DEGs in HE group were significantly enriched in energy and lipid metabolism, such as cellular carbohydrate catabolic and metabolic process (DGKI, SOCS2, GHR, GHRHR, CSKMT), lipid metabolic and transport process (ALDH6A1, ABCA9, G0S2, PPARGC1) and monosaccharide metabolic process (PDK4, LPIN1, ABCA9, SLC45A3), etc. Additionally, we concluded an interaction network related to energy metabolism, which showed that a short-term nutritional supplementation in sheep may be associated with liver metabolism by PPAR signaling pathway, AMPK signaling and Insulin signaling pathway. Importantly, PDK4 and G0S2 may be core essential genes and play an important role in these pathways. All these results might be contributed to detect related genes associated with energy metabolism in the liver tissues of sheep. Overall, the findings presented here provide the first evidence for key candidate genes affecting liver function.
Small Ruminant Research, Volume 202; doi:10.1016/j.smallrumres.2021.106472
Considering the dominance and epistasis effects in the analysis can increase the accuracy of estimating breeding values. The objective of this study was to fit the best model for each average daily gain trait (average daily gain from birth to weaning (adgbwww), from birth to 3 months (adgbww3), from birth to 6 months (adgbww6), from weaning to 3 months (adgwww3), from 3 to 6 months (adgw3w6), from 6 to 9 months (adgw6w9), and from 9 to 12 months (adgw9w12)) and the estimation of the genetic parameters and variance components, especially non-additive genetic effects, in Adani goats. Analyses were carried out using the Bayesian method via the Gibbs sampler animal model by fitting 18 different models. With the best model, direct heritability estimates were 0.093, 0.250, 0.256, 0.084, 0.036, 0.048, and 0.151 for adgbwww, adgbww3, adgbww6, adgwww3, adgw3w6, adgw6w9 and adgw9w12 traits, respectively. Maternal genetic and maternal permanent environmental effects were significant only for adgbwww trait. Dominance and epistasis effects were significant almost for all traits and as a proportion of phenotypic variance was the range from 0.068 to 0.221 and 0.106 to 0.237, respectively. Adding dominance and epistasis effects to models reduced the error variance and the accuracy of estimating breeding values was increased. The accuracy of breeding values of these traits with the best models ranged from 0.456 to 0.674, 0.493 to 0.656, and 0.424 to 0.674 for all animals, 10 % of best males and 50 % of the best females, respectively. The result of the present study suggests that dominance and epistasis effect was important for average daily gain traits of Adani goats and should be included in evaluation models.
Small Ruminant Research; doi:10.1016/j.smallrumres.2021.106482
The analysis of stable isotopes applied to the lamb meat matrix is recognized as a technique of choice not only for geographical traceability but also for verifying the correspondence between the diet provided and the prescribed one. Indeed, a large amount of information is stored in animal tissues in terms of stable isotopes relative abundances of different elements. The purpose of this review is to critically analyze all the studies carried out on lambs, focusing in particular on the isotope ratios of carbon, nitrogen, sulfur, hydrogen and oxygen of different matrices, trying to define the different ranges of variability based on the origin and diet of the lambs. Carbon is certainly the most useful for identifying the animal diet while oxygen and hydrogen confirm their ability to geographically discriminate lambs. Overall, the results of statistical models validating isotope traceability systems can reach and exceed 90% of accuracy.
Small Ruminant Research, Volume 200; doi:10.1016/j.smallrumres.2021.106398
Globally, around 1.5 billion sheep and goats provide meat and milk on an annual basis and are important sources of nutrition as well as economic subsistence. The popularity of sheep and goat meat, along with milk, and related products occurs due to their unique nutritional properties, physicochemical composition, and sensory attributes while having species-specific flavours compared to other red meats and dairy products. The overall volatile flavour profile and sensory characteristics of the products derived from sheep and goats are key differentiators in the market. However, the flavour variation can lead to inconsistent consumer experiences. A complex relationship exists between factors such as breed, sex, and age along with nutrition which contribute to the overall flavour. Additionally, regional expectations of flavour can also influence consumers. The characteristic flavour associated with dairy products derived from sheep and goat, has a tremendous impact on the overall product quality and acceptability, distinct from that found with cow milk. This review focuses on the short branched chain fatty acids identified as relevant to the flavour associated with milk and meat from sheep and goats, the synthesis of these compounds as well as the pre- and post-gate factors which affect their accumulation in meat and milk. It will also present the pros and cons of classical and emerging analytical techniques used for their determination.
Small Ruminant Research, Volume 200; doi:10.1016/j.smallrumres.2021.106397
It was reasoned that, incorporating reproductive technologies and genomic selection in the current dairy goats breeding programme would generate higher response to selection compared to use of natural mating in the current conventional breeding programme. This premise was tested by deterministic simulation approach and compared to the current breeding programme where natural mating and conventional breeding programme is used in the tropics. Two breeding schemes with three breeding strategies were simulated. The first scheme was conventional breeding scheme (CS) which represented the current dairy goat-breeding programme in the tropics. An alternative scheme was genomic breeding scheme (GS). Each scheme was evaluated with three mating strategies. They include; conventional scheme using natural mating (CNM), AI-Liquid semen (CLS) and AI-Frozen semen (CFS), and genomic scheme using natural mating (GNM), AI-Liquid semen (GLS) and AI-Frozen semen (GFS) strategies, with 5% of the total population in the nucleus and 95 % in the commercial. The current study found that CLS and GLS were superior compared to CFS and GFS, and CNM and GNM strategies in terms of annual genetic gain, returns and profit per doe per year. The CLS realised additional Kenya Shillings (KES) 3.00 and 3.61, 151.31 and KES 46.72, 148.89 and 47.81, in genetic gain, returns and profitability compared to CNM and CFS, respectively. The CLS incurred low costs KES 23.38 compared to CFS with KES 24.47 but higher than CNM with KES 20.96. On the other hand, CFS strategy has generated additional returns KES 104.59 and profit KES 101.08 but lower by KES 0.61 in genetic gain compared to CNM strategy. Implementation of genomic scheme has generated additional improvement across the three mating strategies in all the parameters measured compared to the conventional scheme. The GS realised additional KES 11.54, 10.80 and 10.21 in genetic gain, KES 161.30, 183.48 and 175.90 returns, and 136.30, 158.48 and 150.90 profit in the GNM, GLS and GFS, respectively, compared to those realised in CNM, CLS and CFS. Genetic gain increased with increased nucleus population size up to 15 % and thereafter, it declines in both CS and GS schemes with optimal nucleus size ranging between 14 % and 16 %. In conclusion, the current study demonstrated that adoption of reproductive technologies such as AI would optimize response to selection in dairy goat breeding programs in the tropics. The response to selection in such breeding programmes could be maximized in combination with genomic selection.