Animal Production Science最新文献

Delaying sowing date of maize allows producers to achieve stabilised yield. Delays in the sowing date generate changes in the grain structure, which may affect the ruminal degradability of the maize starch.

The objective of this study was to evaluate the effects of maize sowing date on ruminal starch degradability, and how it is related with grain physical characteristics and source:sink ratio during the grain-filling period.

To study the effects of maize sowing date on grain physical characteristics and on starch in situ effective degradability (ED; 6%/h passage rate from the rumen), eight treatments were defined on the basis of eight different sowing dates in Argentina of a commercial semi-dentate maize hybrid (Dekalb 7210 VT3P), as follows: Treatment 1 (13 October), Treatments 2, 3, and 4 (4, 17 and 26 November respectively), Treatments 5, 6 and 7 (3, 15 and 28 December, respectively) and Treatment 8 (5 January). For each sowing date, three plots of maize were sown in a complete randomised-block design and harvested at grain physiological maturity.

Starch ED of ground (2.0-mm) grains ranged from 631 to 801 g/kg and showed a ‘J’-shape response, being lower for the sowing dates from 17 November to 3 December and highest on the sowing date of 5 January. Grain density increased until the sowing date of 17 November, and then decreased. Grain vitreousness and hardness were initially not affected, but started to decline after the sowing date of 17 November. Grain test weight was not affected until the sowing date of 15 December, when it started to decline. The source:sink ratio during the grain-filling period decreased as the sowing date was delayed. Effective starch degradability was negatively correlated with the physical characteristics evaluated and the source:sink ratio.

Delaying sowing date affected the maize source:sink ratio during the grain-filling period; this was associated with changes in grain physical characteristics and with an increase in ruminal starch degradability.

Delaying sowing date increases dry matter (DM) and starch effective degradability, and therefore could affect cattle weight gain and feed conversion efficiency.

The strategic management of pigs raised in an intensive system has been conducted, in general, according to the average weight of piglets after weaning. Different models using morphometric parameters to predict the probability of any of the three weight classes (light, medium, and heavy) occurring post-weaning present themselves as an alternative to help the producer conduct these strategic managements.

This study aimed to evaluate the development of suckling piglets by using morphometric parameters.

A thousand simple samples were extracted at random from 268 piglets for the training data, which represent 70% of the original data set (384 piglets). The remaining 116 piglets (test data) were excluded from the analysis so as to verify the performance of the prediction (probability of each weight class to occur). Afterwards, the results were compared with the real weight class of the piglet at weaning. The variables in this research were birth weight (PWB), lactation length (Lac), and morphometric parameters of body length (BL), heart girth (HG), body mass index (BMI), ponderal index (PI), surface:mass ratio (SM), and parity order (PO). Different models were developed to predict the probability of any of the three weight classes (light, <3.967 kg; medium, 3.967–5.095 kg; and heavy, >5.095 kg) occurring at piglet weaning on the basis of their parameters 1 day postpartum. An adjustment of the ordinal regression was proposed to predict the weight classifications.

The model with a significant effect of the Lac variables was selected.

One day after birth, light-weight and heavy-weight piglets, regardless of their morphometry, have a high likelihood of remaining in the same weight class at weaning. However, this does not apply to medium-sized piglets with diverse morphometry.

Transport of cattle can be stressful and may lead to increased body temperature. It is necessary to quantify the effect of transport on body temperature so that informed management decisions can be made.

This study aimed to determine the effects of a 5.5 h, 430 km road transport journey on body temperature (T_B) of feedlot steers.

Body temperature was obtained at 30 min intervals. All cattle were weighed and randomly allocated to a truck pen prior to transport. Cattle were transported on a single B-double truck, with three upper-deck and three lower-deck compartments. At 0630 hours, cattle were walked from their pens (25 m), weighed and loaded onto the truck. Loading was completed by 1030 hours.

During the weighing and loading process prior to transport, mean T_B increased from 39.37 ± 0.11°C to 40.21 ± 0.11°C. Immediately following loading, mean T_B increased. The T_B of cattle on the upper deck was 40.96 ± 0.08°C and on the lower deck 40.89 ± 0.08°C (P = 0.6299). During the first 3 h of the journey, the T_B of lower-deck cattle decreased by 1.14°C (P < 0.01), compared with a 0.83°C reduction in cattle on the upper deck. Over the duration of the journey, which took 1 h longer than expected, the mean T_B of the cattle on the upper deck (40.47 ± 0.11°C) was greater (P < 0.0001) than that on the lower deck (40.04 ± 0.12°C). One hour after unloading at the abattoir, pooled T_B was 40.26 ± 0.12°C. Minimum T_B (38.87 ± 0.04°C) occurred at 10.5 h after unloading.

The results from this study highlight that increases in T_B were more associated with cattle handling and loading events, rather than transport, under these environmental conditions. Understanding the magnitude of this increase will help managers decide on pre- and post- transport management of cattle.

Cattle handling and loading for transport may lead to an increase in T_B, which can remain elevated for a number of hours. However, it is unclear what the impact of hotter climatic conditions would have on trailer microclimate and, as such, T_B regulation during road transport.

China has a vast area across many temperature zones and a variety of cattle breeds. These cattle resources are ideal models to research their adaptability to the environment. The KRT38 gene is an acidic protein, and its coding product can be used as a component of hair production.

The objective of this study was to investigate the diversity of the KRT38 gene in Chinese local cattle and the association of different genotypes with mean temperature, relative humidity and temperature humidity index.

A missense mutation g.41650738 A > G in the KRT38 gene was screened from the database of bovine genomic variation (BGVD) and was genotyped in a total of 246 samples from 15 local cattle breeds in China by polymerase chain reaction amplification and sequencing. Finally, the correlation between the locus and the three climatic factors was analysed.

We successfully obtained the frequency of this single-nucelotide polymorphism in three groups of cattle in northern, central and southern China. The frequency of allele A gradually declined from north to south, whereas the frequency of allele G showed the opposite trend with a clear geographic distribution.

Our results indicate that KRT38 variation in Chinese indigenous cattle might be linked to heat tolerance.

Our analysis may assist in determining the importance of the variation as a genetic signal for heat tolerance in cattle reproduction and genetics.

Improving cattle feed efficiency would reduce feed costs and increase herd profitability. Residual feed intake (RFI) is commonly used to rank cattle for feed efficiency, with low-RFI animals being more efficient than high-RFI animals. However, RFI classification merits further investigation because observed differences in heat energy (HE) production between low- and high-RFI cattle may be related to heat associated with differences in dry-matter intake (DMI) rather than maintenance-energy requirements.

To determine energy partitioning of beef heifers with low and high residual feed intake.

Angus crossbred heifers (n = 60) were fed a grower diet (metabolisable energy (ME) = 2.17 Mcal/kg DM) for 70 days. Feed intake was recorded daily using the GrowSafe system, and bodyweight (BW) was recorded every 14 days. Residual feed intake was calculated as the residual from the regression of DMI on mid-test BW^0.75 and average daily gain (ADG) (R² = 0.31). Low-RFI (n = 8) and high-RFI (n = 8) heifers were selected for a metabolism experiment to determine energy partitioning at three feed-intake levels, namely, ad libitum intake, and 1.0× and 0.5× expected maintenance-energy requirement. Apparent nutrient digestibility was determined using indigestible neutral detergent fibre (iNDF) as an internal marker. The sulfur hexafluoride (SF₆) tracer and oxygen-pulse techniques determined methane emissions and heat production respectively. Metabolisable energy required for maintenance (MEm) and fasting heat production (H_eE) were then calculated from the regression of log HP on ME intake (MEI). Efficiencies of ME used for maintenance and growth were calculated from H_eE, MEm, and retained energy at ad libitum intake.

Residual feed intake was strongly correlated with DMI (0.83). Low-RFI heifers consumed 31% less (P = 0.01) feed than high-RFI heifers during the performance experiment. Heifers with low RFI had greater MEm, but similar efficiencies of ME use for maintenance and gain as did high RFI heifers.

These data indicated that selection based on RFI may not lead to improved energy efficiency in growing heifers.

The results of this study indicated that low-RFI cattle may not have lower maintenance-energy requirements or differences in efficiencies of ME use than do high-RFI cattle.

Feedlot entry can be a period of stress for cattle due to transportation, altered diets and other influences. Stress can suppress host defence mechanisms. Innate immune stimulants, such as mycobacterial cell-wall fractions, attract attention for the primary objective of enhancing non-specific immune resistance of cattle against microbial diseases during periods of stress-induced susceptibility. These stimulants are also recognised for their capacity to modify responses of the adaptive immune system to vaccines.

This study aims to evaluate the potential for mycobacterial cell-wall fractions in Amplimune® to modify adaptive immune responses to the commercial vaccines Rhinogard® (modified live bovine alphaherpesvirus-1 (BoHV-1)) and Bovilis MH + IBR® (inactivated Mannheimia haemolytica and BoHV-1) in yearling cattle during simulated feedlot induction.

Fifty-four mixed-sex Angus yearling cattle were transported for 6 h on Day −1 and on Day 0. The cattle were assigned to the following six treatment groups (n = 9/group): Rhinogard plus 2 mL Amplimune, Rhinogard plus 5 mL Amplimune, Bovilis MH + IBR plus 2 mL Amplimune, Bovilis MH + IBR plus 5 mL Amplimune, Rhinogard plus 5 mL saline, and Bovilis MH + IBR plus 5 mL saline. Blood and nasal secretions were sampled at various time points following treatment and antigen-specific antibody (immunoglobulin G) responses to components of the vaccines were assessed. Interferon-γ production by peripheral blood mononuclear cells in response to BoHV-1, Concanavalin A or media only were assessed.

No adverse clinical reactions were observed to administration of Amplimune and vaccines. A systemic antibody response to vaccination was observed for the Bovilis MH + IBR vaccine. Vaccine-specific antibody and cytokine responses were not modified by Amplimune.

Amplimune can be administered at the same time as Rhinogard or Bovilis MH + IBR vaccines, without undesirable effects on specific immune responses to vaccination.

The primary interest in using Amplimune is to potentiate non-specific immune defences as an alternative to antibiotics for the prevention and/or treatment of microbial diseases such as bovine respiratory disease in production animals. In view of its adjuvant-like activities, administration of Amplimune might also confer beneficial or detrimental effects on antigen-specific responses of the adaptive immune system to contemporaneous vaccination.

As evaluation of carcass components is costly and time consuming, models for prediction of broiler carcass components are useful.

The aim was to investigate the feasibility of machine learning methods in the prediction of carcass components from measurements on live birds during the rearing period.

Three machine learning methods, including regression tree, random forest and gradient-boosting trees, were applied to predict carcass yields, and benchmarked against classical linear regression. Two scenarios were defined for prediction. In the first scenario, carcass yields were predicted by live bodyweight, shank length and shank diameter features, recorded at 2, 3 and 4 weeks of age. In the second scenario, predictor features recorded at 5, 6 and 7 weeks of age were used. The two scenarios were reanalysed by including effective single-nucleotide polymorphisms associated with bodyweight, shank length and shank diameter as new predictor features.

The correlation coefficient between predicted and observed values for predicting weight of carcass traits ranged from 0.50 for wing to 0.59 for thigh in the first scenario, and from 0.63 for wing to 0.74 for carcass in the second scenario. These predictions for the percentage of carcass components ranged from 0.30 for wing to 0.39 for carcass and breast in the first scenario, and from 0.34 for thigh to 0.43 for carcass in the second scenario when random forest was used.

Predictive accuracy in the first scenario was lower than in the second scenario for all prediction methods. Including single-nucleotide polymorphisms as predictor features in either scenario did not increase the accuracy of the prediction.

In general, random forest had the best performance among machine learning methods, and classical linear regression in two scenarios, suggesting that it may be considered as an alternative to conventional linear models for prediction of carcass traits in broiler chickens.

Gir is a tropically adapted breed of Bos taurus indicus cattle that has been intensively selected for milk production in Brazil. Selection programs also consider body-conformation traits because these have been associated with health, welfare, and cow longevity, thus affecting productivity.

This study focused on Gir cattle to estimate genetic and phenotypic parameters for body-conformation traits, as well as their correlations with milk production traits.

Body-conformation traits were classified as ‘frame’, ‘foot and leg’, or ‘mammary system’ traits. The dataset contained 1105 cows recorded with body-conformation traits and 38 996 records of 305-day cumulative milk yield, from 24 489 Gir cows. The pedigree file included 38 571 animals, of which 1593 were genotyped using six different single-nucleotide polymorphism panels. After genotyping imputation, and quality control, 42 105 polymorphisms were available for analyses. Univariate and bivariate animal models, using Bayesian approach via the Gibbs sampling algorithm, were used to estimate genetic parameters, benefiting from both genotypes and pedigree data.

The heritabilities for body-conformation traits ranged from a low of 0.08 ± 0.04 to a medium value of 0.35 ± 0.07, and the heritability for milk production was 0.23 ± 0.01. We identified unfavourable genetic correlations between milk yield and udder depth (0.63 ± 0.11) as well as body height (0.31 ± 0.13). In contrast, there was a favourable genetic correlation between milk yield and rear udder width (0.61 ± 0.14).

The heritability estimates confirmed the possibility of selecting animals for milk yield and body conformation traits related to the frame and mammary system categories. Based on the estimated genetic correlations, considerable importance should be given to the emphasis on selection for increased milk yield, because in the long term, this may promote undesirable changes in some type traits as body height and udder depth.

This information is relevant to selective breeding of Gir to enhance tropical milk production.

Heat stress is a major environmental factor negatively affecting animal health and production efficiency of the sow, and causes significant economic losses to the global pig industry. Researchers have developed various thermal indices with different characteristics for assessing the level of heat stress in pigs, including the temperature–humidity index (THI), black globe–humidity index (BGHI), effective temperature (ET), equivalent temperature index of sows (ETIS), and enthalpy (H), among others.

The aim of this study was to evaluate the effect of heat stress on reproductive performance by using different thermal indices based on environmental variables in a temperate climate and to compare the goodness-of-fit among them.

In total, 2951 sow reproductive records were analysed for a Puebla farm in the northern hemisphere.

The overall means for pregnancy, farrowing, and abortion rates over the period from January to December 2020 were 83.1%, 80.67%, and 5.2%, whereas temperature, relative humidity, and air velocity were 24.3°C, 63.0%, and 3.7 m/s respectively. The highest rates of pregnancy and farrowing over the study period were observed in March, while the abortion rate was highest in December. However, the mean daily temperatures exceeded 25°C between March and June, being higher the upper limit of the thermoneutral zone for sows. Many thermal indices have been used to estimate the level of heat stress in pigs, such as the THI, BGHI, ET, and ETIS. We used 11 thermal indices to measure the degree of heat stress affecting fertility traits of animals. Pregnancy and farrowing rates were highest for THI2 and THI6 values, reflecting moderate stress at pregnancy and farrowing periods. Statistically significant differences were found between the THI2, THI4, THI6, and ET values and the pregnancy, farrowing, and abortion rates (P < 0.05).

Our results showed that the THI2 performs better for evaluating the level of heat stress in sows than do other thermal-comfort indices such as the THI4, THI6, and ET.

These results may be useful for accurate assessment of heat stress to mitigate its effects and avoid significant economic losses in sows in temperate climates.