Light microscopic observations of the ruminal papillae of cattle on diets with divergent forage to cereal ratios.

High levels of supplementation with cereal increases production rates in cattle but can increase incidence of disease, ranging from mild indigestion to acute ruminal acidosis and death. Therefore, there is motivation to determine biological markers which can be used to identify whether animals have been, or are being fed, sufficient or excessive cereals. This study aimed to describe light microscopic findings from animals being fed diverse dietary cereal proportions and to test the performance of a novel rumen epithelial scoring system. Rumen wall tissue samples were obtained from the abattoir from 195 cattle from 11 Scottish farms and processed for histological examination. Light microscopic examination was used to characterise ruminal epithelial response to dietary challenge. Secondary objectives included describing the distribution of immune-related cells in bovine ruminal epithelium and assessing the use of a modified Elastin Martius Scarlet Blue stain (EMSB) for histological examination of the rumen epithelium. Cells staining positive for cluster of differentiation 3 were distributed mainly in the lower layers of the stratum basale and were found in higher densities in animals offered lower cereal proportion diets. Cells staining positive for major histocompatibility complex class 2 (MHCII) were most common in perivascular locations and in the junction between the lower stratum basale and the propria-submucosa. The density of MHCII positive staining cells was higher in animals on lower cereal diets. The level of supplementation with cereal was also associated with the thickness of the stratum corneum (SCT) and stratum granulosum (SGT), the integrity of the stratum corneum and sloughing of cornified cells. There were no advantages in using EMSB stain over haematoxylin and eosin (H&E) in this scoring system. We concluded that a scoring system that included only SCT, SGT and a measure of the loss of appearance of intercellular space allowed differentiation of groups of animals according to the level of cereal supplementation.

Predicting feed intake using modelling based on feeding behaviour in finishing beef steers.

Current techniques for measuring feed intake in housed cattle are both expensive and time-consuming making them unsuitable for use on commercial farms. Estimates of individual animal intake are required for assessing production efficiency. The aim of this study was to predict individual animal intake using parameters that can be easily obtained on commercial farms including feeding behaviour, liveweight and age. In total, 80 steers were used, and each steer was allocated to one of two diets (40 per diet) which consisted of (g/kg; DM) forage to concentrate ratios of either 494:506 (MIXED) or 80:920 (CONC). Individual daily fresh weight intakes (FWI; kg/day) were recorded for each animal using 32 electronic feeders over a 56-day period, and individual DM intakes (DMI; kg/day) subsequently calculated. Individual feeding behaviour variables were calculated for each day of the measurement period from the electronic feeders and included: total number of visits to the feeder, total time spent at the feeder (TOTFEEDTIME), total time where feed was consumed (TIMEWITHFEED) and average length of time during each visit to the feeder. These feeding behaviour variables were chosen due to ease of obtaining from accelerometers. Four modelling techniques to predict individual animal intake were examined, based on (i) individual animal TOTFEEDTIME relative expressed as a proportion of the dietary group (GRP) and total GRP intake, (ii) multiple linear regression (REG) (iii) random forests (RF) and (iv) support vector regressor (SVR). Each model was used to predict CONC and MIXED diets separately, giving eight prediction models, (i) GRP_CONC, (ii) GRP_MIXED, (iii) REG_CONC, (iv) REG_MIXED, (v) RF_CONC, (vi) RF_MIXED, (vii) SVR_CONC and (viii) SVR_MIXED. Each model was tested on FWI and DMI. Model performance was assessed using repeated measures correlations (R2_RM) to capture the repeated nature of daily intakes compared with standard R2, RMSE and mean absolute error (MAE). REG, RF and SVR models predicted FWI with R2_RM = 0.1-0.36, RMSE = 1.51-2.96 kg and MAE = 1.19-2.49 kg, and DMI with R2_RM = 0.13-0.19, RMSE = 1.15-1.61 kg and MAE = 0.9-1.28 kg. The GRP models predicted FWI with R2_RM = 0.42-0.49, RMSE = 2.76-3.88 kg and MAE = 2.46-3.47 kg, and DMI with R2_RM = 0.32-0.44, RMSE = 0.32-0.44 kg, MAE = 1.55-2.22 kg. Whilst more simplistic GRP models showed higher R2_RM than regression and machine learning techniques, these models had larger errors, likely due to individual feeding patterns not being captured. Although regression and machine learning techniques produced lower errors associated with individual intakes, overall precision of prediction was too low for practical use.

Using animal-mounted sensor technology and machine learning to predict time-to-calving in beef and dairy cows.

Worldwide, there is a trend towards increased herd sizes, and the animal-to-stockman ratio is increasing within the beef and dairy sectors; thus, the time available to monitoring individual animals is reducing. The behaviour of cows is known to change in the hours prior to parturition, for example, less time ruminating and eating and increased activity level and tail-raise events. These behaviours can be monitored non-invasively using animal-mounted sensors. Thus, behavioural traits are ideal variables for the prediction of calving. This study explored the potential of two sensor technologies for their capabilities in predicting when calf expulsion should be expected. Two trials were conducted at separate locations: (i) beef cows (n = 144) and (ii) dairy cows (n = 110). Two sensors were deployed on each cow: (1) Afimilk Silent Herdsman (SHM) collars monitoring time spent ruminating (RUM), eating (EAT) and the relative activity level (ACT) of the cow, and (2) tail-mounted Axivity accelerometers to detect tail-raise events (TAIL). The exact time the calf was expelled from the cow was determined by viewing closed-circuit television camera footage. Machine learning random forest algorithms were developed to predict when calf expulsion should be expected using single-sensor variables and by integrating multiple-sensor data-streams. The performance of the models was tested using the Matthew's correlation coefficient (MCC), the area under the curve, and the sensitivity and specificity of predictions. The TAIL model was slightly better at predicting calving within a 5-h window for beef cows (MCC = 0.31) than for dairy cows (MCC = 0.29). The TAIL + RUM + EAT models were equally as good at predicting calving within a 5-h window for beef and dairy cows (MCC = 0.32 for both models). Combining data-streams from SHM and tail sensors did not substantially improve model performance over tail sensors alone; therefore, hour-by-hour algorithms for the prediction of time of calf expulsion were developed using tail sensor data. Optimal classification occurred at 2 h prior to calving for both beef (MCC = 0.29) and dairy cows (MCC = 0.25). This study showed that tail sensors alone are adequate for the prediction of parturition and that the optimal time for prediction is 2 h before expulsion of the calf.

Postmortem observations on rumen wall histology and gene expression and ruminal and caecal content of beef cattle fattened on barley-based rations.

Sub-acute ruminal acidosis (SARA) can reduce the production efficiency and impair the welfare of cattle, potentially in all production systems. The aim of this study was to characterise measurable postmortem observations from divergently managed intensive beef finishing farms with high rates of concentrate feeding. At the time of slaughter, we obtained samples from 19 to 20 animals on each of 6 beef finishing units (119 animals in total) with diverse feeding practices, which had been subjectively classified as being high risk (three farms) or low risk (three farms) for SARA on the basis of the proportions of barley, silage and straw in the ration. We measured the concentrations of histamine, lipopolysaccharide (LPS), lactate and other short-chain fatty acids (SCFAs) in ruminal fluid, LPS and SCFA in caecal fluid. We also took samples of the ventral blind sac of the rumen for histopathology, immunohistopathology and gene expression. Subjective assessments were made of the presence of lesions on the ruminal wall, the colour of the lining of the ruminal wall and the shape of the ruminal papillae. Almost all variables differed significantly and substantially among farms. Very few pathological changes were detected in any of the rumens examined. The animals on the high-risk diets had lower concentrations of SCFA and higher concentrations of lactate and LPS in the ruminal fluid. Higher LPS concentrations were found in the caecum than the rumen but were not related to the risk status of the farm. The diameters of the stratum granulosum, stratum corneum and of the vasculature of the papillae, and the expression of the gene TLR4 in the ruminal epithelium were all increased on the high-risk farms. The expression of IFN-γ and IL-1ß and the counts of cluster of differentiation 3 positive and major histocompatibility complex class two positive cells were lower on the high-risk farms. High among-farm variation and the unbalanced design inherent in this type of study in the field prevented confident assignment of variation in the dependent variables to individual dietary components; however, the CP percentage of the total mixed ration DM was the factor that was most consistently associated with the variables of interest. Despite the strong effect of farm on the measured variables, there was wide inter-animal variation.

Programmable fiber/integrated-optics bipolar tap.

A programmable bipolar tap implementation is described. The proposed scheme utilizes fiber and integrated-optics technology in conjunction with twos complement number representation and digital multiplication by an analog convolution algorithm. Simple experimental verification of the scheme is presented.

Fiber-optic bipolar tap implementation using an incoherent optical source.

A fiber-optic bipolar tap implementation is described. The proposed scheme utilizes 2's complement-number representation and digital multiplication by an analog convolution algorithm. Simple experimental verification of the scheme is presented. The addition of programmability to the taps results in the realization of a fast, flexible processor for manipulating binary quantities.

Fiber-optic matrix multiplier using a two-dimensional systolic-array architecture.

An optical matrix multiplier based on a two-dimensional systolic-array architecture is described, exploiting the parallelism offered by optical methods. Experimental verification of multiplier performance is presented. A technique for multiple matrix multiplications is suggested.

Perturbation analysis for the design of an optically controlled fiber-optic directional coupler.

A simple analysis is presented for calculating the change in the effective index of a guided mode in an optical fiber with reduced cladding surrounded by an optically nonlinear medium. Using first-order perturbation theory, the optical power required to alter the phase-matched condition in a fiber directional coupler incorporating a nonlinear medium is therefore calculated. This may then be applied to an optically controlled switch, the output of which may be transferred from one port to another by application of a high-intensity pulse. This method may be applied to other fiber components, for example, fiber gratings and polarizers.