Metagenomic analysis of rumen microbial population in dairy heifers fed a high grain diet supplemented with dicarboxylic acids or polyphenols.

BACKGROUND: The aim of this study was to investigate the effects of two feed supplements on rumen bacterial communities of heifers fed a high grain diet. Six Holstein-Friesian heifers received one of the following dietary treatments according to a Latin square design: no supplement (control, C), 60 g/day of fumarate-malate (organic acid, O) and 100 g/day of polyphenol-essential oil (P). Rumen fluid was analyzed to assess the microbial population using Illumina sequencing and quantitative real time PCR. RESULTS: The P treatment had the highest number of observed species (P < 0.10), Chao1 index (P < 0.05), abundance based coverage estimated (ACE) (P < 0.05), and Fisher's alpha diversity (P < 0.10). The O treatment had intermediate values between C and P treatments with the exception of the Chao1 index. The PCoA with unweighted Unifrac distance showed a separation among dietary treatments (P = 0.09), above all between the C and P (P = 0.05). The O and P treatments showed a significant increase of the family Christenenellaceae and a decline of Prevotella brevis compared to C. Additionally, the P treatment enhanced the abundance of many taxa belonging to Bacteroidetes, Firmicutes and Tenericutes phyla due to a potential antimicrobial activity of flavonoids that increased competition among bacteria. CONCLUSIONS: Organic acid and polyphenols significantly modified rumen bacterial populations during high-grain feeding in dairy heifers. In particular the polyphenol treatment increased the richness and diversity of rumen microbiota, which are usually high in conditions of physiological rumen pH and rumen function.

Use of dicarboxylic acids and polyphenols to attenuate reticular pH drop and acute phase response in dairy heifers fed a high grain diet.

BACKGROUND: The aim of this study was to determine the ability of two feed additives, a fumarate-malate (FM) and a polyphenol-essential oil mixture (PM), in attenuating the drop of ruminal pH and the metabolic and immune response resulting from an excessively high grain diet. Six heifers were used in a 3 × 3 Latin square experiment and fed a low starch (LS) diet for 14 d, followed by a high starch (HS) diet for 8 d (NDF 33.6%, starch 30.0% DM). In the last 5 days of each period, barley meal was added to decrease rumen pH. During HS feeding all animals were randomly assigned to one of the following three dietary treatments: no supplement/control (CT), a daily dose of 60 g/d of FM, or 100 g/d of PM. Reticular pH was continuously recorded using wireless boluses. On d 21 of each period, rumen fluid was collected by rumenocentesis (1400 h), together with blood (0800 h) and fecal samples (0800, 1400, and 2100 h). RESULTS: The correlation coefficient of pH values obtained using the boluses and rumenocentesis was 0.83. Compared with CT and PM, the FM treatment led to a lower DMI. Nadir pH was lowest during CT (5.40, 5.69, and 5.62 for CT, FM and PM, respectively), confirming the effectiveness of both supplements in reducing the pH drop caused by high grain feeding. This result was confirmed by the highest average time spent daily below 5.6 pH (199, 16 and 18 min/d) and by the highest acetate to propionate ratio of the CT fed heifers. The PM decreased the concentrations of neutrophils (2.9, 3.2, and 2.8 10(9)/L) and acute phase proteins: SAA (37.1, 28.6 and 20.1 µg/mL), LBP (4.1, 3.8, and 2.9 µg/mL), and Hp (675, 695 and 601 µg/mL). Free lipopolysaccharides (LPS) were detected in blood and feces, but their concentrations were not affected by treatments, as the remaining blood variables. CONCLUSIONS: Data suggest that both additives could be useful in attenuating the effects of excessive grain feeding on rumen pH, but the PM supplement was more effective than FM in reducing the inflammatory response compared to CT.

Effect of induced ruminal acidosis on blood variables in heifers.

BACKGROUND: Ruminal acidosis is responsible for the onset of different pathologies in dairy and feedlot cattle, but there are major difficulties in the diagnosis. This study modelled the data obtained from various blood variables to identify those that could indicate the severity of ruminal acidosis. Six heifers were fed three experimental rations throughout three periods. The diets were characterised by different starch levels: high starch (HS), medium starch (MS) and low starch, as the control diet (CT). Ruminal pH values were continuously measured using wireless sensors and compared with pH measurements obtained by rumenocentesis. Blood samples were analysed for complete blood count, biochemical profile, venous blood gas, blood lipopolysaccharide (LPS) and LPS-binding proteins (LBP). RESULTS: The regression coefficient comparing the ruminal pH values, obtained using the two methods, was 0.56 (P = 0.040). Feeding the CT, MS and HS led to differences in the time spent below the 5.8, 5.5 and 5.0 pH thresholds and in several variables, including dry matter intake (7.7 vs. 6.9 vs. 5.1 kg/d; P = 0.002), ruminal nadir pH (5.69 vs. 5.47 vs. 5.44; P = 0.042), mean ruminal pH (6.50 vs. 6.34 vs. 6.31; P = 0.012), haemoglobin level (11.1 vs. 10.9 vs. 11.4 g/dL; P = 0.010), platelet count (506 vs. 481 vs. 601; P = 0.008), HCO3(-) (31.8 vs. 31.3 vs. 30.6 mmol/L; P = 0.071) and LBP (5.9 vs. 9.5 vs. 10.5 µg/mL; P < 0.001). A canonical discriminant analysis (CDA) was used to classify the animals into four ruminal pH classes (normal, risk of acidosis, subacute ruminal acidosis and acute ruminal acidosis) using haemoglobin, mean platelet volume, ß-hydroxybutyrate, glucose and reduced haemoglobin. CONCLUSIONS: Although additional studies are necessary to confirm the reliability of these discriminant functions, the use of plasma variables in a multifactorial model appeared to be useful for the evaluation of ruminal acidosis severity.

Herd Level Yield Gap Analysis in a Local Scale Dairy Farming System: A Practical Approach to Discriminate between Nutritional and Other Constraining Factors.

This study performed a yield gap analysis to help farmers understand whether their constraints were mainly due to nutritional factors or management and health issues. Twenty-nine farms were periodically evaluated. Milk yield (MY), dry matter intake (DMI), total mixed ration (TMR) composition and homogeneity index (HI), TMR digestibility, income over feed cost (IOFC), and MY summer-winter ratio (SWR) were collected. Farms were divided and compared according to the average annual MY: Low (L), Medium (M) and High (H), characterised by <31.1, 31.1-36.7 and >36.7 kg/head/day. An ANOVA mixed model and a stepwise regression to assess the relationship between nutritional variables and MY were run. H farms showed higher IOFC (p < 0.001), DMI (p = 0.006), DDM (p < 0.001), digestible crude protein (DCP, p = 0.019), HI (p = 0.09), SWR (p = 0.041) and lower HI coefficient of variation (p = 0.04). The conversion of DDM into milk was higher in H and M farms. Stepwise regression for MY selected DDM and CP (R2 = 0.716, p < 0.05). M farms were mainly constrained by nutritional factors, whereas L farms were also affected by other factors such as those related to management and health.

Uncovering Patterns in Dairy Cow Behaviour: A Deep Learning Approach with Tri-Axial Accelerometer Data.

The accurate detection of behavioural changes represents a promising method of detecting the early onset of disease in dairy cows. This study assessed the performance of deep learning (DL) in classifying dairy cows' behaviour from accelerometry data acquired by single sensors on the cows' left flanks and compared the results with those obtained through classical machine learning (ML) from the same raw data. Twelve cows with a tri-axial accelerometer were observed for 136 ± 29 min each to detect five main behaviours: standing still, moving, feeding, ruminating and resting. For each 8 s time interval, 15 metrics were calculated, obtaining a dataset of 211,720 observation units and 15 columns. The entire dataset was randomly split into training (80%) and testing (20%) datasets. The DL accuracy, precision and sensitivity/recall were calculated and compared with the performance of classical ML models. The best predictive model was an 8-layer convolutional neural network (CNN) with an overall accuracy and F1 score equal to 0.96. The precision, sensitivity/recall and F1 score of single behaviours had the following ranges: 0.93-0.99. The CNN outperformed all the classical ML algorithms. The CNN used to monitor the cows' conditions showed an overall high performance in successfully predicting multiple behaviours using a single accelerometer.

Assessment of the Effectiveness of a Portable NIRS Instrument in Controlling the Mixer Wagon Tuning and Ration Management.

The adoption of the mixer wagon and total mixed ration aimed to decrease dysmetabolic diseases and improve feed efficiency in dairy cows. Differences between theoretical and eaten diets are imputable to errors in diet preparation or cow feed sorting. We proposed a method to measure the chemical composition and particle size distribution of the ration and determined its peNDF content through a portable Near Infra-Red spectrophotometer that allowed the calculation of two indexes: the homogeneity and the sorting indexes. In a cohort of 19 Italian Holstein breeding farms, we studied the correlation of these indexes with the mixer wagon settings. Determination coefficients in the validation (Rv2) for dry matter, crude protein, aNDF, and starch were 0.91, 0.54, 0.86, and 0.67, respectively. The ration fractions (%, w/w of wet weight) retained by the 3.8 and 1.8 mm sieves, and the bottom showed Rv2 of 0.46, 0.49, and 0.53, respectively. The homogeneity index regressed negatively with the mixer wagon load fullness (R2 = 0.374). The homogeneity-binary classification showed an odds ratio of 1.72 for dry matter and 0.39 for aNDF (p < 0.05). The sorting-binary classification showed an odds ratio of 2.54 for aNDF (p < 0.05). The studied farms showed low peNDF values (median = 17.9%).

Machine Learning to Detect Posture and Behavior in Dairy Cows: Information from an Accelerometer on the Animal's Left Flank.

The aim of the present study was to develop a model to identify posture and behavior from data collected by a triaxial accelerometer located on the left flank of dairy cows and evaluate its accuracy and precision. Twelve Italian Red-and-White lactating cows were equipped with an accelerometer and observed on average for 136 ± 29 min per cow by two trained operators as a reference. The acceleration data were grouped in time windows of 8 s overlapping by 33.0%, for a total of 35,133 rows. For each row, 32 different features were extracted and used by machine learning algorithms for the classification of posture and behavior. To build up a predictive model, the dataset was split in training and testing datasets, characterized by 75.0 and 25.0% of the observations, respectively. Four algorithms were tested: Random Forest, K Nearest Neighbors, Extreme Boosting Algorithm (XGB), and Support Vector Machine. The XGB model showed the best accuracy (0.99) and Cohen's kappa (0.99) in predicting posture, whereas the Random Forest model had the highest overall accuracy in predicting behaviors (0.76), showing a balanced accuracy from 0.96 for resting to 0.77 for moving. Overall, very accurate detection of the posture and resting behavior were achieved.

Effectiveness of Stocking Density Reduction on Mitigating Lameness in a Charolais Finishing Beef Cattle Farm.

This study aimed at assessing whether a reduction in stocking density (SKD) would mitigate lameness and positively affect the performance and health of Charolais bulls in an Italian commercial farm. Bulls were distributed in groups of 10 or 8 animals/pen for high (HD) or low density (LD) corresponding to an individual space of 3.5 or 4.7 m2, respectively. Bulls were fitted with collars that measured rumination time and activity. Three 8-h observational sessions were conducted to record behaviors. Data about health conditions were collected daily. No differences were found in the animals' performance. However, performance results might have been impaired by the culling rate experienced during the trial, which prevented from keeping a consistent SKD. Behaviors did not differ between groups, except for rumination time, which was higher for LD bulls during the third observation (p < 0.05). However, rumination time, recorded by collars, did not vary among treatments. There were no differences in the percentage of sick or lame bulls, but the percentage of animals treated repeatedly due to relapse was higher for the HD group (p < 0.05). It was concluded that a larger space allowance could improve the health of bulls kept on fully slatted floors.

Research Note: Effect of chicken genotype and white striping-wooden breast condition on breast meat proximate composition and amino acid profile.

The present experiment compared the proximate composition, the amino acid content, and profile of the breast meat of a commercial broiler hybrid (Hybrid-Normal) vs. a broiler hybrid affected by the simultaneous presence of white striping (WS) and wooden breast (WB) myopathies (Hybrid-WSWB) vs. the Italian purebred Polverara chicken (Polverara). To this purpose, a total of n = 30 breast meat cuts from male chickens/group were subjected to meat quality evaluations. Chickens were slaughtered at their commercial age. The meat of the Polverara breed showed the highest protein (P < 0.0001) and the lowest lipids (P < 0.0001) contents, whereas that of the Hybrid-WSWB broiler chickens had the lowest protein and ash (P < 0.0001) contents and the highest (P < 0.0001) amount of fat. Meat of Hybrid-Normal chickens displayed intermediate values. Polverara meat was the richest in most amino acids (g/100 g meat), whereas Hybrid-WSWB one had the lowest content (P < 0.0001). Taurine was not detected in the meat of the Polverara chicken. The meat of Hybrid-Normal chickens was the richest in valine and taurine amino acids (P < 0.0001). Results on the amino acids proportions (% of total amino acids) highlighted that lysine, arginine, leucine, glutamic acid, aspartic acid, alanine, and serine were the most representative essential and nonessential amino acids, respectively, in all 3 meat-types chickens. The study confirmed that WS and WB myopathies negatively affect the meat proximate composition and the amino acid content. The meat of the Polverara breed displayed a remarkable meat quality including a high protein content of very good quality. This may represent a tool to promote its meat among consumers and help the survival of this endangered breed. Furthermore, research efforts should be conducted to understand why taurine was absent in the breast meat of Polverara chicken.

The Effects of Decreasing Dietary Crude Protein on the Growth Performance, Feed Efficiency and Meat Quality of Finishing Charolais Bulls.

This study aimed to evaluate the effect of decreasing dietary crude protein (CP) on the performance of finishing Charolais bulls in the Italian rearing system. Animals were fed two diets, differing only in the CP level (low protein (LP), 13.5% CP versus control (CON), 15.0% CP). Dry matter (DM) intake (DMI) and animals' weights were recorded to obtain average daily gain (ADG) and feed conversion rate (FCR). Feed and fecal samples were collected to evaluate digestibility of diet components. Daily cost of the ration (DRC), feed cost per kg of daily weight gain (CDG) and daily gross margin (DGM) were calculated to analyze the possible benefits of decreasing the protein level. Meat quality analyses were also conducted. Higher DMI (10.6 versus 10 kg/d; p < 0.05) and ADG (1.47 versus 1.36 kg/d; p < 0.05) were observed for CON. No differences in FCR or digestibility were found. Even if the DRC was lower (p < 0.05) for the LP diet (2.26 versus 1.97 €; CON versus LP), no difference was reported for CDG and DGM. Meat lightness and redness were significantly lower and higher in the LP, respectively. To conclude, the CP requirement in these rearing conditions appeared to be higher than 13.5%.

Use of rumination and activity data as health status and performance indicators in beef cattle during the early fattening period.

The aim of this study was to measure the level of activity and rumination in young bulls and to assess whether these data can be used as indicators of health status and average daily weight gain (ADG). Two groups of animals (period 1: n=108 animals; period 2: n=106 animals) were fitted with sensors to measure daily activity and rumination, were weighed on arrival and at the end of the trial (70 days) and were checked twice daily to verify their health condition. Any clinical signs and therapies were recorded. The dishomogeneity index of rumination (DR), and the daily dishomogeneity indices of activity (DDA) and rumination (DDR), were calculated. Bulls had an ADG of 1.42±0.38kg/day and showed an average duration of daily rumination of 404±63min and an average activity of 474±46 bits, respectively. Animals characterised by low ADG had lower values of minimum daily rumination (P=0.01) and DDA (P<0.001), and a greater rumination range (P=0.007) and DR (P=0.003). Bovine respiratory disease and lameness were detected 31 and five times, respectively; among affected animals, the average daily activity, rumination and DDA were lower (P<0.05) at 3-6days before the onset of visible clinical signs, whereas DDR increased compared to the values when individuals were apparently healthy. The use of individual sensors appears promising for the early diagnosis of disease in beef cattle and for improving herd management.

Study of ingredients and nutrient composition of commercially available treats for dogs.

Forty-one dog treats were selected from the market with the aim of providing more insight into supplemental pet food composition. Thirty-two products (four biscuits, nine tender treats, two meat-based strips, five rawhides, eight chewable sticks, four dental care sticks) were analysed for proximate nutrient composition and quantification of minerals, hydroxyproline (Hyp), starch, glucose, fructose and sucrose. Labelled ingredients were often expressed as non-specific categories. A treat supplied a mean of 332.0±39.2 kcal metabolisable energy (ME)/100 g, and the most energy-dense product was a tender treat (475.0 kcal ME/100 g). Small dogs receive the highest percentage of maintenance energy requirement when producers' feeding instructions are followed. Treat categories revealed variability in dry matter, crude protein, ash, Hyp and starch. Rawhides showed the highest Hyp content. Simple sugars were identified in most treats, and sucrose was the most prevalent. Results of the study suggest treat labelling should include more information on the ingredients used, and the varying nutrient and caloric density of treats should be considered. Specific attention should be given to the use of treats in dogs with specific ingredient sensitivities or nutrient considerations.

Effects of space allowance on the behaviour of long-term housed shelter dogs.

The aim of this study was to assess the effects of space allowance (4.5 m(2)/head vs. 9 m(2)/head) on the behaviour of shelter dogs (Canis familiaris) at different times of the day (from 10:30 to 13:30 vs. from 14:30 to 17:30), and the dogs' preference between two types of beds (fabric bed vs. plastic basket). Twelve neutered dogs (seven males and five females aged 3-8 years) housed in pairs were observed using a scan sampling recording method every 20 s for a total of 14,592 scans/treatment. An increase in space allowance increased general level of activity (risk ratio (RR)=1.34), standing (RR=1.37), positive social interactions (RR=2.14), visual exploration of the environment (RR=1.21), and vocalisations (RR=2.35). Dogs spent more time in the sitting (RR=1.39) or standing (RR=1.88) posture, in positive interactions (RR=1.85), and active visual exploration (RR=1.99) during the morning than in the afternoon. The dogs were more often observed in the fabric bed than in the plastic basket (53% vs. 15% of total scans, p<0.001). Results suggest that a 9.0 m(2)/head space allowance could be more beneficial to dogs than one of 4.5 m(2).