The objective of this study was to evaluate whether pre-weaning heifer calves divergent for residual feed intake (RFI) or residual feed intake and body weight gain (RIG) exhibit differences in ...thermography, blood, and ruminal parameters. Thirty-two Gyr heifer calves were enrolled in a 63-d trial and classified into 2 feed efficiency (FE) groups based on RFI and RIG (mean #177; 0.5 SD). The groups were classified as high efficiency (HE) RFI (HE RFI, n = 9), HE RIG (HE RIG, n = 10), low efficiency (LE) RFI (LE RFI, n = 10), and LE RIG (LE RIG, n = 11). The amount of whole milk provided for each calf was calculated based on their metabolic weight at birth (42% x BW.sup.0.75). The liquid diet was divided into two meals at 0700 and 1400 h. The total solid diet (TSD) was composed of 92% concentrate and 8% of Tifton 85 hay chopped in 5-cm lengths, as fed. Intake was measured daily. Blood concentrations of insulin, beta hydroxybutyrate, urea, and glucose, and ruminal pH, N-NH.sub.3, and volatile fatty acids (VFA) were evaluated at 14, 28, 42, 56, and 70 days of age. Thermal images of the calves were taken with an infrared camera (FLIR T420, FLIR Systems Inc., Wilsonville, OR) on d 56 (#177;3) at 0600 h, before the morning feeding. Total VFA concentration and propionate as % of total VFA were 24.2% and 22.2% lower in HE RFI compared to LE RFI calves, respectively. On the other hand, acetate as % of total VFA was 10.6% greater in HE RFI than LE RFI calves. Blood urea concentration tended to be greater in LE RFI than HE RFI calves. High efficiency HE RIG tended to have 6.8% greater acetate and 15.4% lower propionate as % of total VFA than LE RIG. Blood insulin concentration was greater and blood glucose tended to be greater for LE RIG than HE RIG group. Low efficiency RIG group had greater left rib, left flank, and anus surface temperature measured by infrared thermography than the HE RIG group. Differences in ruminal fermentation do not seem to be associated with pre-weaning calves efficiency, while differences in protein metabolism seem to affect RFI during this phase. Infrared thermography appears to be correlated to RIG in pre-weaning heifer calves.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Plant extracts have been proposed as substitutes for chemical feed additives due to their potential as rumen fermentation modifiers and because of their antimicrobial and antioxidant activities, ...possibly reducing methane emissions. This study aimed to evaluate the use of oregano (OR), green tea extracts (GT), and their association as feed additives on the performance and methane emissions from dairy between 28 and 87 d of lactation. Thirty-two lactating dairy cows, blocked into 2 genetic groups: 16 Holstein cows and 16 crossbred Holstein-Gir, with 522.6 ± 58.3 kg of body weight, 57.2 ± 20.9 d in lactation, producing 27.5 ± 5.0 kg/cow of milk and with 3.1 ± 1.8 lactations were evaluated (means ± standard error of the means). Cows were allocated into 4 treatments: control (CON), without plant extracts in the diet; oregano extract (OR), with the addition of 0.056% of oregano extract in the dry matter (DM) of the diet; green tea (GT), with the addition of 0.028% of green tea extract in the DM of the diet; and mixture, with the addition of 0.056% oregano extract and 0.028% green tea extract in the DM of the diet. The forage-to-concentrate ratio was 60:40. Forage was composed of corn silage (94%) and Tifton hay (6%); concentrate was based on ground corn and soybean meal. Plant extracts were supplied as powder, which was previously added and homogenized into 1 kg of concentrate in natural matter, top-dressed onto the total mixed diet. No treatment by day interaction was observed for any of the evaluated variables, but some block by treatment interactions were significant. In Holstein cows, the mixture treatment decreased gross energy and tended to decrease the total-tract apparent digestibility coefficient for crude protein and total digestible nutrients when compared with OR. During the gas measurement period, GT and OR increased the digestible fraction of the ingested DM and decreased CH4 expressed in grams per kilogram of digestible DMI compared with CON. The use of extracts did not change rumen pH, total volatile fatty acid concentration, milk yield, or most milk traits. Compared with CON, oregano addition decreased fat concentration in milk. The use of plant extracts altered some milk fatty acids but did not change milk fatty acids grouped according to chain length (short or long), saturation (unsaturated or saturated), total conjugated linoleic acids, and n-3 and n-6 contents. Green tea and oregano fed separately reduced gas emission in cows during the first third of lactation and have potential to be used as feed additives for dairy cows.
Bovine anaplasmosis causes considerable economic losses in dairy cattle production systems worldwide, ranging from $300 million to $900 million annually. It is commonly detected through rectal ...temperature, blood smear microscopy, and packed cell volume (PCV). Such methodologies are laborious, costly, and difficult to systematically implement in large-scale operations. The objectives of this study were to evaluate (1) rumination and activity data collected by Hr-Tag sensors (SCR Engineers Ltd.) in heifer calves exposed to anaplasmosis; and (2) the predictive ability of recurrent neural networks in early identification of anaplasmosis. Additionally, we aimed to investigate the effect of time series length before disease diagnosis (5, 7, 10, or 12 consecutive days) on the predictive performance of recurrent neural networks, and how early anaplasmosis disease can be detected in dairy calves (5, 3, and 1 d in advance). Twenty-three heifer calves aged 119 ± 15 (mean ± SD) d and weighing 148 ± 20 kg of body weight were challenged with 2 × 107 erythrocytes infected with UFMG1 strain (GenBank no. EU676176) isolated from Anaplasma marginale. After inoculation, animals were monitored daily by assessing PCV. The lowest PCV value (14 ± 1.8%) and the finding of rickettsia on blood smears were used as a criterion to classify an animal as sick (d 0). Rumination and activity data were collected continuously and automatically at 2-h intervals, using SCR Heatime Hr-Tag collars. Two time series were built including last sequence of −5, −7, −10, or −12 d preceding d 0 or a sequence of 5, 7, 10, or 12 d randomly selected in a window from −50 to −15 d before d 0 to ensure a sequence of days in which PCV was considered normal (32 ± 2.4%). Long short-term memory was used as a predictive approach, and a leave-one-animal-out cross-validation (LOAOCV) was used to assess prediction quality. Anaplasmosis disease reduced 34 and 11% of rumination and activity, respectively. The accuracy, sensitivity, and specificity of long short-term memory in detecting anaplasmosis ranged from 87 to 98%, 83 to 100%, and 83 to 100%, respectively, using rumination data. For activity data, the accuracy, sensitivity, and specificity varied from 70 to 98%, 61 to 100%, and 74 to 100%, respectively. Predictive performance did not improve when combining rumination and activity. The use of longer time-series did not improve the performance of models to predict anaplasmosis. The accuracy and sensitivity in predicting anaplasmosis up to 3 d before clinical diagnosis (d 0) were greater than 80%, confirming the possibility for early identification of anaplasmosis disease. These findings indicate the great potential of wearable sensors in early identification of anaplasmosis diseases. This could positively affect the profitability of dairy farmers and animal welfare.
The objective of this study was to validate an electronic system for monitoring individual feeding behavior and feed intake (Intergado Ltd., Contagem, Minas Gerais, Brazil) in freestall-housed dairy ...cattle. No data have been published that validate either the behavioral measurement or the feed intake of this system. Feeding behavior data were recorded for 12 Holstein cows over 5d using an Intergado system and time-lapse video. The cows were fitted with an ear tag containing a unique passive transponder and provided free access to 12 feed bins. The system documented the visit duration and feed intake by recording the animal identification number, bin number, initial and final times, and the difference between feed weight at start and end of each feed bin visit. These data were exported to Intergado web software and reports were generated. Electronic data on animal behavior were compared with video data collected during the same evaluation period. An external scale was used to manually measure and validate the electronic system’s ability to monitor dairy cow feed intake for each feed bin visit. The feed intake was manually measured for 4-h time periods and compared with the sum of the feed intake recorded by the monitoring system for each cow visit during the same time period. Video and manual weight data were regressed on the electronic feeding behavior and feeding intake data to evaluate the precision of the monitoring system. The Intergado system presented high values for specificity (99.9%) and sensitivity (99.6%) for cow detection. The visit duration and feed intake per visit collected using the electronic monitoring system were similar to the video and manual weighing data, respectively. The difference between the feed intake measured manually and the sum of the electronically recorded feed intake was less than 250g (25,635±2,428 and 25,391±2,428g estimated using manual weighing and the electronic system, respectively). In conclusion, the Intergado system is a reasonable tool to monitor feeding behavior and feed intake for freestall-housed dairy cows.
Accurate estimates of methane (CH4) production by cattle in different contexts are essential to developing mitigation strategies in different regions. We aimed to: (i) compile a database of CH4 ...emissions from Brazilian cattle studies, (ii) evaluate prediction precision and accuracy of extant proposed equations for cattle and (iii) develop specialized equations for predicting CH4 emissions from cattle in tropical conditions. Data of nutrient intake, diet composition and CH4 emissions were compiled from in vivo studies using open-circuit respiratory chambers, SF6 technique or the GreenFeed® system. A final dataset containing intake, diet composition, digestibility and CH4 emissions (677 individual animal observations, 40 treatment means) obtained from 38 studies conducted in Brazil was used. The dataset was divided into three groups: all animals (GEN), lactating dairy cows (LAC) and growing cattle and non-lactating dairy cows (GCNL). A total of 54 prediction equations available in the literature were evaluated. A total of 96 multiple linear models were developed for predicting CH4 production (MJ/day). The predictor variables were DM intake (DMI), gross energy (GE) intake, BW, DMI as proportion of BW, NDF concentration, ether extract (EE) concentration, dietary proportion of concentrate and GE digestibility. Model selection criteria were significance (P < 0.05) and variance inflation factor lower than three for all predictors. Each model performance was evaluated by leave-one-out cross-validation. The Intergovernmental Panel on Climate Change (2006) Tier 2 method performed better for GEN and GCNL than LAC and overpredicted CH4 production for all datasets. Increasing complexity of the newly developed models resulted in greater performance. The GCNL had a greater number of equations with expanded possibilities to correct for diet characteristics such as EE and NDF concentrations and dietary proportion of concentrate. For the LAC dataset, equations based on intake and animal characteristics were developed. The equations developed in the present study can be useful for accurate and precise estimation of CH4 emissions from cattle in tropical conditions. These equations could improve accuracy of greenhouse gas inventories for tropical countries. The results provide a better understanding of the dietary and animal characteristics that influence the production of enteric CH4 in tropical production systems.
•Earlier and automated detection of estrus can improve on-farm decisions.•Estrus events altered feeding and drinking behavior pattern and feed intake.•Behavioral data generated by electronic bins ...have not been explored for estrus detection.•Machine learning algorithms were applied to feeding behavior data for estrus detection.•Feeding and drinking behavior data generated by electronic bins can be used to early predict estrus event.
The recent advances in sensor technology have allowed accurate predictions of estrus events using animal behavior information. Behavioral variables generated by electronic feed and water bins have not been explored as potential predictors for estrus detection. The objectives of this study were: (i) to evaluate the effect of estrus expression on feed intake and animal behavior (feeding and drinking) and (ii) to develop and evaluate predictive approaches to detect estrus expression using electronic feed and water bins data. Feed intake, animal behavior, and estrus events were measured in 57 Holstein × Gyr heifers (374 ± 21.2 kg and 22.6 ± 0.60 months). Previous to each estrus event, the following covariates were computed: total feed intake (FI, as-fed basis), number of visits at the feed bins (VF) and water bins (VW), time spent eating (TE), and time spent drinking water (TD). Three predictive approaches were evaluated: Generalized Linear Models (GLM), Artificial Neural Network (ANN), and Random Forest (RF). Twelve covariate sets were established to investigate: (ii.a) the prediction quality for estrus detection when long (−174 to 0 h) or short (−24 to 0 h) time series were used as predictors (6 h of time window, with estrus event at 0 h); (ii.b) the ability of machine learning algorithms to predict estrus 6 and 12 h in advance; and (ii.c) the predictive quality for estrus detection when only feeding and drinking behavior data (without intake variables) were included as predictors. The predictive approaches were evaluated through Leave-One-Out Cross-validation. Estrus events altered feeding and drinking behavior patterns, and feed intake. ANN, RF, and GLM presented similar accuracies within covariate sets. There was no benefit of using longer time series for estrus detection. Earlier detection of estrus event (6 and 12 h in advance) reduced model accuracy compared to predictions performed at 0 h. However, ANN and RF showed accuracy values ranging between 75.7% and 96.5%, which indicates a great potential for early estrus detection. The exclusion of feed intake data of the covariate sets did not reduce the accuracy, sensitivity, and specificity of the models for estrus detection. These findings suggest that behavioral data can early predict estrus events, which could be incorporated in sensor technologies capable of generating behavioral information, such as electronic bins, wearable sensors, and computer vision systems.
It remains unknown whether dairy cows with more reactive temperament produce more enteric methane (CH4) and are less bioenergetically efficient than the calmer ones. The objectives of this study were ...(a) to evaluate the relationship between cattle temperament assessed by traditionally used tests with energetic metabolism and enteric CH4 emissions by crossbred dairy cows; (b) to assess how cows’ restlessness in respiration chambers affects energetic metabolism and enteric CH4 emissions. Temperament indicators were evaluated for 28 primiparous F1 Holstein-Gyr cows tested singly in the handling corral (entrance time, crush score, flight speed, and flight distance) and during milking (steps, kicks, defecation, rumination, and kick the milking cluster off). Cows’ behaviors within respiration chambers were also recorded for each individual kept singly. Digestibility and calorimetry trials were performed to obtain energy partitioning and CH4 measures. Cows with more reactive temperament in milking (the ones that kicked the milking cluster off more frequently) spent 25.24% less net energy on lactation (P = 0.04) and emitted 36.77% more enteric CH4/kg of milk (P = 0.03). Furthermore, cows that showed a higher frequency of rumination at milking parlor allocated 57.93% more net energy for milk production (P < 0.01), spent 50.00% more metabolizable energy for milk production (P < 0.01) and 37.10% less CH4/kg of milk (P = 0.04). Regarding the handling temperament, most reactive cows according to flight speed, lost 29.16% less energy as urine (P = 0.05) and tended to have 14.30% more enteric CH4 production (P = 0.08), as well as cows with a lower entrance time (most reactive) that also lost 13.29% more energy as enteric CH4 (P = 0.04). Temperament and restless behavior of Holstein-Gyr cows were related to metabolic efficiency and enteric CH4 emissions. Cows’ reactivity and rumination in the milking parlor, in addition to flight speed and entrance time in the squeeze chute during handling in the corral, could be useful measures to predict animals more prone to metabolic inefficiency, which could negatively affect the sustainability of dairy systems.
The effects of divergent phenotypic classification in crossbreed Holstein × Gyr dairy heifers for methane emissions in relation to performance, digestibility, energy and nitrogen partition, blood ...metabolites and temperature of body surface were evaluated. Thirty-five heifers were classified as high and low emission for CH4 production (g/day), yield (g/kg dry matter intake) and intensity (g/kg average daily gain). Digestibility was evaluated by total collection of feces and urine. Gas exchanges were obtained in open-circuit respiratory chambers. A completely randomized design was used and divergent groups were compared by Fisher's test. No differences were found in intake traits between groups of CH4 production and intensity. The low yield group had higher intake. For digestibility and temperature at different body sites were no differences between variables. High production group had higher energy losses as methane and heat production. Low intensity group had higher digestible energy, energy balance and ratio between metabolizable and digestible energy. Urinary nitrogen was 14.3% lower for low production group. There was a difference between methane yield divergent groups for nitrogen intake, digestible and retained. Energy and nitrogen partitioning traits are correlated to the animals divergent for methane production and yield. The low production group presented lower blood insulin concentration. It was not possible to identify divergent animals for CH4 emission using the infrared thermography technique.
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•Dairy sectors are the major producer of enteric CH4 in the world.•The selection for less CH4 emission can affect animal metabolism.•Low emissions animals showed a better efficiency of energy.•Urinary nitrogen was 14.3% lower for low production group.•The insulin decreases 23.1% for low production group.
A respiration system consisting of 4 climate-controlled chambers and 1 set of flowmeters and analyzers was constructed and validated. Each chamber had volume of 21.10m3 (3.68×2.56×2.24m) and was made ...from steel with double-glazed windows on either side enabling visual contact between animals. The chambers are independently climate-controlled and can maintain temperature and relative humidity in a range from 5 to 45°C and 30 to 80%, respectively. A flow generator and mass flowmeter continuously pull air from each chamber and a slight negative pressure inside the chamber is ensured. Air from all chambers and ambient air share a common gas analysis and data acquisition system for monitoring O2, CO2, and CH4 concentrations over the measurement period, with the cycle time set to 20min. Analyzers are regularly calibrated and the chambers have mean recoveries of 99.0 and 98.0% for CO2 and CH4, respectively. The chambers are equipped with infrared cameras and electronic feed and water bins for intake measurements, as well as sensors for monitoring animal position and heart rate. Data acquisition and analysis software is used to calculate the rate of consumption of O2 and production of CO2 and CH4. The dynamic respiration measurements are integrated with feed intake data and other sensors. The daily gas exchanges are estimated by integration to determine methane emission and heat production. We conducted a trial with 12 lactating 3/4 Holstein × 1/4 Gyr crossbred dairy cows (6 multiparous and 6 primiparous) under 2 feeding regimens (ad libitum or restricted) to validate the system. Two 22-h respiration measurements were obtained from each cow. Restricted-fed cows showed lower values for milk yield, methane emission, and heat production compared with ad libitum-fed animals. We found no difference between groups for CH4 produced per kilogram of dry matter intake. Repeatability for CH4 emission and heat production was high (0.97 and 0.92, respectively). The respiration system described herein is a useful tool for measuring the dynamic and accumulated data of heat production, methane emission, and feed intake.
The aims of this study were (1) to assess if there is phenotypical divergence for feed efficiency (FE) during the preweaning phase; (2) if FE is correlated with heat production (HP) measured by the ...face mask method or (3) by surface skin temperature via thermography, and (4) whether these methods are applicable to preweaned calves. Holstein × Gyr heifer calves (n = 36, birth body weight = 32.4 ± 6.6 kg) were enrolled and on trial between 4 and 12 wk of age and were classified into 2 residual feed intake (RFI) and residual body weight gain (RG) groups: high efficiency (HE; RFI, n = 10; and RG, n = 9) and low efficiency (LE; RFI, n = 10; and RG, n = 8). Calves were fed milk (6 L/d) and solid feed (95% starter and 5% chopped Tifton 85 hay, as fed). Growth was monitored weekly and feed intake (milk and solid feed) daily, during the whole period. Gas exchanges (O2 consumption and production of CO2 and CH4) were obtained using a face mask at 45 ± 5 d of age and HP was estimated. Maximum temperatures were measured at 7 sites with an infrared camera at 62 ± 7 d of age. There was divergence in RFI and RG. Respectively, HE and LE calves had RFI of −0.14 and 0.13 kg/d, and RG of 0.05 and −0.07 kg/d. Dry matter intake was 15% lower in HE-RFI compared with LE-RFI, but no differences were observed in average daily weight gain. Within the RG test, no differences were observed in dry matter intake or average daily gain. The HE-RFI calves consumed less O2 (L/d) and produced less CO2 (L/d). Heart rate and HP were lower for HE-RFI calves compared with LE-RFI. Residual feed intake was correlated with HP (r = 0.48), O2 consumption (r = 0.48), CO2 production (r = 0.48), and heart rate (r = 0.40). No differences were observed in HP and gas exchanges between RG groups. Methane production was null in both groups. Eye temperature measured by thermography was 0.5°C greater in HE-RG than LE-RG calves. Differences in skin temperature between HE and LE calves were not observed at the other sites. These results support the hypothesis that calves are divergent for RFI, RG, and FE during preweaning and divergence tests are applicable during this phase. The face mask method described here is a useful tool for estimating differences in HP among phenotypically divergent RFI calves. Eye temperature measured by infrared thermography may have potential to screen phenotypically divergent RG calves.
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