A decision-tree model to detect post-calving diseases based on rumination, activity, milk yield, BW and voluntary visits to the milking robot.

Early detection of post-calving health problems is critical for dairy operations. Separating sick cows from the herd is important, especially in robotic-milking dairy farms, where searching for a sick cow can disturb the other cows' routine. The objectives of this study were to develop and apply a behaviour- and performance-based health-detection model to post-calving cows in a robotic-milking dairy farm, with the aim of detecting sick cows based on available commercial sensors. The study was conducted in an Israeli robotic-milking dairy farm with 250 Israeli-Holstein cows. All cows were equipped with rumination- and neck-activity sensors. Milk yield, visits to the milking robot and BW were recorded in the milking robot. A decision-tree model was developed on a calibration data set (historical data of the 10 months before the study) and was validated on the new data set. The decision model generated a probability of being sick for each cow. The model was applied once a week just before the veterinarian performed the weekly routine post-calving health check. The veterinarian's diagnosis served as a binary reference for the model (healthy-sick). The overall accuracy of the model was 78%, with a specificity of 87% and a sensitivity of 69%, suggesting its practical value.

Feeding behavior improves prediction of dairy cow voluntary feed intake but cannot serve as the sole indicator.

Low-cost feeding-behavior sensors will soon be available for commercial use in dairy farms. The aim of this study was to develop a feed intake model for the individual dairy cow that includes feeding behavior. In a research farm, the individual cows' voluntary feed intake and feeding behavior were monitored at every meal. A feed intake model was developed based on data that exist in commercial modern farms: 'BW,' 'milk yield' and 'days in milking' parameters were applied in this study. At the individual cow level, eating velocity seemed to be correlated with feed intake (R 2=0.93 to 0.94). The eating velocity coefficient varied among individuals, ranging from 150 to 230 g/min per cow. The contribution of feeding behavior (0.28) to the dry matter intake (DMI) model was higher than the contribution of BW (0.20), similar to the contribution of fat-corrected milk (FCM)/BW (0.29) and not as large as the contribution of FCM (0.49). Incorporating feeding behavior into the DMI model improved its accuracy by 1.3 (38%) kg/cow per day. The model is ready to be implemented in commercial farms as soon as companies introduce low-cost feeding-behavior sensors on commercial level.

Lameness detection in dairy cattle: single predictor v. multivariate analysis of image-based posture processing and behaviour and performance sensing.

The objective of this study was to evaluate if a multi-sensor system (milk, activity, body posture) was a better classifier for lameness than the single-sensor-based detection models. Between September 2013 and August 2014, 3629 cow observations were collected on a commercial dairy farm in Belgium. Human locomotion scoring was used as reference for the model development and evaluation. Cow behaviour and performance was measured with existing sensors that were already present at the farm. A prototype of three-dimensional-based video recording system was used to quantify automatically the back posture of a cow. For the single predictor comparisons, a receiver operating characteristics curve was made. For the multivariate detection models, logistic regression and generalized linear mixed models (GLMM) were developed. The best lameness classification model was obtained by the multi-sensor analysis (area under the receiver operating characteristics curve (AUC)=0.757±0.029), containing a combination of milk and milking variables, activity and gait and posture variables from videos. Second, the multivariate video-based system (AUC=0.732±0.011) performed better than the multivariate milk sensors (AUC=0.604±0.026) and the multivariate behaviour sensors (AUC=0.633±0.018). The video-based system performed better than the combined behaviour and performance-based detection model (AUC=0.669±0.028), indicating that it is worthwhile to consider a video-based lameness detection system, regardless the presence of other existing sensors in the farm. The results suggest that Θ2, the feature variable for the back curvature around the hip joints, with an AUC of 0.719 is the best single predictor variable for lameness detection based on locomotion scoring. In general, this study showed that the video-based back posture monitoring system is outperforming the behaviour and performance sensing techniques for locomotion scoring-based lameness detection. A GLMM with seven specific variables (walking speed, back posture measurement, daytime activity, milk yield, lactation stage, milk peak flow rate and milk peak conductivity) is the best combination of variables for lameness classification. The accuracy on four-level lameness classification was 60.3%. The accuracy improved to 79.8% for binary lameness classification. The binary GLMM obtained a sensitivity of 68.5% and a specificity of 87.6%, which both exceed the sensitivity (52.1%±4.7%) and specificity (83.2%±2.3%) of the multi-sensor logistic regression model. This shows that the repeated measures analysis in the GLMM, taking into account the individual history of the animal, outperforms the classification when thresholds based on herd level (a statistical population) are used.

The effect of routine hoof trimming on locomotion score, ruminating time, activity, and milk yield of dairy cows.

The objective of this study was to quantify the effect of hoof trimming on cow behavior (ruminating time, activity, and locomotion score) and performance (milk yield) over time. Data were gathered from a commercial dairy farm in Israel where routine hoof trimming is done by a trained hoof trimmer twice per year on the entire herd. In total, 288 cows spread over 6 groups with varying production levels were used for the analysis. Cow behavior was measured continuously with a commercial neck activity logger and a ruminating time logger (HR-Tag, SCR Engineers Ltd., Netanya, Israel). Milk yield was recorded during each milking session with a commercial milk flow sensor (Free Flow, SCR Engineers Ltd.). A trained observer assigned on the spot 5-point locomotion scores during 19 nighttime milking occasions between 22 October 2012 and 4 February 2013. Behavioral and performance data were gathered from 1wk before hoof trimming until 1wk after hoof trimming. A generalized linear mixed model was used to statistically test all main and interactive effects of hoof trimming, parity, lactation stage, and hoof lesion presence on ruminating time, neck activity, milk yield, and locomotion score. The results on locomotion scores show that the proportional distribution of cows in the different locomotion score classes changes significantly after trimming. The proportion of cows with a locomotion score ≥3 increases from 14% before to 34% directly after the hoof trimming. Two months after the trimming, the number of cows with a locomotion score ≥3 reduced to 20%, which was still higher than the baseline values 2wk before the trimming. The neck activity level was significantly reduced 1d after trimming (380±6 bits/d) compared with before trimming (389±6 bits/d). Each one-unit increase in locomotion score reduced cow activity level by 4.488 bits/d. The effect of hoof trimming on ruminating time was affected by an interaction effect with parity. The effect of hoof trimming on locomotion scores was affected by an interaction effect with lactation stage and tended to be affected by interaction effects with hoof lesion presence, indicating that cows with a lesion reacted different to the trimming than cows without a lesion did. The results show that the routine hoof trimming affected dairy cow behavior and performance in this farm.

Development of an automatic cow body condition scoring using body shape signature and Fourier descriptors.

Body condition evaluation is a common tool to assess energy reserves of dairy cows and to estimate their fatness or thinness. This study presents a computer-vision tool that automatically estimates cow's body condition score. Top-view images of 151 cows were collected on an Israeli research dairy farm using a digital still camera located at the entrance to the milking parlor. The cow's tailhead area and its contour were segmented and extracted automatically. Two types of features of the tailhead contour were extracted: (1) the angles and distances between 5 anatomical points; and (2) the cow signature, which is a 1-dimensional vector of the Euclidean distances from each point in the normalized tailhead contour to the shape center. Two methods were applied to describe the cow's signature and to reduce its dimension: (1) partial least squares regression, and (2) Fourier descriptors of the cow signature. Three prediction models were compared with manual scores of an expert. Results indicate that (1) it is possible to automatically extract and predict body condition from color images without any manual interference; and (2) Fourier descriptors of the cow's signature result in improved performance (R(2)=0.77).

Effect of feeding according to energy balance on performance, nutrient excretion, and feeding behavior of early lactation dairy cows.

The objectives of this study were to evaluate 2 feeding strategies for early lactation cows on performance and efficiency of nutrient utilization. Fifty-eight Holsteins cows were blocked by parity and production during the pretreatment period and then randomly assigned at 21 d postpartum to a control diet [n=29; 16.2% crude protein, 1.64 Mcal of net energy for lactation (NE(L)), 22% starch, and 19% forage neutral detergent fiber (NDF)] or a diet with caloric density manipulated weekly (precision diet; n=29; 16.2% crude protein; 1.59 to 1.68 NE(L); 18 to 26% starch; and 16 to 22% forage NDF) to promote a calculated positive energy balance of 5 Mcal/day. Diets were fed as total mixed rations and precision cows had their diets adjusted individually once a week, by feeding additional grain supplementation from 0 to 25% of daily dry matter (DM) offered, according to the energy balance of the preceding week. Energy balance was calculated daily and then averaged weekly. The study lasted from wk 3 to 19 postpartum, and nutrient digestibility, rumen fluid composition, urinary output, estimates of microbial protein synthesis, and feeding behavior were evaluated between wk 9 and 13 postpartum. Compared with controls, precision cows had similar DM intake (24.3 kg/d), but NE(L) intake tended to be greater primarily between wk 4 and 8 postpartum. Yields of milk (45.2 vs. 41.9 kg/d), milk components, 3.5% fat-corrected milk (44.0 vs. 40.8 kg/d), and energy-corrected milk (43.4 vs. 40.2) were all greater for precision than control cows, resulting in greater energy-corrected milk production per kilogram of diet DM consumed (1.79 vs. 1.72). Precision cows produced more milk calories per kilogram of metabolic weight (0.227 vs. 0.213 Mcal of NE(L)/kg), although the amount of consumed calories partitioned into milk (82.3%) and measures of energy status did not differ between treatments throughout the study. Glucose concentrations were greater throughout the day in precision cows compared with controls at 6 wk, but not 13 wk postpartum. Apparent digestibility of nutrients, composition of rumen fluid, mean and low rumen pH, and estimated rumen microbial N synthesis remained mostly unaltered by treatments. Although precision cows produced more milk true protein, measures of efficiency of dietary N use were not influenced by treatment. On wk 13 postpartum, precision cows consumed a diet with longer NDF particles, which resulted in a tendency for greater intake of NDF >8mm because of less sorting against the long particles than control cows. Meal pattern differed with treatment, and precision cows consumed feed more sparsely throughout the day, spent more time ruminating lying, and had similar meal duration (mean of 36.3 min/meal) compared with control cows, but smaller meal size (3.33 vs. 3.64 kg/meal). Results from the current study indicate that allocating dietary resources according to the individual needs of cows based on energy balance improves lactation performance compared with feeding a single total mixed ration, despite similar average nutrient intake between treatments. Improvements in performance are likely related to allocation of calories based on the needs of the cow and on shifts of feeding behavior that might favor intake of smaller meals.

Lameness detection based on multivariate continuous sensing of milk yield, rumination, and neck activity.

The objective of this study was to develop and validate a mathematical model to detect clinical lameness based on existing sensor data that relate to the behavior and performance of cows in a commercial dairy farm. Identification of lame (44) and not lame (74) cows in the database was done based on the farm's daily herd health reports. All cows were equipped with a behavior sensor that measured neck activity and ruminating time. The cow's performance was measured with a milk yield meter in the milking parlor. In total, 38 model input variables were constructed from the sensor data comprising absolute values, relative values, daily standard deviations, slope coefficients, daytime and nighttime periods, variables related to individual temperament, and milk session-related variables. A lame group, cows recognized and treated for lameness, to not lame group comparison of daily data was done. Correlations between the dichotomous output variable (lame or not lame) and the model input variables were made. The highest correlation coefficient was obtained for the milk yield variable (rMY=0.45). In addition, a logistic regression model was developed based on the 7 highest correlated model input variables (the daily milk yield 4d before diagnosis; the slope coefficient of the daily milk yield 4d before diagnosis; the nighttime to daytime neck activity ratio 6d before diagnosis; the milk yield week difference ratio 4d before diagnosis; the milk yield week difference 4d before diagnosis; the neck activity level during the daytime 7d before diagnosis; the ruminating time during nighttime 6d before diagnosis). After a 10-fold cross-validation, the model obtained a sensitivity of 0.89 and a specificity of 0.85, with a correct classification rate of 0.86 when based on the averaged 10-fold model coefficients. This study demonstrates that existing farm data initially used for other purposes, such as heat detection, can be exploited for the automated detection of clinically lame animals on a daily basis as well.

Feeding soyhulls to high-yielding dairy cows increased milk production, but not milking frequency, in an automatic milking system.

To attract a cow into an automatic milking system (AMS), a certain amount of concentrate pellets is provided while the cow is being milked. If the milking frequency in an AMS is increased, the intake of concentrate pellets might increase accordingly. Replacing conventional starchy pellets with nonstarchy pellets increased milk yield, milk fat, and milk protein and decreased body weight. The hypothesis was that a nonroughage by-product rich in digestible neutral detergent fiber, such as soyhulls and gluten feed, could replace starchy grain in pellets fed in an AMS. Sixty cows were paired by age, milk yield, and days in milk, and were fed a basic mixture ad libitum [16.2 +/- 0.35 (mean +/- SE) kg of dry matter intake/d per cow] plus a pelleted additive (6 to 14 kg of dry matter/d per cow) that was consumed in the AMS and in a concentrate self-feeder, which could only be entered after passing through the AMS. The 2 feeding regimens differed only in the composition of the pelleted additives: the control group contained 52.9% starchy grain, whereas the experimental group contained 25% starchy grain, plus soyhulls and gluten feed as replacement for part of the grain. Wheat bran in the control ration, a source of fiber with low digestibility, was replaced with more digestible soyhulls and gluten. During the first 60 d in milk, a cow received 10 to 12 kg of concentrate pellets. After 60 DIM, concentrate feed was allocated by milk production: < or =25 kg/d of milk entitled a cow to 2 kg/d of concentrate feed; >25 kg/d of milk entitled a cow to receive 1 kg/d of additional concentrate feed per 5 kg/d of additional milk production, and >60 kg/d of milk entitled a cow to receive 9 kg of concentrate. The concentrate feed was split between the AMS and concentrate self-feeder. The 2 diets resulted in similar frequencies of voluntary milking (3.12 +/- 0.03 to 2.65 +/- 0.03 visits/d per cow vs. 3.16 +/- 0.00 to 2.60 +/- 0.01 visits/d per cow). Average milk yields were higher in the experimental group (42.7 +/- 0.76 to 39.09 +/- 0.33 kg/d per cow vs. 39.69 +/- 0.68 to 37.54 +/- 0.40 kg/d per cow) and percentages of milk protein (3.02 +/- 0.06 to 3.12 +/- 0.05% vs. 3.07 +/- 0.04 to 3.20 +/- 0.04%) and milk fat (3.42 +/- 0.17 to 3.44 +/- 0.08% vs. 3.38 +/- 0.13 to 3.55 +/- 0.06%) were similar in the 2 groups. The results suggest that the proposed pellets high in digestible neutral detergent fiber can be allocated via the AMS to selected high-yielding cows without a negative effect on appetite, milk yield, or milk composition while maintaining a high milking frequency.

Stochastic models for simulating parallel, rotary, and side-opening milking parlors.

Simulation models of parallel, rotary, and side-opening milking parlors were built that could predict milking parlor performance according to herd size, number of milking stalls, labor quality, and cow characteristics. The models were validated by statistically comparing the duration of the simulated milking process with actual data collected at 3 dairy farms during 12 mo. Various scenarios were generated to study parlor performance, and the results indicated that for a parlor with up to 14 milking stalls, a side-opening design provided greater capacity than parallel or rotary parlors. Performance of a side-opening parlor was reduced by enlargement up to 20 milking stalls. For 10 to 40 milking stalls, a rotary design gave better performance than a double parallel design in terms of milking process duration and stall utilization. The presented models can serve as a practical tool in designing new parlors or changing operations of existing ones.

Feeding of pellets rich in digestible neutral detergent fiber to lactating cows in an automatic milking system.

If the milking frequency in an automatic milking system (AMS) is increased, the intake of concentrated pellets in the robot may be raised accordingly. Consumption of a large quantity of starchy grains within a short time can impair the appetite, decrease voluntary visits to the milking stall, and lower intakes of dry matter (DM) and neutral detergent fiber (NDF). Therefore, the hypothesis to be tested in this study was whether conventional starchy pellets fed in the AMS could be replaced with pellets rich in digestible NDF without impairing the cows' motivation to visit a milking stall voluntarily. Fifty-four cows were paired according to age, milk yield, and days in milk, and were fed a basic mixture along the feeding lane (19.9 kg of DM/cow per d), plus a pelleted additive (approximately 5.4 kg of DM/cow per d) that they obtained in the milking stall and in the concentrate self-feeder that they could enter only after passing through the milking stall. The 2 feeding regimens differed only in the composition of the pelleted additive, which, for the control group, contained 49% starchy grain, and for the experimental group contained 25% starchy grain plus soy hulls and gluten feed as replacement for part of the grain and other low-digestible, NDF-rich feeds. Both diets resulted in similar rates of voluntary milkings (3.31 vs. 3.39 visits/cow per d). Average yields of milk and percentages of milk protein were also similar in the 2 groups. The results suggest that an alternative pellet composition can be allocated in the AMS in conjunction with basic mixture in the feeding lane, without any negative effect on appetite, milk yield, milk composition, or milking frequency of the cows. It also opens the opportunity to increase yields of milk and milk solids by increasing the amount of pelleted concentrates that can be allocated to selected high-yielding cows via the AMS, because this can be done while maintaining a high frequency of voluntary milkings.

Lactation performance and feeding behavior of dairy cows supplemented via automatic feeders with soy hulls or barley based pellets.

The potential of soy hulls to replace barley grain in pellets supplemented to lactating cows was measured in automatic concentrate feeders (ACF). Thirty-six cows were divided into 2 equal groups and fed 1 of the 2 experimental pellet supplements individually for 7 wk. All cows were group-fed a basic mixture along the feeding lane (~64% of dietary DM) plus a pelleted additive containing 50% barley or soy hulls as barley replacer, fed individually to each cow via the ACF in 6 feeding windows. Extent and rate of in vitro DM digestibility were similar for both types of pellets; however, NDF content and digestibility were higher in the soy hulls pellets. Average number of rewarded cow visits at the ACF, pellets intake per meal, and accumulated intake of pellets (8.64 kg/d DM) were similar in the 2 experimental groups. Most pellets were consumed during day and night in the first 2 h after feeding windows were opened. Total visits per day in the ACF and the maximal interval between visits were similar for the 2 pellets, indicating similar attractiveness to the cow. Predicted intake of the basic mixture was similar in both groups (14.8 to 15.1 kg of DM/d). Higher milk fat content was observed in the soy hulls-fed cows, whereas higher milk protein content was found in the barley-fed cows. Milk yield was similar in both groups. Data suggest that replacement of barley pellets with soy hulls pellets may slightly enhance milk fat while reducing milk protein production for dairy herds using automatic milking systems.

Feeding behavior and performance of dairy cows fed pelleted nonroughage fiber byproducts.

The potential of pellets made of soy hulls (SH) and corn gluten feed (CGF) to replace starchy pelleted supplement in diets of lactating cows was measured in a feeding regime comparable to automatic milking systems. Twenty-four cows were divided into 2 equal groups and fed for 7 wk in individual feeders monitored by computer on one of the 2 experimental diets. Both diets contained 75% basic total mixed ration plus an additional 25% of pelleted supplement (17% CP), being either high starch pellets (HST) in treatment, or pellets made of SH + CGF (2:1) (SHCG) in treatment. In vitro dry matter digestibility was higher in the HST pellets, whereas neutral detergent fiber (NDF) digestibility was higher in the SHCG pellets. The NDF content was higher in the SHCG diet. Individual cow behavior at the feeding lane was analyzed during the experimental period. Average number of meals and daily eating duration of the SHCG cows were significantly greater, as compared with the HST group. However, intake per meal and rate of eating were greater in the HST cows, whereas meal duration was similar in both groups. Feeding behavior resulted in significantly higher daily dry matter and NDF intake by the SHCG cows (27.1 and 11.1 kg, respectively) as compared with the HST group (24.8 and 7.61 kg, respectively). Consequently, significantly higher milk fat content, milk fat yield, and 4% FCM yield were obtained in the SHCG cows. Milk and milk protein yields were similar in both treatments. Data suggest potential advantages of the SHCG pellets for herds using automatic milking systems.

Effects of replacing roughage with soy hulls on feeding behavior and milk production of dairy cows under hot weather conditions.

Two total mixed rations (TMR) containing different proportions of roughage neutral detergent fiber (NDF) were fed to lactating cows under Israeli summer conditions, and the effects on feeding behavior and milk production were measured. Forty-two lactating cows were divided into 2 groups fed ad libitum a TMR containing either 18% NDF of roughage origin (control group) or only 12% roughage NDF, in which the corn silage component (16.5% of dry matter [DM]) was replaced with soy hulls (experiment group). This and additional adjustments in TMR were reflected in higher net energy for lactation and in vitro digestibility of the experimental TMR. Cow behavior was investigated at the feeding lane during June 2001; about 11,000 cow visits were analyzed. Feed intake per meal and average meal duration were significantly higher in the experiment group (1.51 kg of DM per meal and 12.1 min per meal, respectively) as compared with the control group (1.22 kg of DM per meal and 9.47 min per meal, respectively). However, number of meals per day recorded in the feeding lane was significantly higher in the control group (21.0 vs. 16.6 meals/d per cow). Distribution of meals and feed intake along the day depended more on management practices, such as milking and feed dispensing times, than on feed composition or weather conditions. These differences between groups were expressed in similar daily eating duration (approximately 200 min), and because the rate of feed consumption was similar for both treatments (approximately 127 g DM/min), the daily average DM intake was also similar (25.0 to 25.7 kg). However, NDF intake was higher in the experiment group. Consequently, the average milk yield was higher in the experimental group, and production of milk fat, 4% fat-corrected milk, and economically corrected milk were significantly higher in the experiment group than in the control group. Data imply that the experimental TMR containing only 12% NDF of roughage origin is more suitable for cows under hot climate conditions compared with the control TMR.

Predicting feed intake of the individual dairy cow.

The voluntary feed intake of the dairy cow is an important variable in dairy operation but is impossible to measure individually when cows are kept in groups or grazing. Existing formulas that calculate dry matter intake (DMI) from ration and performance variables are not applicable to an individual cow for online decision-making, such as daily ration density adjustment by computerized feeders in a milking robot. This led to a new DMI modeling approach of using only animal factors that are measurable online on an individual basis. In 1997 we published a small-scale attempt of this approach using milk yield (MY) and body weight (BW). In 2001, this approach was adopted by the National Research Council (NRC), using 4% fat-corrected milk rather than MY together with BW and time after calving. In the present study, we increased the number of cows. The model is a multiple regression, where the descriptive variables are the interrelation MY/BW, daily BW change, and milk fat including the effect of previous 2 d. The coefficients are calculated on daily basis, i.e., each day has its own coefficients. Our model differs from that of the NRC by: 1) the descriptive variable, 2) using daily coefficients to deal with the ever-changing physiological state of lactation, and 3) considering previous performance. Two data sets (60 cows together) acquired in 2 intervals of the Volcani Center herd were used to calibrate (18 cows) and test (42 cows) the model. Model validity was statistically tested, compared to that of the NRC, and was not rejected with 99.5% confidence.

A three-cascaded-enzymes biosensor to determine lactose concentration in raw milk.

The increasing demand for on-line measurement of milk composition directs science and industry to search for practical solutions, and biosensors may be a possibility. The specific objective of this work was to develop an electrochemical biosensor to determine lactose concentration in fresh raw milk. The sensor is based on serial reactions of three enzymes--beta-galactosidase, glucose oxidase, and horseradish peroxidase--immobilized on a glassy carbon electrode. The sequential enzymatic reactions increase the selectivity and sensitivity of the sensor. The sensor requires dilution of the raw milk and the addition of 5-aminosalicylic acid. Lactose concentrations in raw milk measured by the sensor were in good agreement with those measured by a reference laboratory using infrared technology. The results were obtained in milk samples that varied in fat and protein composition. From the results, we conclude that an electrochemical biosensor for determination of lactose concentration in fresh raw milk can be developed, and that the biosensor presented in this study maintained the qualities required for further development into an online sensor in the milking parlor.

Metabolic and productive responses of dairy cows to increased ion supplementation at early lactation in warm weather.

We found previously that the current recommendations for Na+, K+, and Cl- contents in the diet do not meet the needs of lactating cows. The response of cows receiving a ration with increased amounts of Na+, K+, and Cl- (E cows) were compared with those of cows consuming the same ration with a fixed concentration of these ions (C cows) between weeks 2 and 8 post partum (PP). Milk, protein, fat and lactose yields, and dry matter intake between weeks 2 and 4 PP were higher in E than in C cows. These differences did not occur between weeks 4 and 8 PP, mainly because of a higher incidence of PP complications in E cows. A greater increase in plasma insulin-like growth factor-1 concentration in E than in C animals during weeks 2 and 3 PP was consistent with the milk responses. A reduction in aldosterone concentration in E cows in weeks 2 and 3 PP was a consequence of their Na+ requirements being satisfied as a result of their enhanced Na+ intake. A subsequent elevation in aldosterone concentration in E animals was probably related to a moderate excess in K+ intake. This increase in aldosterone explains the urinary potassium loss that was detected at week 6 PP. The absence of differences between E and C cows in plasma renin activity was consistent with an absence of differences in urine volume and with the apparent utilization of the enhanced ion intake for body functions.

The effect of enhanced milk yield of dairy cows by frequent milking or suckling on intake and digestibility of the diet.

Groups of 9 or 10 cows were assigned to one of three treatments 1) machine-milking three times daily, 2) machine-milking six times daily, and 3) suckling three times daily in addition to machine-milking three times daily. Treatments were conducted during the first 6 wk postpartum. During wk 5, digestibility of the diet was estimated by the indigestible neutral detergent fiber method. During wk 6, milk yield and dry matter intake (DMI) were recorded daily, and plasma concentrations of glucose, nonesterified fatty acids, urea, protein, growth hormone, insulin, insulin-like growth factor I, oxytocin, and prolactin were determined. Milk yields were 38.5, 46.8, and 52.7 kg/d, and DMI were 18.1, 21.2, and 17.2, for cows on treatments 1, 2, and 3, respectively. Plasma glucose concentrations decreased, and plasma nonesterified fatty acid concentrations increased, for cows on treatments 2 and 3 compared with cows on treatment 1. Digestibility of dry matter was 57.5, 60.5, and 60.6%; of organic matter was 62.6, 64.6, and 66.8%; and of crude protein was 59.3, 62.7, and 64.6% for cows on treatments 1, 2, and 3, respectively. Concentrations of all assayed hormones, except insulin, increased moderately for cows on treatment 2 compared with cows on treatment 1 and increased dramatically for cows on treatment 3. Insulin concentrations followed the opposite trend. The DMI were positively related to milk yields and negatively related to oxytocin concentrations. Digestibility was negatively related to plasma glucose concentrations in a nonlinear pattern. The possible involvement of hormones in improvement of digestibility is discussed.

Increased weight gain and effects on production parameters of Holstein heifer calves that were allowed to suckle from birth to six weeks of age.

Forty Holstein heifer calves were assigned to two treatments. Control calves (n = 20) were fed milk replacer in open buckets, and calves that were allowed to suckle (n = 20) were paired and suckled the same dam three times daily. Treatments were conducted during the first 6 wk following birth; thereafter, all calves received the same management, and weaning was at 60 d of age. During treatment, calves that were allowed to suckle had significantly higher average daily gains than did control calves. However, at 12 wk of age, calves that were allowed to suckle had significantly lower body weights (BW) than did control calves. Age at conception was significantly lower, and BW at conception and conception rate tended to be higher, for calves that were allowed to suckle. Calving age was significantly earlier for heifers that had been allowed to suckle as calves, and BW at calving also tended to be higher. Height at the withers after calving was also significantly higher for those heifers. Milk production during first lactation tended to be higher for the heifers that had been allowed to suckle as calves. Our results indicated that heifer calves that suckled milk during the first 42 d of age had higher average daily gains, higher height at the withers, an earlier age at calving, and a tendency for greater milk production than did calves fed milk replacer.

Metabolism of water, sodium, potassium, and chlorine by high yielding dairy cows at the onset of lactation.

We studied the balance of Na+, K+, Cl-, and water in six high yielding (> 39 kg/d of milk) cows between wk 2 to 1 prepartum and at 2 and 7 wk postpartum during winter in Israel. Cows were fed complete diets; Na+ and Cl- contents exceeded dietary recommendations, and K+ content was equal to dietary recommendations. Milk yield was related positively and significantly to retention of Cl- and K+, indicating that ions that are the main constituents of sweat can limit the ability of cows to express full genetic potential. The highest ion retention was recorded for cows that had the highest dry matter intake and, hence, the highest ion intake. Retention of Cl- was highest for cows that were most efficient in retaining Cl- in the kidney. In hot climates, increasing the concentrations of ions in the diet of early lactation cows according to the actual dry matter intake could prevent or reduce the severity of ion deficiencies. Water turnover rate of the cows was dependent on dry matter intake, milk yield, and respiratory-cutaneous water loss. The milk-free water balance (water turnover rate minus water secreted in milk) could be very efficiently predicted for lactating and nonlactating cows by the following equation: milk-free water balance (kilograms per day) = digestible energy intake (megacalories per day) x 0.58 + respiratory-cutaneous loss (kilograms per day) x 0.97 (n = 18; R2 = 0.97). This formula provides a tool to assess the evaporative-cutaneous water loss from feed and water intake measurements to evaluate the severity of heat stress.

Kidney function and nitrogen balance of high yielding dairy cows at the onset of lactation.

The balance of water, Na+, K+, Cl-, and total solute in the kidney and the N balance of the whole body were measured for six high yielding cows at 2 wk prepartum (period 1) and at 2 wk (period 2) and 7 wk (period 3) postpartum during winter and autumn in Israel. The onset of lactation was not followed by an increase in glomerular filtration rate and urine volume. To meet the deficiency in Na+, K+, and Cl- ions, the kidney conserves them during early lactation, mainly by increasing tubular reabsorption. An interdependent relationship exists between the excreted urea and nonurea solutes. Thus, reduction of ion concentrations in urine during early lactation reflects both the need to excrete a large load of urea and the effort to conserve Na+, K+, and Cl-. The high load of urea during early lactation was a result of a negative N balance that was most likely related to a negative energy balance. We concluded, through a comparison of our results with those of a similar study during summer, that the role of the kidney in ion conservation is more pronounced during summer than during winter and that the recovery of cows from a negative balance of energy and N is faster in summer than in winter.