Ephraim Maltz

A real-time control system for individual dairy cow food intake

A real-time control system for individual food intake of group-housed dairy cows was designed and implemented. The system consists of 40 feeding stations, each position comprising an automatic opening and closing yoke-gate. The specially designed electro-pneumatic yoke-gate combines off-the-shelf identification, weighing and control systems in a unique mechanical implementation. The yoke-system enables real-time control of food intake, which can be specified for each cow, and for each station through an interactive user interface. In addition, the system enables measurement and utilization of on-line data related to individual food intake and feeding behavior information such as food access frequency, meal duration, intake rate and food quantity for each visit of a cow kept in the group. The advantages of this design are: (i) the system is based on commercial components, (ii) simplicity and high reliability resulting in low maintenance, and (iii) continuous measurement of all feeding parameters, including during the meal. Although the yoke-system was built for a research institute, it is a step towards a commercial system.

Near infrared spectrometry of milk in its heterogeneous state.

Composition analysis by NIR spectrometry usually uses models that assume the sample to be homogeneous. However, agricultural fluid products are naturally heterogeneous, and in some cases of on-line sensing, it is very difficult to fulfill the homogeneity requirement, and some precautions are needed. The flow itself might create a non-uniform distribution of the measured ingredient concentrations across the cross-section of the flow. A modified discrete model was developed, which incorporates the concentration distribution of the ingredients. The effects of model parameters (number of layers and of iterations, valid ranges of absorbency and specular reflectance factors) were studied and evaluated. Samples of fresh raw milk were tested, in order to create a known distribution of the fat content in the sample, and were scanned by a NIR spectrometer. In the case of monotonic variation, along the sample, of the concentration of the measured ingredient (fat), the effect on the measured spectrum was similar to that of changes in the average concentration of a homogeneous sample. Comparison of the errors predicted by the model with the result of NIR measurements in heterogeneous conditions of fresh raw cows milk gave close correlation in their direction and their relative size. This created the basis for a technique to evaluate other fluids, in which the distribution of the concentration of the measured ingredient could be evaluated and incorporated in the model simulations.

A Fuzzy Logic Expert System for Dairy Cow Transfer Between Feeding Groups

Fuzzy logic was employed for timing the transfer of dairy cows from a high-energy to a lower energy ration. The transfer decision is based on trends in milk production, body weight change, and the interactions between them. To express these trends, eight fuzzy sets, with corresponding fuzzy variables, were defined by the domain expert on the basis of empirical data obtained from hundreds of individual cow records. Ten rules were defined, incorporating different combinations of the the fuzzy set variables. Operators were defined to combine fuzzy variables into rules and rules into a decision.

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.

Towards practical application of sensors for monitoring animal health: the effect of post-calving health problems on rumination duration, activity and milk yield

Three sources of sensory data: cows individual rumination duration, activity and milk yield were evaluated as possible indicators for clinical diagnosis, focusing on post-calving health problems such as ketosis and metritis. Data were collected from a computerised dairy-management system on a commercial dairy farm with Israeli Holstein cows. In the analysis, 300 healthy and 403 sick multiparous cows were studied during the first 3 weeks after calving. A mixed model with repeated measurements was used to compare healthy cows with sick cows. In the period from 5 d before diagnosis and treatment to 2 d after it, rumination duration and activity were lower in the sick cows compared to healthy cows. The milk yield of sick cows was lower than that of the healthy cows during a period lasting from 5 d before until 5 d after the day of diagnosis and treatment. Differences in the milk yield of sick cows compared with healthy cows became greater from 5 to 1 d before diagnosis and treatment. The greatest significant differences occurred 3 d before diagnosis for rumination duration and 1 d before diagnosis for activity and milk yield. These results indicate that a model can be developed to automatically detect post-calving health problems including ketosis and metritis, based on rumination duration, activity and milk yield.

Towards practical application of sensors for monitoring animal health; design and validation of a model to detect ketosis

The objective of this study was to design and validate a mathematical model to detect post-calving ketosis. The validation was conducted in four commercial dairy farms in Israel, on a total of 706 multiparous Holstein dairy cows: 203 cows clinically diagnosed with ketosis and 503 healthy cows. A logistic binary regression model was developed, where the dependent variable is categorical (healthy/diseased) and a set of explanatory variables were measured with existing commercial sensors: rumination duration, activity and milk yield of each individual cow. In a first validation step (within-farm), the model was calibrated on the database of each farm separately. Two thirds of the sick cows and an equal number of healthy cows were randomly selected for model validation. The remaining one third of the cows, which did not participate in the model validation, were used for model calibration. In order to overcome the random selection effect, this procedure was repeated 100 times. In a second (between-farms) validation step, the model was calibrated on one farm and validated on another farm. Within-farm accuracy, ranging from 74 to 79%, was higher than between-farm accuracy, ranging from 49 to 72%, in all farms. The within-farm sensitivities ranged from 78 to 90%, and specificities ranged from 71 to 74%. The between-farms sensitivities ranged from 65 to 95%. The developed model can be improved in future research, by employing other variables that can be added; or by exploring other models to achieve greater sensitivity and specificity.

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.