Wolfgang Junge

Automation of oestrus detection in dairy cows: a review

Abstract The economic importance of traits like longevity, health and reproduction has increased compared to milk yield in dairy cows. Effective oestrus detection is important for improved reproduction. Commonly, oestrus detection is performed by visual observation, but this is particularly difficult on large dairy farms because of short observation periods during feeding and milking. As a result of technical progress in monitoring cows using computers, automatic oestrus detection has become possible. In many studies different traits have been analysed for utilisation in automatic oestrus detection. The best results were found for detection using pedometers. Results of oestrus detection varied depending on the used threshold value, the number of cows, housing and treatment of cows and the utilised method of time series analysis. The detection rate of most investigations is sufficiently high at 80–90%. Error rates between 17 and 55% and specificities between 96 and 98% indicate a large number of false positive oestrus warnings. The main problem of automatic oestrus detection is to reduce the false positive alerts. In recent years several authors have combined different traits with the objective of improving detection rates. Best multivariate analyses results were found for combinations with activity. Further research should be performed using data from a commercial dairy farm. A comparison of different time series methods and multivariate analysis of traits would be useful.

The carboxylesterases/amidases of mammalian liver and their possible significance.

AbstractWith regard to the acyl moiety, carboxylesterases preferentially split esters of short-chain carboxylic esters. With most carboxylesterases the maximum of the reaction rate is found at an acyl chain length of C3 to C624,77,170,303 (see Section 5.4). However, there are some reports of carboxylesterases acting on medium- and long-chain fatty acid esters as well.143,189,252,253

NMR metabolomic analysis of dairy cows reveals milk glycerophosphocholine to phosphocholine ratio as prognostic biomarker for risk of ketosis.

Ketosis is a common metabolic disease in dairy cows. Diagnostic markers for ketosis such as acetone and beta-hydroxybutyric acid (BHBA) are known, but disease prediction remains an unsolved challenge. Milk is a steadily available biofluid and routinely collected on a daily basis. This high availability makes milk superior to blood or urine samples for diagnostic purposes. In this contribution, we show that high milk glycerophosphocholine (GPC) levels and high ratios of GPC to phosphocholine (PC) allow for the reliable selection of healthy and metabolically stable cows for breeding purposes. Throughout lactation, high GPC values are connected with a low ketosis incidence. During the first month of lactation, molar GPC/PC ratios equal or greater than 2.5 indicate a very low risk for developing ketosis. This threshold was validated for different breeds (Holstein-Friesian, Brown Swiss, and Simmental Fleckvieh) and for animals in different lactations, with observed odds ratios between 1.5 and 2.38. In contrast to acetone and BHBA, these measures are independent of the acute disease status. A possible explanation for the predictive effect is that GPC and PC are measures for the ability to break down phospholipids as a fatty acid source to meet the enhanced energy requirements of early lactation.

Human liver carboxylesterase: Purification and molecular properties☆

An unspecific carboxylesterase was purified 180-fold from acid-precipitated human liver microsomes. The final preparation was homogeneous on disc electrophoresis and polyacrylamide gel electrophoresis in the presence of 6.25 M urea at pH 3.2. A single symmetrical peak was also found on gel filtration and on velocity sedimentation in the analytical ultracentrifuge, whereas slight heterogeneity was observed on isoelectric focusing. The amino acid composition of the purified enzyme is presented. From the results the partial specific volume (0.745 ml × g−1) and the minimal molecular weight (60,000) could be calculated. Fingerprint maps of tryptic peptides from the carboxymethylated enzyme are shown. The molecular weight as determined by gel filtration, disc electrophoresis, and analytical ultracentrifugation is in the range of 181,000–186,000. For the molecular weight of the subunits a value of 61,500 has been obtained by sodium dodecylsulfate polyacrylamide gel electrophoresis. The equivalent weight of the enzyme has been estimated to be 62,500 from stoichiometry of its reaction with diethyl-p-nitrophenyl-phosphate. Partial cross-linking of the subunits with dimethyl suberimidate and subsequent sodium dodecylsulfate polyacrylamide gel electrophoresis yielded three bands with molecular weights of 60,000, 120,000, and 180,000. From these results it is concluded that human liver esterase is a trimeric protein. It is composed of three subunits of equal size, and there is one active site per subunit.

Evaluation of five lactation curve models fitted for fat:protein ratio of milk and daily energy balance

Selection for milk yield increases the metabolic load of dairy cows. The fat:protein ratio of milk (FPR) could serve as a measure of the energy balance status and might be used as a selection criterion to improve metabolic stability. The fit of different fixed and random regression models describing FPR and daily energy balance was tested to establish appropriate models for further genetic analyses. In addition, the relationship between both traits was evaluated for the best fitting model. Data were collected on a dairy research farm running a bull dam performance test. Energy balance was calculated using information on milk yield, feed intake per day, and live weight. Weekly FPR measurements were available. Three data sets were created containing records of 577 primiparous cows with observations from lactation d 11 to 180 as well as records of 613 primiparous cows and 96 multiparous cows with observations from lactation d 11 to 305. Five well-established parametric functions of days in milk (Ali and Schaeffer, Guo and Swalve, Wilmink, Legendre polynomials of third and fourth degree) were chosen for modeling the lactation curves. Evaluation of goodness of fit was based on the corrected Akaike information criterion, the Bayesian information criterion, correlation between the real observation and the estimated value, and on inspection of the residuals plotted against days in milk. The best model was chosen for estimation of correlations between both traits at different lactation stages. Random regression models were superior compared with the fixed regression models. In general, the Ali and Schaeffer function appeared most suitable for modeling both the fixed and the random regression part of the mixed model. The FPR is greatest in the initial lactation period when energy deficit is most pronounced. Energy balance stabilizes at the same point as the decrease in FPR stops. The inverted patterns indicate a causal relationship between the 2 traits. A common pattern was also observed for repeatabilities of both traits, with repeatabilities being largest at the beginning of lactation. Additionally, correlations between cow effects were closest at the beginning of lactation (r(c)=-0.43). The results support the hypothesis that FPR can serve as a suitable indicator for energy status, at least during the most metabolically stressful stage of lactation.

Short communication: Genetic relationships among daily energy balance, feed intake, body condition score, and fat to protein ratio of milk in dairy cows

Postpartum energy status is critically important to health and fertility, and it remains a major task to find suitable indicator traits for energy balance. Therefore, genetic parameters for daily energy balance (EB) and dry matter intake (DMI), weekly milk fat to protein ratio (FPR), and monthly body condition score (BCS) were estimated using random regression on data collected from 682 Holstein-Friesian primiparous cows recorded between lactation d 11 to 180. Average energy-corrected milk (ECM), EB, DMI, BCS, and FPR were 32.0 kg, 9.6 MJ of NE(L), 20.3 kg, 2.95, and 1.12, respectively. Heritability estimates for EB, DMI, BCS, and FPR ranged from 0.03 to 0.13, 0.04 to 0.19, 0.34 to 0.59, and 0.20 to 0.54. Fat to protein ratio was a more valid measure for EB in early lactation than DMI, BCS, or single milk components. Correlations between FPR and EB were highest at the beginning of lactation [genetic correlation (r(g)) = -0.62 at days in milk (DIM) 15] and decreased toward zero. Dry matter intake was the trait most closely correlated with EB in mid lactation (r(g) = 0.73 at DIM 120 and 150). Energy balance in early lactation was negatively correlated to EB in mid lactation. The same applied to DMI. Genetic correlations between FPR across lactation stages were all positive; the lowest genetic correlation (0.55) was estimated between the beginning of lactation and early mid lactation. Hence, to improve EB at the beginning of lactation, EB and indicator traits need to be recorded in early lactation. We concluded that FPR is an adequate indicator for EB during the energy deficit phase. Genetic correlations of FPR with ECM, fat percentage, and protein percentage showed that a reduction of FPR in early lactation would have a slightly negative effect on ECM, whereas milk composition would change in a desirable manner.

Improving oestrus detection by combination of activity measurements with information about previous oestrus cases

Abstract In this study, the potential benefit of combining the traits activity and period since last oestrus for oestrus detection was investigated. The simultaneous analyses of these traits in a fuzzy logic model should reflect the consideration of the dairy farmer regarding his judging of oestrus warnings. The analyses involved 862 cows, each with one verified oestrus case. Information about previous oestrus or inseminations were available for 373 cows. For comparison only, the trait activity was analysed in a preliminary investigation by an univariate fuzzy logic model. The sensitivity was 91.7% and the error rate was 34.6%. By considering the previous information in a multivariate fuzzy logic model, the sensitivity decreased to 87.9% and the error rate improved to 12.5%. The simultaneous analysis of cows with and without previous information in the oestrus detection model resulted in an increase in error rate to 23.8%, due to the high number of cows without previous information. The obtained results indicate that the information about previous oestrus cases is suitable for multivariate oestrus detection.

Analysis of feed intake and energy balance of high-yielding first lactating Holstein cows with fixed and random regression models.

At the dairy research farm Karkendamm, the individual roughage intake was measured since 1 September 2005 using a computerised scale system to estimate daily energy balances as the difference between energy intake and calculated energy requirements for lactation and maintenance. Data of 289 heifers with observations between the 11th and 180th day of lactation over a period of 487 days were analysed. Average energy-corrected milk yield, feed intake, live weight and energy balance were 31.8kg, 20.6kg, 584 kg and 13.6 MJ NEL (net energy lactation), respectively, per day. Fixed and random regression models were used to estimate repeatabilities, correlations between cow effects and genetic parameters. The resulting genetic correlations in different lactation stages demonstrate that feed intake and energy balance at the beginning and the middle of lactation are genetically different traits. Heritability of feed intake is low with h2=0.06 during the first days after parturition and increases in the middle of lactation, whereas the energy balance shows the highest heritability with h2=0.34 in the first 30 days of lactation. Genetic correlations between energy balance and feed intake and milk yield, respectively, illustrate that energy balance depends more on feed intake than on milk yield. Genetic correlation between body condition score and energy balance decreases rapidly within the first 100 days of lactation. Hence, to avoid negative effects on health and reproduction as consequences of strong energy deficits at the beginning of lactation, the energy balance itself should be measured and used as a selection criterion in this lactation stage. Since the number of animals is rather small for a genetic analysis, the genetic parameters have to be evaluated on a more comprehensive dataset.

Genetic parameters for serial, automatically recorded milkability and its relationship to udder health in dairy cattle.

Serial measurements of three milkability traits from two commercial dairy farms in Germany were used to estimate heritabilities and breeding values (BVs). Overall, 6352 cows in first, second and third lactations supplied 2 188 810 records based on daily values recorded from 1998 to 2003. Only the records between day 8 and day 305 after calving were considered. The estimated genetic correlations between different parities within the three milkability traits ranged from rg = 0.88 to 0.98, i.e. they were sufficiently high to warrant a repeatability model. The resulting estimated heritability coefficients were h2 = 0.42 for average milk flow, h2 = 0.56 for maximum milk flow and h2 = 0.38 for milking time. We analysed the genetic correlation between milkability and somatic cell score (SCS) and between milkability and the liability to mastitis, respectively, as the optimum milk flow for udder health is not well defined. There were 66 146 records with information on somatic cell count. Furthermore, 23 488 days of medical treatment for udder diseases were available, resulting in 2 600 302 days of observation in total. Heritabilities for the liability to mastitis, estimated with a test-day threshold model, were h2 = 0.19 and h2 = 0.13, depending on the data-recording period (first 50 days of lactation and first 305 days of lactation, respectively). With respect to the relationship between milkability and udder health, the results indicated a slight and linear correlation insofar as one can assume: the higher the milk flow, the worse the udder health. For this reason, bulls and cows with high BVs for milk flow should be excluded from breeding to avoid a deterioration of udder health. The establishment of a special data-recording scheme for functional traits such as milkability and mastitis on commercial dairy farms may be possible according to these results.

Genetic parameters for energy balance, fat /protein ratio, body condition score and disease traits in German Holstein cows

Various health problems in dairy cows have been related to the magnitude and duration of the energy deficit post partum. Energy balance indicator traits like fat/protein ratio in milk and body condition score could be used in selection programmes to help predicting breeding values for health traits, but currently there is a lack of appropriate genetic parameters. Therefore, genetic correlations among energy balance, fat/protein ratio, and body condition score, and mastitis, claw and leg diseases, and metabolic disorders were estimated using linear and threshold models on data from 1693 primiparous cows recorded within the first 180 days in milk. Average daily energy balance, milk fat/protein ratio and body condition score were 8 MJ NEL, 1.13 and 2.94, respectively. Disease frequencies (% cows with at least one case) were 24.6% for mastitis, 9.7% for metabolic disorders and 28.2% for claw and leg diseases. Heritability estimates were 0.06, 0.30 and 0.34 for energy balance, fat/protein ratio and body condition score, respectively. For the disease traits, heritabilities ranged between 0.04 and 0.15. The genetic correlations were, in general, associated with large standard errors, but, although not significant, the results suggest that an improvement of overall health can be expected if energy balance traits are included into future breeding programmes. A low fat/protein ratio might serve as an indicator for metabolic stability and health of claw and legs. Between body condition and mastitis, a significant negative correlation of -0.40 was estimated. The study provides a new insight into the role energy balance traits can play as auxiliary traits for robustness of dairy cows. It was concluded that both, fat/protein ratio and body condition score, are potential variables to describe how well cows can adapt to the challenge of early lactation. However, the genetic parameters should be re-estimated on a more comprehensive data set.