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Between- and within-herd variation in blood and milk biomarkers in Holstein cows in early lactation
- M. A. Krogh, M. Hostens, M. Salavati, C. Grelet, M. T. Sorensen, D. C. Wathes, C. P. Ferris, C. Marchitelli, F. Signorelli, F. Napolitano, F. Becker, T. Larsen, E. Matthews, F. Carter, A. Vanlierde, G. Opsomer, N. Gengler, F. Dehareng, M. A. Crowe, K. L. Ingvartsen, L. Foldager
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Both blood- and milk-based biomarkers have been analysed for decades in research settings, although often only in one herd, and without focus on the variation in the biomarkers that are specifically related to herd or diet. Biomarkers can be used to detect physiological imbalance and disease risk and may have a role in precision livestock farming (PLF). For use in PLF, it is important to quantify normal variation in specific biomarkers and the source of this variation. The objective of this study was to estimate the between- and within-herd variation in a number of blood metabolites (β-hydroxybutyrate (BHB), non-esterified fatty acids, glucose and serum IGF-1), milk metabolites (free glucose, glucose-6-phosphate, urea, isocitrate, BHB and uric acid), milk enzymes (lactate dehydrogenase and N-acetyl-β-D-glucosaminidase (NAGase)) and composite indicators for metabolic imbalances (Physiological Imbalance-index and energy balance), to help facilitate their adoption within PLF. Blood and milk were sampled from 234 Holstein dairy cows from 6 experimental herds, each in a different European country, and offered a total of 10 different diets. Blood was sampled on 2 occasions at approximately 14 days-in-milk (DIM) and 35 DIM. Milk samples were collected twice weekly (in total 2750 samples) from DIM 1 to 50. Multilevel random regression models were used to estimate the variance components and to calculate the intraclass correlations (ICCs). The ICCs for the milk metabolites, when adjusted for parity and DIM at sampling, demonstrated that between 12% (glucose-6-phosphate) and 46% (urea) of the variation in the metabolites’ levels could be associated with the herd-diet combination. Intraclass Correlations related to the herd-diet combination were generally higher for blood metabolites, from 17% (cholesterol) to approximately 46% (BHB and urea). The high ICCs for urea suggest that this biomarker can be used for monitoring on herd level. The low variance within cow for NAGase indicates that few samples would be needed to describe the status and potentially a general reference value could be used. The low ICC for most of the biomarkers and larger within cow variation emphasises that multiple samples would be needed - most likely on the individual cows - for making the biomarkers useful for monitoring. The majority of biomarkers were influenced by parity and DIM which indicate that these should be accounted for if the biomarker should be used for monitoring.
Potential of milk mid-IR spectra to predict metabolic status of cows through blood components and an innovative clustering approach
- C. Grelet, A. Vanlierde, M. Hostens, L. Foldager, M. Salavati, K. L. Ingvartsen, M. Crowe, M. T. Sorensen, E. Froidmont, C. P. Ferris, C. Marchitelli, F. Becker, T. Larsen, F. Carter, GplusE Consortium, F. Dehareng
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Unbalanced metabolic status in the weeks after calving predisposes dairy cows to metabolic and infectious diseases. Blood glucose, IGF-I, non-esterified fatty acids (NEFA) and β-hydroxybutyrate (BHB) are used as indicators of the metabolic status of cows. This work aims to (1) evaluate the potential of milk mid-IR spectra to predict these blood components individually and (2) to evaluate the possibility of predicting the metabolic status of cows based on the clustering of these blood components. Blood samples were collected from 241 Holstein cows on six experimental farms, at days 14 and 35 after calving. Blood samples were analyzed by reference analysis and metabolic status was defined by k-means clustering (k=3) based on the four blood components. Milk mid-IR analyses were undertaken on different instruments and the spectra were harmonized into a common standardized format. Quantitative models predicting blood components were developed using partial least squares regression and discriminant models aiming to differentiate the metabolic status were developed with partial least squares discriminant analysis. Cross-validations were performed for both quantitative and discriminant models using four subsets randomly constituted. Blood glucose, IGF-I, NEFA and BHB were predicted with respective R2 of calibration of 0.55, 0.69, 0.49 and 0.77, and R2 of cross-validation of 0.44, 0.61, 0.39 and 0.70. Although these models were not able to provide precise quantitative values, they allow for screening of individual milk samples for high or low values. The clustering methodology led to the sharing out of the data set into three groups of cows representing healthy, moderately impacted and imbalanced metabolic status. The discriminant models allow to fairly classify the three groups, with a global percentage of correct classification up to 74%. When discriminating the cows with imbalanced metabolic status from cows with healthy and moderately impacted metabolic status, the models were able to distinguish imbalanced group with a global percentage of correct classification up to 92%. The performances were satisfactory considering the variables are not present in milk, and consequently predicted indirectly. This work showed the potential of milk mid-IR analysis to provide new metabolic status indicators based on individual blood components or a combination of these variables into a global status. Models have been developed within a standardized spectral format, and although robustness should preferably be improved with additional data integrating different geographic regions, diets and breeds, they constitute rapid, cost-effective and large-scale tools for management and breeding of dairy cows.
Evidence for placental compensation in cattle
- M. Van Eetvelde, M. M. Kamal, M. Hostens, L. Vandaele, L. O. Fiems, G. Opsomer
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Prenatal development is known to be extremely sensitive to maternal and environmental challenges. In this study, we hypothesize that body growth and lactation during gestation in cattle reduce nutrient availability for the pregnant uterus, with consequences for placental development. Fetal membranes of 16 growing heifers and 27 fully grown cows of the Belgian Blue (BB) breed were compared to determine the effect of body growth on placental development. Furthermore, the fetal membranes of 49 lactating Holstein Friesian (HF) cows and 27 HF heifers were compared to study the impact of dam lactation compared to dam body growth. After parturition, calf birth weight and body measurements of dam and calf were recorded, as well as weight of total fetal membranes, cotyledons and intercotyledonary membranes. All cotyledons were individually measured to calculate both the surface of each individual cotyledon and the total cotyledonary surface per placenta. Total cotyledonary surface was unaffected by breed or the breed×parity interaction. Besides a 0.3 kg lower cotyledonary weight (P=0.007), heifer placentas had a smaller total cotyledonary surface compared with placentas of cows (0.48±0.017 v. 0.54±0.014 m2, respectively, P<0.001). Within the BB breed, fetal membranes of heifers had a 1.5 kg lower total weight and 1.0 kg lower intercotyledonary membrane weight (P<0.005) compared with cows. A cotyledon number of only 91±5.4 was found in multiparous BB dams, while growing BB heifers had a higher cotyledon number (126±6.7, P<0.001), but a greater proportion of smaller cotyledons (<40 cm2). Within the HF breed, no parity effect on intercotyledonary membrane weight, cotyledon number and individual cotyledonary surface was found. Placental efficiency (calf weight/total cotyledonary surface) was similar in HF and BB heifers but significantly higher in multiparous BB compared with multiparous HF dams (106.0±20.45 v. 74.3±12.27 kg/m2, respectively, P<0.001). Furthermore, a seasonal effect on placental development was found, with winter and spring placentas having smaller cotyledons than summer and fall placentas (P<0.001). Main findings of the present study are that lactation and maternal growth during gestation entail a comparable nutrient diverting constraint, which might alter placental development. However, results suggest that the placenta is able to manage this situation through two potential compensation mechanisms. In early pregnancy the placenta might cope by establishing a higher number of cotyledons, while in late gestation a compensatory expansion of the cotyledonary surface is suggested to meet the nutrient demand of the fetus.
Environmental factors and dam characteristics associated with insulin sensitivity and insulin secretion in newborn Holstein calves
- M. M. Kamal, M. Van Eetvelde, H. Bogaert, M. Hostens, L. Vandaele, M. Shamsuddin, G. Opsomer
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The objective of the present retrospective cohort study was to evaluate potential associations between environmental factors and dam characteristics, including level of milk production during gestation, and insulin traits in newborn Holstein calves. Birth weight and gestational age of the calves at delivery were determined. On the next day, heart girth, wither height and diagonal length of both the calves and their dams were measured. Parity, body condition score and age at calving were recorded for all dams. For the cows, days open before last gestation, lactation length (LL), length of dry period (DP) and calving interval were also calculated. The magnitude and shape of the lactation curve both quantified using the MilkBot model based on monthly milk weights, were used to calculate the amount of milk produced during gestation. Using the same procedure, cumulative milk production from conception to drying off (MGEST) was calculated. A blood sample was collected from all calves (n=481; 169 born to heifers and 312 born to cows) at least 5 h after a milk meal on day 3 of life to measure basal glucose and insulin levels. In addition, an intravenous glucose-stimulated insulin secretion test was performed in a subset of the calves (n=316). After descriptive analysis, generalized linear mixed models were used to identify factors that were significantly associated with the major insulin traits (Insb, basal insulin level; QUICKI, quantitative insulin sensitivity check index; AIR, acute insulin response; DI, disposition index) of the newborn calves. The overall average birth weight of the calves was 42.7±5.92 kg. The insulin traits were significantly associated with gender and season of birth when data of all calves were analyzed. In addition, the insulin traits in calves born to cows were significantly associated with MGEST, DP and LL. The Insb was estimated to be higher in calves born to the cows having passed a higher MGEST (P=0.076) and longer DP (P=0.034). The QUICKI was estimated to be lower in calves born to the cows having passed a higher MGEST (P=0.030) and longer DP (P=0.058). Moreover, the AIR (P=0.009) and DI (P=0.049) were estimated to be lower in male compared with female calves. Furthermore, the AIR (P=0.036) and DI (P=0.039) were estimated to be lower in calves born to cows having passed a longer LL. The decisive effects of MGEST, DP and LL in cows on the insulin traits of their calves may provide a basis for developing managerial interventions to improve metabolic health of the offspring.