scholarly journals Fourier transform infrared spectroscopy of milk samples as a tool to estimate energy balance, energy- and dry matter intake in lactating dairy cows

2020 ◽  
pp. 1-8
Author(s):  
Amira Rachah ◽  
Olav Reksen ◽  
Nils Kristian Afseth ◽  
Valeria Tafintseva ◽  
Sabine Ferneborg ◽  
...  
Keyword(s):  
Dairy Cows ◽  
Dry Matter ◽  
External Validation ◽  
Ftir Spectra ◽  
Dry Matter Intake ◽  
Energy Status ◽  
Test Set ◽  
Milk Samples ◽  
External Test ◽  
Body Energy

Abstract The objective of the study was to evaluate the potential of Fourier transform infrared spectroscopy (FTIR) analysis of milk samples to predict body energy status and related traits (energy balance (EB), dry matter intake (DMI) and efficient energy intake (EEI)) in lactating dairy cows. The data included 2371 milk samples from 63 Norwegian Red dairy cows collected during the first 105 days in milk (DIM). To predict the body energy status traits, calibration models were developed using Partial Least Squares Regression (PLSR). Calibration models were established using split-sample (leave-one cow-out) cross-validation approach and validated using an external test set. The PLSR method was implemented using just the FTIR spectra or using the FTIR together with milk yield (MY) or concentrate intake (CONCTR) as predictors of traits. Analyses were conducted for the entire first 105 DIM and separately for the two lactation periods: 5 ≤ DIM ≤ 55 and 55 < DIM ≤ 105. To test the models, an external validation using an independent test set was performed. Predictions depending on the parity (1st, 2nd and 3rd-to 6th parities) in early lactation were also investigated. Accuracy of prediction (r) for both cross-validation and external test set was defined as the correlation between the predicted and observed values for body energy status traits. Analyzing FTIR in combination with MY by PLSR, resulted in relatively high r-values to estimate EB (r = 0.63), DMI (r = 0.83), EEI (r = 0.84) using an external validation. Only moderate correlations between FTIR spectra and traits like EB, EEI and dry matter intake (DMI) have so far been published. Our hypothesis was that improvements in the FTIR predictions of EB, EEI and DMI can be obtained by (1) stratification into different stages of lactations and different parities, or (2) by adding additional information on milking and feeding traits. Stratification of the lactation stages improved predictions compared with the analyses including all data 5 ≤ DIM ≤105. The accuracy was improved if additional data (MY or CONCTR) were included in the prediction model. Furthermore, stratification into parity groups, improved the predictions of body energy status. Our results show that FTIR spectral data combined with MY or CONCTR can be used to obtain improved estimation of body energy status compared to only using the FTIR spectra in Norwegian Red dairy cattle. The best prediction results were achieved using FTIR spectra together with MY for early lactation. The results obtained in the study suggest that the modeling approach used in this paper can be considered as a viable method for predicting an individual cow's energy status.

Relationships among macro-minerals, other selected serum markers of bone profile and milk components of dairy cows during late-lactation

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Ryszard Mordak ◽  
Zbigniew Dobrzański ◽  
Robert Kupczyński
Keyword(s):  
Dairy Cows ◽  
Milk Fat ◽  
Dry Matter ◽  
Inorganic Phosphorus ◽  
Serum Markers ◽  
Laboratory Diagnostics ◽  
Lactation Period ◽  
Milk Samples ◽  
Milk Components ◽  
Macro Mineral

AbstractTesting blood and milk parameters as well as analysing the relationships among these markers is very useful for monitoring the internal homeostasis and health in high-yielding dairy cows during various production periods. The aim of the study was to assess the correlations (relationships) among macro-minerals, such as calcium (Ca), inorganic phosphorus (P), magnesium (Mg), other selected bone profile markers, such as total protein (TP), albumin, activity of alkaline phosphatase (ALP) measured in serum and selected milk components such as number of somatic cells (SCC), colony-forming units (CFU), milk fat (MF), milk protein (MP), milk lactose (ML), dry matter (DM), non-fat dry matter (FDM) and milk production in late-lactation cows. Both blood and milk samples were collected from 11 clinically healthy milking cows during the late-lactation period. The cows were examined once a day for 3 consecutive days resulting in 33 sets of blood and milk samples for laboratory and statistical analysis. Significant correlations were observed between: Mg and MP, Mg and FDM, ALP and SCC, TP and SCC, TP and MP, TP and FDM, albumin and MP, albumin and FDM, P and Mg, Mg and albumin, and between TP and albumin. When monitoring macro-mineral homeostasis and mammary gland health, especially in intensively fed high-yielding dairy cows correlations between these markers should be considered. The revealed correlations can allow for deeper comparative laboratory diagnostics of homeostasis and can be especially useful for laboratory monitoring of the potential risk of subclinical macro-mineral deficiency in high-yielding dairy cows.

scholarly journals Predicting Daily Dry Matter Intake Using Feed Intake of First Two Hours after Feeding in Mid and Late Lactation Dairy Cows with Fed Ration Three Times Per Day

Animals ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 104
Author(s):  
Shulin Liang ◽  
Chaoqun Wu ◽  
Wenchao Peng ◽  
Jian-Xin Liu ◽  
Hui-Zeng Sun
Keyword(s):  
Dairy Cows ◽  
Milk Yield ◽  
Dry Matter ◽  
Prediction Equation ◽  
Dry Matter Intake ◽  
Validation Dataset ◽  
Nutrient Requirements ◽  
Independent Dataset ◽  
Lactating Dairy Cows ◽  
Proposed Model

The objective of this study was to evaluate the feasibility of using the dry matter intake of first 2 h after feeding (DMI-2h), body weight (BW), and milk yield to estimate daily DMI in mid and late lactating dairy cows with fed ration three times per day. Our dataset included 2840 individual observations from 76 cows enrolled in two studies, of which 2259 observations served as development dataset (DDS) from 54 cows and 581 observations acted as the validation dataset (VDS) from 22 cows. The descriptive statistics of these variables were 26.0 ± 2.77 kg/day (mean ± standard deviation) of DMI, 14.9 ± 3.68 kg/day of DMI-2h, 35.0 ± 5.48 kg/day of milk yield, and 636 ± 82.6 kg/day of BW in DDS and 23.2 ± 4.72 kg/day of DMI, 12.6 ± 4.08 kg/day of DMI-2h, 30.4 ± 5.85 kg/day of milk yield, and 597 ± 63.7 kg/day of BW in VDS, respectively. A multiple regression analysis was conducted using the REG procedure of SAS to develop the forecasting models for DMI. The proposed prediction equation was: DMI (kg/day) = 8.499 + 0.2725 × DMI-2h (kg/day) + 0.2132 × Milk yield (kg/day) + 0.0095 × BW (kg/day) (R2 = 0.46, mean bias = 0 kg/day, RMSPE = 1.26 kg/day). Moreover, when compared with the prediction equation for DMI in Nutrient Requirements of Dairy Cattle (2001) using the independent dataset (VDS), our proposed model shows higher R2 (0.22 vs. 0.07) and smaller mean bias (−0.10 vs. 1.52 kg/day) and RMSPE (1.77 vs. 2.34 kg/day). Overall, we constructed a feasible forecasting model with better precision and accuracy in predicting daily DMI of dairy cows in mid and late lactation when fed ration three times per day.

scholarly journals Prepartum 2,4-Thiazolidinedione Alters Metabolic Dynamics and Dry Matter Intake of Dairy Cows

2007 ◽  
Vol 90 (8) ◽  
pp. 3660-3670 ◽  
Author(s):  
K.L. Smith ◽  
S.E. Stebulis ◽  
M.R. Waldron ◽  
T.R. Overton
Keyword(s):  
Dairy Cows ◽  
Dry Matter ◽  
Dry Matter Intake

scholarly journals Genetic parameters of forage dry matter intake and milk produced from forage in Swedish Red and Holstein dairy cows

2021 ◽  
Vol 104 (4) ◽  
pp. 4424-4440
Author(s):  
Getinet Mekuriaw Tarekegn ◽  
Johanna Karlsson ◽  
Cecilia Kronqvist ◽  
Britt Berglund ◽  
Kjell Holtenius ◽  
...  
Keyword(s):  
Dairy Cows ◽  
Dry Matter ◽  
Genetic Parameters ◽  
Dry Matter Intake ◽  
Holstein Dairy Cows

scholarly journals Determination of organic components of milk as method for evaluating energy status of dairy cows

2010 ◽  
Vol 64 (1-2) ◽  
pp. 21-32
Author(s):  
Djordje Savic ◽  
D. Matarugic ◽  
N. Delic ◽  
D. Kasagic ◽  
M. Stojanovic
Keyword(s):  
Dairy Cows ◽  
Milk Fat ◽  
Protein Concentration ◽  
High Yield ◽  
Energy Status ◽  
Milk Samples ◽  
Organic Components ◽  
Physiological Values ◽  
The Individual

The objective of the investigations described in this work was to determine the energy status and to make recommendations for correcting the cow diet at a farm of high-yield dairy cows, on the grounds of values for the concentration of organic components of milk and their ratios in individual milk samples. A total of 147 cows were examined, including 97 in the first and 50 in the second lactation. Average concentrations of milk fat and urea were within the physiological values. Namely, the milk fat concentration in cows in the first lactation was 38.88?5.07 g/l, and it was 36.47?4.82 g/l in cows in the second lactation, while the urea concentration in cows in the first lactation 3.16?0.58 mmol/l and it was 3.72?0.64 mmol/l in cows in the second lactation. The protein concentration in both groups of cows was below the physiological values, being 30.33?2.35 g/l in cows in the first lactation and 30.17?2.27 g/l in cows in the second lactation. Based on the ratio of urea and protein concentrations, as well as of fat and proteins in the individual milk samples, it was concluded that in most examined cows, both in those in the first and those in the second lactation, there is a deficit of energy, along with a deficit or relative surplus of proteins. On the grounds of the obtained results, recommendations were given for correcting the feed rations in the coming period. .

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