Mid-infrared prediction of lactoferrin content in bovine milk: potential indicator of mastitis

Abstract

Lactoferrin (LTF) is a milk glycoprotein favorably associated with the immune system of dairy cows. Somatic cell count is often used as an indicator of mastitis in dairy cows, but knowledge on the milk LTF content could aid in mastitis detection. An inexpensive, rapid and robust method to predict milk LTF is required. The aim of this study was to develop an equation to quantify the LTF content in bovine milk using mid-infrared (MIR) spectrometry. LTF was quantified by enzyme-linked immunosorbent assay (ELISA), and all milk samples were analyzed by MIR. After discarding samples with a coefficient of variation between 2 ELISA measurements of more than 5% and the spectral outliers, the calibration set consisted of 2499 samples from Belgium (n 5 110), Ireland (n 5 1658) and Scotland (n 5 731). Six statistical methods were evaluated to develop the LTF equation. The best method yielded a cross-validation coefficient of determination for LTF of 0.71 and a cross-validation standard error of 50.55 mg/l of milk. An external validation was undertaken using an additional dataset containing 274 Walloon samples. The validation coefficient of determination was 0.60. To assess the usefulness of the MIR predicted LTF, four logistic regressions using somatic cell score (SCS) and MIR LTF were developed to predict the presence of mastitis. The dataset used to build the logistic regressions consisted of 275 mastitis records and 13 507 MIR data collected in 18 Walloon herds. The LTF and the interaction SCS 3 LTF effects were significant (P , 0.001 and P 5 0.02, respectively). When only the predicted LTF was included in the model, the prediction of the presence of mastitis was not accurate despite a moderate correlation between SCS and LTF (r 5 0.54). The specificity and the sensitivity of models were assessed using Walloon data (i.e. internal validation) and data collected from a research herd at the University of Wisconsin -Madison (i.e. 5886 Wisconsin MIR records related to 93 mastistis events -external validation). Model specificity was better when LTF was included in the regression along with SCS when compared with SCS alone. Correct classification of non-mastitis records was 95.44% and 92.05% from Wisconsin and Walloon data, respectively. The same conclusion was formulated from the Hosmer and Lemeshow test. In conclusion, this study confirms the possibility to quantify an LTF indicator from milk MIR spectra. It suggests the usefulness of this indicator associated to SCS to detect the presence of mastitis. Moreover, the knowledge of milk LTF could also improve the milk nutritional quality.

Short communication: Development of an equation for estimating methane emissions of dairy cows from milk Fourier transform mid-infrared spectra by using reference data obtained exclusively from respiration chambers

“…In the present analysis, only records from HO cows collected between 5 and 365 DIM (the range of modified Legendre polynomials) in the first 3 lactations were considered, leading to a total of 1,679,728 standardized spectral records. To ensure that the spectral variability of the milk recording samples was covered by the equation, only the spectra with a standardized Mahalanobis distance (global H distance) lower than 3 were used in this study (e.g., Shenk and Westerhaus, 1991; Soyeurt et al, 2012). During this process a moderate amount (9.8%) of the spectra was removed.…”

Milk mid-infrared spectra enable prediction of lactation-stage-dependent methane emissions of dairy cattle within routine population-scale milk recording schemes

“…To discard spectra too spectrally different from spectra used for the calibration process, standardised Mahalanobis distance (global H distance; GH) between each spectra and spectra used for the calibration was calculated and spectra with a GH value greater than 3 were deleted from this study (e.g. Shenk and Westerhaus 1991;Soyeurt et al 2012). Methane prediction lower than 150 g/day and higher than 950 g/ day were considered as outliers (Vanlierde et al 2015) and were excluded from this study (0.07% of the 2 049 366 spectra with a GH value lower than 3).…”

Discovery and Validation of Immunological Biomarkers in Milk for Health Monitoring of Dairy Cows - Results from a Multiomics Approach

“…Suitable potential test formats are the lateral-flow assay (i.e. dipstick), mid-infrared measurement [16], high-throughput fluorescence polarization immunoassay [79] or the novel concept for a protein microarray on smart-phones [80].…”

“…Elevated serum concentrations of serum amyloid A (SAA), fibrinogen (FG) and haptoglobin (HP) can indicate acute or chronic inflammation [11][12][13]. In the milk HP, SAA or lactoferrin (LTF) are well-known indicators for clinical or subclinical mastitis [14][15][16] and more recently discussed as indicators for extra-mammary diseases [17,18].…”