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A novel method for the quantification of bovine colostral immunoglobulin G using infrared spectroscopy
Accepted Manuscript A novel method for the quantification of bovine colostral immunoglobulin G using infrared spectroscopy Ibrahim Elsohaby, J Trenton McClure, Siyuan Hou, Christopher B. Riley, R. Anthony Shaw, Gregory P. Keefe PII:
S0958-6946(15)00159-4
DOI:
10.1016/j.idairyj.2015.08.004
Reference:
INDA 3868
To appear in:
International Dairy Journal
Received Date: 27 April 2015 Revised Date:
9 August 2015
Accepted Date: 12 August 2015
Please cite this article as: Elsohaby, I., McClure, J.T., Hou, S., Riley, C.B., Shaw, R.A., Keefe, G.P., A novel method for the quantification of bovine colostral immunoglobulin G using infrared spectroscopy, International Dairy Journal (2015), doi: 10.1016/j.idairyj.2015.08.004. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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A novel method for the quantification of bovine colostral immunoglobulin G using infrared
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spectroscopy
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Ibrahim Elsohaby a,b*, J Trenton McClure a, Siyuan Hou a, Christopher B. Riley a,c, R. Anthony
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Shaw d, Gregory P. Keefe a
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a
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Island, 550 University Avenue, Charlottetown, PEI C1A 4P3, Canada
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b
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University, Zagazig city 44511, Sharkia Province, Egypt
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c
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4442, New Zealand
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d
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1Y6, Canada
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Infectious Diseases, Department of Animal Medicine, Faculty of Veterinary Medicine, Zagazig
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Institute of Veterinary, Animal and Biomedical Sciences, Massey University, Palmerston North
National Research Council of Canada, Medical Devices Portfolio, Winnipeg, Manitoba R3B
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Department of Health Management, Atlantic Veterinary College, University of Prince Edward
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* Corresponding author. Tel.: +1 902 566-0995
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E-mail address: [email protected] (I. Elsohaby)
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Abstract
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Transmission infrared (IR) spectroscopy, in combination with partial least squares (PLS)
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regression, was used as the basis to develop a new method to quantify IgG in bovine colostrum.
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Colostrum samples (n = 250) were tested simultaneously by the reference radial
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immunodiffusion (RID) assay and IR spectroscopy. Colostral IgG concentrations obtained by
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RID assay were linked to pre-processed spectra and divided into two sets, i.e., calibration and
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test. PLS regression was applied to the calibration set and calibration models were developed,
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and the test set was used to assess the accuracy of the analytical method. The Pearson and
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concordance correlations between test set IgG concentrations as determined by the IR assay and
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the RID assay were 0.91. The Bland-Altman plot showed no evidence of systematic bias between
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IR and RID methods. Transmission IR spectroscopy is an effective method for quantification of
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bovine colostral IgG concentration and for assessment of colostrum quality.
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1.
Introduction
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Colostrum is the initial secretion from the mammary gland after parturition, and is an important source of immunity and nutrition for newborn calves (Bielmann et al., 2010).
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Colostrum contains a high concentration of immunoglobulins (particularly IgG1) that are
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absorbed by calves during the first 24 h of life (Baumrucker, Burkett, Magliaro-Macrina, &
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Dechow, 2010). Calves that fail to ingest and absorb a sufficient amount of colostral IgG are
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classified as suffering from failure of transfer of passive immunity (FTPI) (Godden, 2008). As a
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result of FTPI, a calf’s susceptibility to pathogenic infection, morbidity and mortality are
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increased (Donovan, Dohoo, Montgomery, & Bennett, 1998; Robison, Stott, & DeNise, 1988;
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Virtala, Gröhn, Mechor, & Erb, 1999). There are many factors associated with FTPI in newborn
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calves, the most important relating to colostrum management practices, including colostrum
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quality, volume, cleanliness and time of feeding after birth (Beam et al., 2009; Godden, 2008).
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Therefore, measuring IgG concentration in colostrum prior to feeding is a useful management
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tool that may be used to improve calf health.
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Several techniques have been developed to measure IgG concentration in colostrum,
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including laboratory-based techniques such as the radial immunodiffusion (RID) assay
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(McBeath, Penhale, & Logan, 1971), enzyme-linked immunosorbent assay (ELISA) (Gelsinger,
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Jones, & Heinrichs, 2015), immunoassays (Indyk & Filonzi, 2003), high-performance liquid
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chromatography (HPLC) (Dolman & Thorpe, 2002), affinity liquid chromatography (Abernethy
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& Otter, 2010) and electrophoresis (Page & Thorpe, 2002), and farm-based techniques such as
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using a colostrometer (Bartier, Windeyer, & Doepel, 2015), refractometry (Bielmann et al., 2010)
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and colostrum colour (Arguello, Castro, & Capote, 2005). The RID assay is the most widely
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accepted reference method for quantification of colostral IgG (McBeath et al., 1971). However,
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this assay has significant drawbacks, which are shared by most laboratory methods, including the
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time it takes to obtain the result (18-24 h), lack of automation, utilisation of reagents with a short
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shelf-life, high cost (Bielmann et al., 2010; Riley, McClure, Low-Ying, & Shaw, 2007), and
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variability among kits due to inaccuracies associated with the internal standards (Ameri &
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Wilkerson, 2008).
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On-farm methods such as using a colostrometer and refractometry have been used to
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differentiate between good and poor quality colostrum (Bartier et al., 2015; Bielmann et al.,
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2010). A colostrometer measures the specific gravity of colostrum, and readings have a high
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correlation with IgG concentrations as determined by RID (Fleenor & Stott, 1980).
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Unfortunately, the colostrometer has several drawbacks, as it is fragile and needs to be cleaned
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before each use, and outputs are very sensitive to colostrum temperature (Bartier et al., 2015;
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Bielmann et al., 2010); these factors limit its use. For example, only 4% of farms in Quebec
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were reported to use the colostrometer consistently (Vasseur et al., 2010). Unlike the
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colostrometer, refractometry is not sensitive to temperature, but has shown a lower correlation
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with the reference RID method (Bartier et al., 2015; Bielmann et al., 2010). Therefore, an
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accurate, simple, rapid and cost-effective method to measure IgG content that overcomes the
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limitations of the reference and other methods is essential for assessing colostrum quality.
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The measurement of molecular concentrations in biological fluids by transmission
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infrared (IR) spectroscopy has a number of advantages that overcome the drawbacks associated
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with the other analytical methods. It is rapid (turnaround time is ~5 min), requires minimal
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sample preparation, and one spectrum can be used for quantitative analysis of several
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components (Shaw, Kotowich, Leroux, & Mantsch, 1998; Shaw & Mantsch, 1999, 2000). For these
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reasons, transmission IR spectroscopy in combination with partial least squares (PLS) regression
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has been widely used for quantitative and qualitative analysis of biological specimens in human
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and veterinary medicine (Shaw & Mantsch, 2000; Shaw et al., 2008). For example, this approach
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provides the basis for simultaneously quantifying total protein, glucose, albumin, triglyceride,
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cholesterol, and urea in human serum samples (Budinova, Salva, & Volka, 1997; Shaw et al.,
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1998; Ward, Haaland, Robinson, & Eaton, 1989). In animal health, analytical methods based upon
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transmission IR spectroscopy have been proven useful for milk analysis including the
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measurement of its protein (Rutten, Bovenhuis, Heck & van Arendonk, 2011a, b) and mineral
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composition (Soyeurt et al., 2009), determination of animal feed composition, the study of the
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kinetics of nutrient degradation in the rumen (Herrero, Jessop, Fawcett, Murray, & Dent, 1997;
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Ohlsson, Houmøller, Weisbjerg, Lund, & Hvelplund, 2007), the quantification of IgG concentrations
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in bovine (Elsohaby et al., 2014), equine (Riley et al., 2007) and alpaca sera (Burns et al., 2014),
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screening for metabolic diseases such as ketosis (Hansen, 1999), and for the detection of
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foodborne pathogens (Davis & Mauer, 2010) and bovine spongiform encephalopathy (BSE)
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(Lasch et al. 2003).
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To the authors’ knowledge, no study has been published that describes the use of
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transmission IR spectroscopy in combination with PLS regression as the basis for quantifying
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colostral IgG. The objectives of this study were to develop a transmission IR-based analytical
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method for the quantification of bovine colostral IgG, and to demonstrate the utility of the new
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method for the assessment of poor quality colostrum (IgG < 50 g L-1).
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2.
Material and methods
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2.1.
Colostrum samples
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Post-partum milking colostrum samples were collected from 251 Holstein dairy cows
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originating from 7 commercial dairy herds in Prince Edward Island, Canada. Of these, 168
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samples were collected between June and October 2013, while the remaining 83 samples were
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collected between May and August 2014. At each farm, the owner collected 50 mL of colostrum
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in a vial labelled with the identity of the cow and date of sample collection, and then stored these
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on the farm at –20 °C until transportation to the Maritime Quality Milk Laboratory, University of
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Prince Edward Island (UPEI), where samples were stored at –80 °C for later batch analysis.
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Animal care and ethics approval by the Animal Care Committee at UPEI was obtained for all
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procedures followed the Canadian Council on Animal Care guidelines (CCAC, 2009).
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2.2.
Radial immunodiffusion assay for IgG
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Colostral IgG concentrations were measured by the reference method using a commercial Bovine IgG RID Kit in accordance with the manufacturer’s instructions (Triple J Farms;
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Bellingham, WA, USA) (Elsohaby et al., 2014). Samples thawed at room temperature (20–24
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°C) were vortexed at 2700 rpm for 10 s, diluted (1:3) in deionised sterile water, and revortexed at
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2700 rpm for 10 s. The RID standards, from the same lot, provided in the kit, were used
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undiluted for all assays. Each sample and standard was tested in replicates of five to generate an
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average IgG concentration value. Diluted samples (1:3) with IgG concentrations greater than the
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upper standard value (>30 g L-1), were further diluted (1:5) with deionised sterile water and
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retested.
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2.3.
Transmission infra-red spectroscopy
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Thawed colostrum samples were diluted (1:3) with deionised sterile water and mixed by
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vortexing at a maximum of 2700 rpm for 10 s to ensure a uniform dispersion of colostral
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components. Each diluted colostrum sample was tested as previously described in replicates of
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six (Riley et al., 2007). A total of 1506 (251 samples × 6 replicates/sample) spectra were
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collected over the wave number range of 4000–400 cm-1 with a nominal resolution of 4 cm-1, co-
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adding 512 scans for each spectrum.
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2.4.
Spectral analysis
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2.4.1. Spectral pre-processing
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Absorbance spectra were converted into printable format (PRN) (GRAMS/AI version 7.02, Thermo Fisher Scientific, Waltham, MA, USA), imported into MATLAB® (MathWorks
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R2012b, Natick, MA, USA), and further data analysis performed using scripts written by the
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authors. The Savitzky–Golay method was used on first order derivative spectra (2nd order
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polynomial function with nine point smoothing) (Savitzky & Golay, 1964) and then a vector
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normalization procedure performed (Barnes, Dhanoa, & Lister, 1989, 2004) to reduce the effect of
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light scattering. Only the 3700–2600 cm−1 and 1800–1300 cm−1 wavenumber regions were
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selected for further analysis (Elsohaby et al., 2014). Spectrum outlier detection was carried out
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using Dixon’s Q-test (Dean & Dixon, 1951; Rorabacher, 1991) at each wave number with a
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confidence level of 95%. Where over 50% of the absorbance values were detected as outliers
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with an individual spectrum, it was excluded from further analysis, and the average of the
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remaining spectra for each sample used for subsequent analysis.
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2.4.2. Calibration model development
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A multivariate regression method (PLS) was used to create a calibration model to relate
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the IR spectra to the colostral IgG concentrations obtained by the RID method. Diluted samples
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with IgG concentrations outside of the manufacturer’s stated performance range for the RID
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assay were excluded from further analysis (n = 1). Data from the remaining 250 samples were
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used for building and validation of the analytical method. The IgG concentrations obtained by
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the RID method were linked to their corresponding pre-processed IR spectra, and then divided
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into test and calibration sets. The test set of colostral spectra (n = 83) was identified by sorting all
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the samples according to their corresponding RID IgG values. The spectrum of every third
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colostrum sample was selected as a member of the test set; the remainder (n=167) were assigned
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to the calibration set. This approach ensured that the test set encompassed the full range of IgG
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values in evaluating the predictive performance of the new analytical method. The calibration set
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(n = 167) was further split randomly into training (n = 84) and validation (n = 83) data sets for
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model development.
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As previously described, PLS regression was applied to the training set to develop 30 trial
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calibration models with the number of PLS factors ranging from 1 to 30 (Elsohaby et al., 2014).
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There were 10,000 randomly assigned splits of the calibration data into new training and
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validation sets for evaluation. The root mean squared error for the Monte Carlo cross validation
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value (RMMCCV) (Picard & Cook, 1984; Xu & Liang, 2001) was calculated for each of the 30
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trial calibration models, and the optimal number of PLS factors was chosen based on the lowest
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RMMCCV value. Once the number of PLS factors had been determined, the training and
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validation sets were recombined to build the final calibration model (Elsohaby et al., 2014).
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2.4.3. Prediction of colostral IgG concentrations
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The predictive performance of the final calibration model was assessed using the
independent spectral data test set (n = 83). Scatter plots, Pearson correlation coefficients and
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concordance correlation coefficients (Lin, 1989) were calculated to assess the level of agreement
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between IgG concentrations obtained by the reference RID method and those predicted by the
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IR-based assay for the calibration and test data sets. The difference and interchangeability
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between the RID and IR assays for the test set was further evaluated by the Bland-Altman plot
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(Altman & Bland, 1983; Bland & Altman, 1995).
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The precision of both the RID and IR methods was investigated using the test data set. The mean and standard deviation (SD) were calculated from the replicate measurements for each
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colostrum sample, and from these a modified coefficient of variation (CV* = CV (1 + (1/4n))
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where CV* is considered an unbiased estimation of CV for small sample size; n = 6 for IR assay;
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n = 5 for RID assay) was determined for each sample (Salkind, 2010), and for each analytical
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method. The CV* values were then plotted against the corresponding mean IgG concentrations.
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The IR-based assay was further assessed using the ratio of predictive deviation (RPD: the
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RID-determined IgG concentration standard deviation, ratioed to the root mean squared error of
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prediction (RMSEP) for the IR-based assay), and the range error ratio (RER: the RID-determined
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IgG concentration range, ratioed to the RMSEP for the IR-based assay) (Williams & Sobering,
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1996). According to this framework, a RPD <2 is considered to be poorly predictive, values
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between 2.0 and 2.5 are adequate for qualitative evaluation or for screening purposes, values
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>2.5 (or RER >10) are regarded as acceptable for quantification, and values >3 (or RER >20)
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suggest that a model is suitable for very accurate quantitative analysis (Williams & Sobering,
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1996).
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2.5.
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Assessment of colostrum quality
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To evaluate the practical applicability of the IR assay for assessing poor quality
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colostrum, we adopted RID-based colostral IgG <50 g L-1 (McGuirk & Collins, 2004) as the cut-
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off value to differentiate between “poor” and “good” quality colostrum. The diagnostic
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sensitivity, specificity and accuracy were then evaluated for both the test set and the entire data
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set. Sensitivity was defined as the proportion of poor quality colostrum samples correctly
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identified, and specificity was defined as the proportion of good quality colostrum samples
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correctly identified.
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3.
Results
3.1.
Radial immunodiffusion assay
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The IgG content of the 250 colostrum samples (as determined by the RID assay) ranged
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from 4 to 145 g L-1, with an average of 48 g L-1 and SD of 28 g L-1. Only 39% of the colostrum
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samples had an IgG concentration above the standard cut-off point of 50 g L-1 for good quality
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colostrum.
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3.2.
Infra-red spectra
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Colostrum IR spectra showed characteristic absorption peaks over the wavenumber range
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of 4000 to 400 cm-1 (Fig. 1). A broad, strong absorption band centred at 3300 cm-1 can be
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attributed to protein N-H stretching vibration (amide A), and other protein absorptions
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correspond to stretching vibrations of C=O (amide I) and bending vibrations of N-H (amide II)
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were centred around 1650 and 1550 cm−1, respectively. Fat contributed very strong absorptions
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at 2850 and 2920 cm-1 (CH2 stretching modes) and at ~1745 cm-1 (C=O stretch).
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3.3.
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Partial least squares calibration and validation
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The PLS calibration model including 13 PLS factors was selected as optimal, based on the lowest RMMCCV (16 g L-1). This model was based upon the first derivative spectra with
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nine points smoothing (Fig. 2) and vector normalised to the 1600–1800 cm−1 region. The
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parameters and performance characteristics for the 13-factor model applied to both the
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calibration and test data sets are presented in Table 1. A scatter plot (Fig. 3) shows the level of
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agreement between colostral IgG concentrations obtained by the RID assay and predicted by the
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IR-based assay. The Pearson (r) and the concordance correlation coefficients for both the
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calibration and test data sets were 0.91. The Bland-Altman plot (Fig. 4) shows that the mean
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value of the difference between IgG concentrations obtained by IR and RID assays for the test
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data set was –0.5 g L-1, which is close to zero, indicating no significant systematic bias between
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the two methods. However, the 95% confidence interval ranged from –25 g L-1 to 24 g L-1.
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Precision of the IR-based assay and RID method for measuring the IgG content of the colostrum
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samples of the test data set are presented graphically in Figs. 5A and 5B, respectively. The mean
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CV* for the IR-based analyses was 8.9% and the mean CV* for RID analyses was 5.3%. The
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RPD and RER values were 2.3 and 11, respectively (Table 1).
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3.4.
Infra-red assay sensitivity and specificity
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For the test data set (n = 83), 51 (61.5%) colostrum samples had RID IgG concentrations
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below the threshold value of 50 g L-1, and were therefore classified as being of poor quality. The
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sensitivity, specificity and accuracy of the IR-based assay were 88% (95% CI = 76–96), 94%
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(95% CI = 79–99) and 90%, respectively. Similar values were obtained when considering the
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entire data set (n = 250); 153 (61%) colostrum samples had an RID determined IgG content
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below 50 g L-1, the sensitivity was 90% (95% CI = 84–94), specificity was 92% (95% CI = 84–
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96) and accuracy was 90%.
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and 16 were false negatives (Fig. 3).
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4.
Discussion
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Colostrum is an important source of immunity and nutrition for newborn calves. Its
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quality (colostral IgG level) is one of the most important factors influencing calf health and
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future productivity (Bielmann et al., 2010). To address the need for a rapid, accurate analytical
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technique, this aim of this study was to develop a transmission IR spectroscopy-based method
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for the quantification of bovine colostral IgG concentration and thus assess colostrum quality. To
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build a PLS calibration model with a high predictive ability, the data set should have a wide and
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evenly distributed composition (Murray, 1986). In this study, the IgG content of the colostrum
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samples was highly variable, ranged from 4 to 145 g L-1, and more than half of the samples had
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IgG concentration < 50 g L-1 (indicative of poor quality colostrum). Samples were farmer-
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collected and, while they were instructed to collect first feeding samples, it is possible that
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second or later feeding samples were included. However, the large range of IgG concentration
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values is beneficial for the current study of validating a new assay for assessing colostrum
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quality but may not reflect the industry norms for first-fed colostrum.
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The spectra of colostral samples showed complex absorption patterns and baseline shifts
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(Fig. 1). This variability arises from the compositional complexity and variability of colostrum,
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which encompasses high and variable concentrations of various proteins, carbohydrates, lipids,
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and vitamins (Kehoe, Jayarao, & Heinrichs, 2007). Additional considerations for spectral
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variations include the high fat content of colostrum (Norris, 2001), and residual hydration of the
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thin films, which may result in IR scattering. Spectral pre-processing was applied to the spectral
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data to decrease scatter, enhance bands, reduce band shifts (Fig. 2) and improve performance of
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the IR based assay (Zeaiter, Roger, & Bellon-Maurel, 2005).
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The level of agreement between the IgG concentrations obtained by the RID method and those predicted by the IR-based method was evaluated using a scatter plot, Pearson and
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concordance correlation coefficients and Bland-Altman plot. All methods confirmed good
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agreement between the two assays. In a recent study (Rivero, Valderrama, Haines, & Alomar,
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2012), near-infrared spectroscopy was used to predict the IgG concentration of bovine colostrum
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and a slightly higher Pearson correlation coefficient (r = 0.95) was reported. This may be
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attributed to the lower number of colostrum (n = 157) samples and the smaller proportion (13%)
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of samples with IgG levels < 50 g L-1 used for model development for that study. In contrast to
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the current study, 250 colostrum samples were used and almost five times as many samples had
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an IgG concentration < 50 g L-1. As a result, the PLS model development was weighted towards
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colostrum samples with a low IgG content, which is most important for the detection of poor
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quality colostrum (Filteau, Bouchard, Fecteau, Dutil, & DuTremblay, 2003; Godden, 2008; Weaver,
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Tyler, VanMetre, Hostetler, & Barrington, 2000).
The precision of the IR-based assay was somewhat lower than that of the reference RID
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assay. The relatively higher CV* (Fig. 5A) of the IR method typically occurs because the
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samples in the test set were not involved in the calibration model development. However, the
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calibration model is considered very reliable if the coefficient of variation is lower than 10%
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(Albanell, Caceres, Caja, Molina, & Gargouri, 1999; Navrátilová et al., 2006). In addition, the CV*
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of the IR-based assay lies within the acceptable range of the quality control standards of the US
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Food and Drug Administration Agency (US Department of Health and Human Services, 2001).
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The utility of the calibration model for quantification of colostral IgG concentration from the test set samples was assessed using RPD and RER. With a RPD value of 2.3 and RER value
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of 11, this calibration model could be used to predict IgG content of bovine colostrum (Williams,
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2001; Williams & Sobering, 1996). The RPD and RER values were lower than that reported in
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another recent study which used near-infrared spectroscopy for the prediction of IgG content of
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bovine colostrum (Rivero et al., 2012).
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Currently, there are several assays used to assess colostrum quality, including the RID
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assay and on-farm tools such as the colostrometer and refractometry. The IR-based assay showed
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excellent correlation with the reference RID method, and better sensitivity and specificity than
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either the colostrometer or the refractometer (Bartier et al., 2015). The Pearson correlation
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between IgG concentration obtained by RID and IR methods (r = 0.91) was higher than that
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reported for colostrometer (r = 0.77) and Brix refractometer (r = 0.64) (Bartier et al., 2015). The
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sensitivity (90%) and specificity (92%) of the IR method were higher than the sensitivity (84%
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and 66%) and specificity (77% and 83%) recently reported for the colostrometer and Brix
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refractometer, respectively (Bartier et al., 2015). The great majority of colostrum samples were
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correctly classified by the IR-based assay (Fig. 3), using RID IgG 50 g L-1 (McGuirk & Collins,
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2004) as the cut-off value to differentiate between poor and good quality colostrum. The IR-
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based assay misclassified 9.6% of 250 samples; of most concern was the 16 false negatives
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(6.4%). These false negative samples have RID IgG concentration ranged between 35 – 49 g L-1,
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which are close to the cut-off value of 50 g L-1 (Fig. 3) and thus a low risk of FTPI would be
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expected if these colostrum meals were fed to newborn calves (McGuirk & Collins, 2004).
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Conclusions
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The assessment of colostral IgG concentration serves a useful management tool that may
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be used to improve colostrum management practices and calf health. Methods for accurate, rapid
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and cost-effective measurement of colostral IgG are needed. The PLS calibration model in
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combination with transmission IR spectroscopy shows potential as an accurate, rapid, reagent-
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free and inexpensive laboratory-based method for quantification of bovine colostral IgG
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concentration, and thus for assessment of bovine colostrum quality.
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Acknowledgements
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The authors thank Maritime Quality Milk summer students, Theresa Andrews, Natasha
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Robinson and Cynthia Mitchell for their technical assistance and data collection. This research
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was funded by the Atlantic Canada Opportunities Agency. Personal funding for I. Elsohaby was
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provided by Mission Office, Ministry of Higher Education and Scientific Research, Egypt and
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Innovation PEI, Canada.
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Table 1 Descriptive statistics for the colostral immunoglobulin G concentrations obtained by the
transmission infrared spectroscopy calibration model. a
Data sets
RID-determined IgG
PLS model characteristics
Mean
SD
Range
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48.0
28.4
140.4
Test
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47.4
27.6
134.2
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RMSEC/ RPD RMSEP 12.3 -
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Calibration
PLS r factors 13 0.91 0.91
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RER
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reference radial immunodiffusion (RID) assay and for the best partial least squares (PLS)
For RID-determined IgG: mean = the average of RID data (g L-1); SD = standard deviation of
RID data (g L-1); range = difference (highest minus lowest) of RID data (g L-1). For PLS model
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characteristics: r = Pearson correlation coefficient; RMSEC = root mean squared error of calibration (g L-1); RMSEP = root mean squared error of prediction (g L-1); RPD (ratio of
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predictive deviation) = SD divided by RMSEP; RER (range error ratio) = range divided by
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Figure legends
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Fig. 1. Raw infrared spectra of 250 colostrum samples over the spectral range of 400 to 4000 cm-
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1
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H stretching (Amide A), C=O stretching (Amide I) and N-H bending (Amide II), respectively.
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. The strong protein absorptions cantered around 3300, 1650 and 1550 cm-1 were attributed to N-
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Fig. 2. First derivatives of 250 bovine colostrum spectra with nine points Savitzky-Golay
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smoothing.
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Fig. 3. Scatter plot comparing colostral IgG concentrations obtained by the IR-based assay and
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radial immunodiffusion (RID) assay for the calibration () and test () data sets. The lines
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represent the best fit for calibration (dashed line) and test set (solid line). The long dashed lines
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represent the cut-off value (50 g L-1) between poor and good quality colostrum.
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Fig. 4. Bland-Altman plot of the difference in the colostral IgG concentrations obtained by IR-
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based assay and radial immunodiffusion (RID) assay for the test set (n = 83). The solid lines
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represent the 95% confidence limits of agreement (–25 to 24 g L-1). The dashed horizontal line
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represents the mean difference between IR and RID assays (- 0.5 g L-1).
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Fig. 5. Modified coefficient of variance (CV*) plots for (A) the IR-based assay and (B) the radial
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immunodiffusion (RID) assay. The dashed lines represent the mean CV* for the IR-based assay
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(8.9%) and the RID assay (5.3%).
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S0958-6946(15)00159-4
DOI:
10.1016/j.idairyj.2015.08.004
Reference:
INDA 3868
To appear in:
International Dairy Journal
Received Date: 27 April 2015 Revised Date:
9 August 2015
Accepted Date: 12 August 2015
Please cite this article as: Elsohaby, I., McClure, J.T., Hou, S., Riley, C.B., Shaw, R.A., Keefe, G.P., A novel method for the quantification of bovine colostral immunoglobulin G using infrared spectroscopy, International Dairy Journal (2015), doi: 10.1016/j.idairyj.2015.08.004. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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A novel method for the quantification of bovine colostral immunoglobulin G using infrared
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spectroscopy
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Ibrahim Elsohaby a,b*, J Trenton McClure a, Siyuan Hou a, Christopher B. Riley a,c, R. Anthony
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Shaw d, Gregory P. Keefe a
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a
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Island, 550 University Avenue, Charlottetown, PEI C1A 4P3, Canada
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b
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University, Zagazig city 44511, Sharkia Province, Egypt
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c
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4442, New Zealand
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d
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1Y6, Canada
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Infectious Diseases, Department of Animal Medicine, Faculty of Veterinary Medicine, Zagazig
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Institute of Veterinary, Animal and Biomedical Sciences, Massey University, Palmerston North
National Research Council of Canada, Medical Devices Portfolio, Winnipeg, Manitoba R3B
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Department of Health Management, Atlantic Veterinary College, University of Prince Edward
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* Corresponding author. Tel.: +1 902 566-0995
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E-mail address: [email protected] (I. Elsohaby)
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_____________________________________________________________________________
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Abstract
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Transmission infrared (IR) spectroscopy, in combination with partial least squares (PLS)
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regression, was used as the basis to develop a new method to quantify IgG in bovine colostrum.
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Colostrum samples (n = 250) were tested simultaneously by the reference radial
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immunodiffusion (RID) assay and IR spectroscopy. Colostral IgG concentrations obtained by
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RID assay were linked to pre-processed spectra and divided into two sets, i.e., calibration and
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test. PLS regression was applied to the calibration set and calibration models were developed,
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and the test set was used to assess the accuracy of the analytical method. The Pearson and
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concordance correlations between test set IgG concentrations as determined by the IR assay and
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the RID assay were 0.91. The Bland-Altman plot showed no evidence of systematic bias between
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IR and RID methods. Transmission IR spectroscopy is an effective method for quantification of
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bovine colostral IgG concentration and for assessment of colostrum quality.
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1.
Introduction
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Colostrum is the initial secretion from the mammary gland after parturition, and is an important source of immunity and nutrition for newborn calves (Bielmann et al., 2010).
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Colostrum contains a high concentration of immunoglobulins (particularly IgG1) that are
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absorbed by calves during the first 24 h of life (Baumrucker, Burkett, Magliaro-Macrina, &
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Dechow, 2010). Calves that fail to ingest and absorb a sufficient amount of colostral IgG are
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classified as suffering from failure of transfer of passive immunity (FTPI) (Godden, 2008). As a
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result of FTPI, a calf’s susceptibility to pathogenic infection, morbidity and mortality are
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increased (Donovan, Dohoo, Montgomery, & Bennett, 1998; Robison, Stott, & DeNise, 1988;
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Virtala, Gröhn, Mechor, & Erb, 1999). There are many factors associated with FTPI in newborn
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calves, the most important relating to colostrum management practices, including colostrum
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quality, volume, cleanliness and time of feeding after birth (Beam et al., 2009; Godden, 2008).
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Therefore, measuring IgG concentration in colostrum prior to feeding is a useful management
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tool that may be used to improve calf health.
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Several techniques have been developed to measure IgG concentration in colostrum,
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including laboratory-based techniques such as the radial immunodiffusion (RID) assay
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(McBeath, Penhale, & Logan, 1971), enzyme-linked immunosorbent assay (ELISA) (Gelsinger,
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Jones, & Heinrichs, 2015), immunoassays (Indyk & Filonzi, 2003), high-performance liquid
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chromatography (HPLC) (Dolman & Thorpe, 2002), affinity liquid chromatography (Abernethy
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& Otter, 2010) and electrophoresis (Page & Thorpe, 2002), and farm-based techniques such as
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using a colostrometer (Bartier, Windeyer, & Doepel, 2015), refractometry (Bielmann et al., 2010)
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and colostrum colour (Arguello, Castro, & Capote, 2005). The RID assay is the most widely
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accepted reference method for quantification of colostral IgG (McBeath et al., 1971). However,
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this assay has significant drawbacks, which are shared by most laboratory methods, including the
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time it takes to obtain the result (18-24 h), lack of automation, utilisation of reagents with a short
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shelf-life, high cost (Bielmann et al., 2010; Riley, McClure, Low-Ying, & Shaw, 2007), and
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variability among kits due to inaccuracies associated with the internal standards (Ameri &
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Wilkerson, 2008).
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On-farm methods such as using a colostrometer and refractometry have been used to
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differentiate between good and poor quality colostrum (Bartier et al., 2015; Bielmann et al.,
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2010). A colostrometer measures the specific gravity of colostrum, and readings have a high
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correlation with IgG concentrations as determined by RID (Fleenor & Stott, 1980).
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Unfortunately, the colostrometer has several drawbacks, as it is fragile and needs to be cleaned
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before each use, and outputs are very sensitive to colostrum temperature (Bartier et al., 2015;
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Bielmann et al., 2010); these factors limit its use. For example, only 4% of farms in Quebec
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were reported to use the colostrometer consistently (Vasseur et al., 2010). Unlike the
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colostrometer, refractometry is not sensitive to temperature, but has shown a lower correlation
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with the reference RID method (Bartier et al., 2015; Bielmann et al., 2010). Therefore, an
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accurate, simple, rapid and cost-effective method to measure IgG content that overcomes the
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limitations of the reference and other methods is essential for assessing colostrum quality.
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The measurement of molecular concentrations in biological fluids by transmission
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infrared (IR) spectroscopy has a number of advantages that overcome the drawbacks associated
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with the other analytical methods. It is rapid (turnaround time is ~5 min), requires minimal
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sample preparation, and one spectrum can be used for quantitative analysis of several
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components (Shaw, Kotowich, Leroux, & Mantsch, 1998; Shaw & Mantsch, 1999, 2000). For these
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reasons, transmission IR spectroscopy in combination with partial least squares (PLS) regression
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has been widely used for quantitative and qualitative analysis of biological specimens in human
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and veterinary medicine (Shaw & Mantsch, 2000; Shaw et al., 2008). For example, this approach
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provides the basis for simultaneously quantifying total protein, glucose, albumin, triglyceride,
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cholesterol, and urea in human serum samples (Budinova, Salva, & Volka, 1997; Shaw et al.,
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1998; Ward, Haaland, Robinson, & Eaton, 1989). In animal health, analytical methods based upon
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transmission IR spectroscopy have been proven useful for milk analysis including the
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measurement of its protein (Rutten, Bovenhuis, Heck & van Arendonk, 2011a, b) and mineral
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composition (Soyeurt et al., 2009), determination of animal feed composition, the study of the
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kinetics of nutrient degradation in the rumen (Herrero, Jessop, Fawcett, Murray, & Dent, 1997;
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Ohlsson, Houmøller, Weisbjerg, Lund, & Hvelplund, 2007), the quantification of IgG concentrations
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in bovine (Elsohaby et al., 2014), equine (Riley et al., 2007) and alpaca sera (Burns et al., 2014),
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screening for metabolic diseases such as ketosis (Hansen, 1999), and for the detection of
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foodborne pathogens (Davis & Mauer, 2010) and bovine spongiform encephalopathy (BSE)
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(Lasch et al. 2003).
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To the authors’ knowledge, no study has been published that describes the use of
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transmission IR spectroscopy in combination with PLS regression as the basis for quantifying
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colostral IgG. The objectives of this study were to develop a transmission IR-based analytical
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method for the quantification of bovine colostral IgG, and to demonstrate the utility of the new
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method for the assessment of poor quality colostrum (IgG < 50 g L-1).
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Material and methods
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2.1.
Colostrum samples
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Post-partum milking colostrum samples were collected from 251 Holstein dairy cows
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originating from 7 commercial dairy herds in Prince Edward Island, Canada. Of these, 168
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samples were collected between June and October 2013, while the remaining 83 samples were
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collected between May and August 2014. At each farm, the owner collected 50 mL of colostrum
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in a vial labelled with the identity of the cow and date of sample collection, and then stored these
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on the farm at –20 °C until transportation to the Maritime Quality Milk Laboratory, University of
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Prince Edward Island (UPEI), where samples were stored at –80 °C for later batch analysis.
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Animal care and ethics approval by the Animal Care Committee at UPEI was obtained for all
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procedures followed the Canadian Council on Animal Care guidelines (CCAC, 2009).
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Radial immunodiffusion assay for IgG
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Colostral IgG concentrations were measured by the reference method using a commercial Bovine IgG RID Kit in accordance with the manufacturer’s instructions (Triple J Farms;
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Bellingham, WA, USA) (Elsohaby et al., 2014). Samples thawed at room temperature (20–24
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°C) were vortexed at 2700 rpm for 10 s, diluted (1:3) in deionised sterile water, and revortexed at
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2700 rpm for 10 s. The RID standards, from the same lot, provided in the kit, were used
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undiluted for all assays. Each sample and standard was tested in replicates of five to generate an
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average IgG concentration value. Diluted samples (1:3) with IgG concentrations greater than the
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upper standard value (>30 g L-1), were further diluted (1:5) with deionised sterile water and
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retested.
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2.3.
Transmission infra-red spectroscopy
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Thawed colostrum samples were diluted (1:3) with deionised sterile water and mixed by
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vortexing at a maximum of 2700 rpm for 10 s to ensure a uniform dispersion of colostral
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components. Each diluted colostrum sample was tested as previously described in replicates of
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six (Riley et al., 2007). A total of 1506 (251 samples × 6 replicates/sample) spectra were
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collected over the wave number range of 4000–400 cm-1 with a nominal resolution of 4 cm-1, co-
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adding 512 scans for each spectrum.
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2.4.
Spectral analysis
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2.4.1. Spectral pre-processing
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Absorbance spectra were converted into printable format (PRN) (GRAMS/AI version 7.02, Thermo Fisher Scientific, Waltham, MA, USA), imported into MATLAB® (MathWorks
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R2012b, Natick, MA, USA), and further data analysis performed using scripts written by the
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authors. The Savitzky–Golay method was used on first order derivative spectra (2nd order
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polynomial function with nine point smoothing) (Savitzky & Golay, 1964) and then a vector
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normalization procedure performed (Barnes, Dhanoa, & Lister, 1989, 2004) to reduce the effect of
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light scattering. Only the 3700–2600 cm−1 and 1800–1300 cm−1 wavenumber regions were
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selected for further analysis (Elsohaby et al., 2014). Spectrum outlier detection was carried out
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using Dixon’s Q-test (Dean & Dixon, 1951; Rorabacher, 1991) at each wave number with a
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confidence level of 95%. Where over 50% of the absorbance values were detected as outliers
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with an individual spectrum, it was excluded from further analysis, and the average of the
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remaining spectra for each sample used for subsequent analysis.
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2.4.2. Calibration model development
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A multivariate regression method (PLS) was used to create a calibration model to relate
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the IR spectra to the colostral IgG concentrations obtained by the RID method. Diluted samples
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with IgG concentrations outside of the manufacturer’s stated performance range for the RID
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assay were excluded from further analysis (n = 1). Data from the remaining 250 samples were
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used for building and validation of the analytical method. The IgG concentrations obtained by
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the RID method were linked to their corresponding pre-processed IR spectra, and then divided
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into test and calibration sets. The test set of colostral spectra (n = 83) was identified by sorting all
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the samples according to their corresponding RID IgG values. The spectrum of every third
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colostrum sample was selected as a member of the test set; the remainder (n=167) were assigned
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to the calibration set. This approach ensured that the test set encompassed the full range of IgG
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values in evaluating the predictive performance of the new analytical method. The calibration set
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(n = 167) was further split randomly into training (n = 84) and validation (n = 83) data sets for
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model development.
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As previously described, PLS regression was applied to the training set to develop 30 trial
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calibration models with the number of PLS factors ranging from 1 to 30 (Elsohaby et al., 2014).
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There were 10,000 randomly assigned splits of the calibration data into new training and
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validation sets for evaluation. The root mean squared error for the Monte Carlo cross validation
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value (RMMCCV) (Picard & Cook, 1984; Xu & Liang, 2001) was calculated for each of the 30
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trial calibration models, and the optimal number of PLS factors was chosen based on the lowest
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RMMCCV value. Once the number of PLS factors had been determined, the training and
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validation sets were recombined to build the final calibration model (Elsohaby et al., 2014).
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2.4.3. Prediction of colostral IgG concentrations
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The predictive performance of the final calibration model was assessed using the
independent spectral data test set (n = 83). Scatter plots, Pearson correlation coefficients and
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concordance correlation coefficients (Lin, 1989) were calculated to assess the level of agreement
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between IgG concentrations obtained by the reference RID method and those predicted by the
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IR-based assay for the calibration and test data sets. The difference and interchangeability
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between the RID and IR assays for the test set was further evaluated by the Bland-Altman plot
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(Altman & Bland, 1983; Bland & Altman, 1995).
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The precision of both the RID and IR methods was investigated using the test data set. The mean and standard deviation (SD) were calculated from the replicate measurements for each
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colostrum sample, and from these a modified coefficient of variation (CV* = CV (1 + (1/4n))
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where CV* is considered an unbiased estimation of CV for small sample size; n = 6 for IR assay;
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n = 5 for RID assay) was determined for each sample (Salkind, 2010), and for each analytical
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method. The CV* values were then plotted against the corresponding mean IgG concentrations.
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The IR-based assay was further assessed using the ratio of predictive deviation (RPD: the
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RID-determined IgG concentration standard deviation, ratioed to the root mean squared error of
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prediction (RMSEP) for the IR-based assay), and the range error ratio (RER: the RID-determined
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IgG concentration range, ratioed to the RMSEP for the IR-based assay) (Williams & Sobering,
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1996). According to this framework, a RPD <2 is considered to be poorly predictive, values
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between 2.0 and 2.5 are adequate for qualitative evaluation or for screening purposes, values
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>2.5 (or RER >10) are regarded as acceptable for quantification, and values >3 (or RER >20)
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suggest that a model is suitable for very accurate quantitative analysis (Williams & Sobering,
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1996).
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2.5.
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Assessment of colostrum quality
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To evaluate the practical applicability of the IR assay for assessing poor quality
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colostrum, we adopted RID-based colostral IgG <50 g L-1 (McGuirk & Collins, 2004) as the cut-
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off value to differentiate between “poor” and “good” quality colostrum. The diagnostic
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sensitivity, specificity and accuracy were then evaluated for both the test set and the entire data
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set. Sensitivity was defined as the proportion of poor quality colostrum samples correctly
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identified, and specificity was defined as the proportion of good quality colostrum samples
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correctly identified.
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3.
Results
3.1.
Radial immunodiffusion assay
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The IgG content of the 250 colostrum samples (as determined by the RID assay) ranged
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from 4 to 145 g L-1, with an average of 48 g L-1 and SD of 28 g L-1. Only 39% of the colostrum
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samples had an IgG concentration above the standard cut-off point of 50 g L-1 for good quality
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colostrum.
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3.2.
Infra-red spectra
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Colostrum IR spectra showed characteristic absorption peaks over the wavenumber range
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of 4000 to 400 cm-1 (Fig. 1). A broad, strong absorption band centred at 3300 cm-1 can be
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attributed to protein N-H stretching vibration (amide A), and other protein absorptions
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correspond to stretching vibrations of C=O (amide I) and bending vibrations of N-H (amide II)
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were centred around 1650 and 1550 cm−1, respectively. Fat contributed very strong absorptions
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at 2850 and 2920 cm-1 (CH2 stretching modes) and at ~1745 cm-1 (C=O stretch).
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3.3.
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Partial least squares calibration and validation
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The PLS calibration model including 13 PLS factors was selected as optimal, based on the lowest RMMCCV (16 g L-1). This model was based upon the first derivative spectra with
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nine points smoothing (Fig. 2) and vector normalised to the 1600–1800 cm−1 region. The
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parameters and performance characteristics for the 13-factor model applied to both the
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calibration and test data sets are presented in Table 1. A scatter plot (Fig. 3) shows the level of
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agreement between colostral IgG concentrations obtained by the RID assay and predicted by the
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IR-based assay. The Pearson (r) and the concordance correlation coefficients for both the
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calibration and test data sets were 0.91. The Bland-Altman plot (Fig. 4) shows that the mean
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value of the difference between IgG concentrations obtained by IR and RID assays for the test
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data set was –0.5 g L-1, which is close to zero, indicating no significant systematic bias between
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the two methods. However, the 95% confidence interval ranged from –25 g L-1 to 24 g L-1.
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Precision of the IR-based assay and RID method for measuring the IgG content of the colostrum
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samples of the test data set are presented graphically in Figs. 5A and 5B, respectively. The mean
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CV* for the IR-based analyses was 8.9% and the mean CV* for RID analyses was 5.3%. The
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RPD and RER values were 2.3 and 11, respectively (Table 1).
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3.4.
Infra-red assay sensitivity and specificity
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For the test data set (n = 83), 51 (61.5%) colostrum samples had RID IgG concentrations
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below the threshold value of 50 g L-1, and were therefore classified as being of poor quality. The
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sensitivity, specificity and accuracy of the IR-based assay were 88% (95% CI = 76–96), 94%
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(95% CI = 79–99) and 90%, respectively. Similar values were obtained when considering the
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entire data set (n = 250); 153 (61%) colostrum samples had an RID determined IgG content
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below 50 g L-1, the sensitivity was 90% (95% CI = 84–94), specificity was 92% (95% CI = 84–
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96) and accuracy was 90%.
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and 16 were false negatives (Fig. 3).
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4.
Discussion
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Colostrum is an important source of immunity and nutrition for newborn calves. Its
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quality (colostral IgG level) is one of the most important factors influencing calf health and
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future productivity (Bielmann et al., 2010). To address the need for a rapid, accurate analytical
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technique, this aim of this study was to develop a transmission IR spectroscopy-based method
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for the quantification of bovine colostral IgG concentration and thus assess colostrum quality. To
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build a PLS calibration model with a high predictive ability, the data set should have a wide and
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evenly distributed composition (Murray, 1986). In this study, the IgG content of the colostrum
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samples was highly variable, ranged from 4 to 145 g L-1, and more than half of the samples had
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IgG concentration < 50 g L-1 (indicative of poor quality colostrum). Samples were farmer-
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collected and, while they were instructed to collect first feeding samples, it is possible that
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second or later feeding samples were included. However, the large range of IgG concentration
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values is beneficial for the current study of validating a new assay for assessing colostrum
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quality but may not reflect the industry norms for first-fed colostrum.
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The spectra of colostral samples showed complex absorption patterns and baseline shifts
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(Fig. 1). This variability arises from the compositional complexity and variability of colostrum,
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which encompasses high and variable concentrations of various proteins, carbohydrates, lipids,
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and vitamins (Kehoe, Jayarao, & Heinrichs, 2007). Additional considerations for spectral
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variations include the high fat content of colostrum (Norris, 2001), and residual hydration of the
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thin films, which may result in IR scattering. Spectral pre-processing was applied to the spectral
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data to decrease scatter, enhance bands, reduce band shifts (Fig. 2) and improve performance of
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the IR based assay (Zeaiter, Roger, & Bellon-Maurel, 2005).
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The level of agreement between the IgG concentrations obtained by the RID method and those predicted by the IR-based method was evaluated using a scatter plot, Pearson and
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concordance correlation coefficients and Bland-Altman plot. All methods confirmed good
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agreement between the two assays. In a recent study (Rivero, Valderrama, Haines, & Alomar,
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2012), near-infrared spectroscopy was used to predict the IgG concentration of bovine colostrum
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and a slightly higher Pearson correlation coefficient (r = 0.95) was reported. This may be
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attributed to the lower number of colostrum (n = 157) samples and the smaller proportion (13%)
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of samples with IgG levels < 50 g L-1 used for model development for that study. In contrast to
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the current study, 250 colostrum samples were used and almost five times as many samples had
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an IgG concentration < 50 g L-1. As a result, the PLS model development was weighted towards
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colostrum samples with a low IgG content, which is most important for the detection of poor
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quality colostrum (Filteau, Bouchard, Fecteau, Dutil, & DuTremblay, 2003; Godden, 2008; Weaver,
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Tyler, VanMetre, Hostetler, & Barrington, 2000).
The precision of the IR-based assay was somewhat lower than that of the reference RID
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assay. The relatively higher CV* (Fig. 5A) of the IR method typically occurs because the
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samples in the test set were not involved in the calibration model development. However, the
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calibration model is considered very reliable if the coefficient of variation is lower than 10%
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(Albanell, Caceres, Caja, Molina, & Gargouri, 1999; Navrátilová et al., 2006). In addition, the CV*
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of the IR-based assay lies within the acceptable range of the quality control standards of the US
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Food and Drug Administration Agency (US Department of Health and Human Services, 2001).
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The utility of the calibration model for quantification of colostral IgG concentration from the test set samples was assessed using RPD and RER. With a RPD value of 2.3 and RER value
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of 11, this calibration model could be used to predict IgG content of bovine colostrum (Williams,
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2001; Williams & Sobering, 1996). The RPD and RER values were lower than that reported in
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another recent study which used near-infrared spectroscopy for the prediction of IgG content of
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bovine colostrum (Rivero et al., 2012).
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Currently, there are several assays used to assess colostrum quality, including the RID
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assay and on-farm tools such as the colostrometer and refractometry. The IR-based assay showed
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excellent correlation with the reference RID method, and better sensitivity and specificity than
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either the colostrometer or the refractometer (Bartier et al., 2015). The Pearson correlation
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between IgG concentration obtained by RID and IR methods (r = 0.91) was higher than that
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reported for colostrometer (r = 0.77) and Brix refractometer (r = 0.64) (Bartier et al., 2015). The
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sensitivity (90%) and specificity (92%) of the IR method were higher than the sensitivity (84%
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and 66%) and specificity (77% and 83%) recently reported for the colostrometer and Brix
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refractometer, respectively (Bartier et al., 2015). The great majority of colostrum samples were
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correctly classified by the IR-based assay (Fig. 3), using RID IgG 50 g L-1 (McGuirk & Collins,
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2004) as the cut-off value to differentiate between poor and good quality colostrum. The IR-
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based assay misclassified 9.6% of 250 samples; of most concern was the 16 false negatives
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(6.4%). These false negative samples have RID IgG concentration ranged between 35 – 49 g L-1,
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which are close to the cut-off value of 50 g L-1 (Fig. 3) and thus a low risk of FTPI would be
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expected if these colostrum meals were fed to newborn calves (McGuirk & Collins, 2004).
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Conclusions
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The assessment of colostral IgG concentration serves a useful management tool that may
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be used to improve colostrum management practices and calf health. Methods for accurate, rapid
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and cost-effective measurement of colostral IgG are needed. The PLS calibration model in
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combination with transmission IR spectroscopy shows potential as an accurate, rapid, reagent-
333
free and inexpensive laboratory-based method for quantification of bovine colostral IgG
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concentration, and thus for assessment of bovine colostrum quality.
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Acknowledgements
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The authors thank Maritime Quality Milk summer students, Theresa Andrews, Natasha
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Robinson and Cynthia Mitchell for their technical assistance and data collection. This research
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was funded by the Atlantic Canada Opportunities Agency. Personal funding for I. Elsohaby was
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provided by Mission Office, Ministry of Higher Education and Scientific Research, Egypt and
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Innovation PEI, Canada.
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Table 1 Descriptive statistics for the colostral immunoglobulin G concentrations obtained by the
transmission infrared spectroscopy calibration model. a
Data sets
RID-determined IgG
PLS model characteristics
Mean
SD
Range
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48.0
28.4
140.4
Test
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47.4
27.6
134.2
13
RMSEC/ RPD RMSEP 12.3 -
-
12.2
11
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Calibration
PLS r factors 13 0.91 0.91
2.3
RER
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reference radial immunodiffusion (RID) assay and for the best partial least squares (PLS)
For RID-determined IgG: mean = the average of RID data (g L-1); SD = standard deviation of
RID data (g L-1); range = difference (highest minus lowest) of RID data (g L-1). For PLS model
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characteristics: r = Pearson correlation coefficient; RMSEC = root mean squared error of calibration (g L-1); RMSEP = root mean squared error of prediction (g L-1); RPD (ratio of
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predictive deviation) = SD divided by RMSEP; RER (range error ratio) = range divided by
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Figure legends
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Fig. 1. Raw infrared spectra of 250 colostrum samples over the spectral range of 400 to 4000 cm-
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1
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H stretching (Amide A), C=O stretching (Amide I) and N-H bending (Amide II), respectively.
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. The strong protein absorptions cantered around 3300, 1650 and 1550 cm-1 were attributed to N-
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Fig. 2. First derivatives of 250 bovine colostrum spectra with nine points Savitzky-Golay
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smoothing.
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Fig. 3. Scatter plot comparing colostral IgG concentrations obtained by the IR-based assay and
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radial immunodiffusion (RID) assay for the calibration () and test () data sets. The lines
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represent the best fit for calibration (dashed line) and test set (solid line). The long dashed lines
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represent the cut-off value (50 g L-1) between poor and good quality colostrum.
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Fig. 4. Bland-Altman plot of the difference in the colostral IgG concentrations obtained by IR-
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based assay and radial immunodiffusion (RID) assay for the test set (n = 83). The solid lines
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represent the 95% confidence limits of agreement (–25 to 24 g L-1). The dashed horizontal line
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represents the mean difference between IR and RID assays (- 0.5 g L-1).
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Fig. 5. Modified coefficient of variance (CV*) plots for (A) the IR-based assay and (B) the radial
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immunodiffusion (RID) assay. The dashed lines represent the mean CV* for the IR-based assay
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(8.9%) and the RID assay (5.3%).
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