105 NEAR-INFRARED SPECTROSCOPY AND AQUAPHOTOMICS ANALYSIS OF SERUM FROM MARES EXPOSED TO THE FUNGAL MYCOTOXIN ZEARALENONE

2017 ◽  
Vol 29 (1) ◽  
pp. 160
Author(s):  
C. K. Vance ◽  
K. R. Counsell ◽  
L. A. Agcanas ◽  
N. Shappell ◽  
S. Bowers ◽  
...  

Aquaphotomics is a branch of near-infrared (NIR) spectroscopy in which bond vibrations from organic molecules and water create unique spectral absorbance patterns to profile complex aqueous mixtures. Aquaphotomics has been shown to detect virus infected soybean plants from extracts, classify probiotic bacteria, and detect contamination of aquatic ecosystems. We have used aquaphotomics to characterise serum profiles from horses in various phases of the reproductive cycle such as oestrus and diestrus. Because serum is a complex solution of biomolecules, various modes of serum processing (e.g. large protein removal for proteomics or mass spectrometry) may provide different NIR spectral profiles for quantitative analysis of specific compounds or their effects. Zearalenone is a fungal mycotoxin that may have estrogenic potential in mares and is found in feedstuffs. The objectives of this study were to (1) establish NIR spectral profiles of serum and protein-precipitated serum (PPS) collected at peak oestrus from mares; (2) determine if NIR profiles correlate and quantify E2 concentrations in serum or PPS; and (3) determine if NIR can detect differences in serum chemistry of zearalenone-treated mares. Mares were fed zearalenone daily at low (2 mg, 2 mares, 5 cycles) and high (8 mg, 1 mare, 3 cycles) concentrations, plus control (0 mg, 1 mare, 3 cycles). Oestrus cycles were monitored by ultrasound and serum hormone analysis. Serum collected at peak oestrus had E2 values determined by radioimmunoassay (range 0.02–16.87 pg mL−1). Protein precipitated serum had high and medium MW proteins removed with acetonitrile. NIR spectra, collected in triplicate with a 1 mm quartz cuvette and ASD FieldSpec®3 (Boulder, CO, USA), were pre-treated with a Savitsky-Golay 1st derivative for inspection of spectral features, principal component analysis, and partial least-squares regression (PLS) to investigate spectral correlations to E2 concentrations and zearalenone treatment effects. The NIR profiles contrasting serum and PPS at oestrus had distinct spectral features differing significantly at 1320, 1491, 1536, and 1566 nm in the NIR water spectrum, and principal component-1 accounted for 97% of principal component analysis variance in spectra from serum compared to PPS. In the PLS cross-validation linear fit regression model, NIR predicted E2 concentrations (validated by RIA) from serum (slope = 0.89, SECV = 1.92, R2 = 0.81, 3 factors), and from PPS (slope = 0.61; SECV = 1.84, R2 = 0.76, 4 factors). Spectral predictions were poorest at the low E2 threshold, E2 = 0.02 pg mL−1. The PLS model validation metrics of zearalenone dose-dependent effects were also evident in serum (slope = 0.88, SECV = 1.26, R2 = 0.86) and in PPS (slope = 0.67, SECV = 1.96, R2 = 0.66). Correlations of quantitative values of E2 and zearalenone were both better for spectra taken of serum compared to PPS. In summary, NIR spectral profiles of serum chemistry may be able to map E2 hormone levels during reproductive cycling, and these spectra may also have correlations that reflect exposure of mares to estrogenic toxins such as zearalenone. Research was supported by USDA-ARS Biophotonics grant #58-6402-3-018.

2017 ◽  
Vol 29 (1) ◽  
pp. 140
Author(s):  
K. R. Counsell ◽  
C. L. Durfey ◽  
J. M. Feugang ◽  
S. T. Willard ◽  
P. L. Ryan ◽  
...  

In vitro fertilization is optimized when there is a homogenous population of viable spermatozoa, not subjected toxic waste products of apoptotic cells. In a previous study, we developed a “nanopurification” technique to magnetically target and remove non-viable spermatozoa from a boar insemination dose. Nanopurified semen has successfully been studied with IVF in swine and bovine but lacks health data regarding offspring produced from exposed semen. Developmental health performance in mammals is typically assessed through measurements of immune related biomolecules in plasma (e.g. immunoglobulins), quantifying each variable with a specific analytical assay. Recent developments in aqueous based near infrared spectroscopy (NIR), aquaphotomics, have been shown to distinguish reproductive stages (e.g. oestrus, diestrus) in blood serum. Thus, application of aquaphotomics may be ideal for analysis of offspring resulting from fertilization with nanopurified semen, using serum or plasma. Our study objective was to identify holistic differences in blood plasma by characterising NIR spectral profiles in offspring produced from nanopurified semen. Extended boar semen doses were mixed with or without specific nanoparticles to target non-viable spermatozoa. Semen doses were exposed to an electromagnetic field, noninvasively separating non-viable spermatozoa from the insemination dose. Six gilts were bred with (n = 3) or without (n = 3) nanopurified semen. Following birth and weaning, 20 offspring of equal sexes were randomly selected from control and nanopurified litters (10/group) for growth and developmental measurements up until market weight. Blood plasma was collected from offspring at market weight for NIR analysis. Spectral data were collected with a quartz cuvette and ASD FieldSpec® 3 spectrophotometer (ASD Inc., Boulder, CO, USA). Chemometric analysis (Unscrambler® X version 10.4; CAMO Software, Oslo, Norway) included a Savistsky-Golay 1st and 2nd derivative for detection of distinct spectral features. Principal component analysis and partial least-squares block-discrimination were used to examine treatment effects, in a blind experiment. Plasma spectral profiles from control and nanopurified offspring contained 6 shared peaks at 1360, 1373, 1402, 1404, 1422, and 1428 nm. Principle components 1 and 2 accounted for 96.26% of the total variance, with no separation of principal component analysis scores for plasma spectra between groups. Partial least-squares discriminant analysis metrics (slope = 0.026, SECV = 0.52) and Students t-test showed no significant difference (P = 0.57) between groups. Results indicate blood plasma content is not influenced in nanopurified offspring when compared with the control. In addition, solute NIR has shown to be a valuable promising tool for assessing complex aqueous solutions in swine. Further effects on growth and development from offspring born from nanopurified continue to be investigated. This work was supported by USDA-ARS Biophotonics Initiative grant #58–6402–3-018.


2011 ◽  
Vol 41 (No. 3) ◽  
pp. 89-95 ◽  
Author(s):  
L. Munck ◽  
B. Møller

Near infrared technology, now widespread in quality control, makes it possible to obtain a total multivariate physical chemical fingerprint of the barley endosperm with high precision. Whole spectroscopic fingerprints of the physics and chemistry of barley seeds can be interpreted by multivariate analysis (chemometrics), by Principal Component Analysis (PCA) for classification and Partial Least Squares Regression (PLSR) for correlation. PCA classification of Near Infrared Reflectance (NIR) spectra can differentiate between mutants and alleles in the lys3 and lys5 loci. PCA on NIR can also be used as a routine in barley breeding to select for a multi-gene quality complex in barley as a whole e.g. increasing starch and reducing fibre content. This is done directly from the PCA classification plot by “data breeding” selecting the recombinants which are approaching the position of the normal high starch controls on the plot. Based on classification of NIR spectra, two alleles in the lys5 locus were characterised as a new class of (1→3,1→4)--glucan compensating starch mutants indicating a metabolic connection between starch and -glucan.  


2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Elise A. Kho ◽  
Jill N. Fernandes ◽  
Andrew C. Kotze ◽  
Glen P. Fox ◽  
Maggy T. Sikulu-Lord ◽  
...  

Abstract Background Existing diagnostic methods for the parasitic gastrointestinal nematode, Haemonchus contortus, are time consuming and require specialised expertise, limiting their utility in the field. A practical, on-farm diagnostic tool could facilitate timely treatment decisions, thereby preventing losses in production and flock welfare. We previously demonstrated the ability of visible–near-infrared (Vis–NIR) spectroscopy to detect and quantify blood in sheep faeces with high accuracy. Here we report our investigation of whether variation in sheep type and environment affect the prediction accuracy of Vis–NIR spectroscopy in quantifying blood in faeces. Methods Visible–NIR spectra were obtained from worm-free sheep faeces collected from different environments and sheep types in South Australia (SA) and New South Wales, Australia and spiked with various sheep blood concentrations. Spectra were analysed using principal component analysis (PCA), and calibration models were built around the haemoglobin (Hb) wavelength region (387–609 nm) using partial least squares regression. Models were used to predict Hb concentrations in spiked faeces from SA and naturally infected sheep faeces from Queensland (QLD). Samples from QLD were quantified using Hemastix® test strip and FAMACHA© diagnostic test scores. Results Principal component analysis showed that location, class of sheep and pooled versus individual samples were factors affecting the Hb predictions. The models successfully differentiated ‘healthy’ SA samples from those requiring anthelmintic treatment with moderate to good prediction accuracy (sensitivity 57–94%, specificity 44–79%). The models were not predictive for blood in the naturally infected QLD samples, which may be due in part to variability of faecal background and blood chemistry between samples, or the difference in validation methods used for blood quantification. PCA of the QLD samples, however, identified a difference between samples containing high and low quantities of blood. Conclusion This study demonstrates the potential of Vis–NIR spectroscopy for estimating blood concentration in faeces from various types of sheep and environmental backgrounds. However, the calibration models developed here did not capture sufficient environmental variation to accurately predict Hb in faeces collected from environments different to those used in the calibration model. Consequently, it will be necessary to establish models that incorporate samples that are more representative of areas where H. contortus is endemic.


1996 ◽  
Vol 50 (12) ◽  
pp. 1541-1544 ◽  
Author(s):  
Hans-René Bjørsvik

A method of combining spectroscopy and multivariate data analysis for obtaining quantitative information on how a reaction proceeds is presented. The method is an approach for the explorative synthetic organic laboratory rather than the analytical chemistry laboratory. The method implements near-infrared spectroscopy with an optical fiber transreflectance probe as instrumentation. The data analysis consists of decomposition of the spectral data, which are recorded during the course of a reaction by using principal component analysis to obtain latent variables, scores, and loading. From the scores and the corresponding reaction time, it is possible to obtain a reaction profile. This reaction profile can easily be recalculated to obtain the concentration profile over time. This calculation is based on only two quantitative measurements, which can be (1) measurement from the work-up of the reaction or (2) chromatographic analysis from two withdrawn samples during the reaction. The method is applied to the synthesis of 3-amino-propan-1,2-diol.


2019 ◽  
Vol 59 (6) ◽  
pp. 1190 ◽  
Author(s):  
A. Bahri ◽  
S. Nawar ◽  
H. Selmi ◽  
M. Amraoui ◽  
H. Rouissi ◽  
...  

Rapid measurement optical techniques have the advantage over traditional methods of being faster and non-destructive. In this work visible and near-infrared spectroscopy (vis-NIRS) was used to investigate differences between measured values of key milk properties (e.g. fat, protein and lactose) in 30 samples of ewes milk according to three feed systems; faba beans, field peas and control diet. A mobile fibre-optic vis-NIR spectrophotometer (350–2500 nm) was used to collect reflectance spectra from milk samples. Principal component analysis was used to explore differences between milk samples according to the feed supplied, and a partial least-squares regression and random forest regression were adopted to develop calibration models for the prediction of milk properties. Results of the principal component analysis showed clear separation between the three groups of milk samples according to the diet of the ewes throughout the lactation period. Milk fat, protein and lactose were predicted with good accuracy by means of partial least-squares regression (R2 = 0.70–0.83 and ratio of prediction deviation, which is the ratio of standard deviation to root mean square error of prediction = 1.85–2.44). However, the best prediction results were obtained with random forest regression models (R2 = 0.86–0.90; ratio of prediction deviation = 2.73–3.26). The adoption of the vis-NIRS coupled with multivariate modelling tools can be recommended for exploring to differences between milk samples according to different feed systems, and to predict key milk properties, based particularly on the random forest regression modelling technique.


2013 ◽  
Vol 834-836 ◽  
pp. 935-938
Author(s):  
Lian Shun Zhang ◽  
Chao Guo ◽  
Bao Quan Wang

In this paper, the liquor brands were identified based on the near infrared spectroscopy method and the principal component analysis. 60 samples of 6 different brands liquor were measured by the spectrometer of USB4000. Then, in order to eliminate the noise caused by the external factors, the smoothing method and the multiplicative scatter correction method were used. After the preprocessing, we got the revised spectra of the 60 samples. The difference of the spectrum shape of different brands is not much enough to classify them. So the principal component analysis was applied for further analysis. The results showed that the first two principal components variance contribution rate had reached 99.06%, which can effectively represent the information of the spectrums after preprocessing. From the scatter plot of the two principal components, the 6 different brands of liquor were identified more accurate and easier than the spectra curves.


2002 ◽  
Vol 10 (4) ◽  
pp. 247-255 ◽  
Author(s):  
Masanori Kumagai ◽  
Hideto Suyama ◽  
Tomoaki Sato ◽  
Toshio Amano ◽  
Nobuaki Ogawa

A portable near infrared (NIR) spectrometer was used to accomplish rapid identification of plastics. Thirteen kinds of plastics were collected and their NIR spectra were measured. Standardised normalisation treatment of the original spectra reveals the differences of the spectra more clearly. Absorbance spectra can be used to distinguish easily between polyethylene (PE) and polypropylene (PP) with the absorption band of the methylene group at 1410 nm. The result can be used to discriminate PE, PP and the copolymer. This suggestion is supported by a principal component analysis of the second-order derivatives spectrum.


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