Multicomponent blood lipid analysis by means of near infrared spectroscopy, in geese

Abstract

a b s t r a c tThis study provides accurate near infrared (NIR) spectroscopic models on some laboratory determined clinicochemical parameters (i.e. total lipid (5.57 71.95 g/l), triglyceride (2.59 71.36 mmol/l), total cholesterol (3.81 7 0.68 mmol/l), high density lipoprotein (HDL) cholesterol (2.45 70.58 mmol/l)) of blood serum samples of fattened geese. To increase the performance of multivariate chemometrics, samples significantly deviating from the regression models implying laboratory error were excluded from the final calibration datasets. Reference data of excluded samples having outlier spectra in principal component analysis were not marked as false. Samples deviating from the regression models but having non outlier spectra in PCA were identified as having false reference constituent values. Based on the NIR selection methods, 5% of the reference measurement data were rated as doubtful. The achieved models reached R 2 of 0.864, 0.966, 0.850, 0.793, and RMSE of 0.639 g/l, 0.232 mmol/l, 0.210 mmol/l, 0.241 mmol/l for total lipid, triglyceride, total cholesterol and HDL cholesterol, respectively, during independent validation. Classical analytical techniques focus on single constituents and often require chemicals, timeconsuming measurements, and experienced technicians. NIR technique provides a quick, cost effective, non-hazardous alternative method for analysis of several constituents based on one single spectrum of each sample, and it also offers the possibility for looking at the laboratory reference data critically. Evaluation of reference data to identify and exclude falsely analyzed samples can provide warning feedback to the reference laboratory, especially in the case of analyses where laboratory methods are not perfectly suited to the subjected material and there is an increased chance of laboratory error.

Application of FTIR Spectroscopy for Quantitative Analysis of Blood Serum: A Preliminary Study

“…It has been shown that spectroscopy in the mid-IR range can serve as an alternative basis for the clinical measurement of urea and glucose in blood serum [ 25 ]. The literature reports promising results on important serum parameters such as urea, total protein, albumin, triglycerides or total cholesterol [ 26 , 27 , 28 , 29 ]. Nevertheless, the possibility of simultaneous determination of several blood parameters has not been studied enough.…”

Identification of gallbladder cancer by direct near-infrared measurement of raw bile combined with two-trace two-dimensional correlation analysis

“…This previously reported NIR bile analysis scheme has potential for clinical on-site analysis due to the simple and rapid analysis that requires no pretreatment of raw bile. Other than the analysis of bile, NIR spectroscopy has been extensively adopted for biomedical diagnosis 2,3 using relevant biological specimens including blood, 4,5 serum, [6][7][8] saliva, 9 and tissue, 10,11 and diverse chemometric and deep learning methods such as partial least squares (PLS), [5][6][7][8]12 linear discriminant analysis (LDA), 3,11,14 support vector machine (SVM), 13 and artificial neural network (ANN) 13 are combined for multivariate analysis of acquired NIR spectra.…”

Rapid determination of triglyceride and glucose levels in Drosophila melanogaster induced by high-sugar or high-fat diets based on near-infrared spectroscopy

“…And nowadays, NIR spectroscopy has been widely studied and applied for measuring biochemical parameters. Bazar et al utilized NIR spectroscopy to predict total lipids, triglycerides, total cholesterol and high-density lipoprotein cholesterol in goose serum samples, and the correlation coefficients of prediction ( R P ) were 0.864, 0.966, 0.850 and 0.793, respectively [ 29 ]. Filho et al applied the NIR spectroscopy to determine the triglyceride level in human plasma.…”