Improving Prediction of Peroxide Value of Edible Oils Using Regularized Regression Models.

We present four unique prediction techniques, combined with multiple data pre-processing methods, utilizing a wide range of both oil types and oil peroxide values (PV) as well as incorporating natural aging for peroxide creation. Samples were PV assayed using a standard starch titration method, AOCS Method Cd 8-53, and used as a verified reference method for PV determination. Near-infrared (NIR) spectra were collected from each sample in two unique optical pathlengths (OPLs), 2 and 24 mm, then fused into a third distinct set. All three sets were used in partial least squares (PLS) regression, ridge regression, LASSO regression, and elastic net regression model calculation. While no individual regression model was established as the best, global models for each regression type and pre-processing method show good agreement between all regression types when performed in their optimal scenarios. Furthermore, small spectral window size boxcar averaging shows prediction accuracy improvements for edible oil PVs. Best-performing models for each regression type are: PLS regression, 25 point boxcar window fused OPL spectral information RMSEP = 2.50; ridge regression, 5 point boxcar window, 24 mm OPL, RMSEP = 2.20; LASSO raw spectral information, 24 mm OPL, RMSEP = 1.80; and elastic net, 10 point boxcar window, 24 mm OPL, RMSEP = 1.91. The results show promising advancements in the development of a full global model for PV determination of edible oils.

Comparison of Spectroscopic Techniques for Determining the Peroxide Value of 19 Classes of Naturally Aged, Plant-Based Edible Oils.

The peroxide value of edible oils is a measure of the degree of oxidation, which directly relates to the freshness of the oil sample. Several studies previously reported in the literature have paired various spectroscopic techniques with multivariate analyses to rapidly determine peroxide values using field portable and process instrumentation; those efforts presented "best-case scenarios" with oils from narrowly defined training and test sets. The purpose of this paper is to evaluate the use of near- and mid-infrared absorption and Raman scattering spectroscopies on oil samples from different oil classes, including seasonal and vendor variations, to determine which measurement technique or combination thereof is best for predicting peroxide values. Following peroxide value assays of each oil class using an established titration-based method, global and global-subset calibration models were constructed from spectroscopic data collected on the 19 oil classes used in this study. Spectra from each optical technique were used to create partial least squares regression calibration models to predict the peroxide value of unknown oil samples. A global peroxide value model based on near-infrared (8 mm optical path length) oil measurements produced the lowest RMSEP (4.9), followed by 24 mm optical path length near infrared (5.1), Raman (6.9) and 50 µm optical path length mid-infrared (7.3). However, it was determined that the Raman RMSEP resulted from chance correlations. Global peroxide value models based on low-level fusion of the NIR (8 and 24 mm optical path length) data and all infrared data produced the same RMSEP of 5.1. Global subset models, based on any of the spectroscopies and olive oil training sets from any class (pure, extra light, extra virgin), all failed to extrapolate to the non-olive oils. However, the near-infrared global subset model built on extra virgin olive oil could extrapolate to test samples from other olive oil classes. This work demonstrates the difficulty of developing a truly global method for determining peroxide value of oils.

EXPRESS: Comparison of Spectroscopic Techniques for Determining the Peroxide Value of 19 Classes of Naturally Aged, Plant-Based Edible Oils.

The peroxide value (PV) of edible oils is a measure of the degree of oxidation, which directly relates to the freshness of the oil sample. Several studies previously reported in the literature have paired various spectroscopic techniques with multivariate analyses to rapidly determine PVs using field portable and process instrumentation; those efforts presented âbest-caseâ scenarios with oils from narrowly defined training and test sets. The purpose of this paper is to evaluate the use of near- and mid-infrared absorption and Raman scattering spectroscopies on oil samples from different oil classes, including seasonal and vendor variations, to determine which measurement technique, or combination thereof, is best for predicting PVs. Following PV assays of each oil class using an established titration-based method, global and global-subset calibration models were constructed from spectroscopic data collected on the 19 oil classes used in this study. Spectra from each optical technique were used to create partial least squares regression (PLSR) calibration models to predict the PV of unknown oil samples. A global PV model based on near-infrared (8 mm optical path length â OPL) oil measurements produced the lowest RMSEP (4.9), followed by 24 mm OPL near infrared (5.1), Raman (6.9) and 50 λm OPL mid-infrared (7.3). However, it was determined that the Raman RMSEP resulted from chance correlations. Global PV models based on low-level fusion of the NIR (8 and 24 mm OPL) data and all infrared data produced the same RMSEP of 5.1. Global subset models, based on any of the spectroscopies and olive oil training sets from any class (pure, extra light, extra virgin), all failed to extrapolate to the non-olive oils. However, the near-infrared global subset model built on extra virgin olive oil could extrapolate to test samples from other olive oil classes.

Portable microcoil NMR detection coupled to capillary electrophoresis.

High-efficiency separation techniques, such as capillary electrophoresis (CE), coupled to a nondestructive nuclear magnetic resonance (NMR) spectrometer offer the ability to separate, chemically identify, and provide structural information on analytes in small sample volumes. Previous CE-NMR coupled systems utilized laboratory-scale NMR magnets and spectrometers, which require very long separation capillaries. New technological developments in electronics have reduced the size of the NMR system, and small 1-2 T permanent magnets provide the possibilities of a truly portable NMR. The microcoils used in portable and laboratory-scale NMR may offer the advantage of improved mass sensitivity because the limit of detection (LOD) is proportional to the coil diameter. In this work, CE is coupled with a portable, briefcase-sized NMR system that incorporates a microcoil probe and a 1.8 T permanent magnet to measure (19)F NMR spectra. Separations of fluorinated molecules are demonstrated with stopped- and continuous-flow NMR detection. The results demonstrate that coupling CE to a portable NMR instrument is feasible and can provide a low-cost method to obtain structural information on microliter samples. An LOD of 31.8 nmol for perfluorotributylamine with a resolution of 4 ppm has been achieved with this system.

A sample-in-answer-out instrument for the detection of multiple respiratory pathogens in unprepared nasopharyngeal swab samples.

Multiplex RT-PCR suspension array assays provide a powerful tool for identifying the causative agent(s) of respiratory infections. These assays are time consuming and laborious on a time-per-sample basis if only a few samples require processing. To address this shortcoming and provide an automated solution for fast detection and identification of viral pathogens, we developed the first automated multiplex RT-PCR suspension array instrument capable of handling unprepared clinical samples. The instrument requires less than 3 minutes of hands-on time for a result generated in approximately 2.5 hours. In analytical studies, the instrument performed as well as manually performed assays. The performance of the instrument and loaded multiplex viral detection assay was then tested using unprepared nasopharyngeal samples. The instrument-performed assay detected 61 of 71 RSV positive samples, for a sensitivity of 85.9%. Adenovirus (n = 5) and influenza B (n = 3) were less prevalent in the sample set, but detected to similar levels, 80% and 75%, respectively. The same sample set was also tested using FDA approved immuno-assay rapid tests, and the instrument was found to be more sensitive than the rapid tests with the sole exception being influenza A (n = 16), which was poorly detected due to significant sequence mismatches between the influenza A primer/probe set included in the multiplex mixture and the circulating influenza A strains. Overall, these data demonstrate the developed prototype platform performs multiplex array assays as well as hand-performed assays, and that the instrument's sensitivity and specificity are dictated by the quality of the loaded multiplex assay.

Electronic characterization of lithographically patterned microcoils for high sensitivity NMR detection.

Nuclear magnetic resonance (NMR) offers a non-destructive, powerful, structure-specific analytical method for the identification of chemical and biological systems. The use of radio frequency (RF) microcoils has been shown to increase the sensitivity in mass-limited samples. Recent advances in micro-receiver technology have further demonstrated a substantial increase in mass sensitivity [D.L. Olson, T.L. Peck, A.G. Webb, R.L. Magin, J.V. Sweedler, High-resolution microcoil H-1-NMR for mass-limited, nanoliter-volume samples, Science 270 (5244) (1995) 1967-1970]. Lithographic methods for producing solenoid microcoils possess a level of flexibility and reproducibility that exceeds previous production methods, such as hand winding microcoils. This paper presents electrical characterizations of RF microcoils produced by a unique laser lithography system that can pattern three dimensional surfaces and compares calculated and experimental results to those for wire wound RF microcoils. We show that existing optimization conditions for RF coil design still hold true for RF microcoils produced by lithography. Current lithographic microcoils show somewhat inferior performance to wire wound RF microcoils due to limitations in the existing electroplating technique. In principle, however, when the pitch of the RF microcoil is less than 100mum lithographic coils should show comparable performance to wire wound coils. In the cases of larger pitch, wire cross sections can be significantly larger and resistances lower than microfabricated conductors.

Reagentless detection of Mycobacteria tuberculosis H37Ra in respiratory effluents in minutes.

Two similar mycobacteria, Mycobacteria tuberculosis H37Ra and Mycobacteria smegmatis are rapidly detected and identified within samples containing a complex background of respiratory effluents using single-particle aerosol mass spectrometry (SPAMS). M. tuberculosis H37Ra (TBa), an avirulent strain, is used as a surrogate for virulent tuberculosis; M. smegmatis (MSm) is utilized as a near-neighbor confounder for TBa. Bovine lung surfactant and human exhaled breath condensate are used as first-order surrogates for infected human lung expirations from patients with pulmonary tuberculosis. This simulated background sputum is mixed with TBa or MSm and nebulized to produce conglomerate aerosol particles, single particles that contain a bacterium embedded within a background respiratory matrix. Mass spectra of single conglomerate particles exhibit ions associated with both respiratory effluents and mycobacteria. Spectral features distinguishing TBa from MSm in pure and conglomerate particles are shown. SPAMS pattern matching alarm algorithms are able to distinguish TBa-containing particles from background matrix and MSm for >50% of the test particles, which is sufficient to enable a high probability of detection and a low false alarm rate if an adequate number of such particles are present. These results indicate the potential usefulness of SPAMS for rapid, reagentless tuberculosis screening.

Fe vibrational spectroscopy of myoglobin and cytochrome f.

The Fe vibrational density of states (VDOS) has been determined for the heme proteins deoxymyoglobin, metmyoglobin, and cytochrome f in the oxidized and reduced states, using nuclear resonance vibrational spectroscopy (NRVS). For cytochrome f in particular, the NRVS spectrum is compared with multiwavelength resonance Raman spectra to identify those Raman modes with significant Fe displacement. Modes not seen by Raman due to optical selection rules appear in the NRVS spectrum. The mean Fe force constant extracted from the VDOS illustrates how Fe dynamics varies among these four monoheme proteins, and is correlated with oxidation and spin state trends seen in model heme compounds. The protein's contribution to Fe motion is dominant at low frequencies, where coupling to the backbone tightly constrains Fe displacements in cytochrome f, in contrast to enhanced heme flexibility in myoglobin.