Simultaneous quantification of the boar-taint compounds skatole and androstenone by surface-enhanced Raman scattering (SERS) and multivariate data analysis

Comprehensive SPME-GC-MS Analysis of VOC Profiles Obtained Following High-Temperature Heating of Pork Back Fat with Varying Boar Taint Intensities

Boar taint detection is a major concern for the pork industry. Currently, this taint is mainly detected through a sensory evaluation. However, little is known about the entire volatile organic compounds (VOCs) profile perceived by the assessor. Additionally, many research groups are working on the development of new rapid and reliable detection methods, which include the VOCs sensor-based methods. The latter are susceptible to sensor poisoning by interfering molecules produced during high-temperature heating of fat. Analyzing the VOC profiles obtained by solid phase microextraction gas chromatography–mass spectrometry (SPME-GC-MS) after incubation at 150 and 180 °C helps in the comprehension of the environment in which boar taint is perceived. Many similarities were observed between these temperatures; both profiles were rich in carboxylic acids and aldehydes. Through a principal component analysis (PCA) and analyses of variance (ANOVAs), differences were highlighted. Aldehydes such as (E,E)-nona-2,4-dienal exhibited higher concentrations at 150 °C, while heating at 180 °C resulted in significantly higher concentrations in fatty acids, several amide derivatives, and squalene. These differences stress the need for standardized parameters for sensory evaluation. Lastly, skatole and androstenone, the main compounds involved in boar taint, were perceived in the headspace at these temperatures but remained low (below 1 ppm). Higher temperature should be investigated to increase headspace concentrations provided that rigorous analyses of total VOC profiles are performed.

Feasibility of on/at Line Methods to Determine Boar Taint and Boar Taint Compounds: An Overview

Simple Summary

Due to welfare issues, the physical castration of male pigs is decreasing, and the entire male pig production is increasing. Fattening entire male pigs requires control due to the possibility of accumulating off odour/flavour called boar taint, which is mainly due to two compounds - skatole and androstenone. If carcasses with boar taint reach the market, it can cause a negative consumer reaction which may have economic consequences for the whole meat chain. Thus, it is necessary to sort out carcasses at the slaughter line. Today, a sensory quality control (human nose method) is used in some slaughter plants for this purpose. Detection by physical or chemical methods is also envisaged. A colorimetric method to determine skatole has been used in Danish abattoirs for decades, but it is foreseen that it will soon be replaced by the laser diode thermal desorption ion source coupled with a mass spectrometry equipment that allows a fully automated classification based on skatole and androstenone levels at speed line, with a delay of less than 40 min. Other potential methods such as the electrochemical biosensors, rapid evaporative ionization mass spectroscopy and Raman spectroscopy, still need further development and validation for an application at abattoir level.

Abstract

Classification of carcasses at the slaughter line allows an optimisation of its processing and differentiated payment to producers. Boar taint is a quality characteristic that is evaluated in some slaughter plants. This odour and flavour is mostly present in entire males and perceived generally by sensitive consumers as unpleasant. In the present work, the methodologies currently used in slaughter plants for boar taint classification (colorimetric method and sensory quality control-human nose) and the methodologies that have the potential to be implemented on/at the slaughter line (mass spectrometry, Raman and biosensors) have been summarized. Their main characteristics are presented and an analysis of strengths, weaknesses, opportunities and threats (SWOT) has been carried out. From this, we can conclude that, apart from human nose, the technology that arises as very promising and available on the market, and that will probably become a substitute for the colorimetric method, is the tandem between the laser diode thermal desorption ion source and the mass spectrometry (LDTD-MS/MS) with automation of the sampling and sample pre-treatment, because it is able to work at the slaughter line, is fast and robust, and measures both androstenone and skatole.

Making complex measurements of meat composition fast: Application of rapid evaporative ionisation mass spectrometry to measuring meat quality and fraud

Increasing demands are being placed on meat producers to verify more about their product with regards to safety, quality and authenticity. There are many methods that can detect aspects of these parameters in meat, yet most are too slow to keep up with the demands of modern meat processing plants and supply chains. A new technology, Rapid Evaporative Ionisation Mass Spectrometry (REIMS), has the potential to bridge the gap between advanced laboratory measurements and technology that can screen for quality, safety and authenticity parameters in a single measurement. Analysis with REIMS generates a detailed mass spectral fingerprint representative of a meat sample without the need for sample processing. REIMS has successfully been used to detect species fraud, detect use of hormones in meat animals, monitor meat processing and to detect off flavours such as boar taint. The aim of this review is to summarize these and other applications to highlight the potential of REIMS for meat analysis. Sampling methods and important considerations for data analysis are discussed as well as limitations of the technology and remaining challenges for practical adoption.

Critical Review on the Utilization of Handheld and Portable Raman Spectrometry in Meat Science

Traditional methods for the determination of meat quality-relevant parameters are rather time-consuming and destructive, whereas spectroscopic methods offer fast and non-invasive measurements. This review critically deals with the application of handheld and portable Raman devices in the meat sector. Some published articles on this topic tend to convey the impression of unrestricted applicability of mentioned devices in this field of research. Furthermore, results are often subjected to over-optimistic interpretations without being underpinned by adequate test set validation. On the other hand, deviations in reference methods for meat quality assessment and the inhomogeneity of the meat matrix pose a challange to Raman spectroscopy and multivariate models. Nonetheless, handheld and portable Raman devices show considerable potential for some applications in the meat sector.

Multivariate Calibration for Carbon Nanotubes in the Environment Using the Microwave Induced Heating Method

The goal of the present paper is to develop chemometrics-based multivariate calibration approaches for simultaneously determining quantity of individual carbon nanotubes (CNTs) in a multicomponent environmental matrix using a microwave induced heating method. A multifactor and multilevel experiment design was used to create 4 separate calibration datasets. Each calibration dataset contained 25 orthogonal CNTs with 2 or 3 factors (CNTs: single-walled CNTs (SWCNTs)/multi-walled CNTs (MWCNTs)/carboxylated MWCNTs (MWCNT-COOH)) and 5 levels (CNTs mass). The temperature rise (ΔT) spectral information was obtained for each sample by exposing to varying microwave conditions. This study showed the potential and applicability of partial least square regression (PLS), least square-support vector machine (LS-SVM) and artificial neural networks (ANN) in predicting quantities of SWCNTs, MWCNTs and MWCNT-COOH in environmental matrices with microwave induced temperature rises data. Our results revealed that the developed LS-SVM model presented higher R2 and lower root mean square error of prediction (RMSEP) (R2 = 0.74-0.93, RMSEP =0.0251 mg to 0.0328 mg in 2-component systems and R2 = 0.64-0.95, RMSEP = 0.0243 mg to 0.0410 mg in 3-component systems), while the ANN model was only accurate in estimating mass of SWCNT and MWCNT in a 2-component mixture (R2 = 0.77-0.89, RMSEP = 0.0322 mg to 0.0503 mg). The PLS model was found not effectively interpret relationship between microwave induced temperature rises data and mass of CNTs, indicated by small R2 (0.20-0.87) and large RMSEP (0.0209 mg -0.1021 mg).

Absolute Quantification of Uric Acid in Human Urine Using Surface Enhanced Raman Scattering with the Standard Addition Method

High levels of uric acid in urine and serum can be indicative of hypertension and the pregnancy related condition, preeclampsia. We have developed a simple, cost-effective, portable surface enhanced Raman scattering (SERS) approach for the routine analysis of uric acid at clinically relevant levels in urine patient samples. This approach, combined with the standard addition method (SAM), allows for the absolute quantification of uric acid directly in a complex matrix such as that from human urine. Results are highly comparable and in very good agreement with HPLC results, with an average <9% difference in predictions between the two analytical approaches across all samples analyzed, with SERS demonstrating a 60-fold reduction in acquisition time compared with HPLC. For the first time, clinical prepreeclampsia patient samples have been used for quantitative uric acid detection using a simple, rapid colloidal SERS approach without the need for complex data analysis.