Chemometric analysis for discrimination of extra virgin olive oils from whole and stoned olive pastes

Toward the Non-Targeted Detection of Adulterated Virgin Olive Oil with Edible Oils via FTIR Spectroscopy & Chemometrics: Research Methodology Trends, Gaps and Future Perspectives

Fourier-Transform mid-infrared (FTIR) spectroscopy offers a strong candidate screening tool for rapid, non-destructive and early detection of unauthorized virgin olive oil blends with other edible oils. Potential applications to the official anti-fraud control are supported by dozens of research articles with a "proof-of-concept" study approach through different chemometric workflows for comprehensive spectral analysis. It may also assist non-targeted authenticity testing, an emerging goal for modern food fraud inspection systems. Hence, FTIR-based methods need to be standardized and validated to be accepted by the olive industry and official regulators. Thus far, several literature reviews evaluated the competence of FTIR standalone or compared with other vibrational techniques only in view of the chemometric methodology, regardless of the inherent characteristics of the product spectra or the application scope. Regarding authenticity testing, every step of the methodology workflow, and not only the post-acquisition steps, need thorough validation. In this context, the present review investigates the progress in the research methodology on FTIR-based detection of virgin olive oil adulteration over a period of more than 25 years with the aim to capture the trends, identify gaps or misuses in the existing literature and highlight intriguing topics for future studies. An extensive search in Scopus, Web of Science and Google Scholar, combined with bibliometric analysis, helped to extract qualitative and quantitative information from publication sources. Our findings verified that intercomparison of literature results is often impossible; sampling design, FTIR spectral acquisition and performance evaluation are critical methodological issues that need more specific guidance and criteria for application to product authenticity testing.

Exploring the anticancer and antioxidant properties of Vicia faba L. pods extracts, a promising source of nutraceuticals

Background

Pulse crops are considered the major sources of proteins, dietary fiber, micronutrients, and bioactive phytochemicals. Among the numerous pulse crops, broad beans (Vicia faba L.) have received particular attention due to their nutraceutical, functional and economic importance. Our attention was mainly focused on the broad bean pods (VFs), which are the primary by-product of the domestic and industrial processing of broad beans and an attractive source of valuable ingredients.

Methods

In order to investigate the VFs properties, the flours from broad beans of three different harvest periods were extracted with acetone, methanol and 70% aqueous ethanol and the dried extracts were analyzed, qualitatively and quantitatively, and tested for their antioxidant through DPPH and ABTS assay and anticancer activities using the MTT assay and immunofluorescence analysis.

Results

The VF extracts demonstrated a good in vitro radical scavenging activity from the first stage of collection of all the V. faba L. extracts. Additionally, the extracts were tested for their cytotoxicity against a panel of cancer and normal cells and the outcomes indicated the ethanol extract as the most active against the melanoma cell line Sk-Mel-28, without affecting the viability of the normal cells. Finally, we found out that the ethanol extract interfered with the microtubules organization, leading to the cancer cells death by apoptosis.

Extra Virgin Olive Oil from Destoned Fruits to Improve the Quality of the Oil and Environmental Sustainability

The world production of olive oil represented 3.1 million tons in 2021 and the choice aimed at high quality extra virgin olive oils is increasingly appearing (IOC, 2022). Moreover, the production of a product of quality with environmental respect is grown in demand. Consequently, the so-called "ecological" processes mostly interest the production market of extra virgin olive oils. Despite the current processing and extraction technologies, the characteristics of olive oil can still be optimized. In this regard, interesting technology to produce olive oil remains the stone removal of the olives before the extraction of the oil. Recently, the destoners preserved a less low oil yield. In light of recent progress, the review focuses on the influence of destoning on the quality of extra virgin olive oil, using a systematic approach. Interest in this technology is increasing and many researchers report that destoned olive oils show superior characteristics confronting with those obtained by the traditional method. These data indicate that destoning is one of the most significant advantages for the improvement of the oil qualitative traits and the system's sustainability.

Ultrasound-Assisted Extraction, Chemical Characterization, and Impact on Cell Viability of Food Wastes Derived from Southern Italy Autochthonous Citrus Fruits

Citrus fruits are one of the principal fruits used to produce juices. Over the years, these fruits have been recognized as new health-promoting agents. In this work, food wastes derived from autochthonous citrus fruits of Southern Italy, named Limone di Rocca Imperiale, Arancia Rossa Moro, and Arancia Bionda Tardivo from Trebisacce, were analyzed. After fresh-squeezing juice, peel and pomace were employed to obtain six different extracts using an ultrasound-assisted method in a hydroalcoholic solvent. The extracts were analyzed in terms of qualitative composition, antioxidant properties, and antiproliferative activity on MCF-7, MDA-MB-231, and BJ-hTERT cell lines. GC-MS and LC-ESI-MS analyses showed different compounds: of note, limonin-hexoside, neodiosmin, obacunone glucoside, and diacetyl nomilinic acid glucoside have been identified as limonoid structures present in all the samples, in addition to different polyphenols including naringenin-glucoside, hesperetin-O-hexoside-O-rhamnoside-O-glucoside, diferuloyl-glucaric acid ester, chlorogenic acid, and the presence of fatty acids such as palmitic, myristic, and linoleic acids. These extracts were able to exert antioxidant activity as demonstrated by DPPH and ABTS assays and, although at higher doses, to reduce the cell viability of different solid tumor cell lines, as shown in MTT assays.

Correlation between Chemical Characterization and Biological Activity: An Urgent Need for Human Studies Using Extra Virgin Olive Oil

Extra virgin olive oil (EVOO) is one of the most important functional foods from the Mediterranean Diet due to its beneficial effect on human health in terms of prevention and/or adjuvant treatment of different pathological conditions. The positive effects linked to EVOO consumption are not only due to its major (monounsaturated fatty acids), but also to its minor components (phenolics), whose roles were greatly re-evaluated in the last years. Notwithstanding the huge number of studies demonstrating the antioxidant, anti-inflammatory and anti-cancer properties of EVOO’s phenolic compounds, only their antioxidant ability was supported by a Health Claim. However, to bear the claim, a specific phenolic composition is needed, thus reinforcing the need to correlate the characterization of the phenolic compounds to their biological activity. In fact, although the chemical characterization of VOO’s phenolic compounds was extensively studied, its correlation with biological effects is only partially investigated; this is especially true for human studies. This review aims to study the correlation between the chemical characterization of EVOO’s phenolics and the biological effects in terms of antioxidant/anti-inflammatory potentials, with a focus on the human studies and the relative concern on getting a specific Health Claim.

Ultrasound Assisted Extraction of Polyphenols from Ripe Carob Pods (Ceratonia siliqua L.): Combined Designs for Screening and Optimizing the Processing Parameters

Carob pulp has recently received great attention due to its considerable content of polyphenols having a wide range of health promoting effects. In this work, ultrasound assisted extraction was optimized sequentially using a screening Plackett–Burman design and non-standard central composite design coupled to response surface methodology and desirability function statistical tools, to find the best conditions for the extraction of nine polyphenols from carob pods. The gathered mathematical models showed that the highest significant factors influencing the extraction of all compounds were solid–solvent ratio, solvent concentration, and particle size, with the optimal results obtained at values of 0.2 g/mL, 40% ethanol, and 0.3 mm, respectively. Extraction temperature, time, sonication power, and frequency were set at 35 °C, 15 min, 100 W, and 37 kHz, respectively. These parameters help to reduce energy costs and to obtain the best possible extraction of polyphenols.

A Tara Gum/Olive Mill Wastewaters Phytochemicals Conjugate as a New Ingredient for the Formulation of an Antioxidant-Enriched Pudding

Olive mill wastewater, a high polyphenols agro-food by-product, was successfully exploited in an eco-friendly radical process to synthesize an antioxidant macromolecule, usefully engaged as a functional ingredient to prepare functional puddings. The chemical composition of lyophilized olive mill wastewaters (LOMW) was investigated by HPLC-MS/MS and ¹H-NMR analyses, while antioxidant profile was in vitro evaluated by colorimetric assays. Oleuropein aglycone (5.8 μg mL^-1) appeared as the main compound, although relevant amounts of an isomer of the 3-hydroxytyrosol glucoside (4.3 μg mL^-1) and quinic acid (4.1 μg mL^-1) were also detected. LOMW was able to greatly inhibit ABTS radical (IC₅₀ equal to 0.019 mg mL^-1), displaying, in the aqueous medium, an increase in its scavenger properties by almost one order of magnitude compared to the organic one. LOMW reactive species and tara gum chains were involved in an eco-friendly grafting reaction to synthesize a polymeric conjugate that was characterized by spectroscopic, calorimetric and toxicity studies. In vitro acute oral toxicity was tested against 3T3 fibroblasts and Caco-2 cells, confirming that the polymers do not have any effect on cell viability at the dietary use concentrations. Antioxidant properties of the polymeric conjugate were also evaluated, suggesting its employment as a thickening agent, in the preparation of pear puree-based pudding. High performance of consistency and relevant antioxidants features over time (28 days) were detected in the milk-based foodstuff, in comparison with its non-functional counterparts, confirming LOWM as an attractive source to achieve high performing functional foods.

Innovative Extraction Technologies for Development of Functional Ingredients Based on Polyphenols from Olive Leaves

Olive tree (Olea europea L.) leaves represent around 10% of the total weight of olives arriving at any given mill, which are generally discarded, causing economic and environmental issues. However, these are rich sources of natural bioactive compounds (i.e., polyphenols), which have health-promoting potential. Thus, the valorization of olive leaves by recovering and reusing their components should be a must for food sustainability and circular economy. This review provides an insight into the principal polyphenols present in olive leaves, together with agronomic variables influencing their content. It also summarizes the recent advances in the application of novel extraction technologies that have shown promising extraction efficacy, reducing the volume of extraction solvent and saving time and cost. Moreover, potential industrial uses and international patents filed in the pharmaceutic, food, and cosmetic sectors are discussed.

Evaluation of Olive Oil Quality with Electrochemical Sensors and Biosensors: A Review

Electrochemical sensors, sensor arrays and biosensors, alongside chemometric instruments, have progressed remarkably of late, being used on a wide scale in the qualitative and quantitative evaluation of olive oil. Olive oil is a natural product of significant importance, since it is a rich source of bioactive compounds with nutritional and therapeutic properties, and its quality is important both for consumers and for distributors. This review aims at analysing the progress reported in the literature regarding the use of devices based on electrochemical (bio)sensors to evaluate the bioactive compounds in olive oil. The main advantages and limitations of these approaches on construction technique, analysed compounds, calculus models, as well as results obtained, are discussed in view of estimation of future progress related to achieving a portable, practical and rapid miniature device for analysing the quality of virgin olive oil (VOO) at different stages in the manufacturing process.

Olive Sound: A Sustainable Radical Innovation

Olive Sound is the acronym of a Horizon 2020 European Project aimed at the development of a high-flow oil extraction plant, the Sono-Heat-Exchanger, which combines ultrasound and heat exchange in order to break, through a radical innovation model in the oil mill, the historical paradigm that sees as inversely correlated the oil yield and the content of bio-phenols. These compounds are biologically active molecules that transform the product, extra virgin olive oil, from a mere condiment into a functional food. The primary objective of the project, financially supported by the European Union through the “Fast Track to Innovation” program, is the development of a product “ready for the market” (TRL 9) capable of making the involved companies more competitive while increasing the competitiveness of European extra virgin olive oil in the international context.

Chemometric Discrimination of the Varietal Origin of Extra Virgin Olive Oils: Usefulness of 13C Distortionless Enhancement by Polarization Transfer Pulse Sequence and 1H Nuclear Magnetic Resonance Data and Effectiveness of Fusion with Mid-Infrared Spectroscopy Data

The label authentication of monovarietal extra virgin olives is of great relevance from a socio-economical point of view. This work aims to gain insights into the prediction of the varietal origin of extra virgin olive oil (EVOO) samples obtained from single olive cultivars, French cultivars Olivière, Salonenque, and Tanche and Portuguese cultivars Blanqueta, Carrasquenha, and Galega Vulgar, collected in 2016-2017 and 2017-2018 harvest seasons. To pursue this study, spectroscopic approaches based on one-dimensional nuclear magnetic resonance (1D NMR) spectroscopy, namely, ¹H and ¹³C NMR distortionless enhancement by polarization transfer (DEPT) 45 pulse sequence, and Fourier transform mid-infrared spectroscopy (FT-MIR) are used in combination with partial least square discriminant analysis (PLS1-DA). The results obtained by PLS1-DA models using ¹H and ¹³C NMR DEPT 45 data are compared to those of PLS1-DA models using MIR data. The application of a control chart method allows for the optimization of the interpretation of the PLS1-DA results, and an efficient two-step strategy is proposed to improve the discrimination of the six studied cultivars. Then, NMR and MIR data are combined by either a mid- or high-level data fusion approach to further improve the discrimination. The models are also tested on samples from other cultivars to check their ability to reject varieties that were not considered in the calibration process.

Simulation and Non-Invasive Testing of Vinegar Storage Time by Olfaction Visualization System and Volatile Organic Compounds Analysis

An olfactory visualization system conducts a qualitative or quantitative analysis of volatile organic compounds (VOCs) by utilizing the sensor array made of color sensitive dyes. The reaction chamber is important to the sensor array's sufficient and even exposure to VOCs. In the current work, a reaction chamber with an arc baffle embedded in the front of the air inlet for drainage effect was designed. The velocity of field and particle distribution of flow field in the reaction chamber was simulated by COMSOL Multiphysics. Through repeated simulation, the chamber achieved optimal result when the baffle curvature was 3.1 and the vertical distance between the baffle front end and the air inlet was 1.6 cm. Under the new reaction chamber, principal component analysis (PCA) and linear discriminant analysis (LDA) were employed to identify vinegar samples with different storage time through analyzing their VOCs. The LDA model achieved optimal performance when 8 principal components (PCs) were used, and the recognition rate was 95% in both training and prediction sets. The new reaction chamber could improve the stability and precision of an olfactory visualization system for VOCs analysis, and achieve the accurate differentiation and rapid discrimination of Zhenjiang vinegar with different storage time.

Pre etched Ag nanocluster as SERS substrate for the rapid quantification of AFB1 in peanut oil via DFT coupled multivariate calibration

The current study extends the use of surface-enhanced Raman spectroscopy (SERS) combined with density functional theory (DFT) and multivariate calibration towards the rapid quantification of aflatoxin B1 (AFB1) in peanut oil samples. It reports the design of pre etched Ag nanocluster as an active SERS substrate for quantifying AFB1, after being impregnated on its surface. The SERS spectra of AFB1@pre etched Ag nanocluster was recorded and its respective theoretical spectrum was calculated by density functional theory (DFT) to assign the characteristic peaks. The baseline drift and rotation effects were masked by the first-order derivative preprocessing method followed by multivariate calibration. The BP-AdaBoost model exhibited optimum prediction (Rp = 0.9283 and 0.9332) ability over the concentration range 5-100 and 100-1000 ngmL^-1, respectively. The limit of detection calculated was 5.0 ngmL^-1 and the obtained recoveries were in the range from 90.4% to 113.1% in spiked peanut oil samples. Additionally, precision analysis revealed an RSD ca. 5%, suggesting the applicability of the pre etched Ag nanocluster SERS substrate towards AFB1 detection. Thus, the proposed SERS platform exploiting DFT and BP-AdaBoost model was found reproducible for the quantification of AFB1 in peanut oil.

Rapid Classification and Quantification of Camellia (Camellia oleifera Abel.) Oil Blended with Rapeseed Oil Using FTIR-ATR Spectroscopy

Currently, the authentication of camellia oil (CAO) has become very important due to the possible adulteration of CAO with cheaper vegetable oils such as rapeseed oil (RSO). Therefore, we report a Fourier transform infrared (FTIR) spectroscopic method for detecting the authenticity of CAO and quantifying the blended levels of RSO. In this study, two characteristic spectral bands (1119 cm^-1 and 1096 cm^-1) were selected and used for monitoring the purity of CAO. In combination with principal component analysis (PCA), linear discriminant analysis (LDA), and partial least squares regression (PLSR) analysis, qualitative and quantitative methods for the detection of camellia oil adulteration were proposed. The results showed that the calculated I₁₁₁₉/I₁₀₉₆ intensity ratio facilitated an initial check for pure CAO and six other edible oils. PCA was used on the optimized spectral region of 1800-650 cm^-1. We observed the classification of CAO and RSO as well as discrimination of CAO with RSO adulterants. LDA was utilized to classify CAO from RSO. We could differentiate and classify RSO adulterants up to 1% v/v. In the quantitative PLSR models, the plots of actual values versus predicted values exhibited high linearity. Root mean square error of calibration (RMSEC) and root mean square error of cross validation (RMSECV) values of the PLSR models were 1.4518%-3.3164% v/v and 1.7196%-3.8136% v/v, respectively. This method was successfully applied in the classification and quantification of CAO adulteration with RSO.

Chemometric tools for food fraud detection: The role of target class in non-targeted analysis

The chemometric issues related to the application of non-targeted analysis for the detection of food frauds were analyzed employing discriminant analysis and a one-class classifier. The similarities and differences between the two methods were investigated. The results of classification are characterized by a set of indices called figures of merit. They comprehensively characterized the quality and reliability of classification. The principle is illustrated using an actual example of Oregano herbs adulteration. The informative region 9000-4000 cm^-1 of near-Infrared spectroscopy is used as analytical means. The results of the application of each method for Oregano data collection are presented. It is shown that the discriminant method is only partially appropriate for solving the authentication problem. One class classifier is a powerful and devoted for non-targeted analysis. The step by step analysis introduced in the paper can also be successfully utilized in apply for revealing of forgeries of various food products.

Use of FTIR Spectroscopy and Chemometrics with Respect to Storage Conditions of Moldavian Dragonhead Oil

Oils often have similar properties and can be difficult to identify based on color, smell or taste alone. The present paper suggests the use of Fourier-transform infrared spectroscopy (FTIR) in combination with chemometric methods to explore similarities and differentiate between samples of Moldavian dragonhead oil subjected to different storage conditions. Dragonhead is a plant characterized by very good honey output and ease of cultivation. Principal component analysis (PCA) was applied to a standard, full range of FTIR spectra. Additionally, hierarchical cluster analysis (HCA) was employed to explore the organization of the samples in groups relative to their “proximity” (similarity), by way of Euclidean distance measurement. PC1 and PC2 accounted respectively for 85.4% and 10.1% of the total data variance. PC1 and PC2 were strongly, negatively correlated within the entire spectral range; the only exception was the region corresponding to νs(-C-Hvst, -CH2) vibrations (aliphatic groups in triglycerides), where PC2 was positively correlated. The use of FTIR spectral analysis revealed noticeable differences in the intensity of bands characteristic of the ageing processes (markers of oxidative processes, etc.) taking place in oleaginous samples and related to the processes of fatty acids oxidation.

Rapid Classification of Wheat Grain Varieties Using Hyperspectral Imaging and Chemometrics

The classification of wheat grain varieties is of great value because its high purity is the yield and quality guarantee. In this study, hyperspectral imaging combined with the chemometric methods was applied to explore and implement the varieties classification of wheat seeds. The hyperspectral images of all the samples covering 874–1734 nm bands were collected. Exploratory analysis was first carried out while using principal component analysis (PCA) and linear discrimination analysis (LDA). Spectral preprocessing methods including standard normal variate (SNV), multiplicative scatter correction (MSC), and wavelet transform (WT) were introduced, and their effects on discriminant models were studied to eliminate the interference of instrumental and environmental factors. PCA loading, successive projections algorithm (SPA), and random frog (RF) were applied to extract feature wavelengths for redundancy elimination owing to the possibility of existing redundant spectral information. Classification models were developed based on full wavelengths and feature wavelengths using LDA, support vector machine (SVM), and extreme learning machine (ELM). This optimal model was finally utilized to generate visualization map to observe the classification performance intuitively. When comparing with other models, ELM based on full wavelengths achieved the best accuracy up to 91.3%. The overall results suggested that hyperspectral imaging was a potential tool for the rapid and accurate identification of wheat varieties, which could be conducted in large-scale seeds classification and quality detection in modern seed industry.

Evaluation of human breastmilk adulteration by combining Fourier transform infrared spectroscopy and partial least square modeling

A two-step chemometric procedure was developed on the attenuated total reflection-Fourier transform infrared data of human breastmilk to detect adulteration by water or cow milk. The samples, collected from a Milk Bank, were analyzed before and after adulteration with whole, skimmed, semi-skimmed cow milk and water. A preliminary clustering via principal component analysis distinguished three classes: pure milk, milk adulterated with water, and milk adulterated with cow milk. A first partial least square-discriminant analysis (PLS-DA) classification model was built and then applied on new samples to identify the specific adulterants. The external validation on this model reached 100% of the correct identification of pure milk and 90% of the type of adulterants. In the following step, four PLS calibration models were built to quantify the amount of the adulterant detected in the classification analysis. The prediction performance of these models on new samples showed satisfactory parameters with root mean square error of prediction and percentage relative error lower than 1.38% and 3.31%, respectively.

Industrial Ultrasound Applications in The Extra-Virgin Olive Oil Extraction Process: History, Approaches, and Key Questions

Taking an idea from a basic concept to a commercially available product is highly rewarding, but it can be a very long, complex, and difficult journey. Recognizing and understanding the stages of the process and using the right support to help you navigate through it can mean all the difference between success and failure. The road from concept to market is marred with obstacles, and many businesses fail to pass beyond the development stage. A better understanding of the innovation process is essential from the outset if the pioneers of innovation are to overcome the dangers that they are likely to face along the way and maximize their opportunities for success. In the olive oil sector, the most recent radical innovation is the introduction of ultrasound into the industrial extraction process. Many efforts have been made in order to overcome the Valley of Death. The strategy of designing, implementing, and testing an innovative system that combines the mechanical energy of ultrasound with the possibility of modulating the thermal exchange of olive paste (heating or cooling) has enabled the following: (1) Eliminating malaxation by realizing a real continuous process; (2) raising extraction yields by recovering a further quota of extra-virgin olive oil that is usually lost in the pomace; (3) improving the content of antioxidant molecules simultaneously with yields; and (4) offering a sustainable plant solution that can guarantee the right income for producers.

Photo and thermal stress of linseed oil and stabilization strategies

The thermal and light stability of linseed oil has been studied by monitoring the concentrations of fatty acids and lignans, as main nutraceutical components. Linseed oil was subjected to stressing light and temperature conditions, in accordance with the ICH international rules, and monitored by UV-vis spectroscopy and HPLC-DAD. The change of UV spectra along the photodegradation tests, setting the irradiation power at 350 W/m2, confirmed a significant overall sensitivity of linseed oil to light. At the same time, the HPLC determination of the major fatty acids showed a marked variation in their concentration up to a residual concentration of 62.3 and 67.2% for α-linolenic and linoleic acid, respectively, after 18 h. In contrast, thermal tests at 60 °C showed some stability, with a concentration of residual fatty acids in the range 82-95% after 48 h. The examined lignans showed significant stability when exposed to both light and heat. Several photoprotection approaches have been also studied to increase the photostability of linseed oil. A significant increase in the stability of fatty acids has been observed using amber glass containers or ascorbic acid or by combining the two protection factors.

Trends in Chemometrics: Food Authentication, Microbiology, and Effects of Processing

In the last decade, the use of multivariate statistical techniques developed for analytical chemistry has been adopted widely in food science and technology. Usually, chemometrics is applied when there is a large and complex dataset, in terms of sample numbers, types, and responses. The results are used for authentication of geographical origin, farming systems, or even to trace adulteration of high value-added commodities. In this article, we provide an extensive practical and pragmatic overview on the use of the main chemometrics tools in food science studies, focusing on the effects of process variables on chemical composition and on the authentication of foods based on chemical markers. Pattern recognition methods, such as principal component analysis and cluster analysis, have been used to associate the level of bioactive components with in vitro functional properties, although supervised multivariate statistical methods have been used for authentication purposes. Overall, chemometrics is a useful aid when extensive, multiple, and complex real-life problems need to be addressed in a multifactorial and holistic context. Undoubtedly, chemometrics should be used by governmental bodies and industries that need to monitor the quality of foods, raw materials, and processes when high-dimensional data are available. We have focused on practical examples and listed the pros and cons of the most used chemometric tools to help the user choose the most appropriate statistical approach for analysis of complex and multivariate data.

A scoring metric for multivariate data for reproducibility analysis using chemometric methods

Process quality control and reproducibility in emerging measurement fields such as metabolomics is normally assured by interlaboratory comparison testing. As a part of this testing process, spectral features from a spectroscopic method such as nuclear magnetic resonance (NMR) spectroscopy are attributed to particular analytes within a mixture, and it is the metabolite concentrations that are returned for comparison between laboratories. However, data quality may also be assessed directly by using binned spectral data before the time-consuming identification and quantification. Use of the binned spectra has some advantages, including preserving information about trace constituents and enabling identification of process difficulties. In this paper, we demonstrate the use of binned NMR spectra to conduct a detailed interlaboratory comparison and composition analysis. Spectra of synthetic and biologically-obtained metabolite mixtures, taken from a previous interlaboratory study, are compared with cluster analysis using a variety of distance and entropy metrics. The individual measurements are then evaluated based on where they fall within their clusters, and a laboratory-level scoring metric is developed, which provides an assessment of each laboratory's individual performance.