Saskia M. van Ruth

A review of analytical methods for the identification and characterization of nano delivery systems in food.

Detection and characterization of nano delivery systems is an essential part of understanding the benefits as well as the potential toxicity of these systems in food. This review gives a detailed description of food nano delivery systems based on lipids, proteins, and/or polysaccharides and investigates the current analytical techniques that can be used for the identification and characterization of these delivery systems in food products. The analytical approaches have been subdivided into three groups; separation techniques, imaging techniques, and characterization techniques. The principles of the techniques together with their advantages and drawbacks, and reported applications concerning nano delivery systems, or otherwise related compounds are discussed. The review shows that for a sufficient characterization, the nano delivery systems need to be separated from the food matrix, for which high-performance liquid chromatography or field flow fractionation are the most promising techniques. Subsequently, online photon correlation spectroscopy and mass spectrometry seem to be a convenient combination of techniques to characterize a wide variety of nano delivery systems.

Chemical Composition, Sensory Properties, Provenance, and Bioactivity of Fruit Juices as Assessed by Chemometrics: A Critical Review and Guideline

The use of univariate, bivariate, and multivariate statistical techniques, such as analysis of variance, multiple comparisons of means, and linear correlations, has spread widely in the area of Food Science and Technology. However, the use of supervised and unsupervised statistical techniques (chemometrics) in order to analyze and model experimental data from physicochemical, sensory, metabolomics, quality control, nutritional, microbiological, and chemical assays in food research has gained more space. Therefore, we present here a manuscript with theoretical details, a critical analysis of published work, and a guideline for the reader to check and propose mathematical models of experimental results using the most promising supervised and unsupervised multivariate statistical techniques, namely: principal component analysis, hierarchical cluster analysis, linear discriminant analysis, partial least square regression, k-nearest neighbors, and soft independent modeling of class analogy. In addition, the overall features, advantages, and limitations of such statistical methods are presented and discussed. Published examples are focused on sensory, chemical, and antioxidant activity of a wide range of fruit juices consumed worldwide.

Identification and age estimation of blood stains on colored backgrounds by near infrared spectroscopy

Non-destructive identification and subsequent age estimation of blood stains are significant steps in forensic casework. The latter can provide important information on the temporal aspects of a crime. As previously shown, visible spectroscopy of blood stains on white backgrounds can successfully be used for their identification and age estimation. The use of this technique however, is hampered by dark backgrounds. In the present study the feasibility to use near infrared (NIR) spectroscopy was evaluated for blood stain identification and age estimation on dark backgrounds. Using NIR reflectance spectroscopy, blood stains were distinguished from other substances with 100% sensitivity and 100% specificity. In addition, Partial Least Squares Regression analysis was applied to estimate the age of blood stains on colored backgrounds. The age of blood stains up to 1 month old was estimated successfully with a root mean squared error of prediction of 8.9%. These findings are an important step toward the practical implementation of blood stain identification and age estimation in forensic casework, where a large variety of backgrounds can be encountered.

Authentication of Geographical Origin and Crop System of Grape Juices by Phenolic Compounds and Antioxidant Activity Using Chemometrics

The main goal of this work was to propose an authentication model based on the phenolic composition and antioxidant and metal chelating capacities of purple grape juices produced in Brazil and Europe in order to assess their typicality. For this purpose, organic, conventional, and biodynamic grape juices produced in Brazil (n = 65) and in Europe (n = 31) were analyzed and different multivariate class-modeling and classification statistical techniques were employed to differentiate juices based on the geographical origin and crop system. Overall, Brazilian juices, regardless of the crop system adopted, presented higher contents of total phenolic compounds and flavonoids, total monomeric anthocyanins, proanthocyanidins, flavonols, flavanols, cyanidin-3-glucoside, delphinidin-3-glucoside, and malvidin-3,5-glucoside. No differences were observed for trans-resveratrol, malvidin-3-glucoside, and pelargonidin-3-glucoside between countries and among crop systems. A total of 91% of Brazilian and 97% of European juices were adroitly classified using partial least squares discriminant analysis when the producing region was considered (92% efficiency), in which the free-radical scavenging activity toward 2,2-diphenyl-1-picrylhydrazyl, content of total phenolic compounds, gallic acid, and malvidin-3-glucoside were the variables responsible for the classification. Intraregional models based on soft independent modeling of class analogy were able to differentiate organic from conventional Brazilian juices as well as conventional and organic/biodynamic European juices.

Verification of fresh grass feeding, pasture grazing and organic farming by cows farm milk fatty acid profile.

The present study investigated the use of fatty acid (FA) profiling in combination with chemometric modelling to verify claims for cow milk in terms of fresh grass feeding, pasture grazing and organic/biodynamic farming. The FA profile was determined for 113 tank milk samples collected in the Netherlands from 30 farms over four different months, and used to develop classification models based on the PLS-DA algorithm. Milk from cows with daily rations of fresh grass could be successfully distinguished from milk from cows with no fresh grass in their diet. Milk from cows at pasture could easily be distinguished from milk from stabled cows without fresh grass in the diet, but the correct prediction of milk from stabled cows fed fresh grass indoors proved difficult. The FA profile of organic/biodynamic milk was different compared to conventional milk but an unequivocal discrimination was not possible either in summer or in winter.

Authentication of geographical origin of palm oil by chromatographic fingerprinting of triacylglycerols and partial least square-discriminant analysis

Main goals of the present work were to develop authentication models based on liquid and gas chromatographic fingerprinting of triacylglycerols (TAGs) from palm oil of different geographical origins in order to compare them. For this purpose, a set of palm oil samples were collected from different continents: South eastern Asia, Africa and South America. For the analysis of the information in these fingerprint profiles, a pattern recognition technique such as partial least square discriminant analysis (PLS-DA) was applied to discriminate the geographical origin of these oils, at continent level. The liquid chromatography, coupled to a charged aerosol detector, (HPLC-CAD) TAGs separation was optimized in terms of mobile phase composition and by means of a solid silica core column. The gas chromatographic method with a mass spectrometer was applied under high temperature (HTGC-MS) in order to analyze the intact TAGs. Satisfactory chromatographic resolution within a short total analysis time was achieved with both chromatographic approaches and without any prior sample treatment. The rates of successful in prediction of the geographical origin of the 85 samples varied between 70% and 100%.

Applicability of PTR-MS in the quality control of saffron

The applicability of the emerging non-destructive technique, proton transfer reaction mass spectrometry (PTR-MS), was explored for the first time in the quality control of saffron. Monitoring of volatile organic compounds (VOCs) was achieved using a minute sample (35 mg). Fresh saffron was stored under selected conditions (25 and 40 °C, aw=0.64) over a five weeks period to produce lower quality material, which was used to prepare mixtures with fresh saffron. Analysis showed that the VOCs fingerprint changed upon storage, and the concentration of initially dominant VOC safranal decreased progressively. Examination of calculated and recorded fingerprints for various admixtures showed that PTR-MS VOCs analysis, in combination with chemometrics, could be used to screen for the presence of lower quality saffron in a commercial product in a few minutes. The technique can be used in a complementary fashion, adding to the battery of advanced analytical techniques available to address the quality and authenticity issues of saffron.

Geographical provenancing of purple grape juices from different farming systems by proton transfer reaction mass spectrometry using supervised statistical techniques

BACKGROUND Organic, biodynamic and conventional purple grape juices (PGJ; n = 79) produced in Brazil and Europe were characterized by volatile organic compounds (m/z 20-160) measured by proton transfer reaction mass spectrometry (PTR-MS), and classification models were built using supervised statistical techniques. RESULTS k-Nearest neighbours and soft independent modelling of class analogy (SIMCA) models discriminated adequately the Brazilian from European PGJ (overall efficiency of 81% and 87%, respectively). Partial least squares discriminant analysis (PLSDA) classified 100% European and 96% Brazilian PGJ. Similarly, when samples were grouped as either conventional or organic/biodynamic, the PLSDA model classified 81% conventional and 83% organic/biodynamic juices. Intraregional PLSDA models (juices produced in the same region - either Europe or Brazil) were developed and were deemed accurate in discriminating Brazilian organic from conventional PGJ (81% efficiency), as well as European conventional from organic/biodynamic PGJ (94% efficiency). CONCLUSIONS PGJ from Brazil and Europe, as well as conventional and organic/biodynamic PGJ, were distinguished with high efficiency, but no statistical model was able to differentiate organic and biodynamic grape juices. These data support the hypothesis that no clear distinction between organic and biodynamic grape juices can be made with respect to volatile organic compounds.

Portraying and tracing the impact of different production systems on the volatile organic compound composition of milk by PTR-(Quad)MS and PTR-(ToF)MS

The aim of this study was to discover the unique volatile compositional traits of retail milk from different production systems. Forty-four retail milk samples were analyzed, including organic milk (n=10), conventional milk (n=14) and pasture milk (n=20) from winter (n=22) and summer (n=22). Proton transfer reaction quadrupole mass spectrometry (PTR-(Quad)MS) was utilized to obtain the mass-resolved fingerprints (76 masses per sample) of volatile organic compounds (VOCs). Principal component analysis (PCA) and analysis of variance (ANOVA) were performed to evaluate the differences between the groups. The production systems were characterized by six masses, while season showed larger differences, with twenty-two masses discriminating between the milks. For 2 masses, a significant interaction of systems and seasons was observed. The chemical formula of these VOC masses were tentatively identified by Proton Transfer Reaction Time-of-Flight Mass Spectrometric (PTR-(ToF)MS). These results illustrate that the type of feed is reflected in the VOC composition of milks.

Status quo and future research challenges on organic food quality determination with focus on laboratory methods

Organic food quality determination needs multi-dimensional evaluation tools. The main focus is on the authentication as an analytical verification of the certification process. New fingerprinting approaches such as ultra-performance liquid chromatography-mass spectrometry, gas chromatography-mass spectrometry, direct analysis in real time-high-resolution mass spectrometry as well as crystallization with and without the presence of additives seem to be promising methods in terms of time of analysis and detecting organic system-related parameters. For further methodological development, a system approach is recommended, which also takes into account food structure aspects. Furthermore, the authentication of processed organic samples needs more consciousness, hence most of organic food is complex and processed.