Wine authentication: Current progress and state of the art

Wine authentication is vital in identifying malpractice and fraud, and various physical and chemical analytical techniques have been employed for this purpose. Besides wet chemistry, these include chromatography, isotopic ratio mass spectrometry, optical spectroscopy, and nuclear magnetic resonance (NMR) spectroscopy, which have been applied in recent years in combination with chemometric approaches. For many years, 2 H NMR spectroscopy was the method of choice and achieved official recognition in the detection of sugar addition to grape products. Recently, 1 H NMR spectroscopy, a simpler and faster method (in terms of sample preparation), has gathered more and more attention in wine analysis, even if it still lacks official recognition. This technique makes targeted quantitative determination of wine ingredients and nontargeted detection of the metabolomic fingerprint of a wine sample possible. This review summarizes the possibilities and limitations of 1 H NMR spectroscopy in analytical wine authentication, by reviewing its applications as reported in the literature. Examples of commercial and open-source solutions combining NMR spectroscopy and chemometrics are also examined herein, together with its opportunities of becoming an official method.

Quantitation of thin-layer chromatography (TLC) using image analysis is attractive for its low cost and convenience. The image analysis is investigated by designing a digital imaging system with simple equipment, developing an image analysis software based on our algorithm, and validated the system in the TLC quantitative assay of cichoric acid present in Echinacea purpurea (L.) Moench. TLC used a polyamide thin-layer plate with chloroform-methanol formic acid-water (3:6:1:1) as the mobile phase and 3% (m/v) aqueous aluminum chloride solution as the visualization reagent. Images are acquired with a standard digital camera under a UV viewing lamp (365 nm) in a dark room. The three-dimensional gray scale digital image dataset (x, y, gray) is reduced to two-dimensional dataset (distance, accumulative gray) and then plotted as a curve. The area under the peak corresponding to the cichoric acid spot is integrated and used for quantitation. The whole method was validated by the assay tests of detection limit, calibration curve, repeatability, reproducibility, and recovery. The results showed that our digital imaging method and image analysis algorithm were applicable for the quantification of TLC. The whole method is convenient, efficient, and moderately accurate for the quantitative assay of cichoric acid present in Echinacea purpurea (L.) Moench.

SummaryAfter‐cooking darkening (ACD) phenomenon occurs when potato tubers develop greyish dark colour after boiling, frying, or steaming. The pigment responsible for ACD is a complex of chlorogenic acid and iron, which is formed during cooking and oxidised during cooling. The evaluation of ACD is thus based either on the amount of chlorogenic acid in raw tubers or the greyish colour intensity on cooked tuber surfaces. This study introduced a new method, the digital imaging method, for evaluation of potato ACD. The comparison of this new method with visual evaluation and the measurement of chlorogenic acid using HPLC were also presented. The digital imaging method is based on the direct measurement of the degree of dark colour on cut tuber surfaces, expressed by pixel levels. The new method is faster, more reliable and simpler when compared with any methods presently used. It is particularly applicable to handling large sample numbers.

A progressive reduction in the area of foot ulcer on serial measurement is traditionally done by tracing the margin of the ulcer on a transparent film and counting the number of squares on a graph paper underneath. We set out to use and validate the measurement of foot ulcers using a digital imaging technique and compare this with the traditional method. Thirty diabetic foot ulcers (18 patients) were studied over 10 weeks. Each ulcer was traced by three independent observers with a pen over a flexigrid Opsite film and digital photographs were taken. Each observer calculated the area of an ulcer first using a 1-mm2 graph paper and then with the computer software. For each ulcer we calculated the mean area using measurements from all the observers. We then calculated the deviation from this mean for each observer. There was significantly less interobserver variation using the digital image than the traditional method with mean coefficient of variation (CV) 16% vs. 27%; P = 0.05. The digital imaging method was faster and easier to use and the patients preferred it, as it was a noncontact method. In addition it also provides a photographic record for comparison.

Measuring volume and density of a barley grain using ellipsoid approximation from a 2-D digital image

The study of grain size distribution of gravels is an important and challenging issue in stratigraphy and morphology, especially in the field of automated measurement. It largely reduces many manual processes and time consumption. Using digital image processing method to extract effective information from digital images is a more advanced method. In this study, a digital image method using automated multiple superpixel segmentation and merging is proposed for extraction of the grain size data. It adds grain size estimation and improved merging rules and repeated execution rules to the superpixel segmentation and merging. It has made great improvements in many respects, especially in the accuracy of edge segmentation and measurement. Compared with manual measurement and other image processing ways, the method proposed in this paper is an efficient approach for precisely measuring the grain size distribution of riverbed material.

Medidas do índice de área foliar são necessárias para a maioria dos estudos agronômicos e fisiológicos envolvendo crescimento vegetal. Foi desenvolvido um experimento no Instituto Agronômico do Paraná (IAPAR), em Londrina (PR), durante a safra 2005/2006, com objetivo de avaliar dois métodos diretos de medição de área de folíolos de soja por meio de dimensões foliares e por imagens digitais capturadas por máquina fotográfica digital amadora, em duas situações distintas, folíolos íntegros e folíolos danificados. As estimativas obtidas foram comparadas com as medidas feitas com um integrador de área foliar LI-COR®, modelo LI 3100, tomado como referência. Nas estimativas realizadas em folíolos íntegros, tanto pelo método de dimensões foliares como no de imagem digital, notou-se excelente concordância com as medidas obtidas pelo método LI-COR® (R² = 0,983 e R² = 0,997 respectivamente). Para folíolos danificados, o método de imagem digital revelou coeficiente de determinação um pouco superior ao método de dimensões foliares, mas com um erro-padrão três vezes menor. O método de imagem digital pode substituir o método usado como referência (LI 3100) com vantagens de custo inferior e acuracidade similar.

A methodology is proposed, which employs duplicated primary sampling and subsequent duplicated physical preparation coupled with duplicated chemical analyses. Sample preparation duplicates should be prepared under conditions that represent normal variability in routine laboratory practice. The proposed methodology requires duplicated chemical analysis on a minimum of two of the sample preparation duplicates. Data produced from the hierarchical design is treated with robust analysis of variance (ANOVA) to generate uncertainty estimates, as standard uncertainties ('u' expressed as standard deviation), for primary sampling (ssamp), physical sample preparation (sprep) and chemical analysis (sanal). The ANOVA results allow the contribution of the sample preparation process to the overall uncertainty to be assessed. This methodology has been applied for the first time to a case study of pesticide residues in retail strawberry samples. Duplicated sample preparation was performed under ambient conditions on two consecutive days. Multi-residue analysis (quantification by GC-MS) was undertaken for a range of incurred pesticide residues including those suspected of being susceptible to loss during sample preparation procedures. Sampling and analytical uncertainties dominated at low analyte concentrations. The sample preparation process contributed up to 20% to the total variability and had a relative uncertainty (Uprep%) of up to 66% (for bupirimate at 95% confidence). Estimates of systematic errors during physical sample preparation were also made using spike recovery experiments. Four options for the estimation of measurement uncertainty are discussed, which both include and exclude systematic error arising from sample preparation and chemical analysis. A holistic approach to the combination and subsequent expression of uncertainty is advised.

As the trend of the new generation of intelligent transportation systems, the application of the cooperative vehicle-infrastructure system (CVIS) is important to reduce traffic congestion and accidents. For the cooperative vehicle-infrastructure system, the roadside unit (RSU) is a new application without enough deployment experience. Meanwhile the deployment of traditional mechanical and electrical infrastructure is generally based on experience and is easy to change the design. This paper analyzes the key technical parameters of RSU and the Digital Measurable Image (DMI) method in context of the CVIS. After collecting field data from a smart highway pilot project (the Deqing-Fuyang expanded Huzhou section in Chang-Shen Highway) and matching the DMI method with highway mileage pile numbers, an RSU deployment scheme based on DMI data was completed. It provides significant support for smart highway demonstration projects with cooperative vehicle-infrastructure intelligent management and control applications.

The most important characteristics of IR versus Raman spectroscopy, their uses, according to recent literature data, are reviewed here. These advanced analytical methods are non-destructive and versatile, useful to identify plant biomarkers (metabolomics) and for agrifood quality and authenticity assessment.To give some relevant examples, we present here recent experimental data for edible oils and fruit juices FTIR fingerprints, trying to identify directly the relevant IR markers of their authenticity. Raman spectroscopy is needed to follow as complementary measurement. Both these methods are useful to fingerprint non-destructively different samples (powders, extracts, emulsions) without any preliminary processing, there are rapid and cheaper than chromatography. As complementary tools, IR and Raman spectroscopy can give added-value information on all types of molecules found in plants and food. The sine-qua-non condition to make appropriate interpretations of FTIR-Raman fingerprint markers is a good chemometric analysis (processing of raw spectra by first and second derivatives, PLS comparisons with validated methods, such as GC and HPLC).

Digital image counting system for nuclear track detectors

The assessment of dietary intake with food records has traditionally been a burdensome experience for both the person keeping the records and the dietitian/nutritionist analysing the record. The advent of Smartphones with high-resolution cameras, the ability to run apps and internet connections has enabled developments in the field. Pubmed and Web of Science databases were searched for relevant articles from 2013 to present to synthesize this review. The digital methods for dietary assessment fall into three categories: apps that require digital entry of foods (researcher and commercial); digital images; and image-assisted methods. All categories have advanced substantially. Researcher apps have shown good agreement between energy and food intakes when compared with a 24-hour dietary recall but no biomarker studies were located. Commercial apps can yield valid results for energy but when used in the community with uncontrolled conditions significant omission of foods and underestimation occurs. Digital image methods whereby the participant's photos with or without audio or text messages are submitted to the researchers' server are increasingly being used. Some of these methods have been tested by comparison with energy intake estimated from doubly labelled water and demonstrate promising results. This accuracy combined with user acceptability likely means this will become the preferred method for prospective food records. Continuous capture of images is being employed to complement other methods of dietary intake that mostly underestimate energy and food intake. The potential of these new methods of capturing accurate food intake data is yet to be fully realized.

Determination of Nitrite in Processed Meat Using Digital Image Method and Powdered Reagent

Part 1 Methods for authentication and traceability: Advanced PCR techniques in identifying food components DNA methods for identifying plant and animal species in food Enzyme immunoassays for identifying animal species in food Proteome and metabolome analysis for food authentication Near infra-red absorption technology for analysing food composition NMR spectroscopy in food authentication Using stable isotope ration mass spectrometry (IRMS) in food authentication and traceability Spectrophotometric techniques Gas chromatography High pressure liquid chromatograophy (HPLC) in food authentication Enzymatic techniques for authenticating food components In-line sensors for food analysis Chemometrics in data analysis. Part 2 Authenticating and tracing particular foods: Species identification in processed seafoods Meat and meat products Milk and dairy products Cereals Herbs and spices Identifying GMO's Wine authenticity. Part 3 Traceability: Traceability in food processing: an introduction Developing traceability systems across the supply chain Developing and implementing an effective traceability and product recall system Traceability in fish processing Safety and traceability of animal feed Geographical traceability of cheese Advanced DNA-based detection techniques for genetically-modified food.

In this paper, the quality assessment of image reconstructed based on filtered-back-projection (FBP) on microwave tomography is presented. It is a common to use the algorithm of back-projection for image reconstruction in classical tomography where the imaging beam passes the object in a straight line. Here, the quality assessment is conducted for the image of cross-sectional wood of tree trunk reconstructed from the measured data at some frequency bands of microwave region, i.e. L-band, S-band, and C-band. Two different techniques of quality assessment, namely Mean Squared Error (MSE) and Structured Similarity Indexing Method (SSIM), are proposed to assess the image quality. The assessment results show that the use of FBP could produce better quality for both MSE and SSIM techniques. While the use of different frequency bands is insensitive to the result of quality assessment.