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Application of Spectrometric Technologies in the Monitoring and Control of Foods and Beverages

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A special issue of Foods (ISSN 2304-8158). This special issue belongs to the section "Food Engineering and Technology".

Deadline for manuscript submissions: closed (30 November 2020) | Viewed by 43706

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Prof. Dr. Ricard Boqué

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Department of Analytical Chemistry and Organic Chemistry, Universitat Rovira i Virgili, Tarragona, Catalunya, Spain
Interests: analytical chemistry; chemometrics; spectroscopy; food analysis

Prof. Dr. Barbara Giussani

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Department of Science and High Technology, University of Insubria, Via Valleggio, 11, 22100 Como, Italy
Interests: control process strategies through multivariate analysis; design and development of smart analytical strategies to solve real-world problems, from sampling to data analysis; Infrared and near-infrared spectroscopies; especially using portable sensors
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Special Issue Information

Dear Colleagues,

In order to obtain high-quality products and to gain competitive advantage, food producers seek improved manufacturing processes, even more when physicochemical and sensory properties add significant value to the product. Improving the chemical and sensory properties requires a deeper understanding and control of the production process. From an analytical point of view, this can be gained by using the process analytical technologies (PAT) approach, namely: a system for designing, analyzing, and controlling manufacturing through the timely measurements of the critical quality attributes of raw and in-process materials and processes, with the goal of ensuring final product quality.

Spectrometric techniques fall into the PAT guidelines, as they allow for getting real-time information (composition and properties) in the production process, and taking corrective measures, if necessary, before obtaining the final product.

The present Special Issue aims at visualizing the recent advances of spectrometric techniques, such as infrared and Raman spectroscopy, and mass spectrometry (HS-MS and GC-MS), in the monitoring and control of foodstuffs, such as wine, beer, milk, meat, vegetables, fruits/fruit juices, olive oil, or any other product of domestic or international origin.

As the data collected from the different spectrometric techniques have to be processed, a second aim is to review the chemometric tools available to correlate the spectrometric data with the different food quality parameters.

Prof. Ricard Boqué
Dr. Barbara Giussani
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Foods is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

PAT
Spectrometry
Food analysis
Food monitoring
Chemometrics
Quality control

Published Papers (10 papers)

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Editorial

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3 pages, 184 KiB

Open AccessEditorial

Application of Spectrometric Technologies in the Monitoring and Control of Foods and Beverages

by Ricard Boqué and Barbara Giussani

Foods 2021, 10(5), 948; https://doi.org/10.3390/foods10050948 - 26 Apr 2021

Cited by 2 | Viewed by 1592

Abstract

In order to obtain high-quality products and gain a competitive advantage, food producers seek improved manufacturing processes, particularly when physicochemical and sensory properties add significant value to the product [...] Full article

(This article belongs to the Special Issue Application of Spectrometric Technologies in the Monitoring and Control of Foods and Beverages)

Research

Jump to: Editorial

17 pages, 2162 KiB

Open AccessArticle

Elemental Analysis and Phenolic Profiles of Selected Italian Wines

by Paola Fermo, Valeria Comite, Milica Sredojević, Ivanka Ćirić, Uroš Gašić, Jelena Mutić, Rada Baošić and Živoslav Tešić

Foods 2021, 10(1), 158; https://doi.org/10.3390/foods10010158 - 13 Jan 2021

Cited by 20 | Viewed by 2727

Abstract

The study of the chemical composition of wines is nowadays a topic of great interest because of the importance of this market, especially in Italy, and also considering the numerous cases of falsification of famous and very expensive wines. The present paper focused on the analysis of metals and polyphenols in Italian wines belonging to different provenance and types. At this purpose 20 elements were quantified by inductively coupled plasma optical emission spectrometry (ICP-OES) and ICP mass spectrometry (ICP-MS). Regarding polyphenols, a total of 32 were quantified, among 6 were anthocyanins. Furthermore, in 4 samples (1 rosè and 3 red wines) 42 anthocyanins and related compounds were identified by ultra-high performance liquid chromatography (UHPLC)-Orbitrap MS technique (among these, 6 were also quantified). Non-anthocyanins were determined using UHPLC coupled with a diode array detector and triple-quadrupole mass spectrometer (UHPLC–DAD-QqQ-MS). Total phenolic content (TPC) and radical scavenging activity (RSA) were measured using spectrophotometric methods. The results obtained by elemental techniques were submitted to principal components analysis (PCA) allowing to get information on both geographical and botanical origin of the examined wine samples. Some polyphenols have been detected in higher concentrations only in a certain type of wine, as for example in the case of Grechetto wine. Most of the identified anthocyanin derivatives (pyranoanthocyanins) are formed during the aging of wine by reaction with the other wine components. Full article

(This article belongs to the Special Issue Application of Spectrometric Technologies in the Monitoring and Control of Foods and Beverages)

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15 pages, 7901 KiB

Open AccessArticle

Preliminary Assessment of Parmigiano Reggiano Authenticity by Handheld Raman Spectroscopy

by Mario Li Vigni, Caterina Durante, Sara Michelini, Marco Nocetti and Marina Cocchi

Foods 2020, 9(11), 1563; https://doi.org/10.3390/foods9111563 - 28 Oct 2020

Cited by 18 | Viewed by 3048

Abstract

Raman spectroscopy, and handheld spectrometers in particular, are gaining increasing attention in food quality control as a fast, portable, non-destructive technique. Furthermore, this technology also allows for measuring the intact sample through the packaging and, with respect to near infrared spectroscopy, it is not affected by the water content of the samples. In this work, we evaluate the potential of the methodology to model, by multivariate data analysis, the authenticity of Parmigiano Reggiano cheese, which is one of the most well-known and appreciated hard cheeses worldwide, with protected denomination of origin (PDO). On the other hand, it is also highly subject to counterfeiting. In particular, it is critical to assess the authenticity of grated cheese, to which, under strictly specified conditions, the PDO is extended. To this aim, it would be highly valuable to develop an authenticity model based on a fast, non-destructive technique. In this work, we present preliminary results obtained by a handheld Raman spectrometer and class-modeling (Soft Independent Modeling of Class Analogy, SIMCA), which are extremely promising, showing sensitivity and specificity of 100% for the test set. Moreover, another salient issue, namely the percentage of rind in grated cheese, was addressed by developing a multivariate calibration model based on Raman spectra. It was possible to obtain a prediction error around 5%, with 18% being the maximum content allowed by the production protocol. Full article

(This article belongs to the Special Issue Application of Spectrometric Technologies in the Monitoring and Control of Foods and Beverages)

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11 pages, 1482 KiB

Open AccessArticle

Application of Non-Destructive Rapid Determination of Piperine in Piper nigrum L. (Black Pepper) Using NIR and Multivariate Statistical Analysis: A Promising Quality Control Tool

by Jong-Rak Park, Hyun-Hee Kang, Jong-Ku Cho, Kwang-Deog Moon and Young-Jun Kim

Foods 2020, 9(10), 1437; https://doi.org/10.3390/foods9101437 - 11 Oct 2020

Cited by 6 | Viewed by 3015

Abstract

Piperine is a bioactive alkaloid compound which provides a unique spicy flavor derived from plants of the Piper nigrum L. Black pepper (n = 160) collected from Vietnam was studied using non-destructive near infrared spectroscopy (NIRS). The spectral acquisition ranged from 1100 to 2500 nm, and a chemometrics analysis program was performed to quantify the piperine contents. High performance liquid chromatography (HPLC) analysis was carried out to develop a chemometric model based on reference values. The black pepper samples were divided into two groups used for calibration (n = 120) and prediction (n = 40) sets. The optimum calibration model was developed by pretreatment of the spectra. The analyses results based on the prediction samples included a coefficient of determination (R²) of 0.914, a root mean square error of prediction (RMSEP) and a standard error of prediction (SEP) of about 0.220 g/100 g, and a ratio performance to deviation (RPD) value of 3.378 regarding the partial least square (PLS) regression model, and an R² of 0.921, an RMSEP and SEP of 0.210 g/100 g, and an RPD of 3.571, with respect to the principal components (PC) regression model. These results indicate that NIRS can be applicable as a control, or as an alternative rapid and effective method to quantify piperine in P. nigrum L. Full article

(This article belongs to the Special Issue Application of Spectrometric Technologies in the Monitoring and Control of Foods and Beverages)

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18 pages, 2771 KiB

Open AccessArticle

Rapid Analysis of Milk Using Low-Cost Pocket-Size NIR Spectrometers and Multivariate Analysis

by Jordi Riu, Giulia Gorla, Dib Chakif, Ricard Boqué and Barbara Giussani

Foods 2020, 9(8), 1090; https://doi.org/10.3390/foods9081090 - 10 Aug 2020

Cited by 33 | Viewed by 6299

Abstract

The miniaturisation of analytical devices, reduction of analytical data acquisition time, or the reduction of waste generation throughout the analytical process are important requirements of modern analytical chemistry, and in particular of green analytical chemistry. Green analytical chemistry has fostered the development of a new generation of miniaturized near-infrared spectroscopy (NIR) spectrometric systems. However, one of the drawbacks of these systems is the need for a compromise between the performance parameters (accuracy and sensitivity) and the aforementioned requirements of green analytical chemistry. In this paper, we evaluated the capabilities of two recently developed portable NIR instruments (SCiO and NeoSpectra) to achieve a rapid, simple and low-cost quantitative determination of commercial milk macronutrients. Commercial milk samples from Italy, Switzerland and Spain were chosen, covering the maximum range of variability in protein, carbohydrate and fat content, and multivariate calibration was used to correlate the recorded spectra with the macronutrient content of milk. Both SCiO and NeoSpectra can provide a fast and reliable analysis of fats in commercial milk, and they are able to correctly classify milk according to fat level. SCiO can also provide predictions of protein content and classification according to presence or absence of lactose. Full article

(This article belongs to the Special Issue Application of Spectrometric Technologies in the Monitoring and Control of Foods and Beverages)

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15 pages, 2564 KiB

Open AccessArticle

The Detection of Substitution Adulteration of Paprika with Spent Paprika by the Application of Molecular Spectroscopy Tools

by Pamela Galvin-King, Simon A. Haughey and Christopher T. Elliott

Foods 2020, 9(7), 944; https://doi.org/10.3390/foods9070944 - 16 Jul 2020

Cited by 17 | Viewed by 4879

Abstract

The spice paprika (Capsicum annuum and frutescens) is used in a wide variety of cooking methods as well as seasonings and sauces. The oil, paprika oleoresin, is a valuable product; however, once removed from paprika, the remaining spent product can be used to adulterate paprika. Near-infrared (NIR) and Fourier transform infrared (FTIR) were the platforms selected for the development of methods to detect paprika adulteration in conjunction with chemometrics. Orthogonal partial least squares discriminant analysis (OPLS-DA), a supervised technique, was used to develop the chemometric models, and the measurement of fit (R²) and measurement of prediction (Q²) values were 0.853 and 0.819, respectively, for the NIR method and 0.943 and 0.898 respectively for the FTIR method. An external validation set was tested against the model, and a receiver operating curve (ROC) was created. The area under the curve (AUC) for both methods was highly accurate at 0.951 (NIR) and 0.907 (FTIR). The levels of adulteration with 100% correct classification were 50–90% (NIR) and 40–90% (FTIR). Sudan I dye is a commonly used adulterant in paprika; however, in this study it was found that this dye had no effect on the outcome of the result for spent material adulteration. Full article

(This article belongs to the Special Issue Application of Spectrometric Technologies in the Monitoring and Control of Foods and Beverages)

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14 pages, 1863 KiB

Open AccessArticle

Quantification of Polyphenols and Metals in Chinese Tea Infusions by Mass Spectrometry

by Gabriella Pinto, Anna Illiano, Andrea Carpentieri, Michele Spinelli, Chiara Melchiorre, Carolina Fontanarosa, Martino di Serio and Angela Amoresano

Foods 2020, 9(6), 835; https://doi.org/10.3390/foods9060835 - 25 Jun 2020

Cited by 25 | Viewed by 4516

Abstract

Chemical compounds within tea (Camellia sinensis) are characterized by an extensive heterogeneity; some of them are crucial for their protective and defensive role in plants, and are closely connected to the benefits that the consumption of tea can provide. This paper is mainly focused on the characterization of polyphenols (secondary metabolites generally involved in defense against ultraviolet radiation and aggression by pathogens) and metals, extracted from nine Chinese tea samples, by integrating different mass spectrometry methodologies, LC-MS/MS in multiple reaction monitoring (MRM) and inductively coupled plasma mass spectrometry (ICP-MS). Our approach allowed to identify and compare forty polyphenols differently distributed in tea infusions at various fermentation levels. The exploration of polyphenols with nutraceutical potential in tea infusions can widely benefit especially tea-oriented populations. The worldwide consumption of tea requires at the same time a careful monitoring of metals released during the infusion of tea leaves. Metal analysis can provide the identification of many healthy minerals such as potassium, sodium, calcium, magnesium, differently affected by the fermentation of leaves. Our results allowed us: (i) to draw up a polyphenols profile of tea leaves subjected to different fermentation processes; (ii) to identify and quantify metals released from tea leaves during infusion. In this way, we obtained a molecular fingerprint useful for both nutraceutical applications and food control/typization, as well as for frauds detection and counterfeiting. Full article

(This article belongs to the Special Issue Application of Spectrometric Technologies in the Monitoring and Control of Foods and Beverages)

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11 pages, 1337 KiB

Open AccessCommunication

FT-NIRS Coupled with PLS Regression as a Complement to HPLC Routine Analysis of Caffeine in Tea Samples

by Najeeb Ur Rehman, Ahmed Al-Harrasi, Ricard Boqué, Fazal Mabood, Muhammed Al-Broumi, Javid Hussain and Saif Alameri

Foods 2020, 9(6), 827; https://doi.org/10.3390/foods9060827 - 24 Jun 2020

Cited by 6 | Viewed by 4138

Abstract

Daily consumption of caffeine in coffee, tea, chocolate, cocoa, and soft drinks has gained wide and plentiful public and scientific attention over the past few decades. The concentration of caffeine in vivo is a crucial indicator of some disorders—for example, kidney malfunction, heart disease, increase of blood pressure and alertness—and can cause some severe diseases including type 2 diabetes mellitus (DM), stroke risk, liver disease, and some cancers. In the present study, near-infrared spectroscopy (NIRS) coupled with partial least-squares regression (PLSR) was proposed as an alternative method for the quantification of caffeine in 25 commercially available tea samples consumed in Oman. This method is a fast, complementary technique to wet chemistry procedures as well as to high-performance liquid chromatography (HPLC) methods for the quantitative analysis of caffeine in tea samples because it is reagent-less and needs little or no pre-treatment of samples. In the current study, the partial least-squares (PLS) algorithm was built by using the near-infrared NIR spectra of caffeine standards prepared in tea samples scanned by a Frontier NIR spectrophotometer (L1280034) by PerkinElmer. Spectra were collected in the absorption mode in the wavenumber range of 10,000–4000 cm⁻¹, using a 0.2 mm path length and CaF₂ sealed cells with a resolution of 2 cm⁻¹. The NIR results for the contents of caffeine in tea samples were also compared with results obtained by HPLC analysis. Both techniques provided good results for predicting the caffeine contents in commercially available tea samples. The results of the proposed study show that the suggested FT-NIRS coupled with PLS regression algorithun has a high potential to be routinely used for the quick and reproducible analysis of caffeine contents in tea samples. For the NIR method, the limit of quantification (LOQ) was estimated as 10 times the error of calibration (root mean square error of calibration (RMSECV)) of the model; thus, RMSEC was calculated as 0.03 ppm and the LOQ as 0.3 ppm. Full article

(This article belongs to the Special Issue Application of Spectrometric Technologies in the Monitoring and Control of Foods and Beverages)

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14 pages, 2526 KiB

Open AccessArticle

Colorimetric Sensor Array for Monitoring, Modelling and Comparing Spoilage Processes of Different Meat and Fish Foods

by Lisa Rita Magnaghi, Federica Capone, Camilla Zanoni, Giancarla Alberti, Paolo Quadrelli and Raffaela Biesuz

Foods 2020, 9(5), 684; https://doi.org/10.3390/foods9050684 - 25 May 2020

Cited by 45 | Viewed by 5903

Abstract

Meat spoilage is a very complex combination of processes related to bacterial activities. Numerous efforts are underway to develop automated techniques for monitoring this process. We selected a panel of pH indicators and a colourimetric dye, selective for thiols. Embedding these dyes into an anion exchange cellulose sheets, i.e., the commercial paper sheet known as “Colour Catcher^®” commonly used in the washing machine to prevent colour run problems, we obtained an array made of six coloured spots (here named Dye name-CC@). The array, placed over the tray containing a sample of meat or fish (not enriched at any extend with spoilage products), progressively shows a colour change in the six spots. Photos of the array were acquired as a function of time, RGB indices were used to follow the spoilage, Principal Component Analysis to model the data set. We demonstrate that the array allows for the monitoring the overall spoilage process of chicken, beef, pork and fish, obtaining different models that mimic the degradation pathway. The spoilage processes for each kind of food, followed by the array colour evolution, were eventually compared using three-way PCA, which clearly shows same degradation pattern of protein foods, altered only according to the different substrates. Full article

(This article belongs to the Special Issue Application of Spectrometric Technologies in the Monitoring and Control of Foods and Beverages)

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13 pages, 2558 KiB

Open AccessArticle

Application of the Non-Destructive NIR Technique for the Evaluation of Strawberry Fruits Quality Parameters

by Manuela Mancini, Luca Mazzoni, Francesco Gagliardi, Francesca Balducci, Daniele Duca, Giuseppe Toscano, Bruno Mezzetti and Franco Capocasa

Foods 2020, 9(4), 441; https://doi.org/10.3390/foods9040441 - 06 Apr 2020

Cited by 39 | Viewed by 6551

Abstract

The determination of strawberry fruit quality through the traditional destructive lab techniques has some limitations related to the amplitude of the samples, the timing and the applicability along all phases of the supply chain. The aim of this study was to determine the main qualitative characteristics through traditional lab destructive techniques and Near Infrared Spectroscopy (NIR) in fruits of five strawberry genotypes. Principal Component Analysis (PCA) was applied to search for spectral differences among all the collected samples. A Partial Least Squares regression (PLS) technique was computed in order to predict the quality parameters of interest. The PLS model for the soluble solids content prediction was the best performing—in fact, it is a robust and reliable model and the validation values suggested possibilities for its use in quality applications. A suitable PLS model is also obtained for the firmness prediction—the validation values tend to worsen slightly but can still be accepted in screening applications. NIR spectroscopy represents an important alternative to destructive techniques, using the infrared region of the electromagnetic spectrum to investigate in a non-destructive way the chemical–physical properties of the samples, finding remarkable applications in the agro-food market. Full article

(This article belongs to the Special Issue Application of Spectrometric Technologies in the Monitoring and Control of Foods and Beverages)

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