Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.8
5.2
Journals
Foods
Special Issues
Foods Quality Assessed by Chemometrics
share announcement

Foods Quality Assessed by Chemometrics

A special issue of Foods (ISSN 2304-8158). This special issue belongs to the section "Food Analytical Methods".

Deadline for manuscript submissions: closed (31 January 2020) | Viewed by 30782

Special Issue Editors

Dr. Christos Soukoulis

E-Mail Website
Guest Editor
Environmental Research and Innovation Department, Luxembourg Institute of Science and Technology, Belvaux, Luxembourg
Interests: dairy proteins; food hydrocolloids; food waste valorization; food structure and rheology; probiotics; functional food innovation
Special Issues, Collections and Topics in MDPI journals
Dr. Christelle Andre

E-Mail Website
Guest Editor
Luxembourg Institute of Science and Technology, Belvaux, Luxembourg
Interests: plant natural products; food chemistry; nutrition; bioactive compound

Special Issue Information

Dear Colleagues,

Food market globalisation, food security, as well as increasing consumer demand for safe, minimally-processed and wholesome food, impose the need to establish new approaches to identify and assess food quality markers. Nowadays, food industry stakeholders are challenged to promote food quality meeting several prerequisites encompassing sustainable and eco-green processing, increased shelf-life without safety, sensory satisfaction and nutritional value compromises. In addition, food fraud related to deliberate product mislabelling or economically intended adulteration, is of major concern for both industry and regulatory authorities due to cost and public health implications. Notwithstanding a great number of state-of-the-art analytical tools available for food quality fingerprinting their use in most of the cases results in highly complex and big dataset. In this context, chemometrics tools, such as optimisation designs, supervised and unsupervised exploratory analyses and multivariate regression modelling, are commonly implemented as part of food quality assessment.

In this Special Issue, we aim at publishing innovative research and review papers on: Food authenticity and adulteration case studies, foodomics, mathematical modelling and optimisation of food industry relevant unit operations including bioprocessing and food waste valorisation, optimisation of food composition, nutritional value, storage stability and consumers’ acceptability, as well as prediction of food shelf-life, adopting chemometrics assisted instrumental and sensory data analysis approaches.

Dr. Christos Soukoulis
Dr. Christelle Andre
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

  • Food quality
  • Food authenticity
  • Food safety
  • Foodomics
  • Sensory quality and consumers’ preference
  • Food product development
  • Process optimization and modelling
  • Chemometrics
  • Data mining
  • Bioactive compounds

Published Papers (6 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Editorial

Jump to: Research, Other

4 pages, 157 KiB  
Editorial
Food Quality Assessed by Chemometrics
by Christelle M. Andre and Christos Soukoulis
Foods 2020, 9(7), 897; https://doi.org/10.3390/foods9070897 - 08 Jul 2020
Cited by 17 | Viewed by 4263
Abstract
Food market globalization, food security as well as increasing consumer demand for safe, minimally processed and healthy food impose the need to establish new approaches for identifying and assessing food quality markers. Nowadays, food industry stakeholders are challenged to assure food quality and [...] Read more.
Food market globalization, food security as well as increasing consumer demand for safe, minimally processed and healthy food impose the need to establish new approaches for identifying and assessing food quality markers. Nowadays, food industry stakeholders are challenged to assure food quality and safety without compromising several prerequisites such as sustainable and ecologically resilient food production, prolonged shelf life, satisfactory sensory quality, enhanced nutritional value and health-promoting properties. In addition, food fraud related to deliberate product mislabeling or economically intended adulteration is of major concern for both industry and regulatory authorities due to cost and public health implications. Notwithstanding the great number of state-of-the-art analytical tools available for quantifying food quality markers, their implementation results in highly complex and big datasets, which are not easily interpretable. In this context, chemometrics e.g., supervised and unsupervised multivariate exploratory analyses, design-of-experiment methodology, univariate or multivariate regression modelling etc., are commonly implemented as part of food process optimization and food quality assessment. In this Special Issue, we aimed to publish innovative research and perspective papers on chemometric-assisted case studies relating to food quality assessment, food authenticity, mathematical modelling and optimization of processes involved in food manufacturing. Full article
(This article belongs to the Special Issue Foods Quality Assessed by Chemometrics)

Research

Jump to: Editorial, Other

16 pages, 1395 KiB  
Article
Impact of Type and Enzymatic/High Pressure Treatment of Milk on the Quality and Bio-Functional Profile of Yoghurt
by Maria Tsevdou, Georgios Theodorou, Sofia Pantelaiou, Artemis Chatzigeorgiou, Ioannis Politis and Petros Taoukis
Foods 2020, 9(1), 49; https://doi.org/10.3390/foods9010049 - 04 Jan 2020
Cited by 3 | Viewed by 2659
Abstract
The objective of the present study was to investigate the effect of the high pressure (HP) processing and transglutaminase (TGase) treatment of bovine (cow) or ovine (sheep) milk, when applied individually or sequentially, on the quality parameters and anti-hypertensive and immunomodulatory properties of [...] Read more.
The objective of the present study was to investigate the effect of the high pressure (HP) processing and transglutaminase (TGase) treatment of bovine (cow) or ovine (sheep) milk, when applied individually or sequentially, on the quality parameters and anti-hypertensive and immunomodulatory properties of yoghurt. Low-fat (2% w/w) bovine or ovine milk samples were used. Results showed that HP treatment of milk led to acid gels with equivalent quality attributes to thermal treatment, with the more representative attributes being whey separation and firmness, which ranged from 47.5% to 49.8% and 23.8% to 32.2% for bovine and ovine yoghurt, respectively, and 74.3–89.0 g and 219–220 g for bovine and ovine yoghurt, respectively. On the other hand, TGase treatment of milk, solely or more effectively following HP processing, resulted in the improvement of the textural attributes of yoghurt and reduced whey separation, regardless of milk type, exhibiting values of 32.9% and 8.7% for the whey separation of bovine and ovine yoghurt, respectively, and 333 g and 548 g for the firmness of bovine and ovine yoghurt, respectively. The HP processing and TGase treatment of milk led to the preservation or improvement of the anti-hypertensive activity of the samples, especially in the case in which ovine milk was used, with Inhibitory activity of Angiotensin Converting Enzyme (IACE) values of 76.9% and 88.5% for bovine and ovine yoghurt, respectively. The expression of pro-inflammatory genes decreased and that of anti-inflammatory genes increased in the case of samples from HP-processed and/or TGase-treated milk as compared to the corresponding expressions for samples from thermally treated milk. Thus, it can be stated that, apart from the quality improvement, HP processing and TGase treatment of milk may lead to the enhancement of the bio-functional properties of low-fat yoghurt made from either bovine or ovine milk. Full article
(This article belongs to the Special Issue Foods Quality Assessed by Chemometrics)
►▼ Show Figures

Figure 1

14 pages, 2667 KiB  
Article
Estimation of Minced Pork Microbiological Spoilage through Fourier Transform Infrared and Visible Spectroscopy and Multispectral Vision Technology
by Lemonia-Christina Fengou, Evgenia Spyrelli, Alexandra Lianou, Panagiotis Tsakanikas, Efstathios Z. Panagou and George-John E. Nychas
Foods 2019, 8(7), 238; https://doi.org/10.3390/foods8070238 - 01 Jul 2019
Cited by 20 | Viewed by 4167
Abstract
Spectroscopic and imaging methods coupled with multivariate data analysis have been increasingly studied for the assessment of food quality. The objective of this work was the estimation of microbiological quality of minced pork using non-invasive spectroscopy-based sensors. For this purpose, minced pork patties [...] Read more.
Spectroscopic and imaging methods coupled with multivariate data analysis have been increasingly studied for the assessment of food quality. The objective of this work was the estimation of microbiological quality of minced pork using non-invasive spectroscopy-based sensors. For this purpose, minced pork patties were stored aerobically at different isothermal (4, 8, and 12 °C) and dynamic temperature conditions, and at regular time intervals duplicate samples were subjected to (i) microbiological analyses, (ii) Fourier transform infrared (FTIR) and visible (VIS) spectroscopy measurements, and (iii) multispectral image (MSI) acquisition. Partial-least squares regression models were trained and externally validated using the microbiological/spectral data collected at the isothermal and dynamic temperature storage conditions, respectively. The root mean squared error (RMSE, log CFU/g) for the prediction of the test (external validation) dataset for the FTIR, MSI, and VIS models was 0.915, 1.173, and 1.034, respectively, while the corresponding values of the coefficient of determination (R2) were 0.834, 0.727, and 0.788. Overall, all three tested sensors exhibited a considerable potential for the prediction of the microbiological quality of minced pork. Full article
(This article belongs to the Special Issue Foods Quality Assessed by Chemometrics)
►▼ Show Figures

Figure 1

7 pages, 1346 KiB  
Article
Nondestructive Classification Analysis of Green Coffee Beans by Using Near-Infrared Spectroscopy
by Naoya Okubo and Yohei Kurata
Foods 2019, 8(2), 82; https://doi.org/10.3390/foods8020082 - 22 Feb 2019
Cited by 35 | Viewed by 6216
Abstract
Near-infrared spectroscopy (NIRS) is a powerful tool for the nondestructive evaluation of organic materials, and it has found widespread use in a variety of industries. In the food industry, it is important to know the district in which a particular food was produced. [...] Read more.
Near-infrared spectroscopy (NIRS) is a powerful tool for the nondestructive evaluation of organic materials, and it has found widespread use in a variety of industries. In the food industry, it is important to know the district in which a particular food was produced. Therefore, in this study, we focused on determining the production area (five areas and three districts) of green coffee beans using classification analysis and NIRS. Soft independent modeling of class analogy (SIMCA) was applied as the classification method. Samples of green coffee beans produced in seven locations—Cuba, Ethiopia, Indonesia (Bari, Java, and Sumatra), Tanzania, and Yemen—were analyzed. These regions were selected since green coffee beans from these locations are commonly sold in Japan supermarkets. A good classification result was obtained with SIMCA for the seven green bean samples, although some samples were partly classified into several categories. Then, the model distance values of SIMCA were calculated and compared. A few model distance values were ~10; such small values may be the reason for misclassification. However, over a 73% correct classification rate could be achieved for the different kinds of green coffee beans using NIRS. Full article
(This article belongs to the Special Issue Foods Quality Assessed by Chemometrics)
►▼ Show Figures

Figure 1

9 pages, 4593 KiB  
Article
Applying Fourier Transform Mid Infrared Spectroscopy to Detect the Adulteration of Salmo salar with Oncorhynchus mykiss
by Nuno Sousa, Maria João Moreira, Cristina Saraiva and José M. M. M. De Almeida
Foods 2018, 7(4), 55; https://doi.org/10.3390/foods7040055 - 05 Apr 2018
Cited by 14 | Viewed by 8063
Abstract
The aim of this study was to evaluate the potential of Fourier transform infrared (FTIR) spectroscopy coupled with chemometric methods to detect fish adulteration. Muscles of Atlantic salmon (Salmo salar) (SS) and Salmon trout (Onconrhynchus mykiss) (OM) muscles were [...] Read more.
The aim of this study was to evaluate the potential of Fourier transform infrared (FTIR) spectroscopy coupled with chemometric methods to detect fish adulteration. Muscles of Atlantic salmon (Salmo salar) (SS) and Salmon trout (Onconrhynchus mykiss) (OM) muscles were mixed in different percentages and transformed into mini-burgers. These were stored at 3 °C, then examined at 0, 72, 160, and 240 h for deteriorative microorganisms. Mini-burgers was submitted to Soxhlet extraction, following which lipid extracts were analyzed by FTIR. The principal component analysis (PCA) described the studied adulteration using four principal components with an explained variance of 95.60%. PCA showed that the absorbance in the spectral region from 721, 1097, 1370, 1464, 1655, 2805, to 2935, 3009 cm−1 may be attributed to biochemical fingerprints related to differences between SS and OM. The partial least squares regression (PLS-R) predicted the presence/absence of adulteration in fish samples of an external set with high accuracy. The proposed methods have the advantage of allowing quick measurements, despite the storage time of the adulterated fish. FTIR combined with chemometrics showed that a methodology to identify the adulteration of SS with OM can be established, even when stored for different periods of time. Full article
(This article belongs to the Special Issue Foods Quality Assessed by Chemometrics)
►▼ Show Figures

Figure 1

Other

Jump to: Editorial, Research

10 pages, 813 KiB  
Perspective
From Academia to Reality Check: A Theoretical Framework on the Use of Chemometric in Food Sciences
by Vi Khanh Truong, Madeleine Dupont, Aaron Elbourne, Sheeana Gangadoo, Piumie Rajapaksha Pathirannahalage , Samuel Cheeseman, James Chapman and Daniel Cozzolino
Foods 2019, 8(5), 164; https://doi.org/10.3390/foods8050164 - 14 May 2019
Cited by 30 | Viewed by 4794
Abstract
There is no doubt that the current knowledge in chemistry, biochemistry, biology, and mathematics have led to advances in our understanding about food and food systems. However, the so-called reductionist approach has dominated food research, hindering new developments and innovation in the field. [...] Read more.
There is no doubt that the current knowledge in chemistry, biochemistry, biology, and mathematics have led to advances in our understanding about food and food systems. However, the so-called reductionist approach has dominated food research, hindering new developments and innovation in the field. In the last three decades, food science has moved into the digital and technological era, inducing several challenges resulting from the use of modern instrumental techniques, computing and algorithms incorporated to the exploration, mining, and description of data derived from this complexity. In this environment, food scientists need to be mindful of the issues (advantages and disadvantages) involved in the routine applications of chemometrics. The objective of this opinion paper is to give an overview of the key issues associated with the implementation of chemometrics in food research and development. Please note that specifics about the different methodologies and techniques are beyond the scope of this review. Full article
(This article belongs to the Special Issue Foods Quality Assessed by Chemometrics)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-6
Back to TopTop