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Foods
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Spectroscopy Analysis for Foods
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Spectroscopy Analysis for Foods

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

Deadline for manuscript submissions: closed (10 October 2022) | Viewed by 5767

Special Issue Editor

Prof. Dr. Marco Flôres Ferrão

E-Mail Website
Guest Editor
Instituto de Química, Universidade Federal do Rio Grande do Sul, Av. Bento Gonçalves, Porto Alegre 9500, Brazil
Interests: chemometrics; instrumental analysis; image analysis; molecular spectroscopy; beverages; multivariate analysis; experimental design

Special Issue Information

Dear Colleagues,

In this special issue of Foods we are looking for papers that employ spectroscopic techniques in food analysis. Contributions that combine data from analytical instrumentation and chemometric tools are welcome. New approaches that demonstrate the portability of new technologies for the analysis of in natural or processed foods. As well as works that demonstrate the potential of spectroscopy for quality assurance and safety. We look forward to receiving your contribution in advancing the Spectroscopy Analysis for Foods.

Prof. Dr. Marco Flôres Ferrão
Guest Editor

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 and safety
  • food authentication
  • foodomics
  • food microbiology
  • spectroscopy techniques
  • molecular spectroscopy
  • atomic spectroscopy
  • chemometrics
  • forensic applications

Published Papers (3 papers)

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Research

22 pages, 11239 KiB  
Article
Prediction Models for the Content of Calcium, Boron and Potassium in the Fruit of ‘Huangguan’ Pears Established by Using Near-Infrared Spectroscopy
by Jing Fang, Xiu Jin, Lin Wu, Yuxin Zhang, Bing Jia, Zhenfeng Ye, Wei Heng and Li Liu
Foods 2022, 11(22), 3642; https://doi.org/10.3390/foods11223642 - 14 Nov 2022
Cited by 1 | Viewed by 1404
Abstract
It has been proved that the imbalance of the proportion of elements of ‘Huangguan’ pears in the pulp and peel, especially calcium, boron and potassium, may be important factors that can seriously affect the pears’ appearance quality and economic benefits. The objective of [...] Read more.
It has been proved that the imbalance of the proportion of elements of ‘Huangguan’ pears in the pulp and peel, especially calcium, boron and potassium, may be important factors that can seriously affect the pears’ appearance quality and economic benefits. The objective of this study was to predict the content of calcium, boron and potassium in the pulp and peel of ‘Huangguan’ pears nondestructively and conveniently by using near-infrared spectroscopy (900–1700 nm) technology. Firstly, 12 algorithms were used to preprocess the original spectral data. Then, based on the original and preprocessed spectral data, full-band prediction models were established by using Partial Least Squares Regression and Gradient Boosting Regression Tree. Finally, the characteristic wavelengths were extracted by Genetic Algorithms to establish the characteristic wavelength prediction models. According to the prediction results, the value of the determination coefficient of the prediction sets of the best prediction models for the three elements all reached ideal levels, and the values of their Relative analysis error also showed high levels. Therefore, the micro near-infrared spectrometer based on machine learning can predict the content of calcium, boron and potassium in the pulp and peel of ‘Huangguan’ pears accurately and quickly. The results also provide an important scientific theoretical basis for further research on the degradation of the quality of ‘Huangguan’ pears caused by a lack of nutrients. Full article
(This article belongs to the Special Issue Spectroscopy Analysis for Foods)
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15 pages, 1903 KiB  
Article
Prediction of Anthocyanin Color Stability against Iron Co-Pigmentation by Surface-Enhanced Raman Spectroscopy
by Haochen Dai, Adam Forbes, Xin Guo and Lili He
Foods 2022, 11(21), 3436; https://doi.org/10.3390/foods11213436 - 29 Oct 2022
Cited by 2 | Viewed by 2038
Abstract
The color change resulting from anthocyanin and iron co-pigmentation has been a significant challenge for the food industry in the development of many iron-fortified foods. This present study aims to establish a quantitative model to predict the degree of color stability in the [...] Read more.
The color change resulting from anthocyanin and iron co-pigmentation has been a significant challenge for the food industry in the development of many iron-fortified foods. This present study aims to establish a quantitative model to predict the degree of color stability in the presence of dissolved iron using surface-enhanced Raman spectroscopic (SERS) spectra. The SERS spectra of anthocyanin extracts from seven different plant sources were measured and analyzed by principal component analysis (PCA). Discrimination among different sources of anthocyanin was observed in the PCA plot. Different stability indexes, obtained by measuring both the color intensity stability and color hue stability of each sample, were established based on UV–vis analysis of anthocyanin at pH 3 and 6 with and without ferric sulfate. Partial least square (PLS) regression models were applied to establish the correlation between SERS spectra and stability indexes. The best PLS model was built based on the stability index calculated from the bathochromic shift (UV–vis spectral range: 380–750 nm) in pH3 buffer and the SERS spectra, achieving a root mean square error of prediction (RMSEP) of 2.16 nm and a correlation coefficient value (R2) of 0.98. In conclusion, the present study developed a feasible approach to predict the stability of anthocyanin colorants against iron co-pigmentation. The developed method and models can be used for fast screenings of raw ingredients in iron-fortified food products. Full article
(This article belongs to the Special Issue Spectroscopy Analysis for Foods)
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13 pages, 1798 KiB  
Article
Bluetooth-Connected Pocket Spectrometer and Chemometrics for Olive Oil Applications
by Leonardo Ciaccheri, Barbara Adinolfi, Andrea Azelio Mencaglia and Anna Grazia Mignani
Foods 2022, 11(15), 2265; https://doi.org/10.3390/foods11152265 - 29 Jul 2022
Cited by 1 | Viewed by 1782
Abstract
Unsaturated fatty acids are renowned for their beneficial effects on the cardiovascular system. The high content of unsaturated fatty acids is a benefit of vegetable fats and an important nutraceutical indicator. The ability to quickly check fat composition of an edible oil could [...] Read more.
Unsaturated fatty acids are renowned for their beneficial effects on the cardiovascular system. The high content of unsaturated fatty acids is a benefit of vegetable fats and an important nutraceutical indicator. The ability to quickly check fat composition of an edible oil could be advantageous for both consumers and retailers. A Bluetooth-connected pocket spectrometer operating in NIR band was used for analyzing olive oils of different qualities. Reference data for fatty acid composition were obtained from a certified analytical laboratory. Chemometrics was used for processing data, and predictive models were created for determining saturated and unsaturated fatty acid content. The NIR spectrum also demonstrated good capability in classifying extra virgin and non-extra virgin olive oils. The pocket spectrometer used in this study has a relatively low cost, which makes it affordable for a wide class of users. Therefore, it may open the opportunity for quick and non-destructive testing of edible oil, which can be of interest for consumer, retailers, and for small/medium-size producers, which lack easy access to conventional analytics. Full article
(This article belongs to the Special Issue Spectroscopy Analysis for Foods)
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