Editorial

4 pages, 205 KiB

Open AccessEditorial

Application of Spectroscopy in Food Analysis: Volume II

by Federico Marini and Alessandra Biancolillo

Appl. Sci. 2023, 13(9), 5633; https://doi.org/10.3390/app13095633 - 03 May 2023

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“Man is What He Eats”: food represents one of the fundamental needs of human beings, and, therefore, food analysis is a field of utmost importance [...] Full article

(This article belongs to the Special Issue Application of Spectroscopy in Food Analysis: Volume II)

Research

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24 pages, 10592 KiB

Open AccessArticle

Spectroscopic and Spectrometric Applications for the Identification of Bioactive Compounds from Vegetal Extracts

by José Daniel Lozada-Ramírez, Ana E. Ortega-Regules, Luis Ricardo Hernández and Cecilia Anaya de Parrodi

Appl. Sci. 2021, 11(7), 3039; https://doi.org/10.3390/app11073039 - 29 Mar 2021

Cited by 4 | Viewed by 3584

Abstract

The use of spectroscopic and spectrometric techniques to isolate, quantify, and characterize bioactive compounds from edible plants has become a common and mandatory activity in food chemistry. As technology advances, diverse methodologies are being applied more frequently, which are coupled most of the [...] Read more.

The use of spectroscopic and spectrometric techniques to isolate, quantify, and characterize bioactive compounds from edible plants has become a common and mandatory activity in food chemistry. As technology advances, diverse methodologies are being applied more frequently, which are coupled most of the time to give the best diagnosis and information of a metabolite of interest. In this paper, we state the different approaches that have been performed by our research group to isolate, identify, and apply the different bioactive organic compounds obtained from some vegetal extracts. Through this review, we show the importance of the use of those analytical tools to evaluate the possible impact of some plants we included on diet for improving human health. Full article

(This article belongs to the Special Issue Application of Spectroscopy in Food Analysis: Volume II)

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15 pages, 3690 KiB

Open AccessArticle

Rapid Nondestructive Postharvest Potato Freshness and Cultivar Discrimination Assessment

by Dimitrios S. Kasampalis, Pavlos Tsouvaltzis, Konstantinos Ntouros, Athanasios Gertsis, Dimitrios Moshou and Anastasios S. Siomos

Appl. Sci. 2021, 11(6), 2630; https://doi.org/10.3390/app11062630 - 16 Mar 2021

Cited by 6 | Viewed by 2161

Abstract

Background: Quality and safety of potato is both cultivar and postharvest management dependent. The precise assessment of freshness and cultivar are complex tasks requiring time-consuming, expensive, and destructive techniques. Method: Potatoes from three commercial cultivars were stored for 5 months at 5 °C. [...] Read more.

Background: Quality and safety of potato is both cultivar and postharvest management dependent. The precise assessment of freshness and cultivar are complex tasks requiring time-consuming, expensive, and destructive techniques. Method: Potatoes from three commercial cultivars were stored for 5 months at 5 °C. Color and chlorophyll fluorescence were recorded, Red-Green-Blue (R-G-B), Red-Green-Near infrared (R-G-NIR) and Red-Blue-Near infrared (R-B-NIR) digital images, as well as hyperspectral images were acquired both on the external periderm of the tuber and in the inner flesh part. Partial least square regression (PLSR) and discriminant analysis, combined with feature selection techniques were implemented, in order to assess the potato freshness and to classify them into the respective genotypes. Results: The PLSR analysis of visible/near infrared (Vis/NIR) spectra reflectance most reliably predicted potato freshness, with a cross-validated regression coefficient equal to 0.981 and 0.947, as determined by external or internal measurements, respectively. Variance inflation factor, variable importance scores, and genetic algorithms identified specific wavelength regions that mostly affected the accuracy of the model in terms of strongest regression and lowest collinearity and root mean cross validation error. Conclusions: Vis/NIR spectra reflectance data from the skin of the potato tubers may be reliably used in the assessment of postharvest storage life, as well as in the cultivar discrimination process. Full article

(This article belongs to the Special Issue Application of Spectroscopy in Food Analysis: Volume II)

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11 pages, 880 KiB

Open AccessArticle

Sequential Data Fusion Techniques for the Authentication of the P.G.I. Senise (“Crusco”) Bell Pepper

by Alessandra Biancolillo, Francesca Di Donato, Francesco Merola, Federico Marini and Angelo Antonio D’Archivio

Appl. Sci. 2021, 11(4), 1709; https://doi.org/10.3390/app11041709 - 14 Feb 2021

Cited by 10 | Viewed by 1778

Abstract

Bell pepper is the common name of the berry obtained from some varieties of the Capsicum annuum species. This agro-food is appreciated all over the world and represents one of the key ingredients of several traditional dishes. It is used as a fresh [...] Read more.

Bell pepper is the common name of the berry obtained from some varieties of the Capsicum annuum species. This agro-food is appreciated all over the world and represents one of the key ingredients of several traditional dishes. It is used as a fresh product, or dried and ground as a seasoning (e.g., paprika). Specific varieties of sweet pepper present organoleptic peculiarities and they have been awarded by quality marks as a further confirmation of their unicity (e.g., Piment d’Espelette, Pimiento de Herbón, Peperone di Senise). Due to the market value of this aliment, it can be subjected to frauds, such as adulterations and sophistication. The present study lays on these considerations and aims at developing a spectroscopy-based approach for authenticating Senise bell pepper and for detecting its adulteration with common paprika. In order to achieve this goal, 60 pure samples of bell pepper from Senise were analyzed by mid- and near-infrared spectroscopies. Then, in order to mimic the adulteration, 40 mixtures of Senise bell pepper and paprika were prepared and analyzed (by the same spectroscopic techniques). Eventually, two different multi-block classification approaches (sequential and orthogonalized partial least squares linear discriminant analysis and sequential and orthogonalized covariance selection linear discriminant analysis) were used to discriminate between pure and adulterated Senise bell pepper samples. Both proposed procedures achieved extremely successful results in external validation, correctly classifying all the (thirty-five) test samples, indicating that both approaches represent a winning solution for the investigated classification problem. Full article

(This article belongs to the Special Issue Application of Spectroscopy in Food Analysis: Volume II)

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13 pages, 1429 KiB

Open AccessArticle

A Four-Level Maturity Index for Hot Peppers (Capsicum annum) Using Non-Invasive Automated Mobile Raman Spectroscopy for On-Site Testing

by Robin Legner, Melanie Voigt, Carla Servatius, Johannes Klein, Antje Hambitzer and Martin Jaeger

Appl. Sci. 2021, 11(4), 1614; https://doi.org/10.3390/app11041614 - 10 Feb 2021

Cited by 10 | Viewed by 2425

Abstract

A handheld Raman spectrometer was used to determine the ripeness of peppers. Raman spectra were recorded non-invasively on the fruit surface. The spectroscopic data were transformed into a classification scheme referred to as the maturity index which allowed for attribution of the fruit [...] Read more.

A handheld Raman spectrometer was used to determine the ripeness of peppers. Raman spectra were recorded non-invasively on the fruit surface. The spectroscopic data were transformed into a classification scheme referred to as the maturity index which allowed for attribution of the fruit stadium to four levels from immature to fully mature. Hot pepper and tomato ripening includes pectic polysaccharide depolymerization, chlorophyll degradation and carotenoid formation, among others. The latter were followed non-invasively by Raman spectroscopy. Two portable systems and one benchtop system were compared for their applicability and robustness to establish a suitable maturity index. Spectral acquisition, data treatment and multivariate data analysis were automated using a Matlab script on a laptop computer. The automated workflow provided a graphic visualization of the relevant parameters and results on-site in real time. In terms of reliability and applicability, the chemometric model to determine the maturity of fruits was compared to a univariate procedure based on the average intensity and ratio of three characteristic signals. Portable Raman spectrometers in combination with the maturity index or a chemometric model should be suitable to assess the stage of maturing for carotenoid-containing fruits and thus to determine ripeness on-site or during a sorting process in an automated manner. Full article

(This article belongs to the Special Issue Application of Spectroscopy in Food Analysis: Volume II)

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12 pages, 2252 KiB

Open AccessArticle

An Unsupervised Prediction Model for Salmonella Detection with Hyperspectral Microscopy: A Multi-Year Validation

by Matthew Eady and Bosoon Park

Appl. Sci. 2021, 11(3), 895; https://doi.org/10.3390/app11030895 - 20 Jan 2021

Cited by 4 | Viewed by 2226

Abstract

Hyperspectral microscope images (HMIs) have been previously explored as a tool for the early and rapid detection of common foodborne pathogenic bacteria. A robust unsupervised classification approach to differentiate bacterial species with the potential for single cell sensitivity is needed for real-world application, [...] Read more.

Hyperspectral microscope images (HMIs) have been previously explored as a tool for the early and rapid detection of common foodborne pathogenic bacteria. A robust unsupervised classification approach to differentiate bacterial species with the potential for single cell sensitivity is needed for real-world application, in order to confirm the identity of pathogenic bacteria isolated from a food product. Here, a one-class soft independent modelling of class analogy (SIMCA) was used to determine if individual cells are Salmonella positive or negative. The model was constructed and validated with a spectral library built over five years, containing 13 Salmonella serotypes and 14 non-Salmonella foodborne pathogens. An image processing method designed to take less than one minute paired with the one-class Salmonella prediction algorithm resulted in an overall classification accuracy of 95.4%, with a Salmonella sensitivity of 0.97, and specificity of 0.92. SIMCA’s prediction accuracy was only achieved after a robust model incorporating multiple serotypes was established. These results demonstrate the potential for HMI as a sensitive and unsupervised presumptive screening method, moving towards the early (<8 h) and rapid (<1 h) identification of Salmonella from food matrices. Full article

(This article belongs to the Special Issue Application of Spectroscopy in Food Analysis: Volume II)

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11 pages, 779 KiB

Open AccessArticle

Authentication of Rice (Oryza sativa L.) Using Near Infrared Spectroscopy Combined with Different Chemometric Classification Strategies

by Duy Le Nguyen Doan, Quoc Cuong Nguyen, Federico Marini and Alessandra Biancolillo

Appl. Sci. 2021, 11(1), 362; https://doi.org/10.3390/app11010362 - 01 Jan 2021

Cited by 20 | Viewed by 3066

Abstract

Rice is a staple food in Vietnam, and the concern about rice is much greater than that for other foods. Preventing fraud against this product has become increasingly important in order to protect producers and consumers from possible economic losses. The possible adulteration [...] Read more.

Rice is a staple food in Vietnam, and the concern about rice is much greater than that for other foods. Preventing fraud against this product has become increasingly important in order to protect producers and consumers from possible economic losses. The possible adulteration of this product is done by mixing, or even replacing, high-quality rice with cheaper rice. This highlights the need for analytical methodologies suitable for its authentication. Given this scenario, the present work aims at testing a rapid and non-destructive approach to detect adulterated rice samples. To fulfill this purpose, 200 rice samples (72 authentic and 128 adulterated samples) were analyzed by near infrared (NIR) spectroscopy coupled, with partial least squares-discriminant analysis (PLS-DA) and soft independent modeling of class analogies (SIMCA). The two approaches provided different results; while PLS-DA analysis was a suitable approach for the purpose of the work, SIMCA was unable to solve the investigated problem. The PLS-DA approach provided satisfactory results in discriminating authentic and adulterated samples (both 5% and 10% counterfeits). Focusing on authentic and 10%-adulterated samples, the accuracy of the approach was even better (with a total classification rate of 82.6% and 82.4%, for authentic and adulterated samples, respectively). Full article

(This article belongs to the Special Issue Application of Spectroscopy in Food Analysis: Volume II)

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12 pages, 1444 KiB

Open AccessArticle

Characteristic of Pseudomonas syringae pv. atrofaciens Isolated from Weeds of Wheat Field

by Liudmyla Butsenko, Lidiia Pasichnyk, Yuliia Kolomiiets, Antonina Kalinichenko, Dariusz Suszanowicz, Monika Sporek and Volodymyr Patyka

Appl. Sci. 2021, 11(1), 286; https://doi.org/10.3390/app11010286 - 30 Dec 2020

Cited by 4 | Viewed by 2866

Abstract

The aim of this study was the identification of the causative agent of the basal glume rot of wheat Pseudomonas syringae pv. atrofaciens from the affected weeds in wheat crops, and determination of its virulent properties. Isolation of P. syringae pv. atrofaciens from [...] Read more.

The aim of this study was the identification of the causative agent of the basal glume rot of wheat Pseudomonas syringae pv. atrofaciens from the affected weeds in wheat crops, and determination of its virulent properties. Isolation of P. syringae pv. atrofaciens from weeds of wheat crops was carried out by classical microbiological methods. To identify isolated bacteria, their morphological, cultural, biochemical, and serological properties as well as fatty acids and Random Amplification of Polymorphic DNA (RAPD)-PCR (Polymerase chain reaction) profiles with the OPA-13 primer were studied. Pathogenic properties were investigated by artificial inoculation of wheat plants and weed plants, from which bacteria were isolated. For the first time, bacteria that are virulent both for weeds and wheat were isolated from weeds growing in wheat crops. It was shown that the fatty acids profiles of the bacteria isolated from the weeds contained typical for P. syringae pv. atrofaciens fatty acids, in particular, hydroxy acids: 3-hydroxydecanoic, 2-hydroxydodecanoic, and 3-hydroxydodecanoic. RAPD-PCR profiles of the newly isolated strains were identical to those of the collection strains P. syringae pv. atrofaciens UCM B-1011 and P. syringae pv. atrofaciens UCM B-1014 and contained a dominant fragment of 700 bp. The isolated strains, according to their phenotypic and genotypic properties, were identified as P. syringae pv. atrofaciens. It was established that the causative agent of basal glume rot of wheat P. syringae pv. atrofaciens is polyphagous and capable of infecting a wide range of plants. The main control measure for cereals diseases caused by P. syringae pv. Atrofaciens—crop rotations with nonhost species, should be revised, and alternative control methods must be proposed. Full article

(This article belongs to the Special Issue Application of Spectroscopy in Food Analysis: Volume II)

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11 pages, 1085 KiB

Open AccessArticle

In Situ Monitoring of Sugar Content in Breakfast Cereals Using a Novel FT-NIR Spectrometer

by Didem Peren Aykas, Christopher Ball, Ahmed Menevseoglu and Luis E. Rodriguez-Saona

Appl. Sci. 2020, 10(24), 8774; https://doi.org/10.3390/app10248774 - 08 Dec 2020

Cited by 8 | Viewed by 2975

Abstract

This research demonstrates simultaneous predictions of individual and total sugars in breakfast cereals using a novel, handheld near-infrared (NIR) spectroscopic sensor. This miniaturized, battery-operated unit based on Fourier Transform (FT)-NIR was used to collect spectra from both ground and intact breakfast cereal samples, [...] Read more.

This research demonstrates simultaneous predictions of individual and total sugars in breakfast cereals using a novel, handheld near-infrared (NIR) spectroscopic sensor. This miniaturized, battery-operated unit based on Fourier Transform (FT)-NIR was used to collect spectra from both ground and intact breakfast cereal samples, followed by real-time wireless data transfer to a commercial tablet for chemometric processing. A total of 164 breakfast cereal samples (60 store-bought and 104 provided by a snack food company) were tested. Reference analysis for the individual (sucrose, glucose, and fructose) and total sugar contents used high-performance liquid chromatography (HPLC). Chemometric prediction models were generated using partial least square regression (PLSR) by combining the HPLC reference analysis data and FT-NIR spectra, and associated calibration models were externally validated through an independent data set. These multivariate models showed excellent correlation (R_pre ≥ 0.93) and low standard error of prediction (SEP ≤ 2.4 g/100 g) between the predicted and the measured sugar values. Analysis results from the FT-NIR data, confirmed by the reference techniques, showed that eight store-bought cereal samples out of 60 (13%) were not compliant with the total sugar content declaration. The results suggest that the FT-NIR prototype can provide reliable analysis for the snack food manufacturers for on-site analysis. Full article

(This article belongs to the Special Issue Application of Spectroscopy in Food Analysis: Volume II)

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15 pages, 3520 KiB

Open AccessArticle

Attenuated Total Reflectance-Fourier Transform Infrared Spectroscopy (ATR-FTIR) Coupled with Chemometrics, to Control the Botanical Authenticity and Quality of Cold-Pressed Functional Oils Commercialized in Romania

by Carmen Socaciu, Florinela Fetea, Floricuta Ranga, Andrea Bunea, Francisc Dulf, Sonia Socaci and Adela Pintea

Appl. Sci. 2020, 10(23), 8695; https://doi.org/10.3390/app10238695 - 04 Dec 2020

Cited by 25 | Viewed by 2740

Abstract

Attenuated total reflectance-Fourier transform infrared ppectroscopy (ATR-FTIR) proved to be a reliable, rapid, and easy-to-use technique to evaluate vegetable oils quality and authenticity. The spectral range of the middle infrared region (MIR) of FTIR spectra, from 4000 to 600 cm⁻¹, has [...] Read more.

Attenuated total reflectance-Fourier transform infrared ppectroscopy (ATR-FTIR) proved to be a reliable, rapid, and easy-to-use technique to evaluate vegetable oils quality and authenticity. The spectral range of the middle infrared region (MIR) of FTIR spectra, from 4000 to 600 cm⁻¹, has been commonly used to fingerprint specific functional groups of lipids and their modified forms induced by oxidation of thermal treatment. The applicability of FTIR-MIR spectroscopy in assessing oil fingerprinting and quality parameters is crucially dependent on the chemometric methods, including calibrations with authentic samples. We report here the evaluation of seven types of cold-pressed functional oils (sunflower, pumpkin, hempseed, soybean, walnut, linseed, sea buckthorn) produced in Romania, provided directly from small enterprises (as genuine, process-controlled authentic samples) comparative to commercialized samples. Concomitantly, olive oils of similar claimed quality were investigated. The ATR-FTIR-MIR data were complemented by UV–Vis spectral fingerprints and multivariate analysis using Unscrambler X.10.4 and Metaboanalyst 4.0 software (e.g., PCA, PLSDA, cluster analysis, heatmap, Random forest analysis) and ANOVA post-hoc analysis using Fischer’s least significant difference. The integration of spectral and chemometric analysis proved to offer valuable criteria for their botanical group recognition, individual authenticity, and quality, easy to be applied for large cohorts of commercialized oils. Full article

(This article belongs to the Special Issue Application of Spectroscopy in Food Analysis: Volume II)

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13 pages, 2477 KiB

Open AccessArticle

NMR-Based Metabolomic Study of Purple Carrot Optimal Harvest Time for Utilization as a Source of Bioactive Compounds

by Fabio Sciubba, Alberta Tomassini, Giorgio Giorgi, Elisa Brasili, Gabriella Pasqua, Giorgio Capuani, Walter Aureli and Alfredo Miccheli

Appl. Sci. 2020, 10(23), 8493; https://doi.org/10.3390/app10238493 - 27 Nov 2020

Cited by 9 | Viewed by 2308

Abstract

The carrot (Daucus carota L.), one of the most important vegetable crops in the world, is recognized as a source of different compounds with healthy properties. Due to their high content of anthocyanins, purple carrots have been used as a natural colorant [...] Read more.

The carrot (Daucus carota L.), one of the most important vegetable crops in the world, is recognized as a source of different compounds with healthy properties. Due to their high content of anthocyanins, purple carrots have been used as a natural colorant source to face the increasing demand of consumers for non-synthetic products. However, the root developmental stage can greatly affect the phytochemical composition and, in this regard, the identification of chemical biomarkers for the optimal harvest time would be of paramount interest both from a nutritional point of view and for the agri-food industry. In the present work, the metabolic profiling of purple carrots was monitored over four months using high-resolution ¹H NMR spectroscopy. Several metabolites were identified, and their quantitative variations allowed for the investigation of the carrot development processes. The metabolic profile analysis showed an increase in amino acid, NAD, and caffeic acid levels during carrot development. A more tardive harvest in December entailed an increase in levels of luteolin-7-O-glucoside, chlorogenic acid, falcarinol, and γ-aminobutyrate, and a decrease in carotenoids and ω-6 fatty acid. The results showed how the harvest time affects the composition in terms of flavonoids, phenols, and polyacetylenes, therefore, improving the bioactive compound content. Full article

(This article belongs to the Special Issue Application of Spectroscopy in Food Analysis: Volume II)

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16 pages, 2644 KiB

Open AccessArticle

Evaluation of the Cultivated Mushroom Pleurotus ostreatus Basidiocarps Using Vibration Spectroscopy and Chemometrics

by Ekaterina Baeva, Roman Bleha, Markéta Sedliaková, Leonid Sushytskyi, Ivan Švec, Jana Čopíková, Ivan Jablonsky, Pavel Klouček and Andriy Synytsya

Appl. Sci. 2020, 10(22), 8156; https://doi.org/10.3390/app10228156 - 18 Nov 2020

Cited by 10 | Viewed by 2222

Abstract

Fruiting bodies (basidiocarps) of the cultivated mushroom Pleurotus ostreatus (16 strains) were characterized by vibration spectroscopy and chemometrics. According to organic elemental analysis and Megazyme assay, the basidiocarps contained ~6.2–17.5% protein and ~18.8–58.2% total glucans. The neutral sugar analysis confirmed that glucose predominated [...] Read more.

Fruiting bodies (basidiocarps) of the cultivated mushroom Pleurotus ostreatus (16 strains) were characterized by vibration spectroscopy and chemometrics. According to organic elemental analysis and Megazyme assay, the basidiocarps contained ~6.2–17.5% protein and ~18.8–58.2% total glucans. The neutral sugar analysis confirmed that glucose predominated in all the samples (~71.3–94.4 mol%). Fourier-transformed (FT) mid- and near-infrared (FT MIR, FT NIR) and FT Raman spectra of the basidiocarps were recorded, and the characteristic bands of proteins, glucans and chitin were assigned. The samples were discriminated based on principal component analysis (PCA) of the spectroscopic data in terms of biopolymeric composition. The partial least squares regression (PLSR) models based on first derivatives of the vibration spectra were obtained for the prediction of the macromolecular components, and the regression coefficients R² and root mean square errors (RMSE) were calculated for the calibration (cal) of proteins (R²_cal 0.981–0.994, RMSE_cal ~0.3–0.5) and total glucans (R²_cal 0.908–0.996, RMSE_cal ~0.6–3.0). According to cross-validation (CV) diagnosis, the protein models were more precise and accurate (R²_cv 0.901–0.970, RMSE_cv ~0.6–1.1) than the corresponding total glucan models (R²_cv 0.370–0.804, RMSE_cv ~4.7–8.5) because of the wide structural diversity of these polysaccharides. Otherwise, the Raman band of phenylalanine ring breathing vibration at 1004 cm⁻¹ was used for direct quantification of proteins in P. ostreatus basidiocarps (R ~0.953). This study showed that the combination of vibration spectroscopy with chemometrics is a powerful tool for the evaluation of culinary and medicinal mushrooms, and this approach can be proposed as an alternative to common analytical methods. Full article

(This article belongs to the Special Issue Application of Spectroscopy in Food Analysis: Volume II)

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14 pages, 13603 KiB

Open AccessArticle

Detection for Frying Times of Various Edible Oils Based on Near-Infrared Spectroscopy

by Yi Liu, Laijun Sun, Hongyi Bai and Zhiyong Ran

Appl. Sci. 2020, 10(21), 7789; https://doi.org/10.3390/app10217789 - 03 Nov 2020

Cited by 6 | Viewed by 2076

Abstract

Taking a variety of edible oils as the research object, including soybean oil, peanut oil, rapeseed oil, a method based on Near-Infrared Spectroscopy (NIRS) to identify the frying times is proposed to evaluate the quality of frying oil. Ten rounds of frying experiments [...] Read more.

Taking a variety of edible oils as the research object, including soybean oil, peanut oil, rapeseed oil, a method based on Near-Infrared Spectroscopy (NIRS) to identify the frying times is proposed to evaluate the quality of frying oil. Ten rounds of frying experiments are carried out for each of the three oils. The spectra of the first eight rounds are used to build the model, and the last two are used for model testing. First, all the original spectra are preprocessed using the first derivative (1D). Then, the correlation coefficient between the sequence of frying times and absorbance is calculated, and the characteristic wavelengths with a high correlation coefficient are extracted. Finally, a differential prediction model is established based on the characteristic wavelengths. The results show that the differential prediction model accurately predicts the frying times of various edible oils and provides a new method for quality inspection of frying oil, and the predicted accuracy of the frying times of three frying oils is 100% within the allowable range of error. Full article

(This article belongs to the Special Issue Application of Spectroscopy in Food Analysis: Volume II)

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12 pages, 2531 KiB

Open AccessArticle

Effect of Sample Preparation Methods on the Prediction Performances of Near Infrared Reflectance Spectroscopy for Quality Traits of Fresh Yam (Dioscorea spp.)

by Emmanuel Oladeji Alamu, Michael Adesokan, Asrat Asfaw and Busie Maziya-Dixon

Appl. Sci. 2020, 10(17), 6035; https://doi.org/10.3390/app10176035 - 31 Aug 2020

Cited by 2 | Viewed by 2315

Abstract

High throughput techniques for phenotyping quality traits in root and tuber crops are useful in breeding programs where thousands of genotypes are screened at the early stages. This study assessed the effects of sample preparation on the prediction accuracies of dry matter, protein, [...] Read more.

High throughput techniques for phenotyping quality traits in root and tuber crops are useful in breeding programs where thousands of genotypes are screened at the early stages. This study assessed the effects of sample preparation on the prediction accuracies of dry matter, protein, and starch content in fresh yam using Near-Infrared Reflectance Spectroscopy (NIRS). Fresh tubers of Dioscorearotundata (D. rotundata) and Dioscoreaalata (D. alata) were prepared using different sampling techniques—blending, chopping, and grating. Spectra of each sample and reference data were used to develop calibration models using Modified Partial Least Square (MPLS). The performance of the model developed from the blended yam samples was tested using a new set of yam samples (N = 50) by comparing their wet laboratory results with the predicted values from NIRS. Blended samples had the highest coefficient of prediction (R²_pre) for dry matter (0.95) and starch (0.83), though very low for protein (0.26), while grated samples had the lowest R²_pre of 0.87 for dry matter and 0.50 for starch. Results showed that blended samples gave a better prediction compared with other methods. The feasibility of NIRS for the prediction of dry matter and starch content in fresh yam was highlighted. Full article

(This article belongs to the Special Issue Application of Spectroscopy in Food Analysis: Volume II)

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17 pages, 8157 KiB

Open AccessArticle

Peak Fitting Applied to Fourier Transform Infrared and Raman Spectroscopic Analysis of Proteins

by Azin Sadat and Iris J. Joye

Appl. Sci. 2020, 10(17), 5918; https://doi.org/10.3390/app10175918 - 26 Aug 2020

Cited by 207 | Viewed by 20309

Abstract

FTIR and Raman spectroscopy are often used to investigate the secondary structure of proteins. Focus is then often laid on the different features that can be distinguished in the Amide I band (1600–1700 cm⁻¹) and, to a lesser extent, the Amide [...] Read more.

FTIR and Raman spectroscopy are often used to investigate the secondary structure of proteins. Focus is then often laid on the different features that can be distinguished in the Amide I band (1600–1700 cm⁻¹) and, to a lesser extent, the Amide II band (1510–1580 cm⁻¹), signature regions for C=O stretching/N-H bending, and N-H bending/C-N stretching vibrations, respectively. Proper investigation of all hidden and overlapping features/peaks is a necessary step to achieve reliable analysis of FTIR and FT-Raman spectra of proteins. This paper discusses a method to identify, separate, and quantify the hidden peaks in the amide I band region of infrared and Raman spectra of four globular proteins in aqueous solution as well as hydrated zein and gluten proteins. The globular proteins studied, which differ widely in terms of their secondary structures, include immunoglobulin G, concanavalin A, lysozyme, and trypsin. Peak finding was done by analysis of the second derivative of the original spectra. Peak separation and quantification was achieved by curve fitting using the Voigt function. Structural data derived from the FT-Raman and FTIR analyses were compared to literature reports on protein structure. This manuscript proposes an accurate method to analyze protein secondary structure based on the amide I band in vibrational spectra. Full article

(This article belongs to the Special Issue Application of Spectroscopy in Food Analysis: Volume II)

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34 pages, 10546 KiB

Open AccessCommentary

Commentary: Iconoclastic Reflections on the ‘Safety’ of Polyunsaturated Fatty Acid-Rich Culinary Frying Oils: Some Cautions regarding the Laboratory Analysis and Dietary Ingestion of Lipid Oxidation Product Toxins

by Martin Grootveld, Benita C. Percival, Sarah Moumtaz, Miles Gibson, Katy Woodason, Azeem Akhtar, Michael Wawire, Mark Edgar and Kerry L. Grootveld

Appl. Sci. 2021, 11(5), 2351; https://doi.org/10.3390/app11052351 - 06 Mar 2021

Cited by 13 | Viewed by 7616

Abstract

Continuous or frequent ingestion of fried foods containing cytotoxic/mutagenic/genotoxic lipid oxidation products (LOPs) may present significant human health risks; such toxins are generated in thermally stressed polyunsaturated fatty acid (PUFA)-rich culinary frying oils (CFOs) during standard frying practices. Since monounsaturated and saturated fatty [...] Read more.

Continuous or frequent ingestion of fried foods containing cytotoxic/mutagenic/genotoxic lipid oxidation products (LOPs) may present significant human health risks; such toxins are generated in thermally stressed polyunsaturated fatty acid (PUFA)-rich culinary frying oils (CFOs) during standard frying practices. Since monounsaturated and saturated fatty acids (MUFAs and SFAs, respectively) are much less susceptible to peroxidation than PUFAs, in this study CFOs of differential unsaturated fatty acid contents were exposed to laboratory-simulated shallow-frying episodes (LSSFEs). Firstly, we present a case study exploring the time-dependent generation of aldehydic LOPs in CFO products undergoing LSSFEs, which was then used to evaluate the relative potential health risks posed by them, and also to provide suitable recommendations concerning their safety when used for frying purposes. Sunflower, rapeseed, extra-virgin olive and coconut oils underwent LSSFEs at 180 °C: Samples were collected at 0–90 min time-points (n = 6 replicates per oil). Aldehydes therein were determined by high-resolution ¹H NMR analysis at 400 and 600 MHz operating frequencies. For one of the first times, CFO LOP analysis was also performed on a non-stationary 60 MHz benchtop NMR spectrometer. ¹H NMR analysis confirmed the thermally promoted, time-dependent production of a wide range of aldehydic LOPs in CFOs. As expected, the highest levels of these toxins were produced in PUFA-rich sunflower oil, with lower concentrations formed in MUFA-rich canola and extra-virgin olive oils; in view of its very high SFA content, only very low levels of selected aldehyde classes were generated in coconut oil during LSSFEs. Secondly, ¹H NMR results acquired are discussed with regard to the suitability and validity of alternative, albeit routinely employed, spectrophotometric methods for evaluating the peroxidation status of CFOs and lipid-containing foods. Thirdly, an updated mini-review of the toxicological properties of and intake limits for LOPs, and deleterious health effects posed by their ingestion, is provided. In conclusion, exposure of PUFA-rich CFOs to high-temperature frying practices generates very high concentrations of aldehydic LOP toxins from thermally promoted, O₂-powered, recycling peroxidation processes; these toxins penetrate into and hence are ‘carried’ by fried foods available for human consumption. Such toxins have the capacity to contribute towards the development and progression of non-communicable chronic diseases (NCDs) if cumulatively ingested by humans. Full article

(This article belongs to the Special Issue Application of Spectroscopy in Food Analysis: Volume II)

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