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3 pages, 202 KiB

Open AccessEditorial

Advances in NIR Spectroscopy Analytical Technology in Food Industries

by Silvia Grassi and Ernestina Casiraghi

Foods 2022, 11(9), 1250; https://doi.org/10.3390/foods11091250 - 26 Apr 2022

Cited by 9 | Viewed by 2621

Abstract

Industry 4 [...] Full article

(This article belongs to the Special Issue Advances in NIR Spectroscopy Analytical Technology in Food Industries)

Research

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17 pages, 14414 KiB

Open AccessEditor’s ChoiceArticle

Use of Artificial Neural Networks and NIR Spectroscopy for Non-Destructive Grape Texture Prediction

by Teodora Basile, Antonio Domenico Marsico and Rocco Perniola

Foods 2022, 11(3), 281; https://doi.org/10.3390/foods11030281 - 20 Jan 2022

Cited by 47 | Viewed by 4118

Abstract

In this article, a combination of non-destructive NIR spectroscopy and machine learning techniques was applied to predict the texture parameters and the total soluble solids content (TSS) in intact berries. The multivariate models obtained by building artificial neural networks (ANNs) and applying partial [...] Read more.

In this article, a combination of non-destructive NIR spectroscopy and machine learning techniques was applied to predict the texture parameters and the total soluble solids content (TSS) in intact berries. The multivariate models obtained by building artificial neural networks (ANNs) and applying partial least squares (PLS) regressions showed a better prediction ability after the elimination of uninformative spectral ranges. A very good prediction was obtained for TSS and springiness (R² 0.82 and 0.72). Qualitative models were obtained for hardness and chewiness (R² 0.50 and 0.53). No satisfactory calibration model could be established between the NIR spectra and cohesiveness. Textural parameters of grape are strictly related to the berry size. Before any grape textural measurement, a time-consuming berry-sorting step is compulsory. This is the first time a complete textural analysis of intact grape berries has been performed by NIR spectroscopy without any a priori knowledge of the berry density class. Full article

(This article belongs to the Special Issue Advances in NIR Spectroscopy Analytical Technology in Food Industries)

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12 pages, 17280 KiB

Open AccessArticle

A FT-NIR Process Analytical Technology Approach for Milk Renneting Control

by Silvia Grassi, Lorenzo Strani, Cristina Alamprese, Nicolò Pricca, Ernestina Casiraghi and Giovanni Cabassi

Foods 2022, 11(1), 33; https://doi.org/10.3390/foods11010033 - 23 Dec 2021

Cited by 12 | Viewed by 4077

Abstract

The study proposes a process analytical technology (PAT) approach for the control of milk coagulation through near infrared spectroscopy (NIRS), computing multivariate statistical process control (MSPC) charts, based on principal component analysis (PCA). Reconstituted skimmed milk and commercial pasteurized skimmed milk were mixed [...] Read more.

The study proposes a process analytical technology (PAT) approach for the control of milk coagulation through near infrared spectroscopy (NIRS), computing multivariate statistical process control (MSPC) charts, based on principal component analysis (PCA). Reconstituted skimmed milk and commercial pasteurized skimmed milk were mixed at two different ratios (60:40 and 40:60). Each mix ratio was prepared in six replicates and used for coagulation trials, monitored by fundamental rheology, as a reference method, and NIRS by inserting a probe directly in the coagulation vat and collecting spectra at two different acquisition times, i.e., 60 s or 10 s. Furthermore, three failure coagulation trials were performed, deliberately changing temperature or rennet and CaCl₂ concentration. The comparison with fundamental rheology results confirmed the effectiveness of NIRS to monitor milk renneting. The reduced spectral acquisition time (10 s) showed data highly correlated (r > 0.99) to those acquired with longer acquisition time. The developed decision trees, based on PC1 scores and T² MSPC charts, confirmed the suitability of the proposed approach for the prediction of coagulation times and for the detection of possible failures. In conclusion, the work provides a robust but simple PAT approach to assist cheesemakers in monitoring the coagulation step in real-time. Full article

(This article belongs to the Special Issue Advances in NIR Spectroscopy Analytical Technology in Food Industries)

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15 pages, 2325 KiB

Open AccessArticle

On-Line Real-Time Monitoring of a Rapid Enzymatic Oil Degumming Process: A Feasibility Study Using Free-Run Near-Infrared Spectroscopy

by Jakob Forsberg, Per Munk Nielsen, Søren Balling Engelsen and Klavs Martin Sørensen

Foods 2021, 10(10), 2368; https://doi.org/10.3390/foods10102368 - 5 Oct 2021

Cited by 3 | Viewed by 2960

Abstract

Enzymatic degumming is a well established process in vegetable oil refinement, resulting in higher oil yield and a more stable downstream processing compared to traditional degumming methods using acid and water. During the reaction, phospholipids in the oil are hydrolyzed to free fatty [...] Read more.

Enzymatic degumming is a well established process in vegetable oil refinement, resulting in higher oil yield and a more stable downstream processing compared to traditional degumming methods using acid and water. During the reaction, phospholipids in the oil are hydrolyzed to free fatty acids and lyso-phospholipids. The process is typically monitored by off-line laboratory measurements of the free fatty acid content in the oil, and there is a demand for an automated on-line monitoring strategy to increase both yield and understanding of the process dynamics. This paper investigates the option of using Near-Infrared spectroscopy (NIRS) to monitor the enzymatic degumming reaction. A new method for balancing spectral noise and keeping the chemical information in the spectra obtained from a rapid changing chemical process is suggested. The effect of a varying measurement averaging window width (0 to 300 s), preprocessing method and variable selection algorithm is evaluated, aiming to obtain the most accurate and robust calibration model for prediction of the free fatty acid content (% (w/w)). The optimal Partial Least Squares (PLS) model includes eight wavelength variables, as found by rPLS (recursive PLS) calibration, and yields an RMSECV (Root Mean Square Error of Cross Validation) of 0.05% (w/w) free fatty acid using five latent variables. Full article

(This article belongs to the Special Issue Advances in NIR Spectroscopy Analytical Technology in Food Industries)

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14 pages, 324 KiB

Open AccessArticle

Near-Infrared Spectroscopy (NIRS) as a Tool for Classification of Pre-Sliced Iberian Salchichón, Modified Atmosphere Packaged (MAP) According to the Official Commercial Categories of Raw Meat

by Alberto Ortiz, Lucía León, Rebeca Contador and David Tejerina

Foods 2021, 10(8), 1865; https://doi.org/10.3390/foods10081865 - 12 Aug 2021

Cited by 9 | Viewed by 2762

Abstract

This study evaluates near-infrared spectroscopy (NIRS) feasibility in combination with various pre-treatments and chemometric approaches for pre-sliced Iberian salchichón under modified atmosphere (MAP) classification according to the official commercial category (defined by the combination of genotype and feeding regime) of the raw material [...] Read more.

This study evaluates near-infrared spectroscopy (NIRS) feasibility in combination with various pre-treatments and chemometric approaches for pre-sliced Iberian salchichón under modified atmosphere (MAP) classification according to the official commercial category (defined by the combination of genotype and feeding regime) of the raw material used for its manufacturing (Black and Red purebred Iberian and Iberian × Duroc crossed (50%) pigs, respectively, reared outdoors in a Montanera system and White Iberian × Duroc crossed (50%) pigs with feed based on commercial fodder) without opening the package. In parallel, NIRS feasibility in combination with partial least squares regression (PLSR) to predict main quality traits was assessed. The best-fitting models developed by means of partial least squares discriminant analysis (PLS-DA) and linear discriminant analysis (LDA) yielded high discriminant ability and thus offered a tool to support the assignment of pre-sliced MAP Iberian salchichón according to the commercial category of the raw material. In addition, good predictive ability for C18:3 n-3 was obtained, which may help to support quality control. Full article

(This article belongs to the Special Issue Advances in NIR Spectroscopy Analytical Technology in Food Industries)

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14 pages, 1752 KiB

Open AccessArticle

Optimization of Instrument Design for In-Line Monitoring of Dry Matter Content in Single Potatoes by NIR Interaction Spectroscopy

by Jens Petter Wold, Marion O’Farrell, Petter Vejle Andersen and Jon Tschudi

Foods 2021, 10(4), 828; https://doi.org/10.3390/foods10040828 - 11 Apr 2021

Cited by 15 | Viewed by 3779

Abstract

Dry matter (DM) content is one of the most important quality features of potatoes. It defines the physical properties of the potatoes and determines what kind of product the potatoes can be used for. This paper presents the results obtained by a novel [...] Read more.

Dry matter (DM) content is one of the most important quality features of potatoes. It defines the physical properties of the potatoes and determines what kind of product the potatoes can be used for. This paper presents the results obtained by a novel prototype NIR (near-infrared) instrument designed to measure DM content in single potatoes in process. The instrument is based on interaction measurements to measure deeper into the potatoes. It measures rapidly, up to 50 measurements per second, allowing several moving potatoes to be measured per second. The instrument also enables several interactance distances to be recorded for each measurement. The instrument was calibrated based on three different potato varieties and the calibration measurements were done in a process plant, making the calibration model suitable for in-line use. A good calibration for DM was obtained by partial least squares regression (RMSECV = 0.78% DM, R² = 0.91). The instrument was tested in-line in the process plant and several batches of potatoes were monitored for the estimation of the DM distribution per batch. Accuracy of DM determination as function of measurement position on the potato was studied, and results indicate that NIR scans along the center part of the potatoes give slightly better results compared to scans taken on either side of the center. Small differences in optical measurement geometry influence the accuracy of the calibration models, underlining the importance of optimizing instrument design for successful measurements. Full article

(This article belongs to the Special Issue Advances in NIR Spectroscopy Analytical Technology in Food Industries)

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12 pages, 3278 KiB

Open AccessArticle

Evaluation of the Changes in Optical Properties of Peaches with Different Maturity Levels during Bruising

by Ye Sun, Yuping Huang, Leiqing Pan and Xiaochan Wang

Foods 2021, 10(2), 388; https://doi.org/10.3390/foods10020388 - 10 Feb 2021

Cited by 19 | Viewed by 3109

Abstract

The main objective was to measure the optical coefficients of peaches after bruising at different maturity levels and detect bruises. A spatially resolved method was used to acquire absorption coefficient (μ_a) and the reduced scattering coefficient (µ_s’) spectra from [...] Read more.

The main objective was to measure the optical coefficients of peaches after bruising at different maturity levels and detect bruises. A spatially resolved method was used to acquire absorption coefficient (μ_a) and the reduced scattering coefficient (µ_s’) spectra from 550 to 1000 nm, and a total of 12 groups (3 maturity levels * 4 detection times) were used to assess changes in µ_a and µ_s’ resulting from bruising. Maturation and bruising both caused a decrease in µ_s’ and an increase in µ_a, and the optical properties of immature peaches changed more after bruising than the optical properties of ripe peaches. Four hours after bruising, the optical properties of most samples were significantly different from those of intact peaches (p < 0.05), and the optical properties showed damage to tissue earlier than the appearance symptoms observed with the naked eye. The classification results of the Support Vector Machine model for bruised peaches showed that μ_a had the best classification accuracy compared to μ_s′ and their combinations (µ_a × µ_s’, µ_eff). Overall, based on μ_a, the average detection accuracies for peaches after bruising of 0 h, 4 h, and 24 h were increased. Full article

(This article belongs to the Special Issue Advances in NIR Spectroscopy Analytical Technology in Food Industries)

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15 pages, 2417 KiB

Open AccessArticle

Determination of the Geographical Origin of Walnuts (Juglans regia L.) Using Near-Infrared Spectroscopy and Chemometrics

by Maike Arndt, Alissa Drees, Christian Ahlers and Markus Fischer

Foods 2020, 9(12), 1860; https://doi.org/10.3390/foods9121860 - 13 Dec 2020

Cited by 29 | Viewed by 3818

Abstract

The prices of walnuts vary according to their geographical origin and, therefore, offer a financial incentive for adulteration. A reliable analysis method is required to quickly detect possible misdeclarations and thus prevent food fraud. In this study, a method to distinguish between seven [...] Read more.

The prices of walnuts vary according to their geographical origin and, therefore, offer a financial incentive for adulteration. A reliable analysis method is required to quickly detect possible misdeclarations and thus prevent food fraud. In this study, a method to distinguish between seven geographical origins of walnuts using Fourier transform near-infrared (FT-NIR) spectroscopy combined with chemometrics as a fast, versatile, and easy to handle analytical tool was developed. NIR spectra of 212 ground and afterwards freeze-dried walnut samples, harvested in three consecutive years (2017–2019), were collected. We optimized the data pre-processing by applying and evaluating 50,545 different pre-processing combinations, followed by linear discriminant analysis (LDA) which was confirmed by nested cross-validation. The results show that in the scope of our research minimal pre-processing led to the best results: By applying just multiplicative scatter correction (MSC) and median centering, a classification accuracy of 77.00% ± 1.60% was achieved. Consequently, this complex model can be used to answer economically relevant questions e.g., to distinguish between European and Chinese walnuts. Furthermore, the great influence of the applied pre-processing methods, e.g., the selected wavenumber range, on the achieved classification accuracy is shown which underlines the importance of optimization of the pre-processing strategy. Full article

(This article belongs to the Special Issue Advances in NIR Spectroscopy Analytical Technology in Food Industries)

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Review

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18 pages, 762 KiB

Open AccessReview

Multi-Way Analysis Coupled with Near-Infrared Spectroscopy in Food Industry: Models and Applications

by Huiwen Yu, Lili Guo, Mourad Kharbach and Wenjie Han

Foods 2021, 10(4), 802; https://doi.org/10.3390/foods10040802 - 8 Apr 2021

Cited by 26 | Viewed by 5516

Abstract

Near-infrared spectroscopy (NIRS) is a fast and powerful analytical tool in the food industry. As an advanced chemometrics tool, multi-way analysis shows great potential for solving a wide range of food problems and analyzing complex spectroscopic data. This paper describes the representative multi-way [...] Read more.

Near-infrared spectroscopy (NIRS) is a fast and powerful analytical tool in the food industry. As an advanced chemometrics tool, multi-way analysis shows great potential for solving a wide range of food problems and analyzing complex spectroscopic data. This paper describes the representative multi-way models which were used for analyzing NIRS data, as well as the advances, advantages and limitations of different multi-way models. The applications of multi-way analysis in NIRS for the food industry in terms of food process control, quality evaluation and fraud, identification and classification, prediction and quantification, and image analysis are also reviewed. It is evident from this report that multi-way analysis is presently an attractive tool for modeling complex NIRS data in the food industry while its full potential is far from reached. The combination of multi-way analysis with NIRS will be a promising practice for turning food data information into operational knowledge, conducting reliable food analyses and improving our understanding about food systems and food processes. To the best of our knowledge, this is the first paper that systematically reports the advances on models and applications of multi-way analysis in NIRS for the food industry. Full article

(This article belongs to the Special Issue Advances in NIR Spectroscopy Analytical Technology in Food Industries)

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