scholarly journals Assessment of chicken breast shelf life based on bench-top and portable NIR spectroscopy tools coupled with chemometrics

2020 ◽  
Author(s):  
Ilaria Lanza ◽  
Daniele Conficoni ◽  
Stefania Balzan ◽  
Marco Cullere ◽  
Luca Fasolato ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
Shelf Life ◽  
Meat Quality ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Life Assessment ◽  
Chicken Breast ◽  
Portable Devices ◽  
Physicochemical Processes ◽  
Insight Into

Abstract Near-infrared (NIR) spectroscopy is a rapid technique able to assess meat quality even if its capability to determine the shelf life of chicken fresh cuts is still debated, especially for portable devices. The aim of the study was to compare bench-top and portable NIR instruments in discriminating between four chicken breast refrigeration times (RT), coupled with multivariate classifier models. Ninety-six samples were analysed by both NIR tools at 2, 6, 10 and 14 days post-mortem. NIR data were subsequently submitted to partial least squares discriminant analysis (PLS-DA) and canonical discriminant analysis (CDA). The latter was preceded by double feature selection based on Boruta and Stepwise procedures. PLS-DA sorted moderate separation of RT theses, while shelf life assessment was more accurate on application of Stepwise-CDA. Bench-top tool had better performance than portable one, probably because it captured more informative spectral data as shown by the variable importance in projection (VIP) and restricted pool of Stepwise-CDA predictive scores (SPS). NIR tools coupled with a multivariate model provide deep insight into the physicochemical processes occurring during storage. Spectroscopy showed reliable effectiveness to recognise a 7-day shelf life threshold of breasts, suitable for routine at-line application for screening of meat quality.

scholarly journals A fast and low-cost approach to quality control of alcohol-based hand sanitizer using portable near infrared spectrometer and chemometrics

2021 ◽  
pp. 096703352098731
Author(s):  
Adenilton C da Silva ◽  
Lívia PD Ribeiro ◽  
Ruth MB Vidal ◽  
Wladiana O Matos ◽  
Gisele S Lopes
Keyword(s):  
Quality Control ◽  
Discriminant Analysis ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Principal Component ◽  
Partial Least Square ◽  
Least Square ◽  
Chemical Components ◽  
Linear Discriminant ◽  
Hand Sanitizer

The use of alcohol-based hand sanitizers is recommended as one of several strategies to minimize contamination and spread of the COVID-19 disease. Current reports suggest that the virucidal potential of ethanol occurs at concentrations close to 70%. Traditional methods of verifying the ethanol concentration in such products invite potential errors due to the viscosity of chemical components or may be prohibitively expensive to undertake in large demand. Near infrared (NIR) spectroscopy and chemometrics have already been used for the determination of ethanol in other matrices and present an alternative fast and reliable approach to quality control of alcohol-based hand sanitizers. In this study, a portable NIR spectrometer combined with classification chemometric tools, i.e., partial least square discriminant analysis (PLS–DA) and linear discriminant analysis with successive algorithm projection (SPA–LDA) were used to construct models to identify conforming and non-conforming commercial and laboratory synthesized hand sanitizer samples. Principal component analysis (PCA) was applied in an exploratory data study. Three principal components accounted for 99% of data variance and demonstrate clustering of conforming and non-conforming samples. The PLS–DA and SPA–LDA classification models presented 77 and 100% of accuracy in cross/internal validation respectively and 100% of accuracy in the classification of test samples. A total of 43% commercial samples evaluated using the PLS–DA and SPA–LDA presented ethanol content non-conforming for hand sanitizer gel. These results indicate that use of NIR spectroscopy and chemometrics is a promising strategy, yielding a method that is fast, portable, and reliable for discrimination of alcohol-based hand sanitizers with respect to conforming and non-conforming ethanol concentrations.

Classification of fish species from different ecosystems using the near infrared diffuse reflectance spectra of otoliths

2020 ◽  
Vol 28 (4) ◽  
pp. 224-235
Author(s):  
Irina M Benson ◽  
Beverly K Barnett ◽  
Thomas E Helser
Keyword(s):  
Discriminant Analysis ◽  
Spatial Variability ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Principal Component ◽  
Classification Model ◽  
Support Vector ◽  
Otolith Chemistry ◽  
K Nearest Neighbor ◽  
Fisheries Science

Applications of Fourier transform near infrared (FT-NIR) spectroscopy in fisheries science are currently limited. This current analysis of otolith spectral data demonstrate the potential applicability of FT-NIR spectroscopy to otolith chemistry and spatial variability in fisheries science. The objective of this study was to examine the use of NIR spectroscopy as a tool to differentiate among marine fishes in four large marine ecosystems. We examined otoliths from 13 different species, with three of these species coming from different regions. Principal component analysis described the main directions along which the specimens were separated. The separation of species and their ecosystems may suggest interactions between fish phylogeny, ontogeny, and environmental conditions that can be evaluated using NIR spectroscopy. In order to discriminate spectra across ecosystems and species, four supervised classification model techniques were utilized: soft independent modelling of class analogies, support vector machine discriminant analysis, partial least squares discriminant analysis, and k-nearest neighbor analysis (KNN). This study showed that the best performing model to classify combined ecosystems, all four ecosystems, and species was the KNN model, which had an overall accuracy rate of 99.9%, 97.6%, and 91.5%, respectively. Results from this study suggest that further investigations are needed to determine applications of NIR spectroscopy to otolith chemistry and spatial variability.

scholarly journals Discrimination of Salvia miltiorrhiza Bunge from Different Geographical Locations Employing High-Performance Liquid Chromatography, Near-Infrared Fingerprinting Combined with Chemometrics

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Jiao Wang ◽  
Yichun Sun ◽  
Zhan Li ◽  
Wei Li ◽  
Yuanyuan Pang ◽  
...  
Keyword(s):  
High Performance Liquid Chromatography ◽  
Liquid Chromatography ◽  
Discriminant Analysis ◽  
High Performance ◽  
Near Infrared ◽  
Salvia Miltiorrhiza ◽  
Nir Spectroscopy ◽  
Gradient Elution ◽  
Array Detector ◽  
Geographical Locations

To evaluate the quality of Salvia miltiorrhiza Bunge, high-performance liquid chromatography-diode array detector (HPLC/UV-PAD), near infrared (NIR) spectroscopy, and chemometrics were used to discriminate nine components of samples from four different geographical locations. HPLC was performed with a C18 (5 μm, 4.6 mm × 250 mm) column and 0.1% formic acid aqueous solution-acetonitrile with a gradient elution system. Orthogonal partial least squares discriminant analysis was used to identify the amounts of salvianolic acid B. NIR was used to distinguish rapidly S. miltiorrhiza Bunge samples from different geographical locations. In this assay, discriminant analysis was performed, and the accuracy was found to be 100%. The combination of these two methods can be used to quickly and accurately identify S. miltiorrhiza Bunge from different geographical locations.

Authentication of organic sugars by NIR spectroscopy and partial least squares with discriminant analysis

2020 ◽  
Vol 12 (5) ◽  
pp. 701-705 ◽  
Author(s):  
Vitória Maria Almeida Teodoro de Oliveira ◽  
Michel Rocha Baqueta ◽  
Paulo Henrique Março ◽  
Patrícia Valderrama
Keyword(s):  
Discriminant Analysis ◽  
Least Squares ◽  
Partial Least Squares ◽  
Near Infrared ◽  
Nir Spectroscopy

The present study evaluated the potential of near-infrared (NIR) spectroscopy coupled with partial least squares with discriminant analysis (PLS-DA) for the authentication of organic sugars.

scholarly journals Ability of NIR spectroscopy to predict meat chemical composition and quality – a review

2011 ◽  
Vol 49 (No. 11) ◽  
pp. 500-510 ◽  
Author(s):  
M. Prevolnik ◽  
M. Čandek-Potokar ◽  
D. Škorjanc
Keyword(s):  
Chemical Composition ◽  
Meat Quality ◽  
Quality Evaluation ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
The Other ◽  
Meat Composition ◽  
Feeding Regimes ◽  
Simultaneous Assessment

In contrast to conventional methods for the determination of meat chemical composition and quality, near infrared spectroscopy (NIRS) enables rapid, simple and simultaneous assessment of numerous meat properties. The present article is a review of published studies that examined the ability of NIRS to predict different meat properties. According to the published results, NIRS shows a great potential to replace the expensive and time-consuming chemical analysis of meat composition. On the other hand, NIRS is less accurate for predicting different attributes of meat quality. In view of meat quality evaluation, the use of NIRS appears more promising when categorizing meat into quality classes on the basis of meat quality traits for example discriminating between feeding regimes, discriminating fresh from frozen-thawed meat, discriminating strains, etc. The performance of NIRS to predict meat properties seems limited by the reliability of the method to which it is calibrated. Moreover, the use of NIRS may also be limited by the fact that it needs a laborious calibration for every purpose. In spite of that, NIRS is considered to be a very promising method for rapid meat evaluation.    

scholarly journals Use of near infrared spectroscopy and chemometrics to evaluate the shelf-life of cloudy sonicated apple juice

2019 ◽  
Vol 27 (1) ◽  
pp. 75-85 ◽  
Author(s):  
Lorenzo Serva ◽  
Stefania Balzan ◽  
Vittoria Bisutti ◽  
Filomena Montemurro ◽  
Giorgio Marchesini ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Discriminant Analysis ◽  
Shelf Life ◽  
Near Infrared Spectroscopy ◽  
Storage Time ◽  
Apple Juice ◽  
Near Infrared ◽  
Partial Least Square ◽  
Feasibility Trial ◽  
End Point

Fresh products, such as cloudy apple juice, could be preserved from early spoilage through the application of non-thermal processes such as sonication. However, shelf-life analyses based on microbiological and sensory evaluations are expensive and time consuming. Few studies have applied near infrared spectroscopy to evaluate the quality and decay of apple juices. Here, a feasibility trial was conducted to study the spectral behaviour at 1300–2500 nm combined with chemometric approaches. The shelf-life was monitored during two experiments, a challenge test with juices inoculated with spoilage yeasts (inoculated non-sonicated (INS)) and then submitted to sonication treatments (inoculated sonicated (IS)), and a storage test to evaluate the spoilage on non-inoculated juices (non-inoculated non-sonicated (NINS)) and sonicated non-inoculated juices (non-inoculated sonicated (NIS)). These experiments were investigated at six different refrigeration times 7, 14, 21, 28 and 60 days. Two functions were modelled to describe the behaviours of the first principal component according to the storage time. In agreement with a previous chemical and sensory evaluation, this approach allowed us to highlight shelf-life end points of 7 and 14 days for non-sonicated and sonicated samples, respectively. Three different models were evaluated for classification purposes: (1) sonicated versus non-treated samples, (2) end-point shelf-life evaluation at seven days for the NINS and INS juices and (3) end-point shelf-life discrimination at 14 days for IS and NIS samples. A partial least square-discriminant analysis enabled a group classification with accuracy values ranging from 0.63 to 1.00. The application of a variable importance in projection index to interpret the wavelengths of the spectral features suggests a contribution of organic acids and lipids to the prediction of decay. A canonical discriminant analysis provided a clearer separation of samples according to the storage time, especially in relation to the two time thresholds of 7 and 14 days.

scholarly journals Post-Mortem Chemical Changes in Poultry Breast Meat Monitored With Visible-Near Infrared Spectroscopy

2014 ◽  
Vol 3 (3) ◽  
pp. 57 ◽  
Author(s):  
Samantha A. Hawkins ◽  
Brian Bowker ◽  
Hong Zhuang ◽  
Gary Gamble ◽  
Ronald Holser
Keyword(s):  
Meat Quality ◽  
Structural Changes ◽  
Near Infrared ◽  
Muscle Protein ◽  
Visible Region ◽  
Bound Water ◽  
Nir Spectroscopy ◽  
Spectra Analysis ◽  
Freeze Dried ◽  
Postmortem Aging

<p>Chicken meat undergoes significant chemical and structural changes with postmortem time that influence meat quality characteristics. The objective of this study was to measure the visible-near infrared (vis-NIR) spectral differences in broiler breast fillets at 0.5, 4, 24, and 120 h postmortem. Muscle samples were flash frozen and freeze-dried prior to spectra analysis. In the visible region of the spectra (400-700 nm) changes in myoglobin protein peaks were observed with postmortem time. Freeze-drying muscle samples provided additional information from the NIR region of the spectra (800-2500 nm) on muscle protein changes during postmortem aging. Alterations to the b-sheet and a-helix structures of myofibrillar proteins and changes in the amount of bound water were observed in the NIR region with postmortem aging. Data from this study demonstrate that changes in breast fillets with postmortem time that are related to meat quality traits are detectable using vis-NIR spectroscopy.</p>

scholarly journals Discrimination of E uterpe oleracea  Mart. (Açaí) and E uterpe edulis  Mart. (Juçara) Intact Fruit Using Near-Infrared (NIR) Spectroscopy and Linear Discriminant Analysis

2015 ◽  
Vol 39 (6) ◽  
pp. 2856-2865 ◽  
Author(s):  
Yara Gurgel Dall' Acqua ◽  
Luis Carlos Cunha Júnior ◽  
Viviani Nardini ◽  
Valquira Garcia Lopes ◽  
José Dalton da Cruz Pessoa ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
Linear Discriminant Analysis ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Linear Discriminant

scholarly journals Rapid Recognition of Geoherbalism and Authenticity of a Chinese Herb by Data Fusion of Near-Infrared Spectroscopy (NIR) and Mid-Infrared (MIR) Spectroscopy Combined with Chemometrics

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Haiyan Fu ◽  
Qiong Shi ◽  
Liuna Wei ◽  
Lu Xu ◽  
Xiaoming Guo ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
Data Fusion ◽  
Near Infrared ◽  
Chinese Herb ◽  
Nir Spectroscopy ◽  
Chinese Herbs ◽  
Angelica Dahurica ◽  
Mid Infrared ◽  
Linear Discriminant ◽  
Mir Spectroscopy

Fourier transform near-infrared (NIR) spectroscopy and mid-infrared (MIR) spectroscopy play important roles in all fingerprint techniques because of their unique characteristics such as reliability, versatility, precision, and ease of measurement. In this paper, a supervised pattern recognition method based on the PLSDA algorithm by NIR and the NIR-MIR fusion spectra has been established to identify geoherbalism of Angelica dahurica from different regions and authenticity of Corydalis yanhusuo W. T. Wang. Comparing principle component analysis (PCA) cannot successfully identify geographical origins of Angelica dahurica. Linear discriminant analysis (LDA) also hardly distinguishes those origins. Furthermore, the PLSDA model based on the data fusion of NIR and IR was more accurate and efficient. But, the identification of authenticity of Corydalis yanhusuo W. T. Wang was still inaccurate in the PLSDA model. Consequently, data fusion of NIR-MIR original spectra combined with moving window partial least-squares discriminant analysis was firstly used and showed perfect properties on authenticity and adulteration discrimination of Corydalis yanhusuo W. T. Wang. It indicated that data fusion of NIR-MIR spectra combined with MWPLSDA could be considered as the promising tool for rapid discrimination of the geoherbalism and authenticity of more Chinese herbs in the future.

Comparative non-destructive classification of partial waxy wheats using near-infrared and Raman spectroscopy

2019 ◽  
Vol 70 (5) ◽  
pp. 437 ◽  
Author(s):  
Dongli Liu ◽  
Yixuan Wu ◽  
Zongmei Gao ◽  
Yong-Huan Yun
Keyword(s):  
Raman Spectroscopy ◽  
Discriminant Analysis ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Principal Component ◽  
Triticum Aestivum L ◽  
Waxy Wheat ◽  
Waxy Proteins ◽  
Sample Set

Waxy proteins play a key role in amylose synthesis in wheat. Eight lines of common wheat (Triticum aestivum L.) carrying mutations in the three homoeologous waxy loci, Wx-A1, Wx-B1 and Wx-D1, have been classified by near-infrared (NIR) and Raman spectroscopy combined with chemometrics. Sample spectra from wheat seeds were collected by using a NIR spectrometer in the wave rage 1600–2400 nm, and then Raman spectrometer in the wave range 700–2000 cm–1. All samples were split randomly into a calibration sample set containing 284 seeds (~35 seeds per line) and a validation sample set containing the remaining 92 seeds. Classification of these samples was undertaken by discriminant analysis combined with principal component analysis (PCA) based on the raw spectra processed by appropriate pre-treatment methods. The classification results by discriminant analysis indicated that the percentage of correctly identified samples by NIR spectroscopy was 84.2% for the calibration set and 84.8% for the validation set, and by Raman spectroscopy 94.4% and 94.6%, respectively. The results demonstrated that Raman spectroscopy combined with chemometrics as a rapid method is superior to NIR spectroscopy in classifying eight partial waxy wheat lines with different waxy proteins.

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