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 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 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. &nbsp; &nbsp;

scholarly journals Predicting terpene content in dried conifer shoots using near infrared spectroscopy

2020 ◽  
Vol 28 (5-6) ◽  
pp. 308-314
Author(s):  
Emilie Champagne ◽  
Michaël Bonin ◽  
Alejandro A Royo ◽  
Jean-Pierre Tremblay ◽  
Patricia Raymond
Keyword(s):  
Gas Chromatography ◽  
Picea Glauca ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Calibration Method ◽  
Wide Distribution ◽  
Coefficient Of Determination ◽  
Calibration Model ◽  
Freeze Dried ◽  
Terpene Content

Terpenes are phytochemicals found in multiple plant genera, especially aromatic herbs and conifers. Terpene content quantification is costly and complex, requiring the extraction of oil content and gas chromatography analyses. Near infrared (NIR) spectroscopy could provide an alternative quantitative method, especially if calibration can be developed with the spectra of dried plant material, which are easier and faster to acquire than oil-based spectra. Here, multispecies NIR spectroscopy calibrations were developed for total terpene content (mono- and sesquiterpenes) and for specific terpenes (α-pinene, β-pinene and myrcene) with five conifers species ( Picea glauca, Picea rubens, Pinus resinosa, Pinus strobus and Thuja occidentalis). The terpene content of fresh shoot samples was quantified with gas chromatography. The NIR spectra were measured on freeze-dried samples (n = 137). Using a subset of the samples, modified partial least squares regressions of total terpene and the three individual terpenes content were generated as a functions of the NIR spectra. The standard errors of the internal cross-validations (values between 0.25 and 2.28) and the ratio of prediction to deviation ratios (RPD values between 2.20 and 2.38) indicate that all calibrations have similar accuracy. The independent validations, however, suggest that the calibrations for total terpene and α-pinene content are more accurate (respective coefficient of determination: r2 = 0.85 and 0.82). In contrast, calibrations for β-pinene and myrcene had a low accuracy (respectively: r2 = 0.62 and 0.08), potentially because of the low concentration of these terpenes in the species studied. The calibration model fits (i.e., r2) are comparable to previously published calibration using the spectra of dried shoot samples and demonstrate the potential of this method for terpenes in conifer samples. The calibration method used could be useful in several other domains (e.g. seedling breeding program, industrial), because of the wide distribution of terpenes and especially of pinenes.

Lipid Analysis by near Infrared Spectroscopy to Evaluate Inhibitory Effects of Swine Waste Compost on Plant Growth

2008 ◽  
Vol 16 (5) ◽  
pp. 481-486 ◽  
Author(s):  
Takayuki Fujiwara ◽  
Keiichi Murakami
Keyword(s):  
Plant Growth ◽  
Lipid Content ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Swine Waste ◽  
Inhibitory Effects ◽  
Absorption Bands ◽  
Freeze Dried ◽  
Calibration Equations

The lipid content of swine manure decreases during the process of composting, and inhibitory effects of compost on root growth in germination tests are strongly correlated to lipid content. Therefore, we tested whether the determination of the lipid content of swine waste compost by near infrared (NIR) spectroscopy provided a measure by which the degree of inhibition of plant growth by immature compost could be predicted. Reflectance spectra of untreated compost samples, as well as freeze-dried and milled samples, were taken using a scanning monochromator. Second derivative spectra from 700 nm to 2500 nm and multiple regression analysis were used to develop calibration equations for lipid content and moisture. A pronounced absorption peak of lipid was found at 2310 nm, attributable to the absorption bands of the CH2 stretching–bending combination. However, calibration equations containing this absorption band were inappropriate for lipid determination, because sawdust and rice husk, which were added to the compost, influenced the spectra in this band. The standard error of prediction ( SEP) of the best calibrations for lipids in dry and untreated samples was 6.0 g kg−1 and 3.2 g kg−1, while the ratios of the standard deviation and the range in the prediction set to SEP (RPD and RER) were 5.5 and 2.8, and 13.5 and 5.0, respectively. The main wavelengths of these calibration equations were 1700 nm for dry samples and 1764 nm for untreated samples, which were attributed to the absorption bands of the CH2 stretching first overtone. In conclusion, the determination of lipid content in dry compost samples by NIR spectroscopy provided an indirect estimate of the maturity of swine waste compost. Moreover, NIR spectroscopy was found useful for the rough assessment of the maturity of untreated swine waste compost.

Effect of Random Noise on the Performance of NIR Calibrations

1998 ◽  
Vol 6 (1) ◽  
pp. 77-87 ◽  
Author(s):  
Jing Lu ◽  
W.F. McClure ◽  
F.E. Barton ◽  
D.S. Himmelsbach
Keyword(s):  
Least Squares ◽  
Near Infrared ◽  
Multivariate Calibration ◽  
Simple Procedure ◽  
Random Noise ◽  
Nir Spectroscopy ◽  
Principal Component ◽  
Optical Data ◽  
Spectra Analysis ◽  
Calibration Methods

The proliferation of applications for near infrared (NIR) spectroscopy has been fostered by advances in instrumentation and statistics. NIR analytical instrumentation is becoming more stable and reliable. Chemometrics is playing an important role in qualitative and quantitative NIR spectra analysis. The objective of this study was to evaluate the performances of four commonly used calibration models: (1) stepwise multiple linear regression (SMLR); (2) classical least-squares (CLS); (3) principal component regression (PCR); and (4) partial least-squares (PLS) in NIR spectroscopy analysis when random noise is present in the optical data. A conceptually simple procedure for comparing the performance of the four calibration methods in the presence of different levels of random noise in spectra data has been introduced here. This procedure, using the computer simulation data and real spectra of tobacco, has provided useful information for understanding the effects of random noise on the performance of multivariate calibration methods. Both numerical and graphical results will be shown.

scholarly journals Screening of grated cheese authenticity by nir spectroscopy

2013 ◽  
Vol 44 (2s) ◽  
Author(s):  
Chiara Cevoli ◽  
Angelo Fabbri ◽  
Alessandro Gori ◽  
Maria Fiorenza Caboni ◽  
Adriano Guarnieri
Keyword(s):  
Near Infrared ◽  
Nir Spectroscopy ◽  
Principal Component ◽  
Classification Performance ◽  
Integrating Sphere ◽  
Least Squares Regression ◽  
Test Set ◽  
Spectra Analysis ◽  
Protected Designation Of Origin ◽  
Parmigiano Reggiano

Parmigiano–Reggiano (PR) cheese is one of the oldest traditional cheeses produced in Europe, and it is still one of the most valuable Protected Designation of Origin (PDO) cheeses of Italy. The denomination of origin is extended to the grated cheese when manufactured exclusively from whole Parmigiano-Reggiano cheese wheels that respond to the production standard. The grated cheese must be matured for a period of at least 12 months and characterized by a rind content not over 18%. In this investigation the potential of near infrared spectroscopy (NIR), coupled to different statistical methods, were used to estimate the authenticity of grated Parmigiano Reggiano cheese PDO. Cheese samples were classified as: compliance PR, competitors, non-compliance PR (defected PR), and PR with rind content greater then 18%. NIR spectra were obtained using a spectrophotometer Vector 22/N (Bruker Optics, Milan, Italy) in the diffuse reflectance mode. Instrument was equipped with a rotating integrating sphere. Principal Component Analysis (PCA) was conducted for an explorative spectra analysis, while the Artificial Neural Networks (ANN) were used to classify spectra, according to different cheese categories. Subsequently the rind percentage and month of ripening were estimated by a Partial Least Squares regression (PLS). Score plots of the PCA show a clear separation between compliance PR samples and the rest of the sample was observed. Competitors samples and the defected PR samples were grouped together. The classification performance for all sample classes, obtained by ANN analysis, was higher of 90%, in test set validation. Rind content and month of ripening were predicted by PLS a with a determination coefficient greater then 0.95 (test set). These results showed that the method can be suitable for a fast screening of grated cheese authenticity.

scholarly journals Interactions of Linearly Polarized and Unpolarized Light on Kiwifruit Using Aquaphotomics

Molecules ◽  
2022 ◽  
Vol 27 (2) ◽  
pp. 494
Author(s):  
Damenraj Rajkumar ◽  
Rainer Künnemeyer ◽  
Harpreet Kaur ◽  
Jevon Longdell ◽  
Andrew McGlone
Keyword(s):  
Near Infrared ◽  
Polarized Light ◽  
Bound Water ◽  
Free Water ◽  
Nir Spectroscopy ◽  
Soluble Solids ◽  
Unpolarized Light ◽  
Standard Normal Variate ◽  
Linearly Polarized ◽  
Solids Content

Near infrared (NIR) spectroscopy is an important tool for predicting the internal qualities of fruits. Using aquaphotomics, spectral changes between linearly polarized and unpolarized light were assessed on 200 commercially grown yellow-fleshed kiwifruit (Actinidia chinensis var. chinensis ‘Zesy002’). Measurements were performed on different configurations of unpeeled (intact) and peeled (cut) kiwifruit using a commercial handheld NIR instrument. Absorbance after applying standard normal variate (SNV) and second derivative Savitzky–Golay filters produced different spectral features for all configurations. An aquagram depicting all configurations suggests that linearly polarized light activated more free water states and unpolarized light activated more bound water states. At depth (≥1 mm), after several scattering events, all radiation is expected to be fully depolarized and interactions for incident polarized or unpolarized light will be similar, so any observed differences are attributable to the surface layers of the fruit. Aquagrams generated in terms of the fruit soluble solids content (SSC) were similar for all configurations, suggesting the SSC in fruit is not a contributing factor here.

scholarly journals Assessment of Structural Differences between Water-Extracted and Non-Extracted Hydro-Thermally Treated Spruce Wood by NIR Spectroscopy

Forests ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1689
Author(s):  
Carmen-Mihaela Popescu ◽  
Nanami Zeniya ◽  
Kaoru Endo ◽  
Takuma Genkawa ◽  
Miyuki Matsuo-Ueda ◽  
...  
Keyword(s):  
Thermal Treatment ◽  
Relative Humidity ◽  
Structural Changes ◽  
Near Infrared ◽  
Treatment Time ◽  
Nir Spectroscopy ◽  
Principal Component ◽  
Correlation Spectroscopy ◽  
Spruce Wood ◽  
Treatment Conditions

Sitka spruce wood samples were subjected to different conditions of hydro-thermal treatment by varying the relative humidity (RH) and period of exposure at a constant temperature of 120 °C. Near infrared (NIR) spectroscopy, principal component analysis (PCA) and two dimensional correlation spectroscopy (2D-COS) were employed to examine the structural changes which occur in the wood samples during the applied treatment conditions and to quantify the differences between non-extracted and water-extracted wood specimens after the treatment. Modifications were dependent on the amount of water molecules present the medium and also on treatment time. Higher variations were observed for samples treated at higher RH values and for longer periods. At the same time, it was also observed that during the hydro-thermal treatment a high amount of extractives remain in the wood structure, extractives which vary in quantity and composition. PCA and 2D-COS made it possible to discriminate modifications in the wood samples according to treatment time and relative humidity. Non-extracted and water-extracted samples were also examined to identify the sequential order of band modification.

scholarly journals Instrumental Procedures for the Evaluation of Juiciness in Peach and Nectarine Cultivars for Fresh Consumption

Agronomy ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 152 ◽  
Author(s):  
Paola Baltazar ◽  
Eva Cristina Correa ◽  
Belén Diezma
Keyword(s):  
Structural Changes ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Stone Fruits ◽  
Confined Compression ◽  
Decision Tools ◽  
Non Invasive ◽  
Mechanical Procedure

There is growing interest within the peach and nectarine markets in obtaining and selling ready-to-eat fruits. For this, pre-ripening protocols are being applied, which do not always result in sufficiently juicy fruits. Therefore, the aim of this study is the development of objective instrumental procedures for quantification of the juiciness attributes of these fruits. In this work, we evaluated the juiciness of more than 2000 fruits belonging to 20 of the varieties of greatest interest in the southeast of Spain. An instrumental mechanical procedure based on the confined compression of a pulp specimen of known volume was designed and optimized. Instrumental juiciness was defined as the wet area (cm2) on an absorbent paper located under the compression probe. This test allowed for the defining of objective thresholds for the identification of juicy fruits; 90% of the fruits with areas higher than 5.4 cm2 were considered to be juicy. Complementarily, non-invasive supervision by near-infrared (NIR) spectroscopy, based on pulp structural changes during ripening, allowed for estimation of the instrumental juiciness with coefficients of correlation above 0.83. The results of these instrumental procedures contribute to supporting decision tools in the logistics chain of stone fruits.

scholarly journals Food Authentication: Truffle (Tuber spp.) Species Differentiation by FT-NIR and Chemometrics

Foods ◽  
2020 ◽  
Vol 9 (7) ◽  
pp. 922 ◽  
Author(s):  
Torben Segelke ◽  
Stefanie Schelm ◽  
Christian Ahlers ◽  
Markus Fischer
Keyword(s):  
Near Infrared ◽  
Nir Spectroscopy ◽  
Tuber Melanosporum ◽  
Species Differentiation ◽  
Tuber Aestivum ◽  
Food Authentication ◽  
Food Fraud ◽  
Tuber Borchii ◽  
Tuber Magnatum ◽  
Freeze Dried

Truffles are certainly the most expensive mushrooms; the price depends primarily on the species and secondly on the origin. Because of the price differences for the truffle species, food fraud is likely to occur, and the visual differentiation is difficult within the group of white and within the group of black truffles. Thus, the aim of this study was to develop a reliable method for the authentication of five commercially relevant truffle species via Fourier transform near-infrared (FT-NIR) spectroscopy as an easy to handle approach combined with chemometrics. NIR-data from 75 freeze-dried fruiting bodies were recorded. Various spectra pre-processing techniques and classification methods were compared and validated using nested cross-validation. For the white truffle species, the most expensive Tuber magnatum could be differentiated with an accuracy of 100% from Tuber borchii. Regarding the black truffle species, the relatively expensive Tuber melanosporum could be distinguished from Tuber aestivum and the Chinese truffles with an accuracy of 99%. Since the most expensive Italian Tuber magnatum is highly prone to fraud, the origin was investigated and Italian T. magnatum truffles could be differentiated from non-Italian T. magnatum truffles by 83%. Our results demonstrate the potential of FT-NIR spectroscopy for the authentication of truffle species.

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