scholarly journals Analysis of ewe’s milk by FT Near Infrared spectroscopy: measurement of samples on Petri dishes in reflectance mode

2006 ◽  
Vol 54 (2) ◽  
pp. 131-138 ◽  
Author(s):  
Květoslava Šustová ◽  
Jan Kuchtík ◽  
Stanislav Kráčmar
Keyword(s):  
Dry Matter ◽  
Near Infrared ◽  
Correlation Coefficients ◽  
Nir Spectroscopy ◽  
Urea Nitrogen ◽  
Ewe's Milk ◽  
Petri Dishes ◽  
True Protein ◽  
Metallic Mirror

Our work deals with a possibility of determination of basic composition (dry matter, fat, protein, casein, lactose and urea nitrogen) of ewe’s milk and colostrum by FT NIR spectroscopy. Samples of milk were warmed to 40 °C, agitated, cooled to 20 °C, transferred into Petri dishes and analysed by reference methods and by FT NIR in reflectance mode. The measured area was spaced by a metallic mirror. Statistically significant differences between the reference values and the calculated values of NIR were not found (p=0.05). Results of calibration for ewe’s milk determined the highest correlation coefficients: dry matter 0.983, fat 0.989, true protein 0.997, casein 0.977, lactose 0.980 and urea nitrogen 0.973. The study showed that NIRS method, when samples of milk are measured on Petri dishes, is a useful technique for the prediction of dry matter, fat, protein and casein in ewe’s milk.

scholarly journals Application of FT near spectroscopy for determination of true protein and casein in milk

2008 ◽  
Vol 52 (No. 9) ◽  
pp. 284-291 ◽  
Author(s):  
K. Šustová ◽  
J. Růžičková ◽  
J. Kuchtík
Keyword(s):  
Cross Validation ◽  
Reference Data ◽  
Correlation Coefficients ◽  
Nir Spectroscopy ◽  
Rapid Analysis ◽  
Validation Method ◽  
Goat’S Milk ◽  
Goat's Milk ◽  
True Protein

Our study deals with a possibility of determining true protein and casein in cow’s, ewe’s and goat’s milk and in ewe’s colostrums by FT NIR spectroscopy. Samples of milk were analysed by FT NIR in the reflectance mode with the transflectance cuvette. The values of correlation coefficients of calibration were as follows: cow’s protein 0.943; cow’s casein 0.964; ewe’s protein 0.997; ewe’s casein 0.977; goat’s protein 0.989; goat’s casein 0.890; ewe’s colostrum protein 0.983. Calibration was tested using the same set of samples by the cross validation method. The values of correlation coefficients of validation were as follows: cow’s protein 0.923; cow’s casein 0.910; ewe’s protein 0.994; ewe’s casein 0.963; goat’s protein 0.972; goat’s casein 0.814; ewe’s colostrum protein 0.871. The NIRS results were compared with reference data and no significant differences between them were found (<i>P</i> = 0.05). Results of this study indicate that FT NIR spectroscopy can be used for a rapid analysis of protein and casein in cow’s, ewe’s and goat’s milk and ewe’s colostrum.

Waveband Selection for NIR Spectroscopic Analysis of Zn2+ in Soil

2013 ◽  
Vol 365-366 ◽  
pp. 737-740
Author(s):  
Li Jun Yao ◽  
Jie Mei Chen ◽  
Tao Pan
Keyword(s):  
Root Mean Square Error ◽  
Near Infrared ◽  
Spectroscopic Analysis ◽  
Correlation Coefficients ◽  
Nir Spectroscopy ◽  
Optimal Number ◽  
Moving Window ◽  
Mean Square ◽  
Selection For

Near-infrared (NIR) spectroscopy combined with moving window partial least squares (MWPLS) method was successfully applied to the waveband selection for the rapid chemical-free determination of Zn2+ in soil. Based on randomness and similarity, an effective approach was performed to obtain objective and practical models. The optimal MWPLS waveband was 1136-1252 nm, and the corresponding optimal number of PLS factors was 6. The validation root mean square error (V-SEP) and validation correlation coefficients (V-RP) of prediction were 15.658 mg kg-1 and 0.925, respectively. The Zn2+ prediction values of the validation samples are close to the measured values. The results provided a reliable NIR model and can serve as valuable references for designing the dedicated spectroscopic instruments.

scholarly journals Pseudo-Univariate Calibration Based on NIR Spectroscopy in the Determination of Anthocyanins and Antioxidant Activity in Grape Juices

2021 ◽  
Author(s):  
Karla Beltrame ◽  
Thays Gonçalves ◽  
Paulo Março ◽  
Sandra Gomes ◽  
Makoto Matsushita ◽  
...  
Keyword(s):  
Antioxidant Activity ◽  
Near Infrared ◽  
Correlation Coefficients ◽  
Nir Spectroscopy ◽  
Grape Juice ◽  
Calibration Models ◽  
Total Anthocyanins ◽  
Alternative Methodology ◽  
Grape Juices

This work shows an alternative methodology based on a portable near-infrared (NIR) spectroscopy coupled to independent components analysis (ICA) in a pseudo-univariate calibration way to determine total anthocyanins (TA) concentration and antioxidant activity (AA) in whole grape juice. To this, the scores proportions more related to TA and AA were plotted against TA and AA obtained by its respective references methodology to build pseudo-univariate calibration models with correlation coefficients of 0.9699 and 0.9814, respectively. From the results, it is possible the suggestion that NIR spectra coupled to ICA enable to overcome interferences using first-order data and work properly when there is enough selectivity for the analyte profile in the sample data.

scholarly journals Determination of selected parameters of quality of the dairy products by NIR spectroscopy

2011 ◽  
Vol 24 (No. 6) ◽  
pp. 255-260 ◽  
Author(s):  
J. Růžičková ◽  
K. Šustová
Keyword(s):  
Dairy Products ◽  
Near Infrared ◽  
Correlation Coefficients ◽  
Nir Spectroscopy ◽  
Integrating Sphere ◽  
Calibration Model ◽  
Titrable Acidity ◽  
Non Destructive

The possibility of the application of near-infrared spectroscopy to the analysis of the selected parameters of quality of the dairy products was followed. The contents of solids and fat, as well as pH in yoghurts (also the titrable acidity), milk semolina, and milk rice were determined. The samples were analysed by reference methods and by FT NIR spectroscope at integrating sphere within reflectance mode in the wavelength range of 10 000&ndash;4&nbsp;000 cm<sup>&ndash;1 </sup>with 100&nbsp;scans. To develop the calibration model for the components examined, the partial least squares (PLS) was used and this model was validated by full cross validation. The highest correlation coefficients were found with yoghurt: 0.998 (solids), 0.989 (fat), 0.875 (pH) and 0.989 (titrable acidity), with milk semolina: 0.967 (solids), 0.983 (fat) and 0.992 (pH), and with milk rice: 0.987 (solids), 0.990 (fat) and 0.852 (pH). The results of this study showed the availability of NIR spectroscopy for a quick and non-destructive analysis of the dairy products. &nbsp;

Near Infrared Reflectance Spectroscopic Determination of Protein Nitrogen in Plant Tissue

1984 ◽  
Vol 67 (3) ◽  
pp. 506-509
Author(s):  
Robert A Isaac ◽  
William C Johnson
Keyword(s):  
Plant Tissue ◽  
Near Infrared ◽  
Correlation Coefficients ◽  
Leaf Tissue ◽  
Nir Spectroscopy ◽  
Nondestructive Method ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance ◽  
Protein Nitrogen

Abstract A rapid, nondestructive method is described for the determination of protein nitrogen in plant tissue, using near infrared reflectance (NIR) spectroscopy. Procedures for instrument calibration are discussed. Comparisons between Kjeldahl nitrogen and NIR nitrogen are made for corn leaf tissue from Georgia and Indiana. Multiple correlation coefficients for other plant tissues such as peanuts, soybean, wheat, pecan, bermuda grass, and bent grass are also shown.

scholarly journals Analysis of goat’s milk by FT Near Infrared spectroscopy

2007 ◽  
Vol 55 (4) ◽  
pp. 103-110
Author(s):  
Květoslava Šustová ◽  
Jan Kuchtík
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Milk Fat ◽  
Near Infrared ◽  
Somatic Cells ◽  
Correlation Coefficients ◽  
Goat’S Milk ◽  
Petri Dishes ◽  
Goat's Milk ◽  
True Protein

Our work deals with a possibility of determining basic composition (fat, true protein, casein, lactose and somatic cells) of goat’s milk Fourier transform near-infrared spectroscopy (FT NIR). Samples of milk were warmed to 40 °C, agitated, cooled to 20 °C, transferred to Petri dishes and analysed by reference methods and by FT NIR in reflectance mode. The measured area was spaced by a metallic mirror. Statistically significant differences between the reference values and the calculated values of NIR were not found (p = 0.05). Very high correlation coefficients were determined for goat’s milk: fat 0.907, protein 0.989, casein 0.890 and lactose 0.981. The study showed that NIRS method, when samples of milk are measured on Petri dishes, is a useful technique for the prediction of fat, true protein, casein and lactose in goat’s milk. Results of calibration for somatic cells are not accurate (correlation coefficients of calibration 0,885 and correlation coefficients of validation 0.566).

scholarly journals Determination of the composition of multilayer plastic packaging with NIR spectroscopy

Detritus ◽  
2020 ◽  
pp. 62-66
Author(s):  
Xiaozheng Chen ◽  
Nils Kroell ◽  
Alexander Feil ◽  
Thomas Pretz
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared ◽  
State Of The Art ◽  
Nir Spectroscopy ◽  
Waste Recycling ◽  
Point Of View ◽  
Plastic Packaging ◽  
Post Industrial ◽  
Detection And Separation

In food and medical packaging, multiple layers of different polymers are combined in order to achieve optimal functional properties for various applications. Flexible multilayer plastic packaging achieves a reduction in weight compared to other packaging products with the same function, saving material and in transportation costs. Recycling of post-industrial multilayer packaging was achieved by some companies, but the available technologies are limited to specific polymer types. For post-consumer waste, recycling of multilayer packaging has not been achieved yet. One of the main challenges in plastic sorting is that the detection and separation of multilayer packaging from other materials is not possible yet. In this study, the possibility to detect and sort flexible multilayer plastic packaging was investigated with near-infrared spectroscopy, which is the state-of-the-art technology for plastic sorting. The results show that from a detection and classification point of view, sorting of monolayer, two- and three-layers samples under laboratory conditions is possible. According to the captured data, the sequence of layers has little influence on the spectra. In case of glossy samples, the spectra are influenced by printed surfaces. With an increase in thickness, the spectra get more characteristic, which makes the classification easier. Our results indicate that the sorting of post-consumer multilayer plastic packaging by main composition is theoretically achievable.

Application of near Infrared Spectroscopy On-Combine in Corn Grain Breeding

2005 ◽  
Vol 13 (2) ◽  
pp. 69-75 ◽  
Author(s):  
Roland Welle ◽  
Willi Greten ◽  
Thomas Müller ◽  
Gary Weber ◽  
Hartwig Wehrmann
Keyword(s):  
Grain Yield ◽  
Dry Matter ◽  
Near Infrared ◽  
Reference Method ◽  
Nir Spectroscopy ◽  
Coefficient Of Determination ◽  
Successful Implementation ◽  
Grain Moisture ◽  
Yield Determination ◽  
Corn Grain

Improving maize ( Zea mays L.) grain yield and agronomic properties are major goals for corn breeders in northern Europe. In order to facilitate field grain yield determination we measured corn grain moisture content with near infrared (NIR) spectroscopy directly on a harvesting machine. NIR spectroscopy, in combination with harvesting, significantly improved quality and speed of yield determination within the very narrow harvest time window. Moisture calibrations were developed with 2117 samples from the 2001 to 2003 crop seasons using six diode array spectrometers mounted on combines. These models were derived from databases containing spectra from all instruments. Spectrometer-specific calibrations cannot be used to predict samples measured on other instruments of the same type. Standard error of cross-validation ( SECV) and coefficient of determination ( R2) were 0.56 and 0.99%, respectively. Moisture standard errors of prediction ( SEPs) for the six instruments, using varying independent sample sets from the 2004 harvest, ranged between 0.59% and 0.99% with R2 values between 0.92 to 0.98. The six instruments produced the same dry matter predictions on a common sample set as indicated by high R2 and low biases among them, hence there was no need to apply specific standardisation algorithms. Moisture NIR spectroscopy determinations were significantly more precise than those obtained using the reference method. Analysis of variance revealed low least significant differences and high heritabilities. High precision and heritability demonstrate successful implementation of on-combine NIR spectroscopy for routine dry matter (yield) measurements.

scholarly journals Determination of Cell Abundances and Paralytic Shellfish Toxins in Cultures of the Dinoflagellate Gymnodinium catenatum by Fourier Transform Near Infrared Spectroscopy

2018 ◽  
Vol 6 (4) ◽  
pp. 147 ◽  
Author(s):  
Marta Lopes ◽  
Ana Amorim ◽  
Cecília Calado ◽  
Pedro Reis Costa
Keyword(s):  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Near Infrared ◽  
Monitoring Program ◽  
Nir Spectroscopy ◽  
Shellfish Poisoning ◽  
Toxic Algae ◽  
Paralytic Shellfish ◽  
Gymnodinium Catenatum

Harmful algal blooms are responsible worldwide for the contamination of fishery resources, with potential impacts on seafood safety and public health. Most coastal countries rely on an intense monitoring program for the surveillance of toxic algae occurrence and shellfish contamination. The present study investigates the use of near infrared (NIR) spectroscopy for the rapid in situ determination of cell concentrations of toxic algae in seawater. The paralytic shellfish poisoning (PSP) toxin-producing dinoflagellate Gymnodinium catenatum was selected for this study. The spectral modeling by partial least squares (PLS) regression based on the recorded NIR spectra enabled the building of highly accurate (R2 = 0.92) models for cell abundance. The models also provided a good correlation between toxins measured by the conventional methods (high-performance liquid chromatography with fluorescence detection (HPLC-FLD)) and the levels predicted by the PLS/NIR models. This study represents the first necessary step in investigating the potential of application of NIR spectroscopy for algae bloom detection and alerting.

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