scholarly journals Spectra selection methods: A novel optimization way for treating dynamic spectra and in-line near infrared modeling

2020 ◽  
Vol 13 (04) ◽  
pp. 2050015
Author(s):  
Haiyan Wang ◽  
Ronghua Liu ◽  
Lei Nie ◽  
Dongbo Xu ◽  
Wenping Yin ◽  
...  
Keyword(s):  
Moisture Content ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Selection Methods ◽  
Expansion Chamber ◽  
Distance Method ◽  
Modeling Process ◽  
Time Determination ◽  
Cosine Distance

Near infrared (NIR) spectroscopy is now widely used in fluidized bed granulation. However, there are still some demerits that should be overcome in practice. Valid spectra selection during modeling process is now a hard nut to crack. In this study, a novel NIR sensor and a cosine distance method were introduced to solve this problem in order to make the fluidized process into “visualization”. A NIR sensor was fixed on the side of the expansion chamber to acquire the NIR spectra. Then valid spectra were selected based on a cosine distance method to reduce the influence of dynamic disturbances. Finally, spectral pretreatment and wavelength selection methods were investigated to establish partial least squares (PLS) models to monitor the moisture content. The results showed that the root mean square error of prediction (RMSEP) was 0.124% for moisture content model, which was much lower than that without valid spectra selection treatment. All results demonstrated that with the help of valid spectra selection treatment, NIR sensor could be used for real-time determination of critical quality attributes (CQAs) more accurately. It makes the manufacturing easier to understand than the process parameter control.

Determination of Hemoglobin in Human Whole Blood Using Near-Infrared Spectroscopy with Stability

2012 ◽  
Vol 566 ◽  
pp. 660-663
Author(s):  
Zhen Yao Liu ◽  
Tao Pan
Keyword(s):  
Whole Blood ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Short Wave ◽  
Blood Samples ◽  
Human Whole Blood ◽  
Modeling Process ◽  
High Prediction ◽  
Validation Set

Near-infrared (NIR) spectroscopy combined with the partial least-squares (PLS) regression was successfully applied for the rapid quantitative analysis of hemoglobin (HGB) based on human whole blood samples. Based on the varied divisions for the calibration and prediction sets, an appropriate waveband with stability was selected through a rigorous modeling process. Among 215 samples, 80 were randomly selected as the validation set. The remaining 135 samples were divided into the calibration set (80 samples) and the prediction set (55 samples) for a total of 200 times with certain similarities. The selected waveband was the combination of visible and short-wave NIR region at 400 nm to 1100 nm. The optimal PLS factor was 8, the modeling effect M-SEPAve, M-RP,Ave, M-SEPStd and M-RP,Std were 2.88gL-1, 0.986, 0.34gL-1 and 0.003, respectively, the validation effect V-SEP, V-RP and V-RSEP were 2.92gL-1, 0.986 and 2.26%, respectively. The results indicated that the method has high prediction precision and well stability. It is hopeful to be applied to clinic.

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.

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.

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.    

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