scholarly journals Near-Infrared Spectroscopy as a classification tool for agraz (Vaccinium meridionale Swartz)

DYNA ◽  
2020 ◽  
Vol 87 (213) ◽  
pp. 17-21
Author(s):  
Nathalia María Forero-Cabrera ◽  
Carolina Maria Sánchez-Sáenz
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Agricultural Products ◽  
Maturity Stage ◽  
New Techniques ◽  
Classification Tool ◽  
Suitable Technique

The importance of the selection and classification processes in the industry of agricultural products and the increase in the production of fruits make necessary the development and implementation of new techniques to efficiently perform these tasks. Techniques such as NIR spectroscopy have proved to have potential to accomplish this purpose. The aim of this research was to evaluate the performance of near infrared spectroscopy as a classification tool for agraz (Vaccinium meridionale Swartz), according to its state of maturity. In order to obtainthe classification models, the PCA and SIMCA methods were used. Results were obtained close to 100% accuracy in the classification for maturity stages 4 and 5 and between 81 and 90% for maturity stage 3. The NIR spectroscopy appears as a suitable technique for the classification of fruits of agraz according to their state of maturity.

Evaluation of chemometric methodologies for the classification of Coffea canephora cultivars via FT-NIR spectroscopy and direct sample analysis

2017 ◽  
Vol 9 (29) ◽  
pp. 4255-4260 ◽  
Author(s):  
Aderval S. Luna ◽  
Arnaldo P. da Silva ◽  
Enrique A. Alves ◽  
Rodrigo B. Rocha ◽  
Igor C. A. Lima ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Coffea Canephora ◽  
Sample Analysis ◽  
Chemometric Tools ◽  
Direct Sample

This work presents a study of chemometric tools for the classification of Coffea canephora (whole beans) cultivars via in situ direct sample analysis using near-infrared spectroscopy (NIR).

scholarly journals Textile Recognition and Sorting for Recycling at an Automated Line Using Near Infrared Spectroscopy

Recycling ◽  
2021 ◽  
Vol 6 (1) ◽  
pp. 11
Author(s):  
Kirsti Cura ◽  
Niko Rintala ◽  
Taina Kamppuri ◽  
Eetta Saarimäki ◽  
Pirjo Heikkilä
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Automated Recognition ◽  
Textile Materials ◽  
Input Material ◽  
Adequate Quality ◽  
Automated Line

In order to add value to recycled textile material and to guarantee that the input material for recycling processes is of adequate quality, it is essential to be able to accurately recognise and sort items according to their material content. Therefore, there is a need for an economically viable and effective way to recognise and sort textile materials. Automated recognition and sorting lines provide a method for ensuring better quality of the fractions being recycled and thus enhance the availability of such fractions for recycling. The aim of this study was to deepen the understanding of NIR spectroscopy technology in the recognition of textile materials by studying the effects of structural fabric properties on the recognition. The identified properties of fabrics that led non-matching recognition were coating and finishing that lead different recognition of the material depending on the side facing the NIR analyser. In addition, very thin fabrics allowed NIRS to penetrate through the fabric and resulted in the non-matching recognition. Additionally, ageing was found to cause such chemical changes, especially in the spectra of cotton, that hampered the recognition.

Application of Near-Infrared Spectroscopy for the Classification of Fresh Pork Quality in Cooked Ham Production

2015 ◽  
Vol 8 (12) ◽  
pp. 2383-2391 ◽  
Author(s):  
Ellen Neyrinck ◽  
Stefaan De Smet ◽  
Liesbeth Vermeulen ◽  
Danny Telleir ◽  
Stefaan Lescouhier ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Pork Quality ◽  
Cooked Ham

Measurement of the Ratio of Tea Polyphenols to Amino Acids in Green Tea Infusion Based on near Infrared Spectroscopy

2011 ◽  
Vol 301-303 ◽  
pp. 1093-1097 ◽  
Author(s):  
Shi Rong Ai ◽  
Rui Mei Wu ◽  
Lin Yuan Yan ◽  
Yan Hong Wu
Keyword(s):  
Amino Acids ◽  
Infrared Spectroscopy ◽  
Correlation Coefficient ◽  
Green Tea ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Tea Polyphenols ◽  
Strong Absorption ◽  
Tea Infusion

This study attempted the feasibility to determine the ratio of tea polyphenols to amino acids in green tea infusion using near infrared (NIR) spectroscopy combined with synergy interval PLS (siPLS) algorithms. First, SNV was used to preprocess the original spectra of tea infusion; then, siPLS was used to select the efficient spectra regions from the preprocessed spectra. Experimental results showed that the spectra regions [7 8 18] were selected, which were out of the strong absorption of H2O. The optimal PLS model was developed with the selected regions when 6 PCs components were contained. The RMSEP value was equal to 0.316 and the correlation coefficient (R) was equal to 0.8727 in prediction set. The results demonstrated that NIR can be successfully used to determinate the ration of tea polyphenols to amino acids in green tea infusion.

Geographical Classification of Honey Samples by Near-Infrared Spectroscopy: A Feasibility Study

2007 ◽  
Vol 55 (22) ◽  
pp. 9128-9134 ◽  
Author(s):  
Tony Woodcock ◽  
Gerard Downey ◽  
J. Daniel Kelly ◽  
Colm O’Donnell
Keyword(s):  
Infrared Spectroscopy ◽  
Feasibility Study ◽  
Near Infrared Spectroscopy ◽  
Near Infrared

Evaluation and classification of eucalypt charcoal quality by near infrared spectroscopy

2018 ◽  
Vol 112 ◽  
pp. 85-92 ◽  
Author(s):  
Lívia Ribeiro Costa ◽  
Paulo Fernando Trugilho ◽  
Paulo Ricardo Gherardi Hein
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared

scholarly journals Functional Near-Infrared Spectroscopy for the Classification of Motor-Related Brain Activity on the Sensor-Level

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2362 ◽  
Author(s):  
Alexander E. Hramov ◽  
Vadim Grubov ◽  
Artem Badarin ◽  
Vladimir A. Maksimenko ◽  
Alexander N. Pisarchik
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
High Efficiency ◽  
Brain Activity ◽  
Blood Oxygenation ◽  
Hemispheric Lateralization ◽  
Motor Execution ◽  
Functional Near Infrared Spectroscopy

Sensor-level human brain activity is studied during real and imaginary motor execution using functional near-infrared spectroscopy (fNIRS). Blood oxygenation and deoxygenation spatial dynamics exhibit pronounced hemispheric lateralization when performing motor tasks with the left and right hands. This fact allowed us to reveal biomarkers of hemodynamical response of the motor cortex on the motor execution, and use them for designing a sensing method for classification of the type of movement. The recognition accuracy of real movements is close to 100%, while the classification accuracy of imaginary movements is lower but quite high (at the level of 90%). The advantage of the proposed method is its ability to classify real and imaginary movements with sufficiently high efficiency without the need for recalculating parameters. The proposed system can serve as a sensor of motor activity to be used for neurorehabilitation after severe brain injuries, including traumas and strokes.

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