<i>Internal Quality Detection of Apple Based on Near Infrared Spectrum Characteristic Wavelength</i>

2019 ◽  
Author(s):  
Pengkun Quan ◽  
Juan Zhao ◽  
Mengsheng Zhang ◽  
Haihui Zhang
Keyword(s):  
Infrared Spectrum ◽  
Near Infrared ◽  
Internal Quality ◽  
Quality Detection ◽  
Characteristic Wavelength ◽  
Spectrum Characteristic ◽  
Near Infrared Spectrum

scholarly journals Nanopatterned metallic transparent electrodes for the near-infrared spectrum

AIP Advances ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 045005
Author(s):  
Aliaksandr Hubarevich ◽  
Mikita Marus ◽  
Yauhen Mukha ◽  
Aliaksandr Smirnov ◽  
Xiao Wei Sun
Keyword(s):  
Infrared Spectrum ◽  
Near Infrared ◽  
Transparent Electrodes ◽  
Near Infrared Spectrum

An electrically driven whispering gallery polariton microlaser

Nanoscale ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 5448-5459
Author(s):  
Mingming Jiang ◽  
Peng Wan ◽  
Kai Tang ◽  
Maosheng Liu ◽  
Caixia Kan
Keyword(s):  
Infrared Spectrum ◽  
Near Infrared ◽  
Whispering Gallery ◽  
Near Infrared Spectrum

An electrically driven whispering gallery polariton microlaser composed of a ZnO:Ga microwire and a p-GaAs template was fabricated. Its working characteristics of polariton lasing in the near-infrared spectrum were demonstrated.

scholarly journals Theoretical Simulation of Near-Infrared Spectrum of Piperine: Insight into Band Origins and the Features of Regression Models

2021 ◽  
pp. 000370282110279
Author(s):  
Justyna Grabska ◽  
Krzysztof B. Beć ◽  
Sophia Mayr ◽  
Christian W. Huck
Keyword(s):  
Infrared Spectrum ◽  
Regression Models ◽  
Near Infrared ◽  
Computing Time ◽  
Black Pepper ◽  
Partial Least Square ◽  
Least Square ◽  
Complex Nature ◽  
Chemical Information ◽  
Near Infrared Spectrum

We investigated the near-infrared spectrum of piperine using quantum mechanical calculations. We evaluated two efficient approaches, DVPT2//PM6 and DVPT2//ONIOM [PM6:B3LYP/6-311++G(2df, 2pd)] that yielded a simulated spectrum with varying accuracy versus computing time factor. We performed vibrational assignments and unveiled complex nature of the near-infrared spectrum of piperine, resulting from a high level of band convolution. The most meaningful contribution to the near-infrared absorption of piperine results from binary combination bands. With the available detailed near-infrared assignment of piperine, we interpreted the properties of partial least square regression models constructed in our earlier study to describe the piperine content in black pepper samples. Two models were compared with spectral data sets obtained with a benchtop and a miniaturized spectrometer. The two spectrometers implement distinct technology which leads to a profound instrumental difference and discrepancy in the predictive performance when analyzing piperine content. We concluded that the sensitivity of the two instruments to certain types of piperine vibrations is different and that the benchtop spectrometer unveiled higher selectivity. Such difference in obtaining chemical information from a sample can be one of the reasons why the benchtop spectrometer performs better in analyzing the piperine content of black pepper. This evidenced direct correspondence between the features critical for applied near-infrared spectroscopic routine and the underlying vibrational properties of the analyzed constituent in a complex sample.

Functional Classification of Feed Items in Pampa Grassland, Based on Their Near-Infrared Spectrum

2020 ◽  
Vol 73 (3) ◽  
pp. 358-367
Author(s):  
Júlio Cezar Rebés Azambuja Filho ◽  
Paulo Cesar de Faccio Carvalho ◽  
Olivier Jean François Bonnet ◽  
Denis Bastianelli ◽  
Magali Jouven
Keyword(s):  
Infrared Spectrum ◽  
Near Infrared ◽  
Functional Classification ◽  
Near Infrared Spectrum
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