Researches of fruit quality prediction model based on near infrared spectrum

In order to detect the soluble solids content of apples quickly and accurately, a portable apple soluble solids content detector based on USB2000 + micro spectrometer was developed. The instrument can communicate with computer terminal and mobile app through network port, Bluetooth and other ways, which can realize the rapid acquisition of apple spectral information. Firstly, the visible / near-infrared spectrum data and soluble solids content information of 160 apple samples were collected; secondly, the spectral data preprocessing methods were compared, and the results showed that the prediction model of sugar content based on partial least square (PLS) method after average smoothing preprocessing was accurate. The correlation coefficient (RP) and root mean square error (RMSEP) of the prediction model were 0.902 and 0.589 ° Brix, respectively. Finally, on the basis of average smoothing preprocessing, competitive adaptive reweighted sampling (CARS) and successive projections algorithm (SPA) were used to optimize the wavelength of spectral data, and PLS model was constructed based on the selected 17 characteristic wavelengths, which can increase the accuracy of soluble solids content prediction model, increase the RP to 0.912, and reduce RMSEP to 0.511 ° Brix. The portable visible / near infrared spectrum soluble solids prediction model based on the instrument and method has high accuracy, and the detector can quickly and accurately measure the soluble solids content of apple.

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Novel near-infrared spectrum analysis tool: Synergy adaptive moving window model based on immune clone algorithm

Analytica Chimica Acta ◽

10.1016/j.aca.2017.11.028 ◽

2018 ◽

Vol 1000 ◽

pp. 109-122 ◽

Cited By ~ 2

Author(s):

Shenghao Wang ◽

Yuyan Zhang ◽

Fuyi Cao ◽

Zhenying Pei ◽

Xuewei Gao ◽

...

Keyword(s):

Infrared Spectrum ◽

Spectrum Analysis ◽

Near Infrared ◽

Analysis Tool ◽

Moving Window ◽

Model Based ◽

Near Infrared Spectrum

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Development of intelligent data acquisition and processing system for near-infrared spectrum

JOURNAL OF ELECTRONIC MEASUREMENT AND INSTRUMENT ◽

10.3724/sp.j.1187.2013.00319 ◽

2014 ◽

Vol 27 (4) ◽

pp. 319-324 ◽

Cited By ~ 1

Author(s):

Xiaoguang Liu ◽

Xiaojin Men ◽

Manli Dou ◽

Chun Shi ◽

Gang Wu

Keyword(s):

Infrared Spectrum ◽

Data Acquisition ◽

Near Infrared ◽

Processing System ◽

Data Acquisition And Processing ◽

Intelligent Data Acquisition ◽

Near Infrared Spectrum

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Nanopatterned metallic transparent electrodes for the near-infrared spectrum

AIP Advances ◽

10.1063/5.0044447 ◽

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

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An electrically driven whispering gallery polariton microlaser

Nanoscale ◽

10.1039/d0nr08168j ◽

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.

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

Applied Spectroscopy ◽

10.1177/00037028211027951 ◽

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.

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