Diffuse Reflectance Illumination Module Improvements in Near-Infrared Spectrometer for Heterogeneous Sample Analysis

This paper presents a portable and affordable prototype using a Digital Micro-mirror Device (DMD) based Near-Infrared Spectrometer and an improved diffuse reflectance illumination module (DRIM). The improved DRIM produced optical geometry parameters such as 3.5mm standoff distance (SD), 2mm depth of...

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Autores principales: Umachandi Mantena, Sourabh Roy, Ramesh Datla
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Lenguaje:EN
Publicado: IEEE 2021
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spelling oai:doaj.org-article:c5c199badc6b4f389d381e2b80b40cf42021-12-04T00:00:15ZDiffuse Reflectance Illumination Module Improvements in Near-Infrared Spectrometer for Heterogeneous Sample Analysis2169-353610.1109/ACCESS.2021.3126393https://doaj.org/article/c5c199badc6b4f389d381e2b80b40cf42021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9606770/https://doaj.org/toc/2169-3536This paper presents a portable and affordable prototype using a Digital Micro-mirror Device (DMD) based Near-Infrared Spectrometer and an improved diffuse reflectance illumination module (DRIM). The improved DRIM produced optical geometry parameters such as 3.5mm standoff distance (SD), 2mm depth of overlap illumination area (DOIR), and 4mm sample active illumination area (SAIA). It enables the single and multi-point scans to determine the crude content of various food quality parameters and homogeneity by averaging spatial inhomogeneities of raw material and heterogeneous sample mixtures placed at a standoff distance. The prototype outperformed the current portable NIRS by a factor of 2–3 in terms of optical throughput, signal-to-noise ratio, and baseline. The prototype’s repeatability was determined by assessing pure samples such as chalk powder, red chili powder, wheat, and groundnuts using scattering correction techniques and was computed <1% relative standard deviation (RSD). Partial least square regression (PLSR) was used to build a prediction model using around 100 randomly selected poultry feed samples with 10-20% moisture ranges-. Results of the experiments indicated values for the coefficient of determination as high as 0.991, and root mean square error was 0.32%, and a prediction accuracy with maximum deviation of <1%. The results indicated that the prototype was able to efficiently predict heterogeneous mixtures and food grains, provide new specifications for single and multi-point scan measurements, and this carries a lot of potential as a stand-alone or in-line food monitoring tool.Umachandi MantenaSourabh RoyRamesh DatlaIEEEarticleChemometricsdiffuse reflectancedigital micromirror devicefood industriesheterogeneous samplemoisture measurementElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 153508-153517 (2021)
institution DOAJ
collection DOAJ
language EN
topic Chemometrics
diffuse reflectance
digital micromirror device
food industries
heterogeneous sample
moisture measurement
Electrical engineering. Electronics. Nuclear engineering
TK1-9971
spellingShingle Chemometrics
diffuse reflectance
digital micromirror device
food industries
heterogeneous sample
moisture measurement
Electrical engineering. Electronics. Nuclear engineering
TK1-9971
Umachandi Mantena
Sourabh Roy
Ramesh Datla
Diffuse Reflectance Illumination Module Improvements in Near-Infrared Spectrometer for Heterogeneous Sample Analysis
description This paper presents a portable and affordable prototype using a Digital Micro-mirror Device (DMD) based Near-Infrared Spectrometer and an improved diffuse reflectance illumination module (DRIM). The improved DRIM produced optical geometry parameters such as 3.5mm standoff distance (SD), 2mm depth of overlap illumination area (DOIR), and 4mm sample active illumination area (SAIA). It enables the single and multi-point scans to determine the crude content of various food quality parameters and homogeneity by averaging spatial inhomogeneities of raw material and heterogeneous sample mixtures placed at a standoff distance. The prototype outperformed the current portable NIRS by a factor of 2–3 in terms of optical throughput, signal-to-noise ratio, and baseline. The prototype’s repeatability was determined by assessing pure samples such as chalk powder, red chili powder, wheat, and groundnuts using scattering correction techniques and was computed <1% relative standard deviation (RSD). Partial least square regression (PLSR) was used to build a prediction model using around 100 randomly selected poultry feed samples with 10-20% moisture ranges-. Results of the experiments indicated values for the coefficient of determination as high as 0.991, and root mean square error was 0.32%, and a prediction accuracy with maximum deviation of <1%. The results indicated that the prototype was able to efficiently predict heterogeneous mixtures and food grains, provide new specifications for single and multi-point scan measurements, and this carries a lot of potential as a stand-alone or in-line food monitoring tool.
format article
author Umachandi Mantena
Sourabh Roy
Ramesh Datla
author_facet Umachandi Mantena
Sourabh Roy
Ramesh Datla
author_sort Umachandi Mantena
title Diffuse Reflectance Illumination Module Improvements in Near-Infrared Spectrometer for Heterogeneous Sample Analysis
title_short Diffuse Reflectance Illumination Module Improvements in Near-Infrared Spectrometer for Heterogeneous Sample Analysis
title_full Diffuse Reflectance Illumination Module Improvements in Near-Infrared Spectrometer for Heterogeneous Sample Analysis
title_fullStr Diffuse Reflectance Illumination Module Improvements in Near-Infrared Spectrometer for Heterogeneous Sample Analysis
title_full_unstemmed Diffuse Reflectance Illumination Module Improvements in Near-Infrared Spectrometer for Heterogeneous Sample Analysis
title_sort diffuse reflectance illumination module improvements in near-infrared spectrometer for heterogeneous sample analysis
publisher IEEE
publishDate 2021
url https://doaj.org/article/c5c199badc6b4f389d381e2b80b40cf4
work_keys_str_mv AT umachandimantena diffusereflectanceilluminationmoduleimprovementsinnearinfraredspectrometerforheterogeneoussampleanalysis
AT sourabhroy diffusereflectanceilluminationmoduleimprovementsinnearinfraredspectrometerforheterogeneoussampleanalysis
AT rameshdatla diffusereflectanceilluminationmoduleimprovementsinnearinfraredspectrometerforheterogeneoussampleanalysis
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