Semi-Supervised Learning based Calibration Model Building of NIR spectroscopy for In-Situ Measurement of Biochemical Processes under Insufficiently and Inaccurately Labeled Samples

2020 ◽  
pp. 1-1
Author(s):  
Guoqing Mu ◽  
Tao Liu ◽  
Chuang Xue ◽  
Junghui Chen
Keyword(s):  
Supervised Learning ◽  
Model Building ◽  
Nir Spectroscopy ◽  
In Situ Measurement ◽  
Calibration Model ◽  
Biochemical Processes

scholarly journals Implementation of Non Destructive FTNIR Method for Quick Estimation of Peanut Quality Based on FFA and Peroxide Value

2021 ◽  
Author(s):  
Rakesh Kumar Kumar Raigar ◽  
Shubhangi Srivast ◽  
Hari Niwas Mishra
Keyword(s):  
Peroxide Value ◽  
Diffuse Reflectance ◽  
Near Infrared ◽  
Model Building ◽  
Nir Spectroscopy ◽  
Quality Parameters ◽  
Calibration Model ◽  
Peanut Kernel ◽  
Non Destructive

Abstract The possibility of rapid estimation of moisture, protein, fat, free fatty acid (FFA), and peroxide value (PV) content in peanut kernel was studied by Fourier transform near-infrared spectroscopy (FTNIR) in the diffuse reflectance mode along with chemometric technic. The moisture, fat and protein of fresh and damaged seeds of peanuts ranging from 3 to 9 %, 45 to 57 % and 23 to 27 % respectively, were used for the calibration model building based on partial least squares (PLS) regression. The peanut samples had major peaks at wavenumbers 53.0853, 4954.98, 4464.03, 4070.85, 74.75.63, 8230.21, and 6178.13 in per cm. First and second derivate mathematical preprocessing was also applied in order to eliminate multiple baselines for different chemical quality parameters of peanut. The FFA had the lowest value of calibration and validation errors (0.579 and 0.738) followed by the protein (0.736 and 0.765). The quality of peanut seeds with lowest root mean square error of cross validation of 0.76 and maximum correlation coefficient (R2) of 96.8 was obtained. The comprehensive results signify that FT-NIR spectroscopy can be used for rapid, non-destructive quantification of quality parameters in peanuts.

Evaluation of Pozzolanic Activity of Metakaolin Chemometric Method According to the UV-VIS-NIR Spectroscopy

2021 ◽  
Vol 887 ◽  
pp. 586-590
Author(s):  
R.A. Platova ◽  
V.A. Rassulov ◽  
Y.T. Platov
Keyword(s):  
Quality Control ◽  
Mass Loss ◽  
Nir Spectroscopy ◽  
Pozzolanic Activity ◽  
Calibration Model ◽  
Total Acid ◽  
Chemometric Method ◽  
Acid Solubility

It is introduced to use a portable spectrometer along with a calibration model for rapid quality control of metakaolin in situ. Verification of the calibration model for predicting the values of two indicators: total acid solubility and mass loss during calcination, indirectly characterizing the pozzolanic activity of metakaolin.

scholarly journals Implementation of Non Destructive FTNIR Method for Quick Estimation of Peanut Quality Based on FFA and Peroxide Value

2021 ◽  
Author(s):  
Rakesh Kumar Kumar Raigar ◽  
Shubhangi Srivast ◽  
Hari Niwas Mishra
Keyword(s):  
Peroxide Value ◽  
Near Infrared ◽  
Model Building ◽  
Nir Spectroscopy ◽  
Quality Parameters ◽  
Multiple Baseline ◽  
Calibration Model ◽  
Peanut Kernel ◽  
Non Destructive

Abstract The possibility of rapid estimation of moisture, protein, fat, free fatty acid (FFA), and peroxide value (PV) content in peanut kernel was studied by Fourier transform near-infrared spectroscopy (FTNIR) in the diffuse reflectance mode along with chemometric technic. The moisture, fat and protein of fresh and damaged seeds of peanuts ranging from 3 to 9 %, 45 to 57 % and 23 to 27 % respectively, were used for the calibration model building based on partial least squares (PLS) regression. The peanut samples had major peaks at wavenumbers 53.0853, 4954.98, 4464.03, 4070.85, 74.75.63, 8230.21, and 6178.13 in per cm. First and second derivate mathematical preprocessing was also applied in order to eliminate multiple baseline for different chemical quality parameters of peanut. The FFA had the lowest value of calibration and validation errors (0.579 and 0.738) followed by the protein (0.736 and 0.765). The quality of peanut seeds with lowest root mean square error of cross validation of 0.76 and maximum correlation coefficient (R2) of 96.8 was obtained. The comprehensive results signify that FT-NIR spectroscopy can be used for rapid, non destructive quantification of quality parameters in peanut.

3-D imaging of cells using a confocal laser scanning microscope and digital image processing

1988 ◽  
Vol 46 ◽  
pp. 96-97
Author(s):  
Thomas M. Jovin ◽  
Michel Robert-Nicoud ◽  
Donna J. Arndt-Jovin ◽  
Thorsten Schormann
Keyword(s):  
Laser Scanning ◽  
Confocal Laser Scanning Microscope ◽  
Laser Scanning Microscopy ◽  
Confocal Laser Scanning ◽  
Confocal Laser ◽  
Scanning Microscope ◽  
Laser Scanning Microscope ◽  
Biochemical Processes ◽  
Adjacent Structures

Light microscopic techniques for visualizing biomolecules and biochemical processes in situ have become indispensable in studies concerning the structural organization of supramolecular assemblies in cells and of processes during the cell cycle, transformation, differentiation, and development. Confocal laser scanning microscopy offers a number of advantages for the in situ localization and quantitation of fluorescence labeled targets and probes: (i) rejection of interfering signals emanating from out-of-focus and adjacent structures, allowing the “optical sectioning” of the specimen and 3-D reconstruction without time consuming deconvolution; (ii) increased spatial resolution; (iii) electronic control of contrast and magnification; (iv) simultanous imaging of the specimen by optical phenomena based on incident, scattered, emitted, and transmitted light; and (v) simultanous use of different fluorescent probes and types of detectors.We currently use a confocal laser scanning microscope CLSM (Zeiss, Oberkochen) equipped with 3-laser excitation (u.v - visible) and confocal optics in the fluorescence mode, as well as a computer-controlled X-Y-Z scanning stage with 0.1 μ resolution.

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