scholarly journals Estimation for Different Genotypes of Plants based on DNA Analysis using Near-infrared (NIR) and Fourier-transform Infrared (FT-IR) Spectroscopy

2006 ◽  
Vol 56 (4) ◽  
pp. 399-403 ◽  
Author(s):  
Koji Emura ◽  
Shinsuke Yamanaka ◽  
Hiroko Isoda ◽  
Kazuo N. Watanabe
Keyword(s):  
Fourier Transform ◽  
Ir Spectroscopy ◽  
Near Infrared ◽  
Dna Analysis ◽  
Fourier Transform Infrared ◽  
Ft Ir ◽  
Ft Ir Spectroscopy

scholarly journals Analysis of ‘legal high’ substances and common adulterants using handheld spectroscopic techniques

2015 ◽  
Vol 7 (2) ◽  
pp. 736-746 ◽  
Author(s):  
S. Assi ◽  
A. Guirguis ◽  
S. Halsey ◽  
S. Fergus ◽  
J. L. Stair
Keyword(s):  
Fourier Transform ◽  
Ir Spectroscopy ◽  
Near Infrared ◽  
Fourier Transform Infrared ◽  
Attenuated Total Reflectance ◽  
Spectroscopic Techniques ◽  
Total Reflectance ◽  
Legal High ◽  
Ft Ir ◽  
Ft Ir Spectroscopy

Three handheld spectrometers, near-infrared (NIR), Raman and attenuated total reflectance Fourier transform-infrared (ATR-FT-IR) spectroscopy, were used for the identification of ‘legal high’ model mixtures and Internet products.

scholarly journals Application of Fourier Transform Near-Infrared (FT-NIR) and Fourier Transform Infrared (FT-IR) Spectroscopy Coupled with Wavelength Selection for Fast Discrimination of Similar Color of Tuber Flours

2020 ◽  
Vol 20 (3) ◽  
pp. 680 ◽  
Author(s):  
Rudiati Evi Masithoh ◽  
Hanim Zuhrotul Amanah ◽  
Byoung Kwan Cho
Keyword(s):  
Fourier Transform ◽  
Ir Spectroscopy ◽  
Near Infrared ◽  
Fourier Transform Infrared ◽  
Accurate Method ◽  
Coefficient Of Determination ◽  
Wavelength Selection ◽  
Derivative Method ◽  
Ft Ir ◽  
Ft Ir Spectroscopy

This research aimed at providing a fast and accurate method in discriminating tuber flours having similar color by using Fourier transform near-infrared (FT-NIR) and Fourier transform infrared (FT-IR) spectroscopy in order to minimize misclassification if using human eye or avoid adulteration. Reflectance spectra of three types of tubers (consisted of Canna edulis, modified cassava, and white sweet potato) were collected to develop a multivariate model of partial least-squares discriminant analysis (PLS-DA). Several spectra preprocessing methods were applied to obtain the best calibration and prediction model, while variable importance in the projection (VIP) wavelength selection method was used to reduce variables in developing the model. The PLS-DA model achieved 100% accuracy in predicting all types of flours, both for FT-NIR and FT-IR. The model was also able to discriminate all flours with coefficient of determination (R2) of 0.99 and a standard error of prediction (SEP) of 0.03% by using 1st Savitzky Golay (SG) derivative method for the FT-NIR data, as well as R2 of 0.99 and SEP of 0.08% by using 1st Savitzky Golay (SG) derivative method for the FT-IR data. By applying the VIP method, the variables were reduced from 1738 to 608 variables with R2 of 0.99 and SEP of 0.09% for FT IR and from 1557 to 385 variables with R2 of 0.99 and SEP of 0.05% for FT NIR.

scholarly journals Bacterial Typing and Identification Based on Fourier Transform Infrared Spectroscopy

2020 ◽  
Author(s):  
Huayan Yang ◽  
Fangling Wu ◽  
Fuxin Xu ◽  
Keqi Tang ◽  
Chuanfan Ding ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Ir Spectroscopy ◽  
Bacterial Culture ◽  
Clinical Laboratory ◽  
Fourier Transform Infrared ◽  
Identification Accuracy ◽  
Bacterial Typing ◽  
Typical Experiment ◽  
Ft Ir ◽  
Ft Ir Spectroscopy

Abstract Fourier transform infrared (FT-IR) spectroscopy is a label-free and highly sensitive technique that provides complete information on the chemical composition of biological samples. The bacterial FT-IR signals are extremely specific and highly reproducible fingerprint-like patterns, making FT-IR an efficient tool for bacterial typing and identification. Due to the low cost and high flux, FT-IR has been widely used in hospital hygiene management for infection control, epidemiological studies, and routine bacterial determination of clinical laboratory values. However, the typing and identification accuracy could be affected by many factors, and the bacterial FT-IR data from different laboratories are usually not comparable. A standard protocol is required to improve the accuracy of FT-IR-based typing and identification. Here, we detail the principles and procedures of bacterial typing and identification based on FT-IR spectroscopy, including bacterial culture, sample preparation, instrument operation, spectra collection, spectra preprocessing, and mathematical data analysis. Without bacterial culture, a typical experiment generally takes <2 h.

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