scholarly journals Application of ATR-FTIR analysis for determination of fumonisins in corn

2017 ◽  
pp. 47-56
Author(s):  
Sandra Jaksic ◽  
Igor Jajic ◽  
Vesna Despotovic ◽  
Milica Zivkov-Balos ◽  
Igor Stojanov ◽  
...  
Keyword(s):  
Principal Component ◽  
Total Reflection ◽  
Attenuated Total Reflection ◽  
Ftir Analysis ◽  
Elisa Method ◽  
High Concentration ◽  
Genus Fusarium ◽  
And Cluster Analysis

In order to develop rapid, inexpensive and, at the same time, reliable method for the analysis of molds of the genus Fusarium as an indicator of the presence of fumonisins in corn samples, possible application of Fourier transform infrared spectroscopy (FTIR) with attenuated total reflection (ATR) technique was examined. The content of fumonisins in contaminated corn samples had previously been quantified by ELISA method. At the spectrum of the sample contaminated with a high concentration of mycotoxins, there was a lack of the peak at 1,743 cm-1, but the peak was observed at 1709 cm-1. To the purpose of result classification the principal component analysis (PCA) and cluster analysis were applied. Conclusions of the two methods were similar both when applying ATR technique in the whole region of the spectrum (1,150-1,770 cm-1) and when the whole spectrum was divided into two regions: 1,150-1,450 and 1,450-1,770 cm-1. However, classification of samples was somewhat better in the ranges 1,150-1,770 and 1,450-1,770 cm-1 . Of the 16 analyzed corn samples, only very contaminated corn sample with 190 mg/kg was correctly classified as compared to the other samples with the content of less than 10 mg/kg. Also, it was found-passing recording of spectra of contaminated corn of the same genotype in order to avoid the possible impact of different hybrids on the spectrum.

Chemometric Approach to a Rapid Attenuated Total Reflection Fourier Transform Infrared Analysis of Complex Heroin-Based Mixtures

2020 ◽  
pp. 000370282096971
Author(s):  
Nataša Radosavljević Stevanović ◽  
Milena Jovanović ◽  
Federico Marini ◽  
Slavica Ražić
Keyword(s):  
Principal Component Analysis ◽  
Fourier Transform ◽  
Principal Component ◽  
Fourier Transform Infrared ◽  
Total Reflection ◽  
Attenuated Total Reflection ◽  
Illegal Market ◽  
Ft Ir

Heroin is one of the most frequently seized drugs in Southeastern Europe. Due to the position in the Balkan route, the Republic of Serbia keeps important role in suppression of the trafficking of heroin for domestic and foreign illegal market. This research is aimed to provide a good scientific approach in the field of seized heroin analysis. Two different forms of heroin are present in the illegal market, mostly in mixtures with typical “cutting” agents: caffeine, paracetamol, and sugars. It was observed that the quantity of pure heroin in seized samples slightly increases from year to year. The aim of this study was to produce a reliable and fast procedure for classification of illicit heroin samples and determination of the concentration range of heroin in the samples. For that purpose, the attenuated total reflection Fourier transform infrared spectroscopy (ATR FT-IR) technique was used and combined with such chemometric methods as principal component analysis, cluster analysis, and partial least squares. Principal component analysis (PCA) as an unsupervised model was used for exploratory purposes to identify trends, similarities, and differences between samples by reducing the dimensionality of the data. The cluster classification of examined samples turned out to be extremely useful to evaluate the possibilities of the ATR FT-IR technique to classify the samples appropriately into the patterns, the constituted clusters. Additionally, partial least square was the suitable method for the purpose of determination of the heroin hydrochloride concentration range in examined samples. It is proved that the joined application of spectroscopy and chemometrics can be extremely convenient and useful for forensic and drugs control laboratories.

scholarly journals Determination of HPLC-UV Fingerprints of Spanish Paprika (Capsicum annuum L.) for Its Classification by Linear Discriminant Analysis

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4479 ◽  
Author(s):  
Xavier Cetó ◽  
Núria Serrano ◽  
Miriam Aragó ◽  
Alejandro Gámez ◽  
Miquel Esteban ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
Linear Discriminant Analysis ◽  
Principal Component ◽  
Reversed Phase ◽  
Classification Rate ◽  
Phenolic Profile ◽  
Linear Discriminant ◽  
Sample Extraction

The development of a simple HPLC-UV method towards the evaluation of Spanish paprika’s phenolic profile and their discrimination based on the former is reported herein. The approach is based on C18 reversed-phase chromatography to generate characteristic fingerprints, in combination with linear discriminant analysis (LDA) to achieve their classification. To this aim, chromatographic conditions were optimized so as to achieve the separation of major phenolic compounds already identified in paprika. Paprika samples were subjected to a sample extraction stage by sonication and centrifugation; extracting procedure and conditions were optimized to maximize the generation of enough discriminant fingerprints. Finally, chromatograms were baseline corrected, compressed employing fast Fourier transform (FFT), and then analyzed by means of principal component analysis (PCA) and LDA to carry out the classification of paprika samples. Under the developed procedure, a total of 96 paprika samples were analyzed, achieving a classification rate of 100% for the test subset (n = 25).

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