Effect of particle size and spectral sub-range within the UV-VIS-NIR range using diffuse reflectance spectra on multivariate models in evaluating the severity of fusariosis in ground wheat

Balcerowska, G.; Siuda, R.; Skrzypczak, J; Łukanowski, Aleksander; Sadowski, C.

doi:10.1080/02652030802627764

Cited by 5 publications

(1 citation statement)

References 20 publications

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“…This figure can provide additional information on particular spectral sub-ranges and peaks. Wavelengths with a larger coefficient value can contribute more to a calibration model (Balcerowska et al, 2009).…”

Section: Quantification Of Fumonisin In Maize Samplesmentioning

confidence: 99%

Application of Raman spectroscopy for qualitative and quantitative detection of fumonisins in ground maize samples

Lee¹,

Herrman²,

Nansen³

et al. 2013

regsci

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The feasibility of Raman spectroscopy for qualitative and quantitative assessment of fumonisins in ground maize was investigated using the samples with concentration range of 2 to 99 mg/kg. Major Raman bands relevant to fumonisin effects on starch molecules and on increased fumonisin levels were observed in several Raman shift regions. The k-nearest neighbor (KNN) models achieved highest classification accuracies for both training (100%) and independent validation (96-100%) data. Three classification models (k-nearest neighbor, linear discriminant analysis, and partial least squares discriminant analysis) correctly classified fumonisin contaminated samples of >5 mg/kg. All chemometrics models for quantitative determination of fumonisins could explain >90% of variation in spectra data. Multiple linear regression (MLR) and partial least square regression (PLSR) models showed slightly higher predictive accuracies and lower error rates. The statistical results showed no significant difference between LC-MS/MS (liquid chromatography-tandem mass spectrometry) reference and Raman predicted data, implying some models developed have the ability to accurately predict fumonisin levels in ground maize samples for rapid screening and identification of contaminated samples. This work characterizes the capability of Raman spectroscopy as a fast screening tool for high-throughput analysis of fumonisin contaminated samples to improve food and feed safety.

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Section: Quantification Of Fumonisin In Maize Samplesmentioning

confidence: 99%

Application of Raman spectroscopy for qualitative and quantitative detection of fumonisins in ground maize samples

Lee¹,

Herrman²,

Nansen³

et al. 2013

regsci

View full text Add to dashboard Cite

show abstract

High-throughput cereal metabolomics: Current analytical technologies, challenges and perspectives

Khakimov

Bak

Engelsen

2014

Journal of Cereal Science

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Near-infrared spectroscopy as a potential tool with radial basis function for measurement of residual acrylamide in organic polymer

Zhu

Zheng

Zhang

et al. 2013

Environmental Technology

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Poly(acrylamide-co-diallyldimethylammonium chloride) (PDA), which is usually prepared by free radical polymerization of acrylamide monomer (AM) onto the cationic monomer dimethyl diallyl ammonium chloride (DMDAAC), has been widely applied to wastewater treatment; however, the free-radical polymerization is always incomplete with residual AM remaining in the PDA. The residual AM affects the PDA's performance while also posing as a potential threat to human health; therefore, during preparation of the PDA, the rapid detection of the residual AM plays an important role in controlling the residual AM while improving the PDA's performance. The objective of this study was to explore the possibilities for applying near-infrared (NIR) spectroscopy as a potential tool for detecting the residual AM in combination with a statistical tool. In this study, the radial basis function (RBF) network model as the statistical tool was combined with NIR spectroscopy for detection of the residual AM. The experimental results showed that five wavelengths in the NIR spectroscopy were the most important characteristic adsorption peaks, particular at 971.95 and 1077 nm. The simulation of the RBF model presented higher performance with R2-value greater than 0.98, RMSEC and RMSEP less than 7.22 x 10(-5) and coefficient of variation (CV) of the predicted residual AM less than 10%, which demonstrated the feasibility of the NIR spectroscopy being a rapid detection tool for prediction of the residual AM using the RBF model. Wavelet de-nosing was used for removing the interference/noise in the NIR spectroscopy and improved the generalization ability of the RBF model.

show abstract

Effect of particle size and spectral sub-range within the UV-VIS-NIR range using diffuse reflectance spectra on multivariate models in evaluating the severity of fusariosis in ground wheat

Cited by 5 publications

References 20 publications

Application of Raman spectroscopy for qualitative and quantitative detection of fumonisins in ground maize samples

Application of Raman spectroscopy for qualitative and quantitative detection of fumonisins in ground maize samples

High-throughput cereal metabolomics: Current analytical technologies, challenges and perspectives

Near-infrared spectroscopy as a potential tool with radial basis function for measurement of residual acrylamide in organic polymer

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