Discrimination of Boletaceae mushrooms based on data fusion of FT-IR and ICP–AES combined with SVM

Abstract

In this study, the individual and data fusion of Fourier transform infrared (FT-IR) spectroscopy and inductively coupled plasma atomic emission spectrometry (ICP-AES) were used for the discrimination of five species of Boletaceae mushrooms with the aid of support vector machine (SVM). First, the original FT-IR spectra of 230 samples with different species were preprocessed and optimized by second derivative (2D), Savitzky-Golay filter (15:1) and standardized normal variate. Second, the datasets of FT-IR spectra and ICP-AES were integrated, and the low-level data fusion strategy was used to classify different species mushrooms. Third, the latent variables of elements concentration and FT-IR spectra were extracted by partial least square discriminant analysis and two datasets were fused into a new matrix. Finally, the classification models were established by SVM. Compared with single spectroscopic technique, the mid-level data fusion strategy can provide better result. Especially, the accuracy of correct classification of samples in calibration and test sets were 100.00% and 98.68%, respectively. The results demonstrated that the mid-level data fusion of FT-IR and ICP-AES can provide higher synergic effect for the discrimination of different species Boletaceae mushrooms, which could be benefited for the further authentication and quality control of edible mushrooms.

Pleurotus Mushrooms Content in Glucans and Ergosterol Assessed by ATR-FTIR Spectroscopy and Multivariate Analysis

“…In the mushroom industry, such a tool (i.e., predicting the content of mushrooms in selected constituents) could be of great interest both for the growers, as a way of promoting a product of high nutraceutical value, as well as for companies processing mushrooms to produce health promoting foods or drugs/cosmetics. To date, FTIR spectroscopy has been mainly applied to identify various filamentous fungi [27,28], to delimit taxa within the genera Pleurotus, Ganoderma and Boletus [29][30][31], to discriminate among mushroom samples of the same species on the basis of geographic origin [32] or to evaluate the post-harvest quality properties in Agaricus bisporus mushrooms [33]. To the best of the authors' knowledge, no PAT tool exists for the assessment of mushroom content in bioactive compounds.…”

Differentiation of NaCl, NaOH, and β-Phenylethylamine Using Ultraviolet Spectroscopy and Improved Adaptive Artificial Bee Colony Combined with BP-ANN Algorithm

“…Therefore, in this paper, we proposed a new pattern recognition technology based on the comparison of supervised pattern recognition technologies such as DA, sigmoid SVM, radial basis function-SVM (RBF-SVM), BP-ANN, and ABC-BP-ANN, , which used improved adaptive artificial bee colony (IAABC) to optimize the weight and threshold of BP-ANN. From the obtained results of four indicators, accuracy, recall, precision, and F-score, it can be seen that UV spectroscopy combined with IAABC-BP-ANN is a simple, rapid, and reliable classification method for distinguishing NaCl, NaOH, PEA, and their mixtures.…”

Identification of Gyromitra infula: A Rapid and Visual Method Based on Loop-Mediated Isothermal Amplification

“…Rapid detection and identification of poisonous mushrooms (such as G. infula) when mushroom poisoning occurs is essential and urgent for investigating mushroom poisoning and treatment of poisoning patients (Li et al, 2020). Conventional detection methods such as morphology identification, high-performance liquid chromatography, and polymerase chain reaction (PCR; Ahmed et al, 2010;Yao et al, 2018;Wurita et al, 2019;Cevik, 2020) are not suitable for regions that are economically underdeveloped and have a lack of poisonous mushroom knowledge and equipment limitations. Therefore, there is an urgent need for a new, simple, practical, and cheap rapid detection method for G. infula that can be used for onsite applications at the grassroots level.…”