Jie-Qing Li

A mini-review of chemical composition and nutritional value of edible wild-grown mushroom from China.

In China, many species of edible wild-grown mushrooms are appreciated as food and also found use in traditional Chinese medicine. In this mini-review, for the first time, is summarized and discussed data available on chemical components of nutritional significance for wild-grown mushrooms collected from China. We aimed to update and discuss the latest data published on ash, fat, carbohydrates, fibre, proteins, essential amino acids and nonessential amino acids, some essential (P, K, Na, Ca, Mg, Fe, Mn, Zn, Cu) and toxic elements (As, Hg, Cd, Pb), vitamins (thiamine, riboflavin, niacin, tocopherol, vitamin D), flavour and taste compounds, antioxidants and also on less studied organic compounds (lectin, adustin, ribonuclease and nicotine) contents of wild-grown mushrooms.

Mycology, cultivation, traditional uses, phytochemistry and pharmacology of Wolfiporia cocos (Schwein.) Ryvarden et Gilb.: A review

ETHNOPHARMACOLOGICAL RELEVANCE Wolfiporia cocos (Schwein.) Ryvarden et Gilb. has a long history as a Chinese traditional medicine with uses of inducing diuresis, excreting dampness, invigorating the spleen, and tranquilizing the mind. Recently, Wolfiporia cocos has received increasing interest, and phytochemical and pharmacological studies have validated the traditional uses of this species. AIMS OF THE REVIEW To provide an up-to-date and comprehensive overview of the mycology, cultivation, traditional uses, chemical constituents and pharmacological activities aspects of Wolfiporia cocos in order to highlight its ethnopharmacological use and to explore its therapeutic potentials and to provide a basis for future research. MATERIALS AND METHODS The accessible literature, from 1980 to 2012, on Wolfiporia cocos written in English, Chinese, French, Korean, Spanish and Turkish were selected and analyzed. RESULTS The phytochemical and modern pharmacological studies demonstrated that Wolfiporia cocos possess a wide spectrum of pharmacological activities, such as anti-tumor, anti-oxidant, anti-rejection, nematicidal, anti-hyperglycemic, antibacterial, anti-inflammatory and anti-hypertonic stress activities, which could be explained by the presence of various triterpenes and polysaccharides. CONCLUSIONS Modern phytochemical and pharmacological investigations showed that major active components separated from Wolfiporia cocos had anti-tumor, anti-oxidant, anti-rejection activities, and so on. Further investigations are needed to explore the relationship of the molecular mass, chain stiffness, and water solubility of polysaccharide from Wolfiporia cocos with the antitumor activities.

Geographical traceability of wild Boletus edulis based on data fusion of FT-MIR and ICP-AES coupled with data mining methods (SVM)

In this work, the data fusion strategy of Fourier transform mid infrared (FT-MIR) spectroscopy and inductively coupled plasma-atomic emission spectrometry (ICP-AES) was used in combination with Support Vector Machine (SVM) to determine the geographic origin of Boletus edulis collected from nine regions of Yunnan Province in China. Firstly, competitive adaptive reweighted sampling (CARS) was used for selecting an optimal combination of key wavenumbers of second derivative FT-MIR spectra, and thirteen elements were sorted with variable importance in projection (VIP) scores. Secondly, thirteen subsets of multi-elements with the best VIP score were generated and each subset was used to fuse with FT-MIR. Finally, the classification models were established by SVM, and the combination of parameter C and γ (gamma) of SVM models was calculated by the approaches of grid search (GS) and genetic algorithm (GA). The results showed that both GS-SVM and GA-SVM models achieved good performances based on the #9 subset and the prediction accuracy in calibration and validation sets of the two models were 81.40% and 90.91%, correspondingly. In conclusion, it indicated that the data fusion strategy of FT-MIR and ICP-AES coupled with the algorithm of SVM can be used as a reliable tool for accurate identification of B. edulis, and it can provide a useful way of thinking for the quality control of edible mushrooms.

Variations in Element Levels Accumulated in Different Parts of Boletus edulis Collected from Central Yunnan Province, China

ICP-AES and microwave assisted digestion were applied to determine P, Mg, Ca, Zn, Na, Cu, Ba, Ni, V, Cd, Sr, Co, and Li in the caps and stipes of Boletus edulis collected from six spatially distant sites in Yunnan province, China. Fruiting bodies of King Bolete are abundant in P, Mg, Ca, Zn, Cu, and Na, followed by Ba, Cd, Ni, V, Li, Sr, and Co. Contents of P, Mg, Zn, and Cu are more abundant in caps than in stipes of King Bolete. However, elements such as Na, Ba, Cd, Ni, V, Li, Sr, and Co prefer to accumulate in stipes of mushrooms from Yaoan, Chuxiong. The results of this study indicate that spatial variations of elements between caps and stipes are mainly related to different bedrock soil geochemistry and enrichment capability for various elements.

Feature Fusion of ICP-AES, UV-Vis and FT-MIR for Origin Traceability of Boletus edulis Mushrooms in Combination with Chemometrics

Origin traceability is an important step to control the nutritional and pharmacological quality of food products. Boletus edulis mushroom is a well-known food resource in the world. Its nutritional and medicinal properties are drastically varied depending on geographical origins. In this study, three sensor systems (inductively coupled plasma atomic emission spectrophotometer (ICP-AES), ultraviolet-visible (UV-Vis) and Fourier transform mid-infrared spectroscopy (FT-MIR)) were applied for the origin traceability of 184 mushroom samples (caps and stipes) in combination with chemometrics. The difference between cap and stipe was clearly illustrated based on a single sensor technique, respectively. Feature variables from three instruments were used for origin traceability. Two supervised classification methods, partial least square discriminant analysis (FLS-DA) and grid search support vector machine (GS-SVM), were applied to develop mathematical models. Two steps (internal cross-validation and external prediction for unknown samples) were used to evaluate the performance of a classification model. The result is satisfactory with high accuracies ranging from 90.625% to 100%. These models also have an excellent generalization ability with the optimal parameters. Based on the combination of three sensory systems, our study provides a multi-sensory and comprehensive origin traceability of B. edulis mushrooms.

Traceability of Boletaceae Mushrooms Using Data Fusion of UV-vis and FT-IR Combined with Chemometrics Methods.

BACKGROUND Boletaceae mushrooms are wild-grown edible mushrooms that have high nutrition, delicious flavor and large economic value distributing in Yunnan Province, China. Traceability is important for the authentication and quality assessment of Boletaceae mushrooms. In this study, UV-visible and Fourier transform infrared (FTIR) spectroscopies were applied for traceability of 247 Boletaceae mushroom samples in combination with chemometrics. RESULTS Compared with a single spectroscopy technique, data fusion strategy can obviously improve the classification performance in partial least square discriminant analysis (PLS-DA) and grid-search support vector machine (GS-SVM) models, for both species and geographical origin traceability. In addition, PLS-DA and GS-SVM models can provide 100.00% accuracy for species traceability and have reliable evaluation parameters. For geographical origin traceability, the accuracy of prediction in the PLS-DA model by data fusion was just 64.63%, but the GS-SVM model based on data fusion was 100.00%. CONCLUSION The results demonstrated that the data fusion strategy of UV-visible and FTIR combined with GS-SVM could provide a higher synergic effect for traceability of Boletaceae mushrooms and have a good generalization ability for the comprehensive quality control and evaluation of similar foods.

Mineral element content in prized matsutake mushroom (Tricholoma matsutake) collected in China

The contents of Ca, Cu, Fe, K, Mg, Mn, Na, and Zn in fruiting bodies of the highly-prized matsutake mushroom (Tricholoma matsutake) from twelve widely separated sites in Southwest China were determined using AAS. The results for dried mushrooms showed that the mean contents (mg kg−1) of the determined elements decreased in the following order: K (440–2000), Na (150–740), Ca (90–850), Mg (90–680), Zn (20–180), Fe (13–78), Cu (0.34–45), Mn (0.09–7.6).

Geographic Characterization of Leccinum rugosiceps by Ultraviolet and Infrared Spectral Fusion

ABSTRACT Leccinum rugosiceps is an edible mushroom belonging to genus Leccinum of Boletaceae. Its fruiting bodies are richer in nutrients than many vegetables and fruit. The model of support vector machine was established for the discrimination of L. rugosiceps from regions based on rapid and low-cost ultraviolet and infrared spectroscopies. The mid-level data fusion was performed by support vector machine. Compared to a single spectroscopic technique, mid-level data fusion provided higher accuracy by selecting the most significant variance from data matrixes based on partial least squares discriminant analysis. The accuracy of the classification of samples in the calibration and test sets were 85.00 and 94.74%, higher than separate measurements by ultraviolet or infrared spectroscopy. This approach has applications for authentication and quality assessment of L. rugosiceps.

Geographic identification of Boletus mushrooms by data fusion of FT-IR and UV spectroscopies combined with multivariate statistical analysis

Boletus griseus and Boletus edulis are two well-known wild-grown edible mushrooms which have high nutrition, delicious flavor and high economic value distributing in Yunnan Province. In this study, a rapid method using Fourier transform infrared (FT-IR) and ultraviolet (UV) spectroscopies coupled with data fusion was established for the discrimination of Boletus mushrooms from seven different geographical origins with pattern recognition method. Initially, the spectra of 332 mushroom samples obtained from the two spectroscopic techniques were analyzed individually and then the classification performance based on data fusion strategy was investigated. Meanwhile, the latent variables (LVs) of FT-IR and UV spectra were extracted by partial least square discriminant analysis (PLS-DA) and two datasets were concatenated into a new matrix for data fusion. Then, the fusion matrix was further analyzed by support vector machine (SVM). Compared with single spectroscopic technique, data fusion strategy can improve the classification performance effectively. In particular, the accuracy of correct classification of SVM model in training and test sets were 99.10% and 100.00%, respectively. The results demonstrated that data fusion of FT-IR and UV spectra can provide higher synergic effect for the discrimination of different geographical origins of Boletus mushrooms, which may be benefit for further authentication and quality assessment of edible mushrooms.

The Genome Sequences of 90 Mushrooms

Macrofungus is defined as the fungus that grows an observable sporocarp. The sporocarps of many species are commonly called mushrooms and consumed by people all around the world as food and/or medicine. Most macrofungi belong to the divisions Basidiomycetes and Ascomycetes, which are estimated to contain more than 80,000 species in total. We report the draft genome assemblies of macrofungi (83 Basidiomycetes species and 7 Ascomycetes species) based on Illumina sequencing. The genome sizes of these species ranged from 27.4 Mb (Hygrophorus russula) to 202.2 MB (Chroogomphus rutilus). The numbers of protein-coding genes were predicted in the range of 9,511 (Hygrophorus russula) to 52,289 (Craterellus lutescens). This study provides the largest genomic dataset for macrofungi species. This resource will facilitate the artificial cultivation of edible mushrooms and the discovery of novel drug candidates.