Characterization of volatile profile from different coriander (Coriandrum sativum L.) varieties via HS-SPME/GC-MS combined with E-nose analyzed by chemometrics

Headspace-solid phase microextraction/gas chromatography-mass spectrometry (HS-SPME/GC-MS) and electronic nose (E-nose) technologies were implemented to characterize the volatile profile of aerial part from 40 coriander varieties. A total of 207 volatile compounds were identified and quantified, including aldehydes, alcohols, terpenes, hydrocarbons, esters, ketones, acids, furans, phenols and others. E-nose results showed that W5S and W2W were representative sensors responding to coriander odor. Among all varieties, the number (21-30 species) and content (449.94-1050.55 μg/g) of aldehydes were the highest, and the most abundant analytes were (Z)-9-hexadecenal or (E)-2-tetratecenal, which accounted for approximately one-third of the total content. In addition, 37 components were determined the characteristic constituents with odor activity values (OAVs) ≥ 1, mainly presenting citrusy, fatty, soapy and floral smells. Hierarchical cluster analysis (HCA) and principal component analysis (PCA) could effectively distinguish different varieties. This study provided a crucial theoretical basis for flavor evaluation and quality improvement of coriander germplasm resources.

An appearance quality classification method for Auricularia auricula based on deep learning

The intelligent appearance quality classification method for Auricularia auricula is of great significance to promote this industry. This paper proposes an appearance quality classification method for Auricularia auricula based on the improved Faster Region-based Convolutional Neural Networks (improved Faster RCNN) framework. The original Faster RCNN is improved by establishing a multiscale feature fusion detection model to improve the accuracy and real-time performance of the model. The multiscale feature fusion detection model makes full use of shallow feature information to complete target detection. It fuses shallow features with rich detailed information with deep features rich in strong semantic information. Since the fusion algorithm directly uses the existing information of the feature extraction network, there is no additional calculation. The fused features contain more original detailed feature information. Therefore, the improved Faster RCNN can improve the final detection rate without sacrificing speed. By comparing with the original Faster RCNN model, the mean average precision (mAP) of the improved Faster RCNN is increased by 2.13%. The average precision (AP) of the first-level Auricularia auricula is almost unchanged at a high level. The AP of the second-level Auricularia auricula is increased by nearly 5%. And the third-level Auricularia auricula AP is increased by 1%. The improved Faster RCNN improves the frames per second from 6.81 of the original Faster RCNN to 13.5. Meanwhile, the influence of complex environment and image resolution on the Auricularia auricula detection is explored.

The white rot basidiomycete Gelatoporia subvermispora produces fatty aldehydes that enable fungal manganese peroxidases to degrade recalcitrant lignin structures

The ability of some white rot basidiomycetes to remove lignin selectively from wood indicates that low molecular weight oxidants have a role in ligninolysis. These oxidants are likely free radicals generated by fungal peroxidases from compounds in the biodegrading wood. Past work supports a role for manganese peroxidases (MnPs) in the production of ligninolytic oxidants from fungal membrane lipids. However, the fatty acid alkylperoxyl radicals initially formed during this process are not reactive enough to attack the major structures in lignin. Here, we evaluate the hypothesis that the peroxidation of fatty aldehydes might provide a source of more reactive acylperoxyl radicals. We found that Gelatoporia subvermispora produced trans-2-nonenal, trans-2-octenal, and n-hexanal (a likely metabolite of trans-2,4-decadienal) during the incipient decay of aspen wood. Fungal fatty aldehydes supported the in vitro oxidation by MnPs of a nonphenolic lignin model dimer, and also of the monomeric model veratryl alcohol. Experiments with the latter compound showed that the reactions were partially inhibited by oxalate, the chelator that white rot fungi employ to detach Mn3+ from the MnP active site, but nevertheless proceeded at its physiological concentration of 1 mM. The addition of catalase was inhibitory, which suggests that the standard MnP catalytic cycle is involved in the oxidation of aldehydes. MnP oxidized trans-2-nonenal quantitatively to trans-2-nonenoic acid with the consumption of one O2 equivalent. The data suggest that when Mn3+ remains associated with MnP, it can oxidize aldehydes to their acyl radicals, and the latter subsequently add O2 to become ligninolytic acylperoxyl radicals.IMPORTANCEThe biodegradation of lignin by white rot fungi is essential for the natural recycling of plant biomass and has useful applications in lignocellulose bioprocessing. Although fungal peroxidases have a key role in ligninolysis, past work indicates that biodegradation is initiated by smaller, as yet unidentified oxidants that can infiltrate the substrate. Here, we present evidence that the peroxidase-catalyzed oxidation of naturally occurring fungal aldehydes may provide a source of ligninolytic free radical oxidants.

Flavor production in fermented chayote inoculated with lactic acid bacteria strains: Genomics and metabolomics based analysis

In this study, genomics and metabolomics were combined to reveal possible bio-synthetic pathways of core flavor compounds in pickled chayote via lactic acid bacteria (LAB) fermentation. The Lactiplantibacillus plantarum, Levilactobacillus brevis, and Lacticaseibacillus paracasei were selected as core LAB strains with better flavor-producing ability for chayote fermentation. The genomic results showed L. plantarum contained the largest number of metabolism annotated genes, while L. brevis had the fewest. Besides, the largest number of volatile compounds was detected in chayote fermented by L. plantarum, followed by L. brevis and L. paracasei. Some unique odor-active compounds (aldehydes, esters, and alcohols) and taste-active compounds (amino acids and dipeptides) were produced by different LAB strains. Accordingly, phenylalanine metabolic pathway (M00360), amino acid metabolic decomposition pathway (the Ehrlich pathway) and the anabolic pathway (the Harris pathway), and fatty acid biosynthesis pathway (M00061) were the main biosynthesis pathway involved in the flavor formation via LAB fermentation.

The flavors of edible mushrooms: A comprehensive review of volatile organic compounds and their analytical methods

Due to their distinctive flavors, edible mushrooms have gained attention in flavor-related research, and the quality of their flavors determines their consumption. The odor is a vital element of food flavor that significantly impacts consumers' perceptions and purchase decisions. The volatile organic compounds (VOCs) of the odorant ingredient is the primary factors affecting scent characteristics. VOCs analysis and identification require technical assistance. The production and use of edible mushrooms can be aided by a broader examination of their volatile constituents. This review discusses the composition of VOCs in edible mushrooms and how they affect flavors. The principles, advantages, and disadvantages of various methods for extraction, isolation, and characterization of the VOCs of edible mushrooms are also highlighted. The numerous VOCs found in edible mushrooms such as primarily C-8 compounds, organic sulfur compounds, aldehydes, ketones, alcohols, and esters are summarized along with their effects on the various characteristics of scent. Combining multiple extraction, isolation, identification, and quantification technologies will facilitate rapid and accurate analysis of VOCs in edible mushrooms as proof of sensory attributes and quality.

Analysis of Volatile Components in Tremella fuciformis by Electronic Nose Combined with GC-MS

In order to quickly evaluate the quality of Tremella fuciformis, the volatile components of T. fuciformis from 4 provinces in China, including Hebei, Henan, Fujian, and Sichuan, were analyzed by electronic nose combined with gas chromatography-mass spectrometry (GC-MS), and the key aroma compounds were determined by relative odor activity value (ROAV). The results showed that the electronic nose combined with the principal component analysis method could distinguish the samples from four regions with good discrimination. At least 117 volatile components were detected in T. fuciformis by GC-MS and a total of 58, 59, 62, and 55 volatile components were identified from Hebei, Henan, Fujian, and Sichuan, respectively, of which there were 18 common components. The volatile components in T. fuciformis were mainly hydrocarbons, followed by aldehydes, acids, and esters, while acetic acid and hexanal were relatively rich in T. fuciformis. Based on the ROAV, 8 key components affecting the aroma of T. fuciformis strongly were found. Among them, hexanal, nonanal, and pentanal were the common components of T. fuciformis, while butyrolactone, 1-octen-3-ol, and 2-carene were the unique key aroma components of T. fuciformis in Hebei Province. Besides, octanal and butyrolactone were the special key components absent in the Sichuan and Henan samples, respectively.