Raft, Y.Z.; writing–Appl. Sci. 2021, 11,11 ofInstitutional Critique Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: Data sharing isn’t applicable to this short article. Conflicts of Interest: The authors declare no conflict of interest.
applied sciencesArticleEvaluation of Mushrooms Based on FT-IR Fingerprint and ChemometricsIoana Feher 1 , Cornelia Veronica Ganoderic acid N Technical Information Floare-Avram 1, , Florina-Dorina Covaciu 1 , Olivian Marincas 1 , Romulus Puscas 1 , Dana Alina Magdas 1 and Costel S buNational Institute for Analysis and Improvement of Isotopic and Molecular Technologies, 67-103 Donat Street, 400293 Cluj-Napoca, Romania; [email protected] (I.F.); [email protected] (F.-D.C.); [email protected] (O.M.); [email protected] (R.P.); [email protected] (D.A.M.) Faculty of Chemistry and Chemical Engineering, Babes-Bolyai University, 11 Arany J os, , 400028 Cluj-Napoca, Romania; [email protected] Correspondence: [email protected]: Feher, I.; Floare-Avram, C.V.; Covaciu, F.-D.; Marincas, O.; Puscas, R.; Magdas, D.A.; S bu, C. Evaluation of Mushrooms Based on FT-IR Fingerprint and Chemometrics. Appl. Sci. 2021, 11, 9577. https:// doi.org/10.3390/appAbstract: Edible mushrooms have been recognized as a very nutritional food to get a long time, due to their precise flavor and Hexazinone Autophagy texture, also as their therapeutic effects. This study proposes a brand new, simple strategy according to FT-IR analysis, followed by statistical strategies, in order to differentiate three wild mushroom species from Romanian spontaneous flora, namely, Armillaria mellea, Boletus edulis, and Cantharellus cibarius. The preliminary data therapy consisted of information set reduction with principal element analysis (PCA), which supplied scores for the following approaches. Linear discriminant analysis (LDA) managed to classify one hundred on the 3 species, and the cross-validation step from the strategy returned 97.four of properly classified samples. Only one A. mellea sample overlapped on the B. edulis group. When kNN was used in the exact same manner as LDA, the all round percent of correctly classified samples in the training step was 86.21 , while for the holdout set, the percent rose to 94.74 . The lower values obtained for the training set were as a result of one C. cibarius sample, two B. edulis, and 5 A. mellea, which had been placed to other species. In any case, for the holdout sample set, only 1 sample from B. edulis was misclassified. The fuzzy c-means clustering (FCM) analysis successfully classified the investigated mushroom samples based on their species, meaning that, in each partition, the predominant species had the largest DOMs, whilst samples belonging to other species had lower DOMs. Keyword phrases: mushrooms; FT-IR; chemometric; machine mastering; fuzzy c-means clusteringAcademic Editor: Alessandra Durazzo Received: 24 September 2021 Accepted: 13 October 2021 Published: 14 October1. Introduction Edible mushrooms happen to be recognized as a very nutritional meals to get a extended time, due to their precise flavor and texture, as well as their therapeutic effects. From the nutritional point of view, mushrooms represent an important source of proteins, fibers, minerals, and polyunsaturated fatty acids, with large variations in their proportions among distinct species. With regards to vitamin content, it represents the only vegetarian supply of vitamin D [1] at the same time as a crucial supply of B group vitamins [2]. Mor.
