First Steps in Developing a Fast, Cheap, and Reliable Method to Distinguish Wild Mushroom and Truffle Species
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10451/61723 |
Resumo: | Wild mushrooms and truffles (MT) are important resources, which can contribute to the socioeconomic sustainability of forestry ecosystems. However, not all wild MT are edible. Fast, cheap, and reliable methods that distinguish wild MT species (including the deadly ones) can contribute to valuing these important forest resources. Here, we tested if wild MT species, and their edibility, could be distinguished based on their aroma profiles (i.e., smellprints). For that, we combined the use of the electronic nose with classification models (linear discriminant analysis (LDA) and partial least squares discriminant analysis (PLS-DA)) to distinguish between 14 wild MT species (including edible and non-edible species) collected in Portugal. The 14 wild MT species could be accurately distinguished using LDA (93% accuracy), while the edible and non-edible species could be accurately distinguished using both LDA and PLS-DA (97% and 99% accuracy, respectively). Keeping in mind that our methodological design’s feasibility was verified using a small sample, the data show the potential of the combined use of the electronic nose with discriminant analysis to distinguish wild MT species and their edibility based on their aromatic profile. Although a larger dataset will be necessary to develop a quick and reliable identification method, it shows potential to be as accurate as the identification performed by mycologists and molecular biology, yet requiring less technical training, and the analyses are cheaper and faster. |
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First Steps in Developing a Fast, Cheap, and Reliable Method to Distinguish Wild Mushroom and Truffle Specieselectronic nose; forest resources; identification method; volatile profile; wild mushrooms and trufflesWild mushrooms and truffles (MT) are important resources, which can contribute to the socioeconomic sustainability of forestry ecosystems. However, not all wild MT are edible. Fast, cheap, and reliable methods that distinguish wild MT species (including the deadly ones) can contribute to valuing these important forest resources. Here, we tested if wild MT species, and their edibility, could be distinguished based on their aroma profiles (i.e., smellprints). For that, we combined the use of the electronic nose with classification models (linear discriminant analysis (LDA) and partial least squares discriminant analysis (PLS-DA)) to distinguish between 14 wild MT species (including edible and non-edible species) collected in Portugal. The 14 wild MT species could be accurately distinguished using LDA (93% accuracy), while the edible and non-edible species could be accurately distinguished using both LDA and PLS-DA (97% and 99% accuracy, respectively). Keeping in mind that our methodological design’s feasibility was verified using a small sample, the data show the potential of the combined use of the electronic nose with discriminant analysis to distinguish wild MT species and their edibility based on their aromatic profile. Although a larger dataset will be necessary to develop a quick and reliable identification method, it shows potential to be as accurate as the identification performed by mycologists and molecular biology, yet requiring less technical training, and the analyses are cheaper and faster.MDPIRepositório da Universidade de LisboaFerreira, InêsDias, TeresaMelo, JulianaMouazen, Abdul MounemCruz, Cristina2024-01-10T19:07:55Z2023-112023-11-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10451/61723eng10.3390/resources12120139info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-01-15T01:18:29Zoai:repositorio.ul.pt:10451/61723Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:44:31.168197Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
First Steps in Developing a Fast, Cheap, and Reliable Method to Distinguish Wild Mushroom and Truffle Species |
title |
First Steps in Developing a Fast, Cheap, and Reliable Method to Distinguish Wild Mushroom and Truffle Species |
spellingShingle |
First Steps in Developing a Fast, Cheap, and Reliable Method to Distinguish Wild Mushroom and Truffle Species Ferreira, Inês electronic nose; forest resources; identification method; volatile profile; wild mushrooms and truffles |
title_short |
First Steps in Developing a Fast, Cheap, and Reliable Method to Distinguish Wild Mushroom and Truffle Species |
title_full |
First Steps in Developing a Fast, Cheap, and Reliable Method to Distinguish Wild Mushroom and Truffle Species |
title_fullStr |
First Steps in Developing a Fast, Cheap, and Reliable Method to Distinguish Wild Mushroom and Truffle Species |
title_full_unstemmed |
First Steps in Developing a Fast, Cheap, and Reliable Method to Distinguish Wild Mushroom and Truffle Species |
title_sort |
First Steps in Developing a Fast, Cheap, and Reliable Method to Distinguish Wild Mushroom and Truffle Species |
author |
Ferreira, Inês |
author_facet |
Ferreira, Inês Dias, Teresa Melo, Juliana Mouazen, Abdul Mounem Cruz, Cristina |
author_role |
author |
author2 |
Dias, Teresa Melo, Juliana Mouazen, Abdul Mounem Cruz, Cristina |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Repositório da Universidade de Lisboa |
dc.contributor.author.fl_str_mv |
Ferreira, Inês Dias, Teresa Melo, Juliana Mouazen, Abdul Mounem Cruz, Cristina |
dc.subject.por.fl_str_mv |
electronic nose; forest resources; identification method; volatile profile; wild mushrooms and truffles |
topic |
electronic nose; forest resources; identification method; volatile profile; wild mushrooms and truffles |
description |
Wild mushrooms and truffles (MT) are important resources, which can contribute to the socioeconomic sustainability of forestry ecosystems. However, not all wild MT are edible. Fast, cheap, and reliable methods that distinguish wild MT species (including the deadly ones) can contribute to valuing these important forest resources. Here, we tested if wild MT species, and their edibility, could be distinguished based on their aroma profiles (i.e., smellprints). For that, we combined the use of the electronic nose with classification models (linear discriminant analysis (LDA) and partial least squares discriminant analysis (PLS-DA)) to distinguish between 14 wild MT species (including edible and non-edible species) collected in Portugal. The 14 wild MT species could be accurately distinguished using LDA (93% accuracy), while the edible and non-edible species could be accurately distinguished using both LDA and PLS-DA (97% and 99% accuracy, respectively). Keeping in mind that our methodological design’s feasibility was verified using a small sample, the data show the potential of the combined use of the electronic nose with discriminant analysis to distinguish wild MT species and their edibility based on their aromatic profile. Although a larger dataset will be necessary to develop a quick and reliable identification method, it shows potential to be as accurate as the identification performed by mycologists and molecular biology, yet requiring less technical training, and the analyses are cheaper and faster. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-11 2023-11-01T00:00:00Z 2024-01-10T19:07:55Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10451/61723 |
url |
http://hdl.handle.net/10451/61723 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.3390/resources12120139 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
MDPI |
publisher.none.fl_str_mv |
MDPI |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799136940861161472 |