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Provenance Identification of Leaves and Nuts of Bertholletia excelsa Bonpl by Near-Infrared Spectroscopy and Color Parameters for Sustainable Extraction

Nisgoski, Silvana ; dos Santos, Joielan Xipaia ; Vieira, Helena Cristina ; Naide, Tawani Lorena ; Stange, Rafaela ; Silva, Washington Duarte Silva da ; Souza, Deivison Venicio ; Gama, Natally Celestino ; Hamada, Márcia Orie de Souza

Sustainability, 2023-11, Vol.15 (21), p.15606 [Periódico revisado por pares]

Basel: MDPI AG

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  • Título:
    Provenance Identification of Leaves and Nuts of Bertholletia excelsa Bonpl by Near-Infrared Spectroscopy and Color Parameters for Sustainable Extraction
  • Autor: Nisgoski, Silvana ; dos Santos, Joielan Xipaia ; Vieira, Helena Cristina ; Naide, Tawani Lorena ; Stange, Rafaela ; Silva, Washington Duarte Silva da ; Souza, Deivison Venicio ; Gama, Natally Celestino ; Hamada, Márcia Orie de Souza
  • Assuntos: Community ; Drinking water ; Forest products ; Leaves ; Moisture content ; Morphology ; Nuts ; Spectrum analysis ; Sustainability ; Timber ; Trees
  • É parte de: Sustainability, 2023-11, Vol.15 (21), p.15606
  • Descrição: The Brazil nut tree is considered symbolic of the Brazilian Amazon in function of its great importance, being one of the most significant extractivist products and a subsistence practice of the Indigenous people in many municipalities in Pará state. One of the main problems in different communities is related to the marketing process since it is not possible to distinguish the origin of the nuts and this causes inconvenience. The study evaluated the potential of VIS/NIR spectroscopy to identify the origin of leaves and nuts from Brazil nut trees growing in two indigenous villages, in the Xipaya Indigenous Lands, Pará state. Analysis was performed based on CIEL*a*b* parameters and using VIS (360–740 nm) and near-infrared spectra (1000–2500 nm). The samples were differentiated according to means tests, principal component analysis (PCA), and classification analysis based on k-NN. Color parameters and spectra were similar in both communities. Classification models based on k-NN produced adequate results for the distinction of villages in all evaluated situations, with accuracy of 98.54% for leaves, 89% and 90.91% for nuts with and without shell, respectively. Near infrared can be applied in forests as a technique for previous provenance identification and contribute to the subsistence and sustainable practice of extraction.
  • Editor: Basel: MDPI AG
  • Idioma: Inglês
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  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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