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

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

SUSTAINABILITY(2023)

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摘要
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 Para 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, Para 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.
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关键词
VIS/NIR spectroscopy,machine learning,Brazil nut tree,sustainable extractions
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