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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Raw sugarcane classification in the presence of small solid impurity amounts using a simple and effective digital imaging system

Texto completo
Autor(es):
Guedes, Wesley Nascimento [1] ; Verbi Pereira, Fabiola Manhas [2, 1]
Número total de Autores: 2
Afiliação do(s) autor(es):
[1] Sao Paulo State Univ UNESP, Bioenergy Res Inst IPBEN, Inst Chem, BR-14800060 Sao Paulo - Brazil
[2] Idaho State Univ, Dept Chem, Pocatello, ID 83209 - USA
Número total de Afiliações: 2
Tipo de documento: Artigo Científico
Fonte: COMPUTERS AND ELECTRONICS IN AGRICULTURE; v. 156, p. 307-311, JAN 2019.
Citações Web of Science: 0
Resumo

Specific amounts of solid impurities in raw sugarcane need to be detected before raw materials are carried into mills. Solid impurities come from the plant, e.g., green and dry leaves and soil. This study proposed to classify sugarcane via a new strategy using a well-established method that combines digital images converted into ten color-scale color histograms of red (R), green (G) and blue (B), RGB; hue (H), saturation (S) and value (v), HSV; relative colors of RGB, rgb; and luminosity (L) with multivariate classification methods. Sampling was performed using a mixture design that comprised 122 different combinations of sugarcane stalks, vegetal plant parts and soil to achieve 100 wt% for evaluating the desirable and undesirable situations for the solid impurity amounts. Classical algorithms, such as soft independent modeling of class analogy (SIMCA), partial least squares discriminant analysis (PLS-DA) and k nearest neighbors (kNN), were used to perform the calculations. Receive operating characteristic (ROC) revealed the high sensitivity and specificity of the three algorithms using the color histogram data. The outstanding result was the ability to classify sugarcane content higher than 85 wt%, which is considered high-quality raw material by cane mills. (AU)

Processo FAPESP: 16/00779-6 - Obtenção direta de informações químicas de interesse comercial de matrizes analíticas sólidas diversificadas utilizando a espectroscopia de emissão com plasma induzido por laser (LIBS) e quimiometria
Beneficiário:Hideko Yamanaka
Modalidade de apoio: Auxílio à Pesquisa - Regular
Processo FAPESP: 17/05550-0 - Novas estratégias quimiométricas com o uso da regularização de Tikhonov para o ajuste fino de modelos de calibração multivariada
Beneficiário:Fabiola Manhas Verbi Pereira
Modalidade de apoio: Bolsas no Exterior - Pesquisa