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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Potential of near-infrared spectroscopy for quality evaluation of cattle leather

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Author(s):
Braz, Carlos Eduardo M. [1, 2] ; Jacinto, Manuel Antonio C. [1] ; Pereira-Filho, Edenir R. [2] ; Souza, Gilberto B. [1] ; Nogueira, Ana Rita A. [1]
Total Authors: 5
Affiliation:
[1] Embrapa Pecuaria Sudeste, BR-13560970 Sao Carlos, SP - Brazil
[2] Univ Fed Sao Carlos, Dept Chem, GAIA, BR-13565905 Sao Carlos, SP - Brazil
Total Affiliations: 2
Document type: Journal article
Source: SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY; v. 202, p. 182-186, SEP 5 2018.
Web of Science Citations: 1
Abstract

Models using near-infrared spectroscopy (NIRS) were constructed based on physical-mechanical tests to determine the quality of cattle leather. The following official parameters were used, considering the industry requirements: tensile strength (TS), percentage elongation (%E), tear strength (TT), and double hole tear strength (DHS). Classification models were constructed with the use of k-nearest neighbor (kNN), soft independent modeling of class analogy (SIMCA), and partial least squares-discriminant analysis (PLS-DA). The evaluated figures of merit, accuracy, sensitivity, and specificity presented results between 85% and 93%, and the false alarm rates from 9% to 14%. The model with lowest validation percentage (92%) was kNN, and the highest was PLS-DA (100%). For TS, lower values were obtained, from 52% for kNN and 74% for SIMCA. The other parameters %E, TT, and DHS presented hit rates between 87 and 100%. The abilities of the models were similar, showing they can be used to predict the quality of cattle leather. (C) 2018 Elsevier B.V. All rights reserved. (AU)

FAPESP's process: 15/14488-0 - Analytical method development for quality determination of fertilizers and tanning waste
Grantee:Ana Rita de Araujo Nogueira
Support type: Regular Research Grants