Banca de DEFESA: JHON HAROLD ESCUDERO

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
DISCENTE: JHON HAROLD ESCUDERO
DATA: 24/07/2026
HORA: 08:30
LOCAL: meet.google.com/gfs-gncz-szy
TÍTULO:

QUANTIFICATION OF BARK CONTENT AND QUALITY CLASSIFICATION IN Pinus spp. PELLETS: A NON-DESTRUCTIVE APPROACH USING NIR SPECTROSCOPY AND CIELAB COLORIMETRY

PALAVRAS-CHAVES:

Forest residues. Binary blends. Biomass densification. Chemometrics. Energy density.

PÁGINAS: 40
GRANDE ÁREA: Ciências Agrárias
ÁREA: Recursos Florestais e Engenharia Florestal
SUBÁREA: Tecnologia e Utilização de Produtos Florestais
RESUMO:

The incorporation of bark into sawdust pellets from Pinus spp. is a practice for valorizing forest residues, but it systematically alters the density, mechanical durability, and energy content of the final product. Conventional quality control relies on destructive and slow laboratory methods, which do not allow real-time verification of bark proportion or anticipation of quality deviations before pellet commercialization. Near-infrared (NIR) spectroscopy and CIELab colorimetry are non-destructive alternatives to this limitation, but no calibrations exist for binary bark-sawdust blends of Pinus spp. across the full compositional gradient. This thesis evaluated the potential of both techniques to quantify bark content and classify the physical, mechanical, and energy quality of pellets produced from these blends, between 0 and 100% bark. Eleven treatments (T0–T10) were prepared in 10% increments of bark. The physical-mechanical and energy properties of the pellet varied significantly among treatments (p < 0.001); the best balance between durability and energy density was obtained between 40 and 60% sawdust, although no treatment reached even the lowest mechanical durability threshold required by the ISO 17225-2 standard (class B, ≥96.5%). In the first article, benchtop NIR spectroscopy quantified bark content with near-perfect accuracy, both in biomass and in pellets (R²p between 0.997 and 0.998; RPDp between 18.92 and 21.84), and PLS-DA models classified bark content into high, medium, and low categories with an accuracy of between 97.98% and 99.60%, the latter in pellets processed with the first derivative. The physical-mechanical and energy properties of the pellet were better predicted from the pellet spectrum (R²p 0.710–0.974) than from the loose biomass before pelletization (R²p 0.513–0.807); moisture was the best-predicted property, while higher heating value and energy density were the weakest. In the second article, the b* coordinate of the CIELab system showed the strongest association with energy density (r = −0.89; R² = 0.79). The three functional classes, defined according to bark proportion, showed differentiated physical and energy profiles together with distinctive colorimetric ranges, with L* showing no overlap between classes and a* as the coordinate most associated with bark content; Class II (40–70% bark) reached the highest energy density in the system (13.47–14.32 GJ m⁻³). A principal component analysis, integrating these colorimetric, physical, and energy variables, confirmed the separation into three groups and explained 86.1% of the variance in its first three components. The results show that NIR spectroscopy, coupled with PLS-DA and PLS-R chemometric models, offers the highest precision for quantifying bark proportion in blends and pellets of Pinus spp., while CIELab colorimetry allows a fast and direct classification of energy quality on-site, using a portable colorimeter; both techniques have potential for integration into the industrial quality control of pellets produced from bark-sawdust blends.

MEMBROS DA BANCA:
Interno - THIAGO DE PAULA PROTASIO (Suplente)
Presidente - PAULO RICARDO GHERARDI HEIN (Membro)
Interno - PAULO FERNANDO TRUGILHO (Suplente)
Externo à Instituição - MICHAEL DOUGLAS ROQUE LIMA - UEMASUL (Membro)
Externo à Instituição - LÍVIA CÁSSIA VIANA - UFT (Suplente)
Externo à Instituição - EDILSON LEÓN MORENO CÁRDENAS - UNAL (Membro)
Externo à Instituição - ADRIANO REIS PRAZERES MASCARENHAS - UNIR (Membro)