Estimation of the basic density of Eucalyptus grandis wood chips at different moisture levels using benchtop and handheld NIR instruments

Medeiros, Dayane Targino de; Gomes, Jhennyfer Nayara Nogueira; Batista, Felipe Gomes; Mascarenhas, Adriano Reis Prazeres; Pimenta, Emanuella Mesquita; Chaix, Gilles; Hein, Paulo Ricardo Gherardi

doi:10.1016/j.indcrop.2023.117921

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

2025

Publication Types

Select...

Article2

Preprint1

Relationship

Self Cite1

Independent2

Authors

Journals

Cited by 3 publications

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Rapid identification of scoured protein fibers using near-infrared spectroscopy with machine learning: A comparison of handheld and benchtop devices

Ping,

Yuchao,

Peiling

et al. 2025

Microchemical Journal

View full text Add to dashboard Cite

Rapid identification of scoured protein fibers using near-infrared spectroscopy with machine learning: A comparison of handheld and benchtop devices

Ping,

Yuchao,

Peiling

et al. 2025

Microchemical Journal

View full text Add to dashboard Cite

NIR-based models for the evaluation of basic density, moisture and higher heating value of industrial wood chips

Vieira Nunes,

Dias,

Baldin

et al. 2024

Wood Material Science & Engineering

View full text Add to dashboard Cite

Impact of surface quality on the identification of tropical wood species using benchtop and portable NIR instruments

Huancas,

Medeiros,

Dias

et al. 2024

Preprint

Self Cite

View full text Add to dashboard Cite

Near-infrared (NIR) spectroscopy combined with multivariate analysis has proven to be a fast and efficient method for identifying wood species. Despite significant technical advances in recent years, challenges remain that limit its application in field conditions, particularly the influence of sample surface preparation on the performance of classification models. This study aimed to evaluate the impact of wood surface quality on the performance of NIR instruments in identifying tropical wood species. Wood samples were collected from fields and log yards and prepared using different tools. NIR spectra were recorded using portable and benchtop NIR instruments on the transverse surfaces of wood specimens subjected to five treatments: (1) field conditions (untreated), (2) chainsaw, (3) circular saw, (4) bandsaw, and (5) sandpaper. Principal Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA) were performed using the NIR signatures. Spectra collected from surfaces prepared with a circular saw and sandpaper showed clearer groupings in the PCA score plot, facilitating the identification of distinct wood species. Cross-validated PLS-DA models showed high success rates, with classification accuracies ranging from 95.3% to 99.2% for untreated, circular saw, bandsaw, and sanded surfaces. Wood surfaces prepared with a chainsaw yielded lower classification accuracies: 88.7% for benchtop and 92.8% for portable NIR sensors. These results highlight the potential of NIR spectroscopy for classifying tropical woods, even when surface quality varies.

show abstract

Estimation of the basic density of Eucalyptus grandis wood chips at different moisture levels using benchtop and handheld NIR instruments

Cited by 3 publications

References 34 publications

Rapid identification of scoured protein fibers using near-infrared spectroscopy with machine learning: A comparison of handheld and benchtop devices

Rapid identification of scoured protein fibers using near-infrared spectroscopy with machine learning: A comparison of handheld and benchtop devices

NIR-based models for the evaluation of basic density, moisture and higher heating value of industrial wood chips

Impact of surface quality on the identification of tropical wood species using benchtop and portable NIR instruments

Contact Info

Product

Resources

About