<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This study aimed to test near-infrared spectroscopy to assess insect damage to oak acorns collected from a seed orchard of <italic>Quercus acuta</italic> in Jeju Island, Korea. A total of 550 acorns were sorted into 362 sound and 178 unsound (insect-damaged) acorns, followed by near-infrared spectroscopy. To minimize spectral data errors, preprocessing techniques such as first derivative, multiplicative scatter correction, standard normal variate, and Savitzky-Golay filter were applied, along with multivariate analysis methods like partial least squares. Then the model performance, including accuracy and precision, was evaluated using the Variable Importance in Projection. The near-infrared wavelength of the acorns showed strong absorption peaks at 660~720nm and a slight downward trend at 900~1000nm. The most effective model for distinguishing unsound acorns was Savitzky-Golay filtering treatment applied in the 400~1000nm range and used partial least squares, showing prediction accuracy of 86 % (p&lt;0.05). The performance was significantly influenced by absorption points at 660~720nm and 960~1000nm, with the latter range believed to be affected by changes in moisture and carbohydrates due to insect damage. The former range showed lower classification capability due to chlorophyll and color variation but affected the model performance when used with near-infrared wavelength range. These findings can narrow down the scope of investigation for future research using wider wavelength ranges or multispectral analysis.</p>
</abstract>

This study aimed to test near-infrared spectroscopy to assess insect damage to oak acorns collected from a seed orchard of Quercus acuta in Jeju Island, Korea. A total of 550 acorns were sorted into 362 sound and 178 unsound (insect-damaged) acorns, followed by near-infrared spectroscopy. To minimize spectral data errors, preprocessing techniques such as first derivative, multiplicative scatter correction, standard normal variate, and Savitzky-Golay filter were applied, along with multivariate analysis methods like partial least squares. Then the model performance, including accuracy and precision, was evaluated using the Variable Importance in Projection. The near-infrared wavelength of the acorns showed strong absorption peaks at 660~720nm and a slight downward trend at 900~1000nm. The most effective model for distinguishing unsound acorns was Savitzky-Golay filtering treatment applied in the 400~1000nm range and used partial least squares, showing prediction accuracy of 86 % (p<0.05). The performance was significantly influenced by absorption points at 660~720nm and 960~1000nm, with the latter range believed to be affected by changes in moisture and carbohydrates due to insect damage. The former range showed lower classification capability due to chlorophyll and color variation but affected the model performance when used with near-infrared wavelength range. These findings can narrow down the scope of investigation for future research using wider wavelength ranges or multispectral analysis.

Accuracy Evaluation of Visible-Near Infrared Spectroscopy for Detecting Insect Damage in Acorns of <italic>Quercus acuta</italic>

Department of Agriculture, Forestry and Bioresources

Department of Seed and Seedling Management

Silvae Genetica

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Accuracy Evaluation of Visible-Near Infrared Spectroscopy for Detecting Insect Damage in Acorns of 

This study aimed to test near-infrared spectroscopy to assess insect damage to oak acorns collected from a seed orchard of Quercus acuta in Jeju Island, Korea....

Accuracy Evaluation of Visible-Near Infrared Spectroscopy for Detecting Insect Damage in Acorns of Quercus acuta

Publicado en línea: 06 jul 2024

Páginas: 99 - 109

DOI: https://doi.org/10.2478/sg-2024-0010

Palabras clave
Quercus acuta, insect damage, near-infrared spectroscopy, multivariate analysis, nondestructive testing

© 2024 Gye-Hong Cho et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Accuracy Evaluation of Visible-Near Infrared Spectroscopy for Detecting Insect Damage in Acorns of Quercus acuta

Publicado en línea: 06 jul 2024

Páginas: 99 - 109

DOI: https://doi.org/10.2478/sg-2024-0010

Palabras claveQuercus acuta, insect damage, near-infrared spectroscopy, multivariate analysis, nondestructive testing

© 2024 Gye-Hong Cho et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Palabras clave
Quercus acuta, insect damage, near-infrared spectroscopy, multivariate analysis, nondestructive testing