Fresh Biomass Estimation of Lavender (Lavandula spp.) Using UAV-Based RGB Imagery, Volumetric Features and Random Forest Regression

Fatih Bozkurt; Mustafa Teke; Fecir Duran

doi:10.29137/ijerad.1946770

Fresh Biomass Estimation of Lavender (Lavandula spp.) Using UAV-Based RGB Imagery, Volumetric Features and Random Forest Regression

Abstract

For high value-added aromatic plants such as lavender, accurate wet biomass estimation is critical in order to minimize essential oil losses caused by waiting time in post-harvest distillation processes and to optimize logistics operations. This study proposes a non-destructive machine learning model using Unmanned Aerial Vehicle (UAV) based RGB images to overcome the existing methodological limitations in the literature. Within the scope of the research, extended HSV segmentation and elliptic morphological filtering were applied on 224 images obtained from 64 different individual lavender plants. Logarithmic volume attributes were extracted from the pixel areas normalized according to the flight altitude and the Random Forest algorithm was trained on the dataset, which was expanded to 896 samples with data augmentation. The analyses revealed that the integration of traditional two-dimensional spectral indices such as CIVE and VARI into the model relatively weakened the predictive performance (explained variance of 58.1%). In contrast, the model based on the proposed three-dimensional volumetric features demonstrated a Mean Absolute Error (MAE) of 171.55 grams, explaining 59.74% (R2) of the variance. This model offers the potential of a decision support system for agricultural yield planning and industrial process management.

Keywords

Lavender, Fresh Biomass Estimation, UAV RGB Imagery, Random Forest Regression, Precision Agriculture, Image Processing

Ethical Statement

This article does not contain any studies with animal or human participants performed by any of the authors.

Thanks

We would like to thank Prof. Dr Ercüment Osman SARIHAN for his valuable guidance throughout this study, both on the technical aspects of the lavender plant and on its agricultural applications.

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Details

Primary Language

English

Subjects

Software Engineering (Other)

Journal Section

Research Article

Authors

Fatih Bozkurt ^*
0000-0001-8687-4275
Türkiye

Mustafa Teke
0000-0002-7262-4918
Türkiye

Fecir Duran
0000-0001-7256-5471
Türkiye

Publication Date

July 31, 2026

Submission Date

May 7, 2026

Acceptance Date

June 3, 2026

Published in Issue

Year 2026 Volume: 18 Number: 4

DOI

https://doi.org/10.29137/ijerad.1946770

IZ

https://izlik.org/JA44DG54RS

APA

Bozkurt, F., Teke, M., & Duran, F. (2026). Fresh Biomass Estimation of Lavender (Lavandula spp.) Using UAV-Based RGB Imagery, Volumetric Features and Random Forest Regression. International Journal of Engineering Research and Development, 18(4), 80-94. https://doi.org/10.29137/ijerad.1946770

AMA

1.Bozkurt F, Teke M, Duran F. Fresh Biomass Estimation of Lavender (Lavandula spp.) Using UAV-Based RGB Imagery, Volumetric Features and Random Forest Regression. IJERAD. 2026;18(4):80-94. doi:10.29137/ijerad.1946770

Chicago

Bozkurt, Fatih, Mustafa Teke, and Fecir Duran. 2026. “Fresh Biomass Estimation of Lavender (Lavandula Spp.) Using UAV-Based RGB Imagery, Volumetric Features and Random Forest Regression”. International Journal of Engineering Research and Development 18 (4): 80-94. https://doi.org/10.29137/ijerad.1946770.

EndNote

Bozkurt F, Teke M, Duran F (July 1, 2026) Fresh Biomass Estimation of Lavender (Lavandula spp.) Using UAV-Based RGB Imagery, Volumetric Features and Random Forest Regression. International Journal of Engineering Research and Development 18 4 80–94.

IEEE

[1]F. Bozkurt, M. Teke, and F. Duran, “Fresh Biomass Estimation of Lavender (Lavandula spp.) Using UAV-Based RGB Imagery, Volumetric Features and Random Forest Regression”, IJERAD, vol. 18, no. 4, pp. 80–94, July 2026, doi: 10.29137/ijerad.1946770.

ISNAD

Bozkurt, Fatih - Teke, Mustafa - Duran, Fecir. “Fresh Biomass Estimation of Lavender (Lavandula Spp.) Using UAV-Based RGB Imagery, Volumetric Features and Random Forest Regression”. International Journal of Engineering Research and Development 18/4 (July 1, 2026): 80-94. https://doi.org/10.29137/ijerad.1946770.

JAMA

1.Bozkurt F, Teke M, Duran F. Fresh Biomass Estimation of Lavender (Lavandula spp.) Using UAV-Based RGB Imagery, Volumetric Features and Random Forest Regression. IJERAD. 2026;18:80–94.

MLA

Bozkurt, Fatih, et al. “Fresh Biomass Estimation of Lavender (Lavandula Spp.) Using UAV-Based RGB Imagery, Volumetric Features and Random Forest Regression”. International Journal of Engineering Research and Development, vol. 18, no. 4, July 2026, pp. 80-94, doi:10.29137/ijerad.1946770.

Vancouver

1.Fatih Bozkurt, Mustafa Teke, Fecir Duran. Fresh Biomass Estimation of Lavender (Lavandula spp.) Using UAV-Based RGB Imagery, Volumetric Features and Random Forest Regression. IJERAD. 2026 Jul. 1;18(4):80-94. doi:10.29137/ijerad.1946770

Kırıkkale University, Faculty of Engineering and Natural Science, 71450 Yahşihan / Kırıkkale, Türkiye.

ijerad@kku.edu.tr

Fresh Biomass Estimation of Lavender (Lavandula spp.) Using UAV-Based RGB Imagery, Volumetric Features and Random Forest Regression

Abstract

Keywords

Ethical Statement

Thanks

References

Details

Primary Language

Subjects

Journal Section

Authors

Publication Date

Submission Date

Acceptance Date

Published in Issue

DOI

IZ

Cite