Avocado (Persea americana) volume estimation using mathematical profiling with arduino uno and ultrasonic sensor

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Miguel Ángel Lema-Carrera
Nidia Gabriela Collins-Melgar
Alejandro Sebastián Sánchez-Mendoza

Abstract

The volume of avocado (Persea americana) was estimated using mathematical profiling and water displacement methods. In the mathematical profiling, digital images were used and modeled using polynomial functions in Geogebra software, obtaining an average function that was implemented in an Arduino Uno card, where the volume of the fruit is obtained as a function of its length, measured by an HCSR04 ultrasonic sensor. The estimated volume was compared with that obtained by water displacement, based on Archimedes' physical principle. The statistical t-test for paired samples and the Bland-Altman analysis were applied, finding that there were no statistically significant differences between methods (P > 0.05), with an average difference of 5.28 cm³ (95% CI: -2.78 cm³ a 13.33 cm³). Mathematical profiling, together with its implementation on Arduino Uno, provides a fast, inexpensive and portable solution to estimate the volume of avocados, applicable in agricultural environments. 

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How to Cite
Lema-Carrera , M. ., Collins-Melgar , N. ., & Sánchez-Mendoza , A. . (2025). Avocado (Persea americana) volume estimation using mathematical profiling with arduino uno and ultrasonic sensor . 593 Digital Publisher CEIT, 10(1), 316-325. https://doi.org/10.33386/593dp.2025.1.2858
Section
Investigaciones /estudios empíricos
Author Biographies

Miguel Ángel Lema-Carrera , Universidad Estatal de Milagro “UNEMI” / Universidad de las Fuerzas Armadas “ESPE” - Ecuador

https://orcid.org/0000-0001-7934-8891

Electronic and Control Engineer from Escuela Politécnica Nacional. Master in Physics and Mathematics from the University of Castilla-La Mancha, Spain. With over 10 years of experience as a university professor in the field of exact sciences. He has supervised multiple engineering thesis projects and led two research initiatives focused on the application of technology in agricultural sciences. His experience combines solid academic training with a dedication to the development and dissemination of knowledge in higher education. 

Nidia Gabriela Collins-Melgar , Unidad Educativa Fiscomisional “Americano” - Ecuador

https://orcid.org/0009-0005-9181-1531

Agricultural Engineer graduated from the Universidad Estatal Península de Santa Elena with a Master's degree in Educational Management from Cesar Vallejo University, currently pursuing a Master's degree in Didactics of Physics and Mathematics at the National University of Callao. A professional with a solid career of 8 years in both the public and private sectors, with educational experience and practical application of acquired knowledge, covering the fields of exact sciences, mathematics, physics, chemistry, and biology. Additionally, collaborated on agricultural projects with public and private companies. 

Alejandro Sebastián Sánchez-Mendoza , Universidad Estatal de Milagro - Ecuador

https://orcid.org/0009-0002-0618-3162

Mechanical Engineer graduated from the Technical University of Ambato with a master's degree in Renewable Energies. A professional with a solid career in both the public and private sectors, with experience in academia and the practical application of acquired knowledge, covering fields such as exact sciences, mathematics, physics, and chemistry. Additionally, has collaborated in mechanical maintenance work, thermographic studies, and the development of clean energy technologies. 

References

​​Abraham, J. D., Abraham, J., & Takrama, J. F. (2018). Morphological characteristics of avocado (Persea americana Mill.) in Ghana. African Journal of Plant Science, 12(April), 88–97. https://doi.org/10.5897/AJPS2017.1625

​Babic, L., Matic-Kekic, S., Dedovic, N., Babic, M., & Pavkov, I. (2012). Surface area and volume modeling of the williams pear (Pyrus Communis). International Journal of Food Properties, 15(4), 880–890. https://doi.org/10.1080/10942912.2010.506020

​Bland, J. M., & Altman, D. G. (1999). Measuring agreement in method comparison studies. Statistical Methods in Medical Research, 8(2), 135–160. https://doi.org/10.1177/096228029900800204

​Calvache, G. (1995). Geometria plana y del espacio: geometria analitica dibujo. se.

​Concha-Meyer, A., Eifert, J., Wang, H., Sanglay, G., & Meyer, C. (2018). Volume estimation of strawberries, mushrooms, and tomatoes with a machine vision system. International Journal of Food Properties, 21(1), 1867–1874. https://doi.org/10.1080/10942912.2018.1508156

​FAO.2023. (2022). FAO. 2023. Principales Frutas Tropicales. Análisis del mercado. Resultados preliminares 2022. Roma. FAO.2023., 35.

​Forero, M. G., Gómez, F., & Ramírez, M. (2019). Hass avocado classification by color and volume using a Kinect sensor. Applications of Digital Image Processing XLII, 11137, 465–471.

​Hahn, F., & Sanchez, S. (2000). Carrot volume evaluation using imaging algorithms. Journal of Agricultural and Engineering Research, 75(3), 243–249. https://doi.org/10.1006/jaer.1999.0466

​Hu, M. H., Dong, Q. L., Malakar, P. K., Liu, B. L., & Jaganathan, G. K. (2015). Determining banana size based on computer vision. International Journal of Food Properties, 18(3), 508–520. https://doi.org/10.1080/10942912.2013.833223

​Huynh, T. T. M., Tonthat, L., & Dao, S. V. T. (2022). A vision-based method to estimate volume and mass of fruit / vegetable : Case study of sweet potato A vision-based method to estimate volume and mass of fruit / vegetable : Case study of sweet potato. International Journal of Food Properties, 25(1), 717–732. https://doi.org/10.1080/10942912.2022.2057528

​Jadhav, T., Singh, K., & Abhyankar, A. (2019). Volumetric estimation using 3D reconstruction method for grading of fruits. Multimedia Tools and Applications, 78(2), 1613–1634. https://doi.org/10.1007/s11042-018-6271-3

​Kadri Bozokalfa, M., & Kilic, M. (2010). Mathematical Modeling in the Estimation of Pepper (Capsicum annuum L.) Fruit Volume. Chilean Journal of Agricultural Research, 70(4), 626–632. https://doi.org/10.4067/s0718-58392010000400013

​Koc, A. B. (2007). Determination of watermelon volume using ellipsoid approximation and image processing. Postharvest Biology and Technology, 45(3), 366–371. https://doi.org/10.1016/j.postharvbio.2007.03.010

​Mon, T. O., & ZarAung, N. (2020). Vision based volume estimation method for automatic mango grading system. Biosystems Engineering, 198, 338–349. https://doi.org/10.1016/j.biosystemseng.2020.08.021

​Nyalala, I., Okinda, C., Nyalala, L., Makange, N., Chao, Q., Chao, L., Yousaf, K., & Chen, K. (2019). Tomato volume and mass estimation using computer vision and machine learning algorithms: Cherry tomato model. Journal of Food Engineering, 263(July), 288–298. https://doi.org/10.1016/j.jfoodeng.2019.07.012

​Orhevba, B. A., & Jinadu, A. O. (2011). Determination of Physico-Chemical Properties and Nutritional Contents of Avocado Pear ( Persea Americana M .). Academic Research International ISSN:, 1(3), 372–381. www.savap.org.pkwww.journals.savap.org.pk

​Rashidi, M., Gholami, M., & Abbassi, S. (2009). Cantaloupe volume determination through image processing. Journal of Agricultural Science and Technology, 11(5), 623–631.

​Silva, M. V. G., de Almeida, C., Lino, A. C. L., & Fabbro, I. M. D. (2015). Fruit volumetric determination based on moiré techniques. INMATEH - Agricultural Engineering, 45(1), 95–100.

​Thomas, G. B., Weir, M. D., Hass, J., Giordano, F. R., & Korkmaz, R. (2010). Thomas’ calculus (Vol. 12). Pearson Boston.

​Uribe, L.-, Alejandra, N., & Torres-garcía, B. (2019). Modelo de Aprendizaje para Arduino Uno Básico. Revista de Cómputo Aplicado, 3(10), 15–22.

​Urquiza, P., Sebastián, L., Rebollar, R., Juárez, C., Martínez, H., & Tenorio, G. (2015). ANÁLISIS DE VIABILIDAD ECONÓMICA PARA LA PRODUCCIÓN COMERCIAL DE AGUACATE HASS. Revista Mexicana de Agronegocios, 36(1), 1325–1338.

​Venkatesh, G. V., Iqbal, S. M., Gopal, A., & Ganesan, D. (2015). Estimation of Volume and Mass of Axi-Symmetric Fruits Using Image Processing Technique. International Journal of Food Properties, 18(3), 608–626. https://doi.org/10.1080/10942912.2013.831444

​Villordon, A., Gregorie, J. C., & LaBonte, D. (2020). Direct measurement of sweetpotato surface area and volume using a low-cost 3D scanner for identification of shape features related to processing product recovery. HortScience, 55(5), 722–728. https://doi.org/10.21273/HORTSCI14964-20

​Zavala de Paz, J. P., Bucio Castillo, F. J., Anaya Rivera, E. K., Isaza Bohorquez, C. A., Castillo Velásquez, F. A., & Rizzo Sierra, J. A. (2021). Estimating Volume of the Tomato Fruit by 3D Reconstruction Technique. Computacion y Sistemas, 25(4), 813–820. https://doi.org/10.13053/CyS-25-4-4043

​Zhang, B., Guo, N., Huang, J., Gu, B., & Zhou, J. (2020). Computer Vision Estimation of the Volume and Weight of Apples by Using 3D Reconstruction and Noncontact Measuring Methods. Journal of Sensors, 2020. https://doi.org/10.1155/2020/5053407

​Ziaratban, A., Azadbakht, M., & Ghasemnezhad, A. (2017). Modeling of volume and surface area of apple from their geometric characteristics and artificial neural network. International Journal of Food Properties, 20(4), 762–768. https://doi.org/10.1080/10942912.2016.1180533

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