Date of Award
5-1-2025
Document Type
Thesis
Department
Mathematics
First Reader
Dr. Kevin Cornelius
Second Reader
Dr. Johnny Wink
Third Reader
Dr. Jeff Matocha
Abstract
The main goal of this project was to determine the best sound frequencies produced from thumping a watermelon that predict sweetness. Building on previous research, a program using MATLAB would separate the thump signal into its corresponding harmonic frequencies using the Fast Fourier Transform (FFT). These frequencies, along with the watermelon's weight and other information from the FFT spectrum, are used to determine a correlation between the recorded data and a watermelon’s sweetness level, measured by a refractometer in Brix. After testing numerous watermelons, a linear regression model was developed to predict a watermelon’s potential sweetness, with promising results. This process has been programmed into an iPhone app so that testing can be done anywhere within seconds. The hope was to make the process available to the public so that they could regularly select better watermelons before leaving the store and cutting the watermelon, which we have achieved with a new iPhone app. A future goal is to continue to determine if the same regression model will work for similar melons, like cantaloupe and honeydew, as well as bring the app to the Android platform.
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Recommended Citation
New, Rachel, "Predicting Watermelon Sweetness from Induced Vibrations" (2025). Honors Theses. 989.
https://scholarlycommons.obu.edu/honors_theses/989
