DOI: 10.21950/obyucv
title: Acoustic Impulse Response for the detection of Internal Quality in Seedless Watermelon

description: &lt;p&gt;Recent commercialisation of seedless watermelon varieties relies on the guarantee of a high quality product. Several internal defects may deteriorate greatly this fruit: (a) creases and/or large voids in the flesh, (b) overripeness and (c) bruises due to impact. The objective of this research was to develop a feasible non-destructive procedure for detecting these defects in individual fruits, based on acoustic impulse response.&lt;/p&gt;
 
&lt;p&gt;A device consisting of a microphone, structural elements and a mechanical impact generator was designed and tested. Good and defective seedless watermelons were tested with the acoustic device. Spectral parameters were examined as potential non-destructive predictors of internal disorders. Waveband magnitude parameters, obtained by summing the magnitude of the spectrum between two frequencies in a specified band width (always including between 40 and 500 Hz), were the acoustic parameters showing the best ability to detect internal disorders. &lt;/p&gt;

&lt;p&gt;Dataset description&lt;/p&gt;
The acoustic response of 158 watermelons measured by hitting the fruit with an impactor and detecting the output sound by a microphone on the opposite side and 90º (as referred in derived publication and PhD thesis, see further details in this file)

&lt;p&gt;Metodology&lt;/p&gt;
&lt;p&gt;Each watermelon was acoustically excited on two positions, both around the equator and rotated 908. Nine measurements, divided in groups of three repetitions for the same location, together with three locations were performed at each position, therefore 18 measurements in each fruit. Positions identify the different areas of fruit where the impact is applied, locations indicate that the fruit is taken and relocated on the same position after some time, and repetitions refer to repeated data taken without changing or touching the fruit.&lt;/p&gt; 

&lt;p&gt;Acoustic measurements were taken with a device designed and tested by consecutive phases of approximation to the final solution. The laboratory recording system used to acquire the acoustic impulse information is comprised a prepolarised free-field 12mm microphone type 4189 B&K, of a frequency range from 6 3 to 20 kHz and a sensitivity of 50mVPa 1. A signal conditioning amplifier NEXUS B&K supplied power and provided electrical loading to the transducer, amplified the signal, provided appropriate output drive signal and facilitated the selection of the optimum band-pass filters. A microphone preamplifier type 2673 B&K completed the recording system. The preamplifier amplified the signal from the microphone. &lt;/p&gt;


&lt;p&gt;A user friendly Windows-based software, ‘SanSon 1 2’, was developed for the control of the process and the register of data, providing an easy output to be used with Microsoft Excel. The software shows in the screen the acoustic signal ‘time versus intensity’ for each test, and saves it in an ASCII file. &lt;/p&gt;

&lt;p&gt;A fast Fourier transform (FFT) of the signal was performed to determine the frequency spectrum, and subsequently, the natural frequencies of the watermelons. Sampling at 40 kHz for 4096 points results in a frequency resolution for the FFT of 9 766 Hz. A normalised spectrum was obtained by dividing the magnitude at each frequency by the maximum magnitude of the spectrum (see publication). Different acoustic parameters were evaluated for spectral characterisation: resonant frequency, maximum amplitude of the spectrum and band magnitude (BM) of the acoustic spectrum. The frequency resolution for the spectrum (9 766 Hz) is not very narrow. Therefore it is difficult to obtain a good segregation based on the resonant frequency, unless higher differences than the resolution occur between hollow and sound watermelons. This handicap may be overcome by defining the integral in the spectrum or BMs.&lt;/p&gt;
description: Estos datos se emplean en docencia para entender las propiedades físicas de los productos agrícolas y manejar estadística multivariante: PCA, MANIVA

Las muestras no son estables. Estos datos se emplean generalmente se vuelven a adquirir cada año en prácticas de la asignatura I+D+i y Agricultura de Precisión del Master Universitario de Sistemas Agrarios (UPM) https://blogs.upm.es/masteringenieriasistemasagrarios/