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• W3205058754 abstract "Colombian coffee production is well-known, and selective manual harvesting plays a vital task in guaranteeing high ripe coffee fruit rates in this process, leading to its known worldwide aroma and flavor. To maintain this quality approach, selective harvesting methods based on mechanical vibrations are a promising alternative for developing technologies that could accomplish the challenging Colombian coffee production context. In this study, a vibrations analysis in coffee fruits at three ripening stages was carried out to evaluate the dynamic behavior at two frequency windows: 10 to 100 Hz and 100 to 1000 Hz. Two groups of fruits previously classified in the CIELab color space were chosen for the vibration test study samples. Time and frequency signals were characterized via FFT (fast Fourier transform), and bump wavelets were determined to obtain the frequency–time magnitude scalograms. The measurements were obtained in three degrees of freedom over the fruits: one for measuring the input force (computed in voltage way) and the other two measured by the velocity. The results revealed frequency ranges with specific resonant peaks between 24 and 45 Hz, and close to 700 Hz, where the ripe fruits presented higher magnitudes in the calculated parameters. FFT of the velocity and scaled mechanical impedance were used to estimate these frequency ranges. This work is an important step to identify a “vibrational fingerprint” of each Coffea arabica var. Castillo fruit-ripening stage. However, we consider that more experiments should be performed to reconstruct the modal shape in each resonance. In future studies, fatigue analysis could show which are the most effective frequency ranges to detach the ripe fruits from the perspective of a real selective coffee-harvesting scenario." @default.
• W3205058754 created "2021-10-25" @default.
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• W3205058754 date "2021-10-08" @default.
• W3205058754 modified "2023-10-02" @default.
• W3205058754 title "Vibrations Analysis of the Fruit-Pedicel System of Coffea arabica var. Castillo Using Time–Frequency and Wavelets Techniques" @default.
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• W3205058754 doi "https://doi.org/10.3390/app11199346" @default.
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