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Acoustic dataset of coconut (Cocos nucifera) based on tapping system

During the fruit sample preparation process, coconut fruits classified under the tall coconut variety in their post-harvest period are considered the subject of this article. All samples are pre-classified by local farmers and experts into three maturity levels; premature, mature, and overmature. Ea...

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Detalles Bibliográficos
Autores principales: Caladcad, June Anne, Piedad, Eduardo Jr
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9926183/
https://www.ncbi.nlm.nih.gov/pubmed/36798598
http://dx.doi.org/10.1016/j.dib.2023.108936
Descripción
Sumario:During the fruit sample preparation process, coconut fruits classified under the tall coconut variety in their post-harvest period are considered the subject of this article. All samples are pre-classified by local farmers and experts into three maturity levels; premature, mature, and overmature. Each coconut underwent the synchronized tapping and recording process using developed hardware and software. The analog recordings are then converted into digital signals. Sampled frequency and amplitude in discrete-time signals of each sample went through a quantization process. The data presented in this article provides the general differentiation of the coconuts according to their maturity levels through their acoustic properties. This dataset can also be useful in creating an advanced and intelligent classification system of fruits through machine learning and deep learning techniques.