Diseño de un método para la implementación de modelos estimativos de maduración de fruta de banano (Musa acuminata cavendish) mediante el uso del espectrómetro SCiO.
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2020-12
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Universidad EARTH
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El grado de maduración de la fruta de banano, es uno de los puntos que requiere más control en la producción de este cultivo, ya que está estrictamente relacionado con la capacidad de la fruta de soportar periodos largos de transporte para su exportación. Tradicionalmente, en la planta empacadora la evaluación de fruta madura o cremosa, como también se conoce, se hace mediante una técnica destructiva, que implica cortar el dedo lateral de la segunda mano del racimo, realizarle un corte transversal, y determinar si está madura a partir de la observación del color y la consistencia de la pulpa. Esto hace que, además, sea una técnica muy subjetiva. Mediante este proyecto, se evalúo un método para la determinación de grado de maduración de forma cuantitativa y no destructiva con la fruta, mediante la utilización del espectrómetro SCiO. Mediante la utilización del espectrómetro de infrarrojo cercano, la aplicación móvil y la plataforma SCiOLab, se crearon modelos estimativos de maduración, los cuales predicen valores basados en la firma espectral de la muestra (dedo de banano). Se obtuvieron un total de 6 modelos, los cuales mediante una validación, fueron capaces de predecir valores de maduración dentro de los rangos establecidos. Se comprobó la sensibilidad del sensor infrarrojo a la detección de cambios en el proceso de maduración de la fruta, el potencial de los modelos estimativos y una gran posibilidad de la aplicación de esta tecnología al proceso en campo.
The degree of ripeness of banana fruit is one of the factors that require more control in the production of this crop, since it is strictly related to the ability of the fruit to withstand long periods of transportation for export. Traditionally, in the packing plant, the evaluation of ripe or creamy fruit, as it is also known, is done using a destructive technique, which involves cutting the lateral finger of the second hand of the bunch, making a cross-section, and determining if it is ripe upon observation of the color and consistency of the pulp. This also makes it a very subjective technique. Throughout this project, a method was evaluated to determine the degree of ripeness in a quantitative and non-destructive way with the fruit, using the SCiO spectrometer. Using the near infrared spectrometer, the mobile application and the SCiOLab platform, estimative models of ripening were created, whereby these predict values based on the spectral signature of the sample (banana finger). A total of 6 models were obtained, and through validation, were able to predict maturation values within the established ranges. The sensitivity of the infrared sensor to the detection of changes in the ripening process of the fruit, the potential of the estimative models and a great possibility of the application of this technology to the process in the field was verified.
The degree of ripeness of banana fruit is one of the factors that require more control in the production of this crop, since it is strictly related to the ability of the fruit to withstand long periods of transportation for export. Traditionally, in the packing plant, the evaluation of ripe or creamy fruit, as it is also known, is done using a destructive technique, which involves cutting the lateral finger of the second hand of the bunch, making a cross-section, and determining if it is ripe upon observation of the color and consistency of the pulp. This also makes it a very subjective technique. Throughout this project, a method was evaluated to determine the degree of ripeness in a quantitative and non-destructive way with the fruit, using the SCiO spectrometer. Using the near infrared spectrometer, the mobile application and the SCiOLab platform, estimative models of ripening were created, whereby these predict values based on the spectral signature of the sample (banana finger). A total of 6 models were obtained, and through validation, were able to predict maturation values within the established ranges. The sensitivity of the infrared sensor to the detection of changes in the ripening process of the fruit, the potential of the estimative models and a great possibility of the application of this technology to the process in the field was verified.
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BANANOS, MUSA ACUMINATA, MADURAMIENTO, ESPECTROMETRIA