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      Índice de carotenoides de pimiento morrón (Capsicum annuum) basado en la medición de color, utilizando imágenes hiperespectrales y digitales Translated title: Index of carotenoids of bell pepper (Capsicum annuum) based on color measurement, using hyperspectral and digital images

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          Abstract

          El objetivo del estudio fue evaluar métodos no destructivos basados en la medición de color en cinco grados de madurez (100% verde (M1), 10% a 30% de madurez (M2), 40% a 60% de madurez (M3), 70% a 90% de madurez (M4) y 100% maduro (M5) de pimiento morrón mediante el uso de imágenes hiperespectrales en rango visible (Vis) desde 380 a 750 nm (37 bandas espectrales) e imágenes digitales (RGB) y su conversión al espacio de color CIELAB. Los pimientos fueron recolectados en diferentes grados de madurez desde el color verde hasta el rojo completamente, los parámetros de calidad de clorofila y carotenoides totales fue determinado mediante método espectofotométrico y su contenido fue correlacionado con los datos espectrales y de espacio de color CIELAB. El Índice espectral (CRI700) mostró una correlación positiva de 0,915 (p < 0,01) con respecto al contenido de carotenoides y una correlación negativa de -0,972 respecto al contenido de clorofila y la variable a* (verde - rojo) con el contenido de carotenoides mostró una correlación positiva de 0,949 (p < 0,01) y negativa de -0,968 con clorofila. Concluyendo que estos métodos permitirían analizar muestras intactas de pimiento morrón en distintos grados de madurez

          Translated abstract

          The objective of the study was to evaluate non-destructive methods based on the measurement of color at five degrees of maturity (100% green (M1), 10 30% maturity (M2), 40% to 60% maturity (M3), 70% to 90% maturity (M4) and 100% mature (M5) bell pepper by using hyperspectral images in visible range (Vis) from 380 to 750 nm (37 spectral bands) and digital images (RGB) and its conversion to space of CIELAB color. The peppers were collected in different degrees of maturity from green to red completely, the quality parameters of chlorophyll and total carotenoids was determined by spectrophotometric method and its content was correlated with spectral and color space data CIELAB. The spectral index (CRI700) showed a positive correlation of 0.915 (p < 0.01) with respect to the content of carotenoids and a negative correlation of -0.972 with respect to the content of chlorophyll and variable a * (green-red) with the content of carotenoids showed a positive correlation of 0.949 (p < 0.01) and negative correlation of -0.968 with chlorophyll. Concluding that these methods would allow to analyze intact samples of red pepper in different degrees of maturity

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          Most cited references30

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          Assessing carotenoid content in plant leaves with reflectance spectroscopy.

          Spectral reflectance of maple, chestnut and beech leaves in a wide range of pigment content and composition was investigated to devise a nondestructive technique for total carotenoid (Car) content estimation in higher plant leaves. Reciprocal reflectance in the range 510 to 550 nm was found to be closely related to the total pigment content in leaves. The sensitivity of reciprocal reflectance to Car content was maximal in a spectral range around 510 nm; however, chlorophylls (Chl) also affect reflectance in this spectral range. To remove the Chl effect on the reciprocal reflectance at 510 nm, a reciprocal reflectance at either 550 or 700 nm was used, which was linearly proportional to the Chl content. Indices for nondestructive estimation of Car content in leaves were devised and validated. Reflectances in three spectral bands, 510+/-5 nm, either 550+/-15 nm or 700+/-7.5 nm and the near infrared range above 750 nm are sufficient to estimate total Car content in plant leaves nondestructively with a root mean square error of less than 1.75 nmol/cm2.
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            Industrial use of pepper (Capsicum annum L.) derived products: technological benefits and biological advantages

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              • Record: found
              • Abstract: not found
              • Article: not found

              Shape Analysis of Agricultural Products: A Review of Recent Research Advances and Potential Application to Computer Vision

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                Author and article information

                Journal
                agro
                Scientia Agropecuaria
                Scientia Agropecuaria
                Universidad Nacional de Trujillo. Facultad de Ciencias Agropecuarias (Trujillo, , Peru )
                2077-9917
                October 2019
                : 10
                : 4
                : 531-539
                Affiliations
                [01] Lambayeque orgnameUniversidad Nacional Pedro Ruiz Gallo Perú
                Article
                S2077-99172019000400010 S2077-9917(19)01000400010
                10.17268/sci.agropecu.2019.04.10
                a60f744e-4469-42f0-a054-872d48201eee

                This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

                History
                : 15 February 2019
                : 21 December 2019
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 32, Pages: 9
                Product

                SciELO Peru

                Categories
                Artículos originales

                image analysis,visión computacional,análisis de imagen,índice de carotenoides,pimiento morrón,computational vision,red pepper,carotenoid index

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