El sabor de la fruta se puede "ver"

La UPM ha desarrollado un nuevo método para determinar las propiedades internas de la fruta, como el estado de madurez y la vida útil

Modelo para la clasificación no destructiva de fruta en grados de firmeza a partir de medidas ópticas y mecánicas. Aplicación a melocotones amarillos de carne dura.

Los melocotones objeto del estudio son amarillo de carne dura tipo pavía. Durante la campaña 1997, se analizaron muestras representativas de un número importante de variedades de melocotón que llegaban a cooperativas en la Región de Murcia y a un hipermercado de Madrid. Las variedades fueron Caterina, BabyGold, Sudanell, Vesubio y Miraflores. El número de frutos, melocotones amarillos de carne dura, fue de 224. Los ensayos que se realizaron fueron: 1-º Ensayo destructivo de estimación de firmeza por penetrometría Magness Taylor, realizado mediante punzón metálico de 8mm de diámetro, a una velocidad de 20 mm por minuto. 2-. Ensayos no destructivos: Impacto, realizado mediante el impactador del Laboratorio de Propiedades Físicas. 2.- Ensayo de deformación mediante el empleo de durómetro tipo Durofel-10. Posee un cilindro metálico que emerge 3 mm de superficie metálica y plana. Dicho cilindro se aplica perpendicularmente a la superficie del fruto; está conectado a un resorte que registra la fuerza correspondiente a la deformación máxima. Medida de reflectancia en el espectro visible desde 400 a 700 nm, mediante el uso del espectrofotómetro Minolta CM-508Í. Se consideraron las reflectancia correspondientes a 450 nm y a 680 nm, por ser las que mejor se correlacionan con la presencia de carotenoides y clorofila respectivamente. Ambos pigmentos están relacionados con el proceso de maduración, en el cual también se reblandecen los frutos

Hyperspectral Imaging for Peach Ripening Assessment

The present research is focused on the application of artificial vision to peach ripening assessment, avoiding multiplicative and additive effect. Original images were acquired with a hyperspectral camera. Vision allows a spatially detailed determination of the ripening stage of the fruit. Optical indexes are proposed, based on the combination of wavelengths close to the chlorophyll absorption peak at 680 nm. Ind1 corresponds approximately to the depth of the absorption peak, and Ind2 corresponds to the relative absorption peak. An artificial image of each index was obtained by computing the corresponding reflectance images. Score images have been also computed from Principal Components and Partial Least Squares Analysis. In any case the best performances correspond to such images that correct multiplicative and additive effects. Ind2 is the preferred index; it showed the highest discriminating power between ripening stages and no influence of convexity. Ind2 also allowed the differentiation of ripening regions within the fruits, and it showed the evolution of those regions during ripening. This fact has been also observed in some of the score image

Parámetros de calidad organoléptica en el melocotón

En el presente artículo se van a abordar qué factores pueden determinar la calidad organoléptica de los melocotones. Para ello veremos valores de parámetros recomendados por diversas instituciones y bibliografía (contenido en azúcares, acidez, firmeza...). También veremos qué valores presentaron esos parámetros a lo largo de la campaña pasada en todos los melocotones analizados, relacionándolos con valoración gustativa

Instrumental quality assessment of fresh peaches: Optical and mechanical parameters.

In developing instrumentation for the measurement of fruit quality, there is the need for fast and non-destructive devices, based on sensors, to be installed on-line. In the case of some fruits, like peaches, post-harvest ripeness, which is closely related to high quality for the consumer, is a priority. During ripening, external appearance (colour) and internal mechanical (firmness) and chemical (sugars and acids) quality are main features that evolve rapidly from and unripe to a ripe (high quality) stage. When considering the evolution of fruit quality in this scheme, external colour and firmness are shown to evolve in a parallel pattern, if monitored from the time of harvest to full consumer ripeness ( Rood, 1957; Crisosto et al, 1995; Kader, 1996). The visible (VIS) reflectance spectrum is a fast and easy reference that can be used to estimate quality of peaches, if we could show it to be reliably correlated with peach ripening rate during postharvest (Genard et al. 1994; Moras, 1995; Delwiche and Baumgartner, 1983; Delwiche et al. 1987; Slaughter, 1995; Lleo et al., 1998). Taste, described as an expert acceptance score, improves with ripeness (firmness and colour evolution), when considering the fruits on the tree, and also post-harvest

Prediction of destructive properties using descriptive analysis of nd measurements

Three groups of measurements related to peach maturity were acquired through destructive (D) mechanical tests (Magness Taylor Firmness, MTF), mechanical non destructive (ND) tests, and ND optical spectroscopy (Optical indexes). The relationship between these groups of variables was studied in order to estimate D mechanical measurements (MTF, with higher instrumental and sampling variability, time consuming, generally used as a reference for the assessment of peach handling), from ND measurements (quick, applicable on line, dealing better with the high variability found in fruit products). Multivariate exploratory analysis was used to extract the structure of the data. The information about the data structure of ND measurements, the relationship of MTF with the space defined by ND variables, and the expert knowledge regarding to the dataset was then used for modelling MTF (R 2 =0.72 and standard error on validation 5.73 N

Evaluation of enzymatic browning in fresh-cut apple slices applying a multispectral vision system

n this study a vision system was applied for assessing enzymatic browning evolution in fresh-cut apples slices stored at 7.5 °C and 85 % HR. Twenty-four slices were analyzed per day: at zero time and after storage for 1 , 3 ,7 and 9 days. A classification procedure was applied to virtual images obtained as a combination of the red (R) and blue (B) channel (B/R, R-B and R-B/R+B). In all cases, three images based browning reference classes were generated. An external validation was applied to a second set of samples submitted to the same treatments, obtaining a high percentage of samples correctly classified. Camera classification was evaluated according to colorimetric measurements usually utilized to evaluate enzymatic browning: CIE L*a*b* colour parameters and browning index (Bl). Virtual image based on B/R showed the best sensitivity to reflect the change in colours associated with brownin

Development of an image algorithm to assess changes in leaf pigments content of fresh-cut spinach and lettuce leaves.

The aim of this work was to develop an image algorithm to detect changes in colour related with changes in leaf pigments content in leafy spinach during storage. The experiment was carried out on packed ready-to-use spinach stored at 4.5 °C. Seventy-five leaves of spinach were analyzed at zero time and after storage for 7, 14 and 21 days. Multispectral images were acquired in the red (R), infrared (IR) and blue (B) regions. Virtual images were calculated on the basis of spectral indexes usually employed for estimation of leaf pigment content. By considering the sensitive bands to chlorophyll and carotenoids, new virtual images were proposed. A no supervised classification was applied to the obtained virtual images and the results were evaluated according to colorimetric measurements (CIE L*a*b* coordinates). The new proposed indexes were able to correctly classify a high percentage of the samples according to the colour evolution

Enzymatic Browning in Fresh-Cut Apple Slices Measured by Different Kinds of Image Algorithms

Resumen El objetivo final es el desarrollo de un sistema di visión multiespectral que permita asignar manzanas cortadas a clases de distinto nivel de pardeamiento. Se ha analizado un total de 240 imágenes IRRB y RGB, correspondientes a 240 gajos de manzanas de la variedad ‘Granny Smith’ (120 gajos = Set 1; 120 gajos = Set 2). Se analizaron 24 gajos por día: a tiempo cero y después de 1, 3, 7 y 9 días de almacenamiento a 7,5ºC. A las imágenes virtuales obtenidas como combinación del canal rojo y azul (B/R, R-B y (R-B)/(R+B)) se aplicó un procedimiento de clasificación no supervisada que, en todo los casos, generó tres clases de referencia. A la segunda serie de muestras (Set 2), sometidas los mismos tratamientos, se aplicó una validación externa, obteniendo un alto porcentaje de muestras correctamente clasificadas. La clasificación de las cámaras IRRB y RGB se evaluó de acuerdo a parámetros colorimétricos y sensoriales y las imágenes virtuales (R-B)/(R+B) y B/R mostraron la mejor sensibilidad para reflejar el cambio de color asociado con el pardeamiento. Abstract The main objective of this study was to develop a vision system able to classify fresh-cut apple slices according to the development of enzymatic browning. The experiment was carried out on ‘Granny Smith’ apple slices stored at 7.5°C (Set 1 = 120 n). Twenty-four samples were analyzed per day: at zero time and after storage for 1, 3, 7 and 9 days. Digital images were acquired by employing an IRRB camera and by employing a cheaper vision system, consisting in a RGB digital camera. A classification procedure was applied to the histograms of the following virtual images, acquired by the IRRB and by the RGB camera: (R-B)/(R+B), R–B and B/R. In all cases, a non-supervised classification procedure was able to generate three image-based browning reference classes. An internal and an external validation (Set 2 = 120 n) were carried out, with a high percentage of corrected classified samples. The camera classification was evaluated according to reference parameters (colorimetric and sensorial measurements) and the best results were obtained with the (R-B)/(R+B) and B/R virtual images

Monitoring of fresh-cut spinach leaves through multispectral vision and sensory evaluation

The aim of this work was to compare an image algorithm to detect changes in quality related with changes in leaf pigments content in leafy spinach during storage with a visual evaluation using a 1-4 scale, where 1 corresponds to fresh samples without any spoilage and 4 to samples with severe deterioration, in order to obtain a sensory evaluation index (ISE) for each sample. The experiment was carried out on packed ready-to-use spinach stored at 4.5°C or 10ºC. Seventy-five leaves of spinach were analyzed at zero time and after 7, 14 and 21 days of storage at 4.5º C. Twenty-four e samples were measured at zero time and after 3, 6 and 9 days of storage at 10º C. Multispectral images were acquired in the red (R, 680±20 nm), infrared (IR, 800±20 nm) and blue (B, 450±20 nm) regions. Virtual images were calculated on the basis of spectral indexes usually employed for estimation of leaf pigment content. By considering the sensitive bands to chlorophyll, new virtual images were proposed. A non-supervised classification was applied to the obtained virtual images and the results were evaluated according to colorimetric measurements (CIE L*a*b* coordinates) and visual evaluation. Virtual images computed from R and B ranges gave the better results detecting changes in quality along period storage at 4.5º C. These virtual images were able to classify samples into two reference classes, including respectively the major part of the samples analyzed on zero time and on the 7th day and samples analyzed on the 14th and the 21th days