16 results on '"Herrero-Langreo, Ana"'
Search Results
2. Detection of peanut traces in wheat flour through NIR hyperspectral imaging spectroscopy
- Author
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Mishra, Puneet, Barreiro Elorza, Pilar, Roger, Jean-Michel, Diezma Iglesias, Belen, Herrero Langreo, Ana, Lleó García, Lourdes, and Gorretta, Nathalie
- Subjects
Ciencia y Tecnología de Alimentos - Abstract
NIR Hyperspectral images (1000-2200 nm) allowed the detection of peanut traces down to adulteration percentages 0.01 % - Determination coefficient of R2= 0.946 was found for the quantification of peanut adulteration from 10% to 0.1%. - The obtained results shows the feasibility of using HSI systems for the detection of peanut traces in conjuction with chemical procedures, such as RT-PCR and ELISA to facilitate quality control surveyance on food product processing lines.
- Published
- 2014
3. Hyperspectral to multispectral imaging for detection of tree nuts and peanut traces in wheat flour
- Author
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Mishra, Puneet, Herrero Langreo, Ana, Barreiro Elorza, Pilar, Roger, Jean-Michel, Diezma Iglesias, Belen, Gorretta, Nathalie, Lleó García, Lourdes, Mishra, Puneet, Herrero Langreo, Ana, Barreiro Elorza, Pilar, Roger, Jean-Michel, Diezma Iglesias, Belen, Gorretta, Nathalie, and Lleó García, Lourdes
- Abstract
In current industrial environments there is an increasing need for practical and inexpensive quality control systems to detect the foreign food materials in powder food processing lines. This demand is especially important for the detection of product adulteration with traces of highly allergenic products, such as peanuts and tree nuts. Manufacturing industries dealing with the processing of multiple powder food products present a substantial risk for the contamination of powder foods with traces of tree nuts and other adulterants, which might result in unintentional ingestion of nuts by the sensitised population. Hence, the need for an in-line system to detect nut traces at the early stages of food manufacturing is of crucial importance. In this present work, a feasibility study of a spectral index for revealing adulteration of tree nut and peanut traces in wheat flour samples with hyperspectral images is reported. The main nuts responsible for allergenic reactions considered in this work were peanut, hazelnut and walnut. Enhanced contrast between nuts and wheat flour was obtained after the application of the index. Furthermore, the segmentation of these images by selecting different thresholds for different nut and flour mixtures allowed the identification of nut traces in the samples. Pixels identified as nuts were counted and compared with the actual percentage of peanut adulteration. As a result, the multispectral system was able to detect and provide good visualisation of tree nut and peanut trace levels down to 0.01% by weight. In this context, multispectral imaging could operate in conjuction with chemical procedures, such as Real Time Polymerase Chain Reaction and Enzyme-Linked Immunosorbent Assay to save time, money and skilled labour on product quality control. This approach could enable not only a few selected samples to be assessed but also to extensively incorporate quality control surveyance on product processing lines.
- Published
- 2015
4. Detection and quantification of peanut traces in wheat flour by near infrared hyperspectral imaging spectroscopy using principal-component analysis
- Author
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Mishra, T.P., Herrero Langreo, Ana, Barreiro Elorza, Pilar, Roger, Jean-Michel, Diezma Iglesias, Belen, Gorretta, Nathalie, Lleó García, Lourdes, Mishra, T.P., Herrero Langreo, Ana, Barreiro Elorza, Pilar, Roger, Jean-Michel, Diezma Iglesias, Belen, Gorretta, Nathalie, and Lleó García, Lourdes
- Abstract
The use of a common environment for processing different powder foods in the industry has increased the risk of finding peanut traces in powder foods. The analytical methods commonly used for detection of peanut such as enzyme-linked immunosorbent assay (ELISA) and real-time polymerase chain reaction (RT-PCR) represent high specificity and sensitivity but are destructive and time-consuming, and require highly skilled experimenters. The feasibility of NIR hyperspectral imaging (HSI) is studied for the detection of peanut traces down to 0.01% by weight. A principal-component analysis (PCA) was carried out on a dataset of peanut and flour spectra. The obtained loadings were applied to the HSI images of adulterated wheat flour samples with peanut traces. As a result, HSI images were reduced to score images with enhanced contrast between peanut and flour particles. Finally, a threshold was fixed in score images to obtain a binary classification image, and the percentage of peanut adulteration was compared with the percentage of pixels identified as peanut particles. This study allowed the detection of traces of peanut down to 0.01% and quantification of peanut adulteration from 10% to 0.1% with a coefficient of determination (r2) of 0.946. These results show the feasibility of using HSI systems for the detection of peanut traces in conjunction with chemical procedures, such as RT-PCR and ELISA to facilitate enhanced quality-control surveillance on food-product processing lines.
- Published
- 2015
5. Hyperespectral images for the evaluation of the quality of minimally processed vegetables (spinach)
- Author
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Diezma Iglesias, Belen, Lleó García, Lourdes, Herrero Langreo, Ana, Lunadei, Loredana, Jean-Michel, Roger, and Ruiz-Altisent, Margarita
- Subjects
Ciencia y Tecnología de Alimentos - Abstract
The production of minimally processed vegetables and fruits is an emergent sector, however these processes reduce the useful life of the products. Main preservation techniques such cold storage and modified atmosphere are limited. New treatments are being applied (O3 , UV‐C radiation, biodegradable films…etc.). The sector precise of cheap and fast techniques to evaluate the general quality and the security of the processed products, that constitute a tool of aid to the decision in the implementation of new procedures of packaging and/or treatments. Objectives: To explore hyperspectral imaging for monitoring the evolution of minimally processed leafy vegetables during shelf‐life . To identify and classify deterioration rates of the leaves through Multivariate analysis techniques (PLS‐DA)
- Published
- 2011
6. Comparacion de indices opticos de imagenes hiperespectrales en relacion con madurez de melocoton: capacidad de deteccion y robustez
- Author
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Lleó García, Lourdes, Roger, Jean-Michel, Herrero Langreo, Ana, Barreiro Elorza, Pilar, Diezma Iglesias, Belen, and Ruiz-Altisent, Margarita
- Subjects
Agricultura - Abstract
La presente investigación se centra en el uso de la visión artificial para determinar la maduración del melocotón rojo de pulpa blanda (`Richlady'). La visión artificial permite una determinación espacial detallada del estado de maduración del fruto. Los índices ópticos considerados (Ind1 e Ind2, propuestos en la actual investigación, e Ind3 e IAD, propuestos por otros autores) se basan en la combinación de longitudes de onda en la zona del pico de absorción de la clorofila (680 nm). Ind1 corresponde aproximadamente a la profundidad del pico de absorción, e Ind2 corresponde a la profundidad relativa. Se obtuvo una imagen artificial de cada índice computada a partir de imágenes hiperespectales. Todos los índices fueron capaces de corregir el efecto de la convexidad (a excepción de los melocotones recién cosechados y para el Ind1). Ind2 es el índice con mayor capacidad de discriminación en diferentes estados de madurez. Por otra parte Ind2 permite la diferenciación de regiones de maduración dentro de los frutos, mostrando la evolución de esas regiones durante la maduración. The present research is focused on the application of artificial vision to assess the ripening of red skinned softflesh peach (‘Richlady’). Artificial vision allows a spatially detailed determination of the ripening stage of the fruit. The considered optical indexes (Ind1 and Ind2, proposed in the present research, and Ind3 and IAD, proposed by other authors) are 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, which were acquired with a hyperspectral camera. All indexes were able to correct convexity (except for the just-harvested peaches and for Ind1). 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.
- Published
- 2011
7. La imagen hiperespectral como herramienta de evaluación de la calidad de hortaliza de hoja mínimamente procesada
- Author
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Diezma Iglesias, Belen, Lleó García, Lourdes, Herrero Langreo, Ana, Lunadei, Loredana, Roger, Jean-Michel, and Ruiz-Altisent, Margarita
- Subjects
Optica ,Ciencia y Tecnología de Alimentos - Abstract
Resumen En el presente trabajo se explora la técnica de imagen hiperespectral en el ámbito de las hortalizas de hoja mínimamente procesadas para la determinación de atributos de calidad ligados a la evolución durante su almacenamiento y manejo. Se ha implementado un equipo de visión hiperespectral VIS-NIR (400 – 1000 nm) para la adquisición de imágenes de hojas de espinacas. Las muestras han sido sometidas a diferentes periodos de almacenamiento para generar suficiente variabilidad en estados de calidad. Se ha seleccionado una población de calibración de espectros sobre las imágenes considerando tres categorías de calidad. Sobre dicha población de calibración se ha aplicado la técnica de análisis multivariante PLS-DA. El error del modelo de clasificación en la calibración ha sido del 7%. La proyección de las imágenes hiperespectrales en el espacio discriminante generado y la asignación de cada píxel a una de las categorías en función de dicha proyección, han permitido identificar en las hojas regiones con diferentes estados de evolución. Abstract In this paper hyperspectral imaging technique is explored for the determination of quality attributes related to the evolution during storage and handling in the field of minimally processed leafy vegetables. We have implemented a computer vision hyperspectral VIS-NIR (400 - 1000 nm) for the acquisition of images of leaves of spinach. Samples were subjected to different storage periods to generate sufficient variability in quality stages. It has been selected a calibration set of spectra on the images by considering three categories of quality. On this calibration set the multivariate PLS-DA has been performed. The classification error in calibration was 7%. The projection of hyperspectral images on the discriminant space generated and the assignation of each pixel to one of the categories, have allowed the identification of regions in the leaves with different stages of evolution.
- Published
- 2011
8. Extracción de características de la cubierta vegetal del viñedo mediante imágenes RGB y RGIR obtenidas de forma dinámica
- Author
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Correa Farias, Christian, Moya Gonzalez, Adolfo, Baguena Isiegas, Eva, Herrero Langreo, Ana, Paz Diago, M., Baluja, J., Tardaguila Laso, Javier, Valero Ubierna, Constantino, and Barreiro Elorza, Pilar
- Subjects
Agricultura - Abstract
Diversas investigaciones han intentado resolver el problema de identificación de frutos u hojas mediante imágenes digitales, pero sólo lo han logrado parcialmente. Por esto, el objetivo de este trabajo es explorar una metodología de identificación que permita estimar áreas de hojas y racimos en viñedos, empleando imágenes en el espectro visible (RGB) y en el infrarrojo cercano (RGIR). El problema de la identificación fue abordando por dos vías, forma y color. En el caso de la identificación por forma se empleó la transformada circular de Hough y en el de la identificación por color se emplearon las técnicas de clasificación no supervisada denominadas kmeans y Fuzzy c-means. Se determinó que la clasificación mediante k-means sobre el espacio L*a*b*, para imágenes RGB y sobre el índice SAVI en las imágenes RGIR, son las técnicas más adecuadas. En cuanto a la identificación por forma, ésta resultó aplicable sólo en condiciones muy particulares
- Published
- 2011
9. Pixel classification through Mahalanobis distance for identification of grapevine canopy elements on RGB images
- Author
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Herrero Langreo, Ana, Barreiro Elorza, Pilar, Diago Santamaria, Maria Paz, Baluja, J., Ochagavia, H., and Tardaguila Laso, Javier
- Subjects
Agricultura - Abstract
Vine vigour and fruit-cluster exposure to sunlight in a grapevine canopy fruiting zone has been shown to strongly correlate with key fruit composition and diseases incidence. In this framework, the use of automated image analysis for the identification of plant elements is an important issue to be addressed for vineyard assessment (Dunn and Martin, 2004). In addition, optimum segmentation method is strongly application dependent and thus needs to be tested for each particular case (Cheng et al., 2001). The objective of the present work is to propose and test a simple, rapid and practical method for the identification of two relevant elements of grapevines canopy: clusters and green leaves.
- Published
- 2010
10. Medidas no destructivas al servicio de programas de mejora genética: ss en cebollas (NIR), madurez en melocotón VIS/NIR e imagen multiespectral) y calidad en aceitunas (NMR)
- Author
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Herrero Langreo, Ana, Moya Gonzalez, Adolfo, Hernández Sánchez, Natalia, and Ruiz-Altisent, Margarita
- Subjects
Agricultura - Abstract
El presente trabajo presenta diferentes técnicas no destructivas para la determinación de parámetros de calidad en frutas y hortalizas. El desarrollo de estas técnicas para la selección de un elevado número de individuos, y su posible implementación en equipos, tanto de laboratorio, como portátiles que permitan la medición directa en campo, supone una valiosa herramienta para el mejorador. La rápida determinación de parámetros de calidad para un elevado número de individuos resulta de gran ayuda en programas de mejora. Se presentan ejemplos de distintas aplicaciones: Equipos y procedimientos NIR en la mejora del contenido en sólidos solubles (SS) en cebollas; espectrometría en reflectancia y en imagen para establecer la madurez en recolección y en posrecolección en melocotón; y unas primeras aplicaciones de metabonómica para el estudio de aceitunas individuales, procedentes de cruzamientos de distintos cultivares.
- Published
- 2010
11. Integración de métodos no destructivos de medida de la calidad interna en melocotón
- Author
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Valero Ubierna, Constantino, Lleó García, Lourdes, Herrero Langreo, Ana, Ruiz-Altisent, Margarita, Larrigaudiere, Christian, Molina, Diana, Schotsmans, Wendy, Lurol, Sebastien, Gobrecht, Alexia, and Roger, Jean-Michel
- Subjects
Agricultura - Abstract
La demanda por parte del consumidor de frutos con sabo ry textura garantizados hace que los productores, centrales de confeccion y comercializadores busquen herramientas que les permitan conocer la calidad interna del producto que manipulan, para satisfacer esa demanda de forma consistente. En este articulo se presentan los resultados preliminares obtenidos con distintos equipos de estimacion no destructiva de la calidad interna en comparacion con los metodos tradicionales de medida.
- Published
- 2009
12. Evaluación de técnicas acústicas para la determinación de firmeza en melocotón
- Author
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Herrero Langreo, Ana, Diezma Iglesias, Belen, Lleó García, Lourdes, Valero Ubierna, Constantino, and Ruiz-Altisent, Margarita
- Subjects
Agricultura - Abstract
Non destructive determination of stone fruit firmness is a critical factor for improving its quality and handling. This work applies available acoustic techniques to the determination peach firmness, considering and comparing different parameters obtained with 2 devices: AWETA-AFS (Acoustic Firmness Sensor), which integrates impact and acoustic response information; and a prototype device by LPF-TAG, which enables to analyze the whole acoustic spectra. Magness-Taylor, quasiestatic ball compression and non-destructive impact are used as firmness references, obtaining up to 86% R. La determinación no destructiva de la firmeza en melocotón es fundamental para mejorar la calidad y facilitar el manejo de esta fruta por la industria. El presente trabajo se plantea con el objetivo de estudiar la aplicación de técnicas acústicas en la caracterización de firmeza en melocotón. Para ello se evalúan y comparan distintos parámetros obtenidos mediante un sensor comercial, el dispositivo “Acoustic Firmness Sensor” (ASF de AWETA) que incorpora también un sensor de impacto; y un prototipo de equipo acústico desarrollado en el LPF-TAG, que permite analizar el espectro acústico completo. Como medidas de referencia se utilizaron: el ensayo Magness-Taylor (MT), la compresión quasiestática con contacto esférico (B) y la respuesta al impacto, ensayo no destructivo (IMP.) Como principales resultados destacan las correlaciones entre algunos de los parámetros acústicos con las variables de referencia (R de hasta 0,86)
- Published
- 2009
13. Examination of the quality of spinach leaves using hyperspectral imaging
- Author
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Diezma Iglesias, Belen, Lleó García, Lourdes, Roger, Jean-Michel, Herrero Langreo, Ana, Lunadei, Loredana, Ruiz-Altisent, Margarita, Diezma Iglesias, Belen, Lleó García, Lourdes, Roger, Jean-Michel, Herrero Langreo, Ana, Lunadei, Loredana, and Ruiz-Altisent, Margarita
- Abstract
The present research is focused on the application of hyperspectral images for the supervision of quality deterioration in ready to use leafy spinach during storage (Spinacia oleracea). Two sets of samples of packed leafy spinach were considered: (a) a first set of samples was stored at 20 °C (E-20) in order to accelerate the degradation process, and these samples were measured the day of reception in the laboratory and after 2 days of storage; (b) a second set of samples was kept at 10 °C (E-10), and the measurements were taken throughout storage, beginning the day of reception and repeating the acquisition of Images 3, 6 and 9 days later. Twenty leaves per test were analyzed. Hyperspectral images were acquired with a push-broom CCD camera equipped with a spectrograph VNIR (400–1000 nm). Calibration set of spectra was extracted from E-20 samples, containing three classes of degradation: class A (optimal quality), class B and class C (maximum deterioration). Reference average spectra were defined for each class. Three models, computed on the calibration set, with a decreasing degree of complexity were compared, according to their ability for segregating leaves at different quality stages (fresh, with incipient and non-visible symptoms of degradation, and degraded): spectral angle mapper distance (SAM), partial least squares discriminant analysis models (PLS-DA), and a non linear index (Leafy Vegetable Evolution, LEVE) combining five wavelengths were included among the previously selected by CovSel procedure. In sets E-10 and E-20, artificial images of the membership degree according to the distance of each pixel to the reference classes, were computed assigning each pixel to the closest reference class. The three methods were able to show the degradation of the leaves with storage time.
- Published
- 2013
14. Multispectral Vision for Monitoring Peach Ripeness
- Author
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Herrero Langreo, Ana, Lunadei, Loredana, Lleó García, Lourdes, Diezma Iglesias, Belen, Ruiz-Altisent, Margarita, Herrero Langreo, Ana, Lunadei, Loredana, Lleó García, Lourdes, Diezma Iglesias, Belen, and Ruiz-Altisent, Margarita
- Abstract
The main objective of this research was to develop an automatic procedure able to classify Rich Lady commercial peaches according to their ripeness stage through multispectral imaging techniques. A classification procedure was applied to the ratio images calculated as red (R, 680 nm) divided by infrared (IR, 800 nm), that is, R/IR images. Four image-based ripeness reference classes (A: unripe to D: overripe) were generated from 380 fruit images (season 1: 2006) by a nonsupervised classification method and evaluated according to reference measurements of the ripeness of the same samples: Magness-Taylor penetrometry firmness, low-mass impact firmness, reflectance at 680 nm (R680, and soluble solids content. The assignment of unknown sample images from those season 1 images (internal validation, n = 380) and of 240 images from the 2nd season (season 2: 2007) to the ripeness reference classes (external validation) was carried out by computing the minimum Euclidean distance (classification distance, Cd) between each unknown image histogram and the average histogram of each ripeness reference class. For both validation phases, firmness values decreased and R680 increased for increasing alphabetical order of image-based class letter, reflecting the ripening process. Moreover, 70% (season 1) and 80% (season 2) of the samples below bruise susceptibility firmness were classified into class D.
- Published
- 2011
15. Comparison of multispectral indexes extracted from hyperspectral images for the assessment of fruit ripening
- Author
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Lleó García, Lourdes, Roger, Jean-Michel, Herrero Langreo, Ana, Diezma Iglesias, Belen, Barreiro Elorza, Pilar, Lleó García, Lourdes, Roger, Jean-Michel, Herrero Langreo, Ana, Diezma Iglesias, Belen, and Barreiro Elorza, Pilar
- Abstract
The present research is focused on the application of artificial vision to assess the ripening of red skinned soft-flesh peach (‘Richlady’). Artificial vision allows a spatially detailed determination of the ripening stage of the fruit. The considered optical indexes (Ind1 and Ind2, proposed in the present research, and Ind3 and IAD, proposed by other authors) are 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, which were acquired with a hyperspectral camera. All indexes were able to correct convexity (except for the just-harvested peaches and for Ind1). 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.
- Published
- 2011
16. Multispectral images of peach related to firmness and maturity at harvest
- Author
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Lleó García, Lourdes, Barreiro Elorza, Pilar, Ruiz-Altisent, Margarita, Herrero Langreo, Ana, Lleó García, Lourdes, Barreiro Elorza, Pilar, Ruiz-Altisent, Margarita, and Herrero Langreo, Ana
- Abstract
wo multispectral maturity classifications for red soft-flesh peaches (‘Kingcrest’, ‘Rubyrich’ and ‘Richlady’ n = 260) are proposed and compared based on R (red) and R/IR (red divided by infrared) images obtained with a three CCD camera (800 nm, 675 nm and 450 nm). R/IR histograms were able to correct the effect of 3D shape on light reflectance and thus more Gaussian histograms were produced than R images. As fruits ripened, the R/IR histograms showed increasing levels of intensity. Reference measurements such as firmness and visible spectra also varied significantly as the fruit ripens, firmness decreased while reflectance at 680 nm increased (chlorophyll absorption peak).
- Published
- 2009
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