169 results on '"José Blasco"'
Search Results
2. Rapid Prediction of Nutrient Concentration in Citrus Leaves Using Vis-NIR Spectroscopy
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Maylin Acosta, Ana Quiñones, Sandra Munera, José Miguel de Paz, and José Blasco
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citrus nutrition ,agricultural sensors ,fertilisation ,ionomics ,chemometrics ,Chemical technology ,TP1-1185 - Abstract
The nutritional diagnosis of crops is carried out through costly foliar ionomic analysis in laboratories. However, spectroscopy is a sensing technique that could replace these destructive analyses for monitoring nutritional status. This work aimed to develop a calibration model to predict the foliar concentrations of macro and micronutrients in citrus plantations based on rapid non-destructive spectral measurements. To this end, 592 ‘Clementina de Nules’ citrus leaves were collected during several months of growth. In these foliar samples, the spectral absorbance (430–1040 nm) was measured using a portable spectrometer, and the foliar ionomics was determined by emission spectrometry (ICP-OES) for macro and micronutrients, and the Kjeldahl method to quantify N. Models based on partial least squares regression (PLS-R) were calibrated to predict the content of macro and micronutrients in the leaves. The determination coefficients obtained in the model test were between 0.31 and 0.69, the highest values being found for P, K, and B (0.60, 0.63, and 0.69, respectively). Furthermore, the important P, K, and B wavelengths were evaluated using the weighted regression coefficients (BW) obtained from the PLS-R model. The results showed that the selected wavelengths were all in the visible region (430–750 nm) related to foliage pigments. The results indicate that this technique is promising for rapid and non-destructive foliar macro and micronutrient prediction.
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- 2023
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3. Non-Destructive Appraisal of Macro- and Micronutrients in Persimmon Leaves Using Vis/NIR Hyperspectral Imaging
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Maylin Acosta, Isabel Rodríguez-Carretero, José Blasco, José Miguel de Paz, and Ana Quiñones
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hyperspectral imaging ,Vis/NIR ,spectroscopy ,chemometrics ,variable selection ,Agriculture (General) ,S1-972 - Abstract
Visible and near-infrared (Vis/NIR) hyperspectral imaging (HSI) was used for rapid and non-destructive determination of macro- and micronutrient contents in persimmon leaves. Hyperspectral images of 687 leaves were acquired in the 500–980 nm range over 6 months, covering a complete vegetative cycle. The average reflectance spectrum of each leaf was extracted, and foliar ionomic analysis was used as a reference method to determine the actual concentration of the nutrients in the leaves. Analyses were performed via emission spectrometry (ICP-OES) for macro- and micronutrients after microwave digestion and using the Kjeldahl method to quantify nitrogen. Partial least square regression (PLS-R) was used to predict the nutrient concentration based on spectral data from the leaf using actual values of each element as predictor variables. Several methods were used to pre-process the spectra, including Savitzky–Golay (SG) smoothing, standard normal variate (SNV) and first (1D) and second derivatives (2D). Seventy-five percent of the samples were used to calibrate and validate the model by cross-validation, whereas the remaining twenty-five % were used as an independent test set. The best performance of the models for the test set achieved an R2 = 0.80 for nitrogen. Results were also satisfactory for phosphorous, calcium, magnesium and boron, with determination coefficient R2 values of 0.63, 0.66, 0.58 and 0.69, respectively. For the other nutrients, lower prediction rates were attained (R2 = 0.48 for potassium, R2 = 0.38 for iron, R2 = 0.24 for copper, R2 = 0.23 for zinc and R2 = 0.22 for manganese). The variable importance in projection (VIP) was used to extract the most influential bands for the best-predicted nutrients, which were N, K and B.
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- 2023
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4. Estimation of Macro and Micronutrients in Persimmon (Diospyros kaki L.) cv. ‘Rojo Brillante’ Leaves through Vis-NIR Reflectance Spectroscopy
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Maylin Acosta, Fernando Visconti, Ana Quiñones, José Blasco, and José Miguel de Paz
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nutritional diagnosis ,non-destructive ,foliar analysis ,macronutrients ,micronutrients ,Vis-NIR spectroscopy ,Agriculture - Abstract
The nutritional diagnosis of crops is carried out through costly elemental analyses of different plant organs, particularly leaves, in the laboratory. However, visible and near-infrared (Vis-NIR) spectroscopy of unprocessed plant samples has a high potential as a faster, non-destructive, environmental-friendly alternative to elemental analyses. In this work, the potential of this technique to estimate the concentrations of macronutrients such as nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), and magnesium (Mg), and micronutrients such as iron (Fe), manganese (Mn) and boron (B), in persimmon (Diospyros kaki L.) ‘Rojo Brillante’ leaves, has been investigated. Throughout the crop cycle variable rates of N and K were applied to obtain six nutritional status levels in persimmon trees in an experimental orchard. Then, leaves were systematically sampled throughout the cropping season from the different nutritional levels and spectral reflectance measurements were acquired in the 430–1040 nm wavelength range. The concentrations of nutrients were determined by inductively coupled plasma optical emission spectrometry (ICP-OES) for P, K, Ca, Mg, Fe, Mn and B after microwave digestion, while the Kjeldahl method was used for N. Then, partial least squares regression (PLS-R) was used to model the concentrations of these nutrients from the reflectance measurements of the leaves. The model was calibrated using 75% of the samples while the remaining 25% were left as the independent test set for external validation. The results of the test set indicated an acceptable validation for most of the nutrients, with determination coefficients (R2) of 0.74 for N and P, 0.54 for K, 0.77 for Ca, 0.60 for Mg, 0.39 for Fe, 0.69 for Mn and 0.83 for B. These findings support the potential use of Vis-NIR spectrometric techniques as an alternative to conventional laboratory methods for the persimmon nutritional status diagnosis although more research is needed to know how the models developed one year perform in ensuing years.
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- 2023
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5. Detection of Invisible Damages in ‘Rojo Brillante’ Persimmon Fruit at Different Stages Using Hyperspectral Imaging and Chemometrics
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Sandra Munera, Alejandro Rodríguez-Ortega, Nuria Aleixos, Sergio Cubero, Juan Gómez-Sanchis, and José Blasco
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Diospyros kaki ,fruit quality ,browning ,nondestructive ,chemometrics ,computer vision ,Chemical technology ,TP1-1185 - Abstract
The main cause of flesh browning in ‘Rojo Brillante’ persimmon fruit is mechanical damage caused during harvesting and packing. Innovation and research on nondestructive techniques to detect this phenomenon in the packing lines are necessary because this type of alteration is often only seen when the final consumer peels the fruit. In this work, we have studied the application of hyperspectral imaging in the range of 450–1040 nm to detect mechanical damage without any external symptoms. The fruit was damaged in a controlled manner. Later, images were acquired before and at 0, 1, 2 and 3 days after damage induction. First, the spectral data captured from the images were analysed through an algorithm based on principal component analysis (PCA). The aim was to automatically separate intact and damaged fruit, and to detect the damage in the PC images when present. With this algorithm, 90.0% of intact fruit and 90.8% of damaged fruit were correctly detected. A model based on partial least squares—discriminant analysis (PLS-DA), was later calibrated using the mean spectrum of the pixels detected as damaged, to determine the moment when the fruit was damaged. The model differentiated fruit corresponding correctly to 0, 1, 2 and 3 days after damage induction, achieving a total accuracy of 99.4%.
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- 2021
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6. Xf-Rovim. A Field Robot to Detect Olive Trees Infected by Xylella Fastidiosa Using Proximal Sensing
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Beatriz Rey, Nuria Aleixos, Sergio Cubero, and José Blasco
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Robotics ,computer vision ,multispectral imaging ,LiDAR ,pest detection aid ,vegetative indices ,asymptomatic detection ,Science - Abstract
The use of remote sensing to map the distribution of plant diseases has evolved considerably over the last three decades and can be performed at different scales, depending on the area to be monitored, as well as the spatial and spectral resolution required. This work describes the development of a small low-cost field robot (Remotely Operated Vehicle for Infection Monitoring in orchards, XF-ROVIM), which is intended to be a flexible solution for early detection of Xylella fastidiosa (X. fastidiosa) in olive groves at plant to leaf level. The robot is remotely driven and fitted with different sensing equipment to capture thermal, spectral and structural information about the plants. Taking into account the height of the olive trees inspected, the design includes a platform that can raise the cameras to adapt the height of the sensors to a maximum of 200 cm. The robot was tested in an olive grove (4 ha) potentially infected by X. fastidiosa in the region of Apulia, southern Italy. The tests were focused on investigating the reliability of the mechanical and electronic solutions developed as well as the capability of the sensors to obtain accurate data. The four sides of all trees in the crop were inspected by travelling along the rows in both directions, showing that it could be easily adaptable to other crops. XF-ROVIM was capable of inspecting the whole field continuously, capturing geolocated spectral information and the structure of the trees for later comparison with the in situ observations.
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- 2019
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7. Characterization of a Multispectral Imaging System Based on Narrow Bandwidth Power LEDs.
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Manuel Alejandro Tamayo Monsalve, Gustavo Osorio, Nubia Liliana Montes, Santiago Lopez, Sergio Cubero, and José Blasco
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- 2021
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8. Monitorización de glaciares y glaciares rocosos pirenaicos: más de una década aplicando técnicas geomáticas en La Paúl y Maladeta
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Martínez Fernández, Adrián, Serrano Cañadas, Enrique, San José Blasco, José Juan, Martínez Fernández, Adrián, Serrano Cañadas, Enrique, and San José Blasco, José Juan
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This doctoral thesis presents and analyzes the annual monitoring works carried out over 12 years (2008-2020) in Pyrenean glaciers and rock glaciers by the GIR PANGEA. Specifically in the glaciers of La Paúl (2009-2020) and Maladeta (2010-2020) and the rock glaciers of La Paúl (2013-2020) and Maladeta (2008-2020). This research focuses on the technical component of the monitoring works by studying different geomatic techniques applied to the in situ surface control of glaciers and rock glaciers. Thus, the suitability of geomatic studies is evaluated from data acquisition and processing to the production of surface deformation models. Periodic data acquisition was performed using Total Stations, Global Navigation Satellite Systems, Terrestrial Laser Scanners and Terrestrial and low-height Aerial Photogrammetry. Simultaneously, the analysis of surface variations and compatibility between the geomatics techniques employed was performed through coordinate subtraction (1D and 2D), elevation model comparison (2.5D), and point cloud comparison methodologies (3D) from the models obtained or derived from the different techniques. The various configurations and methods used to capture, process, and compare the geographic information obtained in the glaciers and rock glaciers of La Paúl and Maladeta have allowed us to determine the limitations of each geomatic technique as the precise and detailed evolution of the studied scenarios. Some examples include the relative compatibility of quantifying and distributing glacial deformations with total stations, terrestrial laser scanners, and drone photogrammetry is highlighted as the suitability of the aerial point of view in the survey of geometrically complex surfaces such as rock glaciers. Some difficulties encountered focused on generating accurate surveys using terrestrial photogrammetry or the reduced performance of some terrestrial laser scanners for acquiring measurements on ice and snow surfaces. Throughout the chapters of th, En esta tesis doctoral se presentan y analizan los trabajos anuales de monitorización ejecutados durante 12 años (2008-2020) en glaciares y glaciares rocosos pirenaicos por parte del GIR PANGEA. Concretamente, en los glaciares de La Paúl (2009-2020) y la Maladeta (2010-2020), y los glaciares rocosos de La Paúl (2013-2020) y la Maladeta (2008-2020). La investigación se centra en la componente técnica de los trabajos de monitorización, a partir del estudio de diferentes técnicas geomáticas aplicadas al control superficial in situ de los glaciares y glaciares rocosos. De modo que la idoneidad de los trabajos geomáticos se evalúa desde la adquisición de los datos y su tratamiento, hasta la producción de los modelos de deformación superficial de las geoformas estudiadas. La adquisición periódica de datos se llevó a cabo mediante estaciones totales, Sistemas Globales de Navegación por Satélite, escáneres láser terrestres y fotogrametría terrestre y aérea mediante drones. Mientras que el análisis de las variaciones superficiales y la compatibilidad entre las técnicas geomáticas, se realizó a través de la sustracción de coordenadas (1D y 2D), la comparación de modelos de elevación (2.5D) y metodologías de comparación de nubes de puntos (3D). Datos y modelos obtenidos o derivados de las diferentes técnicas en cada uno de los escenarios estudiados. La variedad de configuraciones y métodos empleados para la captura, tratamiento y comparación de la información geoespacial obtenida en La Paúl y la Maladeta, ha permitido determinar las limitaciones de cada técnica geomática; así como la evolución precisa y detallada de las geoformas estudiadas. Algunos ejemplos son la relativa compatibilidad de las estaciones totales, los escáneres láser terrestre y la fotogrametría dron en la cuantificación y distribución de deformaciones glaciares. Así como la idoneidad del punto de vista aéreo en el levantamiento de superficies geométricamente complejas como los glaciares rocosos. Algunas de l, Escuela de Doctorado, Doctorado en Patrimonio Cultural y Natural: Historia, Arte y Territorio
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- 2023
9. Application of deep convolutional neural networks for the detection of anthracnose in olives using VIS/NIR hyperspectral images.
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Antonio Fazari, Oscar J. Pellicer-Valero, Juan Gómez-Sanchís, Bruno Bernardi, Sergio Cubero, Souraya Benalia, Giuseppe Zimbalatti, and José Blasco
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- 2021
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10. MAEGAP: A PILOT INNOVATIVE EDUCATIONAL PROJECT TO IMPROVE THE PRESENCE AND ATTRACTION OF THE BACHELOR’S DEGREE IN PUBLIC MANAGEMENT AND ADMINISTRATION AT THE UNIVERSITAT JAUME I
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Oscar Coltell, Beatriz Susana Tomás, Cristina Pauner, Jaime Clemente, Jorge Agustín Viguri, Luis Vicente Lizán, Mariam Camarero, Alma María Rodríguez, Sergio José Blasco, and Marta Oller
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- 2023
11. HAS TEACHING IN DEGREES STABILIZED IN THE POST-PANDEMIC AT THE UNIVERSITAT JAUME I? THE INSTITUTIONAL REVISION OF THE BACHELOR’S DEGREE IN PUBLIC MANAGEMENT AND ADMINISTRATION
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Oscar Coltell, Beatriz Susana Tomás, Mariam Camarero, Alma María Rodríguez, Luis Vicente Lizán, Sergio José Blasco, Cristina Pauner, Jorge Agustín Viguri, Jaime Clemente, and Marta Oller
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- 2023
12. Computer vision for automatic quality inspection of dried figs (Ficus carica L.) in real-time.
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Souraya Benalia, Sergio Cubero, José Manuel Prats-Montalbán, Bruno Bernardi, Giuseppe Zimbalatti, and José Blasco
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- 2016
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13. A new method to analyse mosaics based on Symmetry Group theory applied to Islamic Geometric Patterns.
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Francisco Albert, José María Gomis, José Blasco, José Miguel Valiente, and Nuria Aleixos
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- 2015
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14. Segmentation of Hyperspectral Images for the Detection of Rotten Mandarins.
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Juan Gómez-Sanchís, Gustavo Camps-Valls, Enrique Moltó, Luis Gómez-Chova, Nuria Aleixos, and José Blasco
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- 2008
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15. Development of a Computer Vision System for the Automatic Quality Grading of Mandarin Segments.
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José Blasco, Sergio Cubero, Raúl Arias, Juan Gómez-Sanchís, Florentino Juste, and Enrique Moltó
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- 2007
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16. Climacturia tras prostatectomía radical laparoscópica asistida por robot
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María Loreto Parra López, José Manuel Conde Sánchez, Rafael Antonio Medina López, Belén Congregado Ruiz, Ignacio Osman García, and José Blasco
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Male ,medicine.medical_specialty ,Función sexual ,Laparoscopic radical prostatectomy ,Sexual function ,Urology ,medicine.medical_treatment ,media_common.quotation_subject ,030232 urology & nephrology ,Urinary incontinence ,Orgasm ,03 medical and health sciences ,0302 clinical medicine ,Erectile Dysfunction ,Robotic Surgical Procedures ,Climacturia ,medicine ,Humans ,Adverse effect ,Retrospective Studies ,media_common ,Prostatectomy ,business.industry ,Prostatectomía radical ,Retrospective cohort study ,Robotics ,Middle Aged ,medicine.disease ,Neurovascular bundle ,Surgery ,Urinary Incontinence ,Erectile dysfunction ,Reproductive Medicine ,030220 oncology & carcinogenesis ,Laparoscopy ,medicine.symptom ,business - Abstract
[EN] Introduction: Adverse effects in the sexual sphere are common in patients who have undergone radical prostatectomy (RP). Climacturia, involuntary loss of urine during orgasm, occurs in 20-40% of cases after PR. We analyse its prevalence and associated risk factors after Robotic-assisted laparoscopic radical prostatectomy (RALRP). Objectives: We analyse the climacturia prevalence after robotic-assisted laparoscopic radical prostatectomy (RALRP) and the association with other related factors. Materials and methods: Retrospective study of 100 patients underwent PRLAR from May 2011 to July 2014. After excluding patients who received radiotherapy after surgery (17), those who did not have sexual activity (7) and those with whom it could not be possible contacted (14), a structured telephone interview was conducted in 62 patients, investigating: presence and intensity of climacturia, orgasmic quality, incontinence and erectile dysfunction (ED). Other factors analysed included neurovascular preservation and rehabilitative treatment for ED. The statistical analysis consisted of Chi2 test and logistic regression to evaluate associated factors. Results: The mean age was 56 vs 59 years and the mean follow-up time was 26.6 vs 20.3 months, in the group with climacturia and without climacturia, respectively. The prevalence of climacturia was 17.9% (slight leaks-82% and severe leaks-18%). In 37% of these patients occurred in all orgasms. The quality of orgasm after surgery was worse in 47%, better in 13% and equal in 40%. The quality of the orgasm worsened more frequently in the climacturia group (63% vs 37%). The urinary incontinence rate was 41%, always effort incontinence. It was more frequent in patients with climacturia (62% vs 38%). In all patients with climacturia, bilateral neurovascular bundles preservation was performed. 32% of the patients had undergone post-surgical erectile rehabilitation with oral drugs. No statistically significant differences were found between patients with or without climacturia respect to the parameters analysed. Conclusions: Climacturia rate after PRLAR in our series was 17.9%. Patients with climacturia presented worse quality orgasms and a higher incontinence rate (p> 0.05). None of the analysed parameters could be defined as predictors of climacturia., [ES] Introducción: Los efectos adversos en la esfera sexual son comunes en pacientes sometidos a prostatectomía radical (PR). La climaturia, pérdida involuntaria de orina durante el orgasmo, se presenta en un 20-40% de casos tras PR. Analizamos su prevalencia y asociación con otros factores relacionados tras prostatectomía radical laparoscópica asistida por robot (PRLAR). Objetivos: Analizamos la prevalencia de climaturia tras PRLAR y su asociación con otros posibles factores riesgo relacionados. Material y métodos: Estudio retrospectivo de 100 pacientes, sometidos a PRLAR desde mayo-2011 a julio-2014. Tras excluir a pacientes que recibieron radioterapia tras la cirugía (17), a los que no tenían actividad sexual (7) y aquellos con los que no se pudo contactar (14), se realizó entrevista telefónica estructurada a 62 pacientes, indagando sobre: presencia e intensidad de climaturia, calidad orgásmica, incontinencia y disfunción eréctil (DE). Otros factores analizados incluyeron la preservación neurovascular y el tratamiento rehabilitador para DE. El análisis estadístico consistió en prueba de Chi2 y regresión logística para evaluar factores asociados. Resultados: La edad media fue 56 vs 59 años y el tiempo medio de seguimiento de 26,6 vs 20,3 meses, en el grupo con climaturia y sin climaturia respectivamente. La prevalencia de climaturia fue del 17.9% (pérdidas leves el 82% y severas el 18%). En el 37% de estos pacientes ocurrió en todos los orgasmos. La calidad del orgasmo tras cirugía fue peor en el 47%, mejor en el 13% e igual en el 40%. La calidad del orgasmo empeoró con más frecuencia en el grupo con climaturia (63% vs 37%). La tasa de incontinencia urinaria fue del 41%, siempre de esfuerzo. Fue más frecuente en pacientes con climaturia (62% vs 38%). El 68% de los pacientes usaba fármacos para DE. En todos los pacientes con climaturia se realizó preservación nerviosa bilateral. El 32% de los pacientes habían realizado rehabilitación eréctil postquirúrgica con fármacos orales. No se encontraron diferencias estadísticamente significativas entre pacientes con o sin climaturia respecto a los parámetros analizados. Conclusiones: La tasa de climaturia tras PRLAR en nuestra serie fue del 17,9%. Los pacientes con climaturia presentaron orgasmos de peor calidad y una tasa de incontinencia superior (p > 0,05). Ninguno de los parámetros analizados pudieron definirse como factores predictivos de climaturia.
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- 2021
17. Detecting rottenness caused by Penicillium genus fungi in citrus fruits using machine learning techniques.
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Juan Gómez-Sanchís, José David Martín-Guerrero, Emilio Soria-Olivas, Marcelino Martínez-Sober, José Rafael Magdalena Benedicto, and José Blasco
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- 2012
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18. Assessment of Citrus Fruit Quality Using a Real-Time Machine Vision System.
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Nuria Aleixos, José Blasco, Enrique Moltó, and F. Navarrón
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- 2000
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19. Efectos del método Pilates en la reducción de caídas, el riesgo y miedo a caer en el adulto mayor: una revisión sistemática
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K. Medina-Alvarado, L.A. Villaplana-Torres, José Blasco, and Celedonia Igual-Camacho
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Physical Therapy, Sports Therapy and Rehabilitation - Abstract
Resumen Antecedentes Las caidas son la segunda causa mundial de muerte por lesiones accidentales. La mayor tasa de mortalidad se produce en los adultos mayores. Objetivo Evaluar si la practica del metodo Pilates es efectiva para reducir las caidas y el riesgo de caida en el adulto mayor. Metodos Revision sistematica de articulos originales publicados desde el inicio hasta octubre de 2018. Bases de datos consultadas Medline, PubMed, Google Scholar, Web of Knowledge, OVID y ScienceDirect. Se incluyeron estudios experimentales y cuasi-experimentales en los que los participantes fueron adultos mayores y recibieron una intervencion basada en el metodo Pilates, y en los que se evaluaron los efectos sobre las caidas, el riesgo o el miedo a las caidas. La sintesis fue descriptiva y se evaluo la calidad de los estudios incluidos con las escalas PEDro y Otawa. Resultados Seis estudios cumplieron los criterios de elegibilidad. Cinco fueron estudios clinicos aleatorizados y el restante un estudio de intervencion. Un total de 216 participantes fueron incluidos. Dos estudios evaluaron el efecto sobre las caidas con resultados inconcluyentes. En general los efectos sobre el equilibrio asociado con el riesgo de caidas fueron positivos. El efecto sobre el miedo a la caida, valorado por un estudio, tambien dedujo resultados positivos derivados de la practica de Pilates. Conclusiones La practica de ejercicio basado en el metodo Pilates es efectiva para mejorar las habilidades de equilibrio estatico y dinamico, asi como la fuerza muscular en adultos mayores (predictores de caidas). Existe escasez de estudios orientados a evaluar especificamente la reduccion del numero de caidas y del miedo a caer. La implementacion de ensayos clinicos con poder adecuado queda justificada para resolver el efecto del metodo Pilates sobre las caidas en el adulto mayor.
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- 2020
20. A randomized controlled trial assessing the effects of preoperative strengthening plus balance training on balance and functional outcome up to 1 year following total knee replacement
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Antonio Silvestre-Muñoz, Celedonia Igual-Camacho, Juan Rodrigo, Alfonso Payá-Rubio, Fernando Domínguez-Navarro, Beatriz Díaz-Díaz, José Blasco, Jose Vicente Torrella, and Sergio Roig-Casasús
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Male ,medicine.medical_specialty ,Knee Joint ,Osteoarthritis ,law.invention ,Treatment and control groups ,03 medical and health sciences ,0302 clinical medicine ,Randomized controlled trial ,law ,Preoperative Care ,Clinical endpoint ,Postural Balance ,Humans ,Medicine ,Orthopedics and Sports Medicine ,Arthroplasty, Replacement, Knee ,Aged ,Balance (ability) ,030222 orthopedics ,business.industry ,Resistance Training ,030229 sport sciences ,Middle Aged ,Osteoarthritis, Knee ,medicine.disease ,Exercise Therapy ,Treatment Outcome ,Berg Balance Scale ,Orthopedic surgery ,Physical therapy ,Female ,Surgery ,business - Abstract
To investigate the effects of including balance training in a preoperative strengthening intervention on balance and functional outcomes in patients undergoing total knee replacement (TKR) and compare these effects to those induced by preoperative strengthening and no intervention. Eighty-two subjects scheduled for TKR were randomly allocated into the strengthening (ST, n = 28) group: a preoperative lower limb strengthening intervention; the strengthening + balance (ST + B, n = 28) group: same intervention augmented with balance training; and the control group (n = 26). The Berg Balance Scale (BBS) and the function in daily living subscale of the Knee Injury and Osteoarthritis Outcome Score (KOOS-ADL) were the primary outcomes. The secondary measures included balance and mobility, self-reported status, and knee function. The outcomes were assessed at baseline, 1 week before surgery, and 2, (primary endpoint), 6 and 52 weeks after surgery. Compared with the controls, the participants in the ST and ST + B groups presented significant improvements from baseline to the end of the preoperative intervention in BBS (p = 0.005) and KOOS-ADL (p
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- 2020
21. Discrimination of astringent and deastringed hard ‘Rojo Brillante’ persimmon fruit using a sensory threshold by means of hyperspectral imaging
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Alejandra Salvador, Cristina Besada, Sandra Munera, Juan Gómez-Sanchis, Nuria Aleixos, José Blasco, Sergio Cubero, and Pau Talens
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EXPRESION GRAFICA EN LA INGENIERIA ,TECNOLOGIA DE ALIMENTOS ,biology ,Astringent ,Astringency ,Inia ,Hyperspectral imaging ,04 agricultural and veterinary sciences ,biology.organism_classification ,040401 food science ,03 medical and health sciences ,Horticulture ,0404 agricultural biotechnology ,0302 clinical medicine ,Soluble tannins ,030221 ophthalmology & optometry ,media_common.cataloged_instance ,Computer vision ,Diospyros kaki ,Chemometrics ,European union ,Food Science ,Mathematics ,media_common - Abstract
[EN] Persimmon fruit cv. 'Rojo Brillante' is an astringent cultivar due to its content of soluble tannins, which are insolubilised during the ripening of the fruit. Traditionally, the consumption of this cultivar has only been possible when the fruit is overripe and the texture is soft. Postharvest treatments based on exposing fruits to high CO2 concentrations allow astringency removal while preserving high flesh firmness. However, the effectiveness of this treatment is controlled by means of slow destructive methods. The aim of this work is to study the application of hyperspectral imaging in the spectral range 450-1040 nm to discriminate astringent (A) and deastringed (DA) fruits non-destructively. To separate both type of fruit, it was used a threshold of soluble tannins based on sensorial perception (0.04% of fresh weight). The spectral information from three different areas of each fruit (calyx, middle and apex) was used to build models to predict the soluble tannins (ST) content using partial least squares regression (PLS-R). The results using this method indicated that it was not possible to accurately discriminate fruit with levels of ST below 0.04%, especially in the case of DA fruits (42.2%). Thus, another classification models were performed using partial least squares discriminant analysis (PLS-DA) that included other properties in order to discriminate between A and DA using the ST threshold. The most accurate models using all and optimal wavelengths selected were those which focused on the middle and apex areas of the fruit, a correct classification rate of 87.0% being achieved for A fruits and above 84.4% for DA fruits. To date, there are only subjective and destructive analytical methods to monitor the effectiveness of the astringency removal treatments in persimmon. The results obtained in this study indicate that hyperspectral images can therefore be considered as an objective and non-destructive alternative in the control of this process., This work was partially funded by INIA and FEDER funds through project RTA2015-00078-00-00. Sandra Munera thanks INIA for the FPI-INIA grant num. 43 (CPR2014-0082), partially supported by European Union FSE funds.
- Published
- 2019
22. Effectiveness of Strategies to Promote Adherence to Rehabilitation in Total Knee Arthroplasty
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José Blasco, Sergio Roig-Casasús, Celedonia Igual-Camacho, Beatriz Díaz-Díaz, José Pérez-Maletzki, and Fernando Domínguez-Navarro
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Rehabilitation ,Physical Therapy, Sports Therapy and Rehabilitation - Published
- 2022
23. Conversational Chatbot to Promote Adherence to Rehabilitation After Total Knee Replacement: Implementation and Feasibility
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José Blasco, Sergio Roig-Casasús, Celedonia Igual-Camacho, Beatriz Díaz-Díaz, and José Pérez-Maletzki
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Rehabilitation ,Physical Therapy, Sports Therapy and Rehabilitation - Published
- 2022
24. Visão computacional aplicada a alimentos e produtos agrícolas
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José Blasco, Juliana Aparecida Fracarolli, Fernanda Fernandes Adimari Pavarin, and Wilson Castro
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Imagens digitais ,Artificial intelligence ,Visão de máquina ,Machine vision ,Computer science ,Agriculture (General) ,Control (management) ,Soil Science ,Composition analysis ,Horticulture ,Field (computer science) ,S1-972 ,Agricultura 4.0 ,Machine learning ,Computer vision ,Agriculture 4.0 ,business.industry ,Deep learning ,Sorting ,Aprendizado de máquina ,Inteligência artificial ,Agriculture ,Key (cryptography) ,business ,Agronomy and Crop Science ,Digital images - Abstract
Computer vision (CV) has been applied for years to automate many human activities. It is one of the key technologies for the modernization of the agri-food industry towards the fourth industrial revolution (Industry 4.0). In the agricultural sector, CV systems are applied to automate or obtain information from many agricultural tasks such as planting, cultivation, farm management, disease control, weed control or robotic harvesting. It is also widely used in postharvest to automate and obtain objective information in processes such as quality control and evaluation, damage detection, classification of fruits or vegetables in commercial categories or composition analysis. One of the main advantages is the ability of this technology to obtain information in regions of the spectrum that are invisible to the human eye. An example is the case of hyperspectral imaging systems. These systems generate a large amount of data that needs to be processed efficiently, creating robust and repeatable statistical models that allow the technology to be implemented at an industrial level. To achieve this, it is necessary to couple CV systems with advanced artificial intelligence tools such as machine learning or deep learning. The objective of this work is to review the latest advances in CV systems applied to food and agricultural products and processes. RESUMO A visão computacional (CV) tem sido aplicada há anos para automatizar muitas atividades humanas. É uma das tecnologias-chave para a modernização da indústria agroalimentar em direção à quarta revolução industrial (Indústria 4.0). No setor agrícola, sistemas CV são aplicados para automatizar ou obter informações de muitas tarefas agrícolas, como plantio, cultivo, gerenciamento de fazenda, controle de doenças, controle de ervas daninhas ou colheita robótica. Também é amplamente utilizado em pós-colheita para automatizar e obter informações objetivas em processos como controle de qualidade e avaliação , detecção de danos, classificação de frutas ou vegetais em categorias comerciais ou análise de composição. Uma das principais vantagens é a capacidade desta tecnologia de obter informações em regiões do espectro invisíveis ao olho humano. Um exemplo é o caso de sistemas de imagens hiperespectrais. Esses sistemas geram uma grande quantidade de dados que precisam ser processados de forma eficiente, criando modelos estatísticos robustos e repetíveis que permitam a tecnologia a ser implementada a nível industrial. Para isso, é necessário acoplar os sistemas de CV a ferramentas avançadas de inteligência artificial, como aprendizado de máquina ou aprendizado profundo. O objetivo deste trabalho é revisar os últimos avanços em sistemas de CV aplicados a alimentos e produtos e processos agrícolas.
- Published
- 2021
25. Claves diagnósticas en dermatología
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Ricardo Ruiz Villaverde, José Blasco Melguizo and Ricardo Ruiz Villaverde, José Blasco Melguizo
- Published
- 2009
26. Efectos de un programa de ejercicio combinado de impacto, fuerza y resistencia en la prevención de osteoporosis de mujeres posmenopáusicas
- Author
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Celedonia Igual-Camacho, José Blasco, David Hernández-Guillén, and C. García-Gomariz
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Exercici terapèutic ,Fisioteràpia ,Physical Therapy, Sports Therapy and Rehabilitation - Abstract
Resumen Antecedentes y objetivo Las mujeres posmenopausicas son una poblacion susceptible de desarrollar osteoporosis. El objetivo del presente estudio fue determinar los efectos de un programa de ejercicio fisico combinado de impacto, fuerza y resistencia en mujeres posmenopausicas. Materiales y metodos Estudio de intervencion prospectivo, con un grupo que incluyo a mujeres posmenopausicas que no tenian pautado tratamiento farmacologico para la prevencion de osteoporosis. Se realizo una intervencion de 2 anos de duracion, con 2 sesiones de entrenamiento por semana, basada en ejercicios de impacto, fuerza y resistencia progresiva. Se estimo el indice T score en femur y columna para determinar posibles cambios en la densidad mineral osea tras la intervencion. Resultados Dieciseis mujeres de 49,4 anos (DE 5,2) formaron parte del estudio. Tras la intervencion, no se encontraron diferencias significativas con respecto a los valores basales de T score de femur y columna (p > 0,05), lo que indica que los niveles de densidad osea se mantuvieron tras 2 anos. Conclusiones Dos anos de entrenamiento para prevencion de osteoporosis basado en un programa combinado de resistencia, fuerza e impacto es efectivo para mantener los niveles de densidad mineral osea de mujeres posmenopausicas. Los resultados indican que el ejercicio fisico sin tratamiento farmacologico es efectivo para la prevencion de osteoporosis en esta poblacion.
- Published
- 2019
27. A comparison between NIR and ATR-FTIR spectroscopy for varietal differentiation of Spanish intact almonds
- Author
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Pau Talens, María Jesús Lerma-García, José Blasco, Victoria Cortés, and José M. Barat
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Intact almond ,QDA ,TECNOLOGIA DE ALIMENTOS ,010401 analytical chemistry ,Near-infrared spectroscopy ,Atr ftir spectroscopy ,NIR ,04 agricultural and veterinary sciences ,Quadratic classifier ,PLS-DA ,040401 food science ,01 natural sciences ,0104 chemical sciences ,0404 agricultural biotechnology ,Varietal differentiation ,Attenuated total reflection ,Classification methods ,Spectral data ,Biological system ,ATR-FTIR ,Food Science ,Biotechnology ,Mathematics - Abstract
[EN] The rapid and easy classification of almond varieties with similar morphology, different quality properties and, in most cases, different prices is interesting to protect both the almond industry and the consumers from fraud. Therefore, in this work, intact almond kernels from four Spanish varieties (`Guara¿, `Rumbeta¿, `Marcona¿ and `Planeta¿) were analysed using both near infrared (NIR) and attenuated total reflectance Fourier-transform infrared (ATR-FTIR) spectroscopy. After spectra measurement, NIR and ATR-FTIR spectral data were pre-treated and employed to construct two classification methods (partial least square-discriminant analysis (PLS-DA) and quadratic discriminant analysis (QDA)) in order to check their ability to classify almonds according to their variety. The best overall accuracies (94.45%) were obtained with the PLS-DA model of ATR-FTIR and the QDA model of NIR data. These results confirm that both spectroscopic techniques, if the optimal statistical model is selected, are powerful tools to reliably discriminate almonds according to their varieties., Victoria Cortés López thanks the Spanish Ministry of Education, Culture and Sports for the FPU grant (FPU13/04202). The authors wish to thank the cooperative Agricoop for kindly providing the samples used in the experiments. This work was partially funded by INIA and FEDER funds through project RTA2015-00078-00-00.
- Published
- 2018
28. WHEN A FULLY FACE-TO-FACE DEGREE BECAME REMOTE IN A FEW DAYS: IMPACT OF THE SPANISH COVID-19 QUARANTINE ON THE DEGREE IN MANAGEMENT AND PUBLIC ADMINISTRATION AT THE UNIVERSITAT JAUME I
- Author
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Sergio José Blasco, Mariam Camarero, Beatriz Susana Tomás, Alma María Rodríguez, Oscar Coltell, Marta Oller, Andreu Arnau, and Adrián Oller
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Face-to-face ,Coronavirus disease 2019 (COVID-19) ,law ,Political science ,Quarantine ,Public administration ,Degree (temperature) ,law.invention - Published
- 2021
29. Editorial: Deep learning approaches applied to spectral images for plant phenotyping
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Gerrit Polder, Jose Blasco, and Haiyan Cen
- Subjects
multispectral imaging ,hyperspectral imaging ,imaging spectroscopy ,deep neural networks ,convolutional neural networks ,pre-trained networks ,Plant culture ,SB1-1110 - Published
- 2024
- Full Text
- View/download PDF
30. Detection of Invisible Damages in ‘Rojo Brillante’ Persimmon Fruit at Different Stages Using Hyperspectral Imaging and Chemometrics
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José Blasco, Alejandro Rodríguez-Ortega, Sergio Cubero, Nuria Aleixos, Juan Gómez-Sanchis, and Sandra Munera
- Subjects
Health (social science) ,N01 Agricultural engineering ,EXPRESION GRAFICA EN LA INGENIERIA ,Nondestructive ,Plant Science ,TP1-1185 ,Biology ,Health Professions (miscellaneous) ,Microbiology ,Article ,computer vision ,Chemometrics ,Browning ,H20 Plant diseases ,Diospyros kaki ,Spectral data ,browning ,Fruit quality ,Chemical technology ,fruit quality ,Hyperspectral imaging ,food and beverages ,chemometrics ,Q01 Food science and technology ,nondestructive ,Q02 Food processing and preservation ,Horticulture ,Principal component analysis ,H50 Miscellaneous plant disorders ,Computer vision ,Food Science - Abstract
[EN] The main cause of flesh browning in 'Rojo Brillante' persimmon fruit is mechanical damage caused during harvesting and packing. Innovation and research on nondestructive techniques to detect this phenomenon in the packing lines are necessary because this type of alteration is often only seen when the final consumer peels the fruit. In this work, we have studied the application of hyperspectral imaging in the range of 450-1040 nm to detect mechanical damage without any external symptoms. The fruit was damaged in a controlled manner. Later, images were acquired before and at 0, 1, 2 and 3 days after damage induction. First, the spectral data captured from the images were analysed through an algorithm based on principal component analysis (PCA). The aim was to automatically separate intact and damaged fruit, and to detect the damage in the PC images when present. With this algorithm, 90.0% of intact fruit and 90.8% of damaged fruit were correctly detected. A model based on partial least squares-discriminant analysis (PLS-DA), was later calibrated using the mean spectrum of the pixels detected as damaged, to determine the moment when the fruit was damaged. The model differentiated fruit corresponding correctly to 0, 1, 2 and 3 days after damage induction, achieving a total accuracy of 99.4%., This work is co-funded by the projects AEI PID2019-107347RR-C31, PID2019-107347RR-C32, PID2019-107347RR-C33, IVIA-GVA 51918 and the European Union through the European Regional Development Fund (ERDF) of the Generalitat Valenciana 2014-2020.
- Published
- 2021
31. Automated Detection of Tetranychus urticae Koch in Citrus Leaves Based on Colour and VIS/NIR Hyperspectral Imaging
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Patricia Chueca, María G. González-González, José Blasco, and Sergio Cubero
- Subjects
0106 biological sciences ,Integrated pest management ,H10 Pests of plants ,optical sensors ,N01 Agricultural engineering ,Automated monitoring pest ,medicine.disease_cause ,01 natural sciences ,Phyllocnistis citrella ,0404 agricultural biotechnology ,Image processing ,Infestation ,medicine ,Tetranychus urticae ,Citrus damage ,two-spotted spider mite ,Red spider mites ,biology ,Spots ,integrated pest management ,citrus damage ,Hyperspectral imaging ,automated monitoring pest ,Agriculture ,04 agricultural and veterinary sciences ,biology.organism_classification ,040401 food science ,image processing ,Two-spotted spider mite ,010602 entomology ,Horticulture ,red spider mite ,Optical sensors ,N20 Agricultural machinery and equipment ,PEST analysis ,Agronomy and Crop Science - Abstract
Tetranychus urticae Koch is an important citrus pest that produces chlorotic spots on the leaves and scars on the fruit of affected trees. It is detected by visual inspection of the leaves. This work studies the potential of colour and hyperspectral imaging (400–1000 nm) under laboratory conditions as a fast and automatic method to detect the damage caused by this pest. The ability of a traditional vision system to differentiate this pest from others, such as Phyllocnistis citrella, and other leaf problems such as those caused by nutritional deficiencies, has been studied and compared with a more advanced hyperspectral system. To analyse the colour images, discriminant analysis has been used to classify the pixels as belonging to either a damaged or healthy leaves. In contrast, the hyperspectral images have been analysed using PLS DA. The rate of detection of the damage caused by T. urticae with colour images reached 92.5%, while leaves that did not present any damage were all correctly identified. Other problems such as damage by P. citrella were also correctly discriminated from T. urticae. Moreover, hyperspectral imaging allowed damage caused by T. urticae to be discriminated from healthy leaves and to distinguish between recent and mature leaves, which indicates whether it is a recent or an older infestation. Furthermore, good results were achieved in the discrimination between damage caused by T. urticae, P. citrella, and nutritional deficiencies.
- Published
- 2021
32. Clinical Simulation in pediatrics and neonatology using EDISON: an educational innovation project
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Pablo García-Molina, Manuel Ruescas-Pérez, José Blasco, Enrique Sanchis-Sánchez, Pedro García-Martínez, Pablo Buck-Sainz-Rozas, and Evelin Balaguer-López
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medicine.medical_specialty ,Medical education ,Cardiopulmonary resuscitation ,Higher education ,business.industry ,medicine.medical_treatment ,Teaching ,Clinical simulation ,Educational systems ,Educational innovation ,Higher Education ,Pediatrics ,University teaching ,medicine ,Learning ,Neonatology ,Psychology ,business - Abstract
Introduction: Clinical simulation is a tool that allows creating controlled and safe spaces that mimic reality, where students can acquire skills and abilities prior to facing real situations. Methodology: This is a study with two phases. The first quasi-experimental phase where 3 questionnaires were used; two of them to assess knowledge (pretest - posttest) and the other one to assess the satisfaction of the training action. And the second phase was analytical, where the effectiveness of a training intervention in a confinement context based on the use of audiovisual materials created through EDISON was evaluated. Results: In 2019 the average satisfaction of the students was 9.22 (SD 0.72) out of 10. The most valued item was the one related to the domain that the instructors had regarding the knowledge imparted, with 9.79 out of 10. The students' knowledge improved in 9 of the 11 questions. Conclusions: The satisfaction of the students and the knowledge acquired were remarkable, being clinical simulation a methodology that helps to consolidate the knowledge and skills put into practice.
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- 2021
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- View/download PDF
33. Near infrared hyperspectral imaging and spectral unmixing methods for evaluation of fiber distribution in enriched pasta
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José Blasco, Maria Teresa Pedrosa Silva Clerici, Nuria Aleixos, Douglas Fernandes Barbin, Amanda Teixeira Badaró, José Manuel Amigo, and Amanda Rios Ferreira
- Subjects
Dietary Fiber ,Materials science ,EXPRESION GRAFICA EN LA INGENIERIA ,Hyperspectral imaging ,Pasta ,Flour ,Wheat flour ,01 natural sciences ,Least squares ,Analytical Chemistry ,Q04 Food composition ,0404 agricultural biotechnology ,Fiber ,Least-Squares Analysis ,Near infrared hyperspectral imaging ,Triticum ,Multivariate curve resolution ,Spectroscopy, Near-Infrared ,010401 analytical chemistry ,Water ,04 agricultural and veterinary sciences ,General Medicine ,Hyperspectral Imaging ,NIR ,Q01 Food science and technology ,040401 food science ,0104 chemical sciences ,Biological system ,Food Analysis ,Spectral unmixing ,Food Science - Abstract
[EN] Pasta is mostly composed by wheat flour and water. Nevertheless, flour can be partially replaced by fibers to provide extra nutrients in the diet. However, fiber can affect the technological quality of pasta if not properly distributed. Usually, determinations of parameters in pasta are destructive and time-consuming. The use of Near Infrared-Hyperspectral Imaging (NIR-HSI), together with machine learning methods, is valuable to improve the efficiency in the assessment of pasta quality. This work aimed to investigate the ability of NIR-HSI and augmented Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) for the evaluation, resolution and quantification of fiber distribution in enriched pasta. Results showed R2V between 0.28 and 0.89, %LOF < 6%, variance explained over 99%, and similarity between pure and recovered spectra over 96% and 98% in models using pure flour and control as initial estimates, respectively, demonstrating the applicability of NIR-HSI and MCR-ALS in the identification of fiber in pasta., This work was supported by the Coordenaçao de Aperfeicoamento de Pessoal de Nivel Superior -Brasil (CAPES) [Finance Code 001]; Sao Paulo Research Foundation (FAPESP) [grant numbers 2008/57808-1, 2014/50951-4, 2015/24351-2, 2017/17628-3, 2019/06842-0]; and by GVA-IVIA and FEDER funds through project IVIA-51918. The authors would like to thank Nutrassim Food Ingredients company for the donation of the fiber samples, the support provided by Mrs. Cristiane Vidal during NIR-HSI system operation and data processing and Dr. Celio Pasquini for promptly receiving us in the laboratory that he coordinates (Grupo de instrumentaçao e automaçao em quimica analitica, Instituto de quimica, Universidade Estadual de Campinas, Campinas-SP, Brazil) to data acquisition.
- Published
- 2021
34. Sensors I: Color Imaging and Basics of Image Processing
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Won Suk Lee, José Blasco, and Karkee, Manoj
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N01 Agricultural engineering ,Computer science ,Machine vision ,Object detection ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Image processing ,HSL and HSV ,Color models ,Imaging sensors ,Hough transform ,law.invention ,Segmentation ,law ,Grouping ,Computer vision ,Features ,business.industry ,Occlusion ,Shutter speed ,Illumination ,U30 Research methods ,Image enhancement ,Outdoor imaging ,CIELUV ,RGB color model ,Artificial intelligence ,business - Abstract
This chapter provides an overview of the basic concepts of color imaging and image processing techniques applied to sensing, monitoring and robotic operations in agriculture. To obtain good results with a vision system, it is very important to acquire high-quality images, particularly when captured with moving platform in a natural environment, by selecting a proper camera, acquisition settings, and lighting conditions. Image acquisition using CMOS and CCD sensors are explained along with proper adjustment of various imaging parameters such as aperture and shutter speed. Various color models that are relevant to image processing are described including RGB, HSV, HLS, CIELAB, and CIELUV as well as conversions between different color models. Following the introduction of color models, some basic image preprocessing techniques including image enhancement using histograms, morphological operations, and lowpass filtering are described. Also, various segmentation methods are discussed such as pixelwise or region–based techniques and classifiers. In addition, the chapter describes different object detection methods (with examples) that utilize various features such as colors, shapes, and textures. Hough transform and pattern matching are also commonly used techniques to detect various objects, and example applications based on these techniques are discussed. Finally, some of the crucial challenges for outdoor imaging such as varying illumination, occlusion, clustering, and movement of either the object or the camera when it is installed on a ground robotic system are discussed and a brief thought on future direction around these topics is presented.
- Published
- 2021
35. Clinical Applications
- Author
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Jose Ignacio Priego-Quesada, Rosario Salvador-Palmer, Enrique Sanchis, José D. Martín-Guerrero, Esther Ballester, José Blasco, Pilar Codoñer-Franch, Carlos Vergara-Hernández, Enrique Sanchis-Sánchez, Rosa Cibrián, and Rolando González-Peña
- Subjects
medicine.medical_specialty ,03 medical and health sciences ,0302 clinical medicine ,business.industry ,General surgery ,Medicine ,030229 sport sciences ,business ,Surgery ,030218 nuclear medicine & medical imaging - Abstract
The study of the diagnostic accuracy of Infrared Thermal Imaging in the diagnosis of orthopaedic injuries in childhood has been motivated by the high incidence of these injuries throughout the world, being one of the most common reasons for urgent medical consultation. Diagnosis of musculoskeletal injuries usually involves radiography, but this exposes children without fractures to unnecessary ionising radiation. This chapter assesses whether infrared thermography could provide a viable alternative in cases of trauma. To evaluate the accuracy of this technique new thermographic variables have been added to those commonly analysed, such as the extent of the injury and the difference in the size of the area that is at an equal temperature or higher than the maximum temperature of the healthy area. Non-linear cataloguing methods (decision tree models) have also been applied. With the protocol presented, infrared thermal imaging had a sensitivity of 0.91, a specificity of 0.88 and a negative predictive value of 0.95 for diagnosing musculoskeletal injuries.
- Published
- 2020
36. Visible-NIR ‘point’ spectroscopy in postharvest fruit and vegetable assessment: The science behind three decades of commercial use
- Author
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José Blasco, Kerry B. Walsh, Manuela Zude-Sasse, and Xudong Sun
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0106 biological sciences ,N01 Agricultural engineering ,Computer science ,Near-infrared spectroscopy ,Hyperspectral imaging ,Context (language use) ,04 agricultural and veterinary sciences ,Benchmarking ,Scientific literature ,Horticulture ,01 natural sciences ,Internal ,Quality ,040501 horticulture ,Colour ,Calibration ,Instrumentation (computer programming) ,0405 other agricultural sciences ,Spectroscopy ,Agronomy and Crop Science ,Instrumentation ,Near infrared spectroscopy ,010606 plant biology & botany ,Food Science ,Remote sensing - Abstract
The application of visible (Vis; 400–750 nm) and near infrared red (NIR; 750–2500 nm) region spectroscopy to assess fruit and vegetables is reviewed in context of ‘point’ spectroscopy, as opposed to multi- or hyperspectral imaging. Vis spectroscopy targets colour assessment and pigment analysis, while NIR spectroscopy has been applied to assessment of macro constituents (principally water) in fresh produce in commercial practice, and a wide range of attributes in the scientific literature. This review focusses to key issues relevant to the widespread implementation of Vis-NIR technology in the fruit sector. A background to the concepts and technology involved in the use of Vis-NIR spectroscopy is provided and instrumentation for in-field and in-line applications, which has been available for two and three decades, respectively, is described. A review of scientific effort is made for the period 2015 - February 2020, in terms of the application areas, instrumentation, chemometric methods and validation procedures, and this work is critiqued through comparison to techniques in commercial use, with focus to wavelength region, optical geometry, experimental design, and validation procedures. Recommendations for future research activity in this area are made, e.g., application development with consideration of the distribution of the attribute of interest in the product and the matching of optically sampled and reference method sampled volume; instrumentation comparisons with consideration of repeatability, optimum optical geometry and wavelength range). Recommendations are also made for reporting requirements, viz. description of the application, the reference method, the composition of calibration and test populations, chemometric reporting and benchmarking to a known instrument/method, with the aim of maximising useful conclusions from the extensive work being done around the world.
- Published
- 2020
37. Reporte de un caso de Cistinuria: Uso de herramientas de diagnóstico a nivel nacional
- Author
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Dominich Granado, José Blasco, Patricia Funes, and Rosa Guillén
- Abstract
La cistinuria es una enfermedad genetica que se engloba dentro de alteraciones congenitas del transporte de aminoacidos con formacion de calculos en las vias urinarias, si bien es poco frecuente se caracteriza por su elevada recurrencia. En este trabajo presentamos el caso de una paciente de 34 anos, con antecedentes de haber perdido un rinon por episodios anteriores de litiasis y con multiples recidivas que es diagnosticada mediante la deteccion de cistina por espectroscopia infrarroja como componente unico de 96 fragmentos de calculos removidos mediante nefrolitotomia percutanea. La paciente fue evaluada laboratorialmente mediante el perfil metabolico y la cristaluria. Las indicaciones de tratamiento especificas incluyeron la administracion de agentes alcalinizantes, regimen nutricional, y entrenamiento para control de pH urinario. Es importante senalar la agresividad de la litiasis de cistina con las consecuencias que puede tener la calidad de vida del paciente, y por tanto la importancia de contar con capacidades instaladas a nivel pais para el diagnostico y seguimiento de litiasis geneticas como la causada por la cistinuria.
- Published
- 2018
38. Potential of VIS-NIR hyperspectral imaging and chemometric methods to identify similar cultivars of nectarine
- Author
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José Manuel Amigo, José Blasco, Sergio Cubero, Pau Talens, Nuria Aleixos, and Sandra Munera
- Subjects
TECNOLOGIA DE ALIMENTOS ,EXPRESION GRAFICA EN LA INGENIERIA ,Stone fruit ,Analytical chemistry ,Image processing ,PLS-DA ,01 natural sciences ,Hyperspectral reflectance ,Non-destructive ,0404 agricultural biotechnology ,Hyperspectral image ,Linear regression ,Partial least squares regression ,Cultivar ,Cultivar discrimination ,Mathematics ,business.industry ,010401 analytical chemistry ,Quality control ,Hyperspectral imaging ,Pattern recognition ,Colour analysis ,04 agricultural and veterinary sciences ,Linear discriminant analysis ,040401 food science ,0104 chemical sciences ,Visual inspection ,Artificial intelligence ,business ,Food Science ,Biotechnology - Abstract
[EN] Product inspection is essential to ensure good quality and to avoid fraud. New nectarine cultivars with similar external appearance but different physicochemical properties may be mixed in the market, causing confusion and rejection among consumers, and consequently affecting sales and prices. Hyperspectral reflectance imaging in the range of 450¿1040 nm was studied as a non-destructive method to differentiate two cultivars of nectarines with a very similar appearance but different taste. Partial least squares discriminant analysis (PLS-DA) was used to develop a prediction model to distinguish intact fruits of the cultivars using pixel-wise and mean spectrum approaches, and then the model was projected onto the complete surface of fruits allowing visual inspection. The results indicated that mean spectrum of the fruit was the most accurate method, a correct discrimination rate of 94% being achieved. Wavelength selection reduced the dimensionality of the hyperspectral images using the regression coefficients of the PLS-DA model. An accuracy of 96% was obtained by using 14 optimal wavelengths, whereas colour imaging and a trained inspection panel achieved a rate of correct classification of only 57% of the fruits., This work was partially funded by INIA and FEDER funds through project RTA2015-00078-00-00. Sandra Munera thanks INIA for the FPI-INIA grant num. 43 (CPR2014-0082), partially supported by European Union FSE funds. The authors wish to thank Fruits de Ponent (Lleida) for providing the fruit.
- Published
- 2018
39. Firmness prediction in ‘Rojo Brillante’ persimmon using hyperspectral imaging technology
- Author
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A. Salvador, Sandra Munera, Sergio Cubero, José Blasco, C. Besada, Pau Talens, and N. Aleixos
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Hyperspectral imaging ,Crop quality ,Environmental science ,Horticulture ,Remote sensing - Published
- 2018
40. Analysis of astringency distribution in ‘Rojo Brillante’ persimmon using hyperspectral imaging
- Author
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José Blasco, Sergio Cubero, C. Besada, Nuria Aleixos, Sandra Munera, A. Salvador, and Rebeca Gil
- Subjects
Distribution (number theory) ,Environmental science ,Hyperspectral imaging ,Horticulture ,Remote sensing - Published
- 2018
41. Application of deep convolutional neural networks for the detection of anthracnose in olives using VIS/NIR hyperspectral images
- Author
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Souraya Benalia, José Blasco, Giuseppe Zimbalatti, Antonio Fazari, Sergio Cubero, Oscar J. Pellicer-Valero, Juan Gómez-Sanchis, and Bruno Bernardi
- Subjects
N01 Agricultural engineering ,business.industry ,Deep learning ,Fungi ,Hyperspectral imaging ,Forestry ,Pattern recognition ,Horticulture ,Biology ,Visual symptoms ,Convolutional neural network ,Computer Science Applications ,Quality inspection ,Spectral imaging ,N20 Agricultural machinery and equipment ,U30 Research methods ,Computer vision ,Artificial intelligence ,H20 Plant diseases ,Olea europaea ,business ,Agronomy and Crop Science - Abstract
Anthracnose is one of the primary diseases that affect olive production before and after harvest, causing severe damage and economic losses. The objective of this work is to detect this disease in the early stages, using hyperspectral images and advanced modelling techniques of Deep Learning (DL) and convolutional neural networks (CNN). The olives were artificially inoculated with the fungus. Hyperspectral images (450–1050 nm) of each olive were acquired until visual symptoms of the disease were observed, in some cases up to 9 days. The olives were classified into two classes: control, inoculated with water, and fungi composed of olives inoculated with the fungus. The ResNet101 architecture was chosen and adapted to process 61-band hyperspectral images with only two classes. The result showed that the applied model is very effective in detecting infected olives since the sensitivity of the method was very high from the beginning (85% on day 3 and 100% onwards). From a commercial point of view, these results align with the need to detect the maximum number of infected fruits.
- Published
- 2021
42. Rapid monitoring 1-MCP-induced modulation of sugars accumulation in ripening ‘Hayward’ kiwifruit by Vis/NIR hyperspectral imaging
- Author
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Da-Wen Sun, José Blasco, and Weihong Hu
- Subjects
Actinidia deliciosa ,Sucrose ,biology ,Chemistry ,Near-infrared spectroscopy ,Hyperspectral imaging ,Ripening ,Fructose ,04 agricultural and veterinary sciences ,Horticulture ,biology.organism_classification ,040401 food science ,Reflectivity ,chemistry.chemical_compound ,0404 agricultural biotechnology ,Biochemistry ,Sugar ,Agronomy and Crop Science ,Food Science - Abstract
This study aimed to rapidly and nondestructively monitor 1-methylcyclopropene (1-MCP)-induced modulation of sugars accumulation in ripening ‘Hayward’ kiwifruit by hyperspectral imaging (HSI). Kiwifruit (Actinidia deliciosa var. Hayward) were treated with 0.5 μL L−1 1-MCP for 24 h at 23 °C and then stored for 20 d at room temperature for ripening. Hyperspectral images of 1-MCP treated and control fruit were recorded using a visible/near infrared (Vis/NIR) HSI system (400–1000 nm). The mean reflectance spectra of the inner cortex and the core were combined together to build a robust model for sugar contents in sliced samples. The best prediction accuracy for glucose, fructose, and sucrose in control fruit based on less than 10 selected features were: R2P of 0.934, 0.867, and 0.705, respectively. Moreover, the visualization maps showed a different sugar accumulation between treated and control fruit, with the sugar contents in the 1-MCP treated kiwifruit being significantly inhibited and the inhibitions were more effective in inner cortex than the core. The current study presented a rapid method for glucose, fructose, and sucrose detection in intact and fresh-cut kiwifruit as well as provided some insights for the effects of 1-MCP action on sugar accumulation through visualizing their distributions.
- Published
- 2017
43. Is English information about erectile dysfunction on YouTube based on scientific evidence?
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Rafael Antonio Medina López, Cristina Baena Villamarín, Javier Mazuecos Quirós, José Blasco, José Pablo Pedraza Sánchez, and Guillermo Lendínez Cano
- Subjects
Male ,Video recording ,medicine.medical_specialty ,business.industry ,Urology ,Video Recording ,MEDLINE ,medicine.disease ,Scientific evidence ,Erectile dysfunction ,Erectile Dysfunction ,Humans ,Medicine ,Social media ,business ,Psychiatry ,Social Media - Abstract
Urological Note.
- Published
- 2020
44. Use of hyperspectral transmittance imaging to evaluate the internal quality of nectarines
- Author
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Sergio Cubero, Nuria Aleixos, José Blasco, Sandra Munera, Pau Talens, and José Manuel Amigo
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Hyperspectral imaging ,TECNOLOGIA DE ALIMENTOS ,EXPRESION GRAFICA EN LA INGENIERIA ,Stone fruit ,Soil Science ,Ripeness ,01 natural sciences ,Prunus ,Transmittance ,Cultivar ,Mathematics ,Flesh ,010401 analytical chemistry ,04 agricultural and veterinary sciences ,Split pit ,0104 chemical sciences ,Internal quality ,Horticulture ,Control and Systems Engineering ,040103 agronomy & agriculture ,0401 agriculture, forestry, and fisheries ,Computer vision ,Agronomy and Crop Science ,Food Science - Abstract
[EN] The internal quality of nectarines (Prunus persica L. Batsch var. nucipersica) cv. 'Big Top' (yellow flesh) and 'Magique' (white flesh) has been inspected using hyperspectral transmittance imaging. Hyperspectral images of intact fruits were acquired in the spectral range of 630-900 nm using transmittance mode during their ripening under controlled conditions. The detection of split pit disorder and classification according to an established firmness threshold were performed using PLS-DA. The prediction of the Internal Quality Index (IQI) related to ripeness was performed using PLS-R. The most important variables were selected using interval-PLS. As a result, an accuracy of 94.7% was obtained in the detection of fruits with split pit of the 'Big Top' cultivar. Accuracies of 95.7% and 94.6% were achieved in the classification of the 'Big Top' and 'Magique' cultivars, respectively, according to the firmness threshold. The internal quality was predicted through the IQI with R-2 values of 0.88 and 0.86 for the two cultivars. The results obtained indicate the great potential of hyperspectral transmittance imaging for the assessment of the internal quality of intact nectarines., This work was partially funded by INIA and FEDER funds through project RTA2015-00078-00-00. Sandra Munera thanks INIA for the FPI-INIA grant num. 43 (CPR2014-0082), partially supported by European Union FSE funds.
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- 2019
45. Preferred Outcome Measures Used in Randomized Clinical Trials of Total Knee Replacement Rehabilitation: A Systematic Review
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María C. Gómez, Pablo Puigcerver‐Aranda, Yolanda Acosta-Ballester, Celedonia Igual-Camacho, David Hernández-Guillén, Sergio Roig-Casasús, and José Blasco
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030506 rehabilitation ,medicine.medical_specialty ,WOMAC ,Geriatric rehabilitation ,Visual analogue scale ,Joint replacement ,medicine.medical_treatment ,Physical Therapy, Sports Therapy and Rehabilitation ,Cochrane Library ,law.invention ,03 medical and health sciences ,0302 clinical medicine ,Randomized controlled trial ,law ,Outcome Assessment, Health Care ,medicine ,Humans ,Range of Motion, Articular ,Arthroplasty, Replacement, Knee ,Randomized Controlled Trials as Topic ,Rehabilitation ,business.industry ,Osteoarthritis, Knee ,Neurology ,Physical therapy ,Quality of Life ,Neurology (clinical) ,0305 other medical science ,Literature survey ,business ,030217 neurology & neurosurgery - Abstract
Objective To determine the most frequently used outcome measures in total knee replacement rehabilitation trials. Literature survey Systematic review of randomized trials searched in five databases: Web of Science, MEDical Literature Analysis and Retrieval System, Physiotherapy Evidence Database, Scopus, and Cochrane Library. Methodology Trials were included if participants underwent total knee replacement rehabilitation and outcome measures were used to assess rehabilitation outcomes. A descriptive synthesis determined the frequency of using outcome measures and preferred assessment time points. Outcomes were classified into eight categories: patient- and clinician-reported function, performance-based function, balance, anxiety and depressive symptoms, quality of life, and others. Synthesis Eighty-one trials were included and 102 different outcome measures were classified. The most frequently reported outcome was knee range of motion, used in 54% of trials, followed by a visual analog scale of pain (43%) and Western Ontario and McMaster Universities Arthritis Index (WOMAC; 40%). Patient- and clinician-reported function were the categories most frequently assessed (74%), whereas performance-based measures were implemented by 56% of trials. The most frequent assessment time points were 1 week presurgery (52%) and 3 months postsurgery (39%). Conclusions There is consensus regarding the need to evaluate functional outcomes in total knee replacement rehabilitation trials but none regarding the outcome measure that should be used. These findings suggest that most trials include patient- and clinician-reported functional measures, along with pain and performance-based measures in trial designs.
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- 2019
46. FIRST OFFICIAL RE-ACCREDITATION OF THE UNIVERSITAT JAUME I DEGREE IN MANAGEMENT AND PUBLIC ADMINISTRATION: WEAKNESSES, STRENGTHS AND IMPROVEMENT INITIATIVES
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Beatriz Susana Tomás, Alma María Rodríguez, Marta Oller, Oscar Coltell, Sergio José Blasco, Andrés Arnau, Mariam Camarero, and Cristina Pauner
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Political science ,Public administration ,Degree (music) ,Accreditation - Published
- 2019
47. In-line Application of Visible and Near-Infrared Diffuse Reflectance Spectroscopy to Identify Apple Varieties
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Pau Talens, Victoria Cortés, Sergio Cubero, Nuria Aleixos, and José Blasco
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0106 biological sciences ,Diffuse reflectance infrared fourier transform ,EXPRESION GRAFICA EN LA INGENIERIA ,TECNOLOGIA DE ALIMENTOS ,Visible-near-infrared spectroscopy ,In-line ,01 natural sciences ,Industrial and Manufacturing Engineering ,Non-destructive ,0404 agricultural biotechnology ,010608 biotechnology ,Safety, Risk, Reliability and Quality ,Spectroscopy ,Remote sensing ,Mathematics ,Varietal discrimination ,Process Chemistry and Technology ,Near-infrared spectroscopy ,Apple ,04 agricultural and veterinary sciences ,Quadratic classifier ,Linear discriminant analysis ,040401 food science ,Internal quality ,Line (geometry) ,Principal component analysis ,Food Science - Abstract
[EN] One of the most studied techniques for the non-destructive determination of the internal quality of fruits has been visible and nearinfrared (VIS-NIR) reflectance spectroscopy. This work evaluates a new non-destructive in-line VIS-NIR spectroscopy prototype for in-line identification of five apple varieties, with the advantage that it allows the spectra to be captured with the probe at the same distance from all the fruits regardless of their size. The prototype was tested using varieties with a similar appearance by acquiring the diffuse reflectance spectrum of the fruits travelling on the conveyor belt at a speed of 0.81 m/s which is nearly 1 fruit/s. Principal component analysis (PCA) was used to determine the variables that explain the most variance in the spectra. Seven principal components were then used to perform linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA). QDA was found to be the best in-line classification method, achieving 98% and 85% success rates for red and yellow apple varieties, respectively. The results indicated that the in-line application of VIS-NIR spectroscopy that was developed is potentially feasible for the detection of apple varieties with an accuracy that is similar to or better than a laboratory system., This work was partially funded by the Generalitat Valenciana through project AICO/2015/122 and by INIA and FEDER funds through project RTA2015-00078-00-00. Victoria Cortes Lopez thanks the Spanish Ministry of Education, Culture and Sports for FPU grant (FPU13/04202).
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- 2019
48. Xf-Rovim. A Field Robot to Detect Olive Trees Infected by Xylella Fastidiosa Using Proximal Sensing
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Sergio Cubero, Beatriz Rey, José Blasco, and Nuria Aleixos
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0106 biological sciences ,LiDAR ,EXPRESION GRAFICA EN LA INGENIERIA ,Machine vision ,Vegetative indices ,Multispectral image ,Remotely operated vehicle ,01 natural sciences ,Asymptomatic detection ,Field (computer science) ,computer vision ,Multispectral imaging ,Pest detection aid ,multispectral imaging ,lcsh:Science ,Remote sensing ,biology ,asymptomatic detection ,Robotics ,pest detection aid ,vegetative indices ,04 agricultural and veterinary sciences ,biology.organism_classification ,Olive trees ,Lidar ,040103 agronomy & agriculture ,0401 agriculture, forestry, and fisheries ,General Earth and Planetary Sciences ,Robot ,Environmental science ,Computer vision ,lcsh:Q ,Xylella fastidiosa ,010606 plant biology & botany - Abstract
[EN] The use of remote sensing to map the distribution of plant diseases has evolved considerably over the last three decades and can be performed at different scales, depending on the area to be monitored, as well as the spatial and spectral resolution required. This work describes the development of a small low-cost field robot (Remotely Operated Vehicle for Infection Monitoring in orchards, XF-ROVIM), which is intended to be a flexible solution for early detection of Xylella fastidiosa (X. fastidiosa) in olive groves at plant to leaf level. The robot is remotely driven and fitted with different sensing equipment to capture thermal, spectral and structural information about the plants. Taking into account the height of the olive trees inspected, the design includes a platform that can raise the cameras to adapt the height of the sensors to a maximum of 200 cm. The robot was tested in an olive grove (4 ha) potentially infected by X. fastidiosa in the region of Apulia, southern Italy. The tests were focused on investigating the reliability of the mechanical and electronic solutions developed as well as the capability of the sensors to obtain accurate data. The four sides of all trees in the crop were inspected by travelling along the rows in both directions, showing that it could be easily adaptable to other crops. XF-ROVIM was capable of inspecting the whole field continuously, capturing geolocated spectral information and the structure of the trees for later comparison with the in situ observations., This work was partially supported by funding from the European Union's Horizon 2020 research and innovation programme under grant agreement 727987 Xylella Fastidiosa Active Containment Through a multidisciplinary-Oriented Research Strategy (XF-ACTORS).
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- 2019
49. Monitoring strategies for quality control of agricultural products using visible and near-infrared spectroscopy: A review
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Victoria Cortés, José Blasco, Nuria Aleixos, Pau Talens, and Sergio Cubero
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EXPRESION GRAFICA EN LA INGENIERIA ,TECNOLOGIA DE ALIMENTOS ,business.industry ,Vis nir spectroscopy ,Vis-NIR spectroscopy ,Visible and near infrared spectroscopy ,In-line ,04 agricultural and veterinary sciences ,040501 horticulture ,Agricultural science ,Work (electrical) ,Agriculture ,Political science ,Quantification ,Christian ministry ,Qualification ,Chemometrics ,0405 other agricultural sciences ,business ,Off line ,040502 food science ,Food Science ,Biotechnology ,Off-line - Abstract
[EN] Background: The increasing demand for quality assurance in agro-food production requires sophisticated analytical methods for in-line quality control. One of these techniques is visible and near-infrared (VIS-NIR) spectroscopy, which has low running costs, does not need sample preparation, and is non-destructive, environmentally friendly, and fast. Despite these advantages, only a limited amount of research has been conducted on VIS-NIR in-line applications to measure, control, and predict quality in fruits and vegetables. Scope and approach: The applicability of VIS-NIR spectroscopy for the off-line and in-line monitoring of quality in postharvest products has been addressed in this review. The document focuses on the comparison between the two processes for the same agro-food product, highlighting the main advantages and disadvantages, problems, solutions, and differences. Key findings and conclusions: VIS-NIR techniques, combined with chemometric methods, have shown great potential due to their fast detection speed, and the possibility of simultaneously predicting multiple quality parameters or distinguishing between products according to the objectives. Being able to automate processes is a great advantage compared to routine off-line analyses, mainly due to the savings achieved in time, material, and personnel. However, in numerous cases, in-line implementation has not been accomplished in the corresponding studies, hence the scarcity of real in-line applications. Recent demands, together with the advances being made in the technology and a reduction in the price of equipment, makes VIS-NIR technology an analytical alternative for continuous real-time food quality controls, which will become predominant in the next few years., This work was partially funded by INIA and FEDER funds through research project RTA2015-00078-00-00.Victoria Cortés López thanks the Spanish Ministry of Education, Culture and Sports for the FPU grant (FPU13/04202).
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- 2019
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50. Food and feed production
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Sandra Munera, Nuria Aleixos, José Blasco, and Sergio Cubero
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business.industry ,Computer science ,Hyperspectral imaging ,Production (economics) ,%22">Fish ,Pattern recognition ,Artificial intelligence ,Large range ,Food quality ,business - Abstract
Conventional analytical techniques employ destructive methods, which are normally expensive, contaminating, time-consuming and only a few samples per batch can be monitored at a time. Hyperspectral imaging, instead, can be applied to the inspection of a large range of food, including fish, meat, fruit, and vegetables. Depending on the type of food and the properties to be analyzed, different wavelength dispersion devices, cameras, or illumination sources have to be used to capture images in the most appropriate spectral ranges. Later, specific statistical prediction or classification models have to be built to analyze the huge amount of data captured by such devices. This chapter explores the use of hyperspectral imaging for practical applications in food quality and safety inspection. Different technologies for acquiring the images as well as the most commonly used methods to extract useful information from the images are described by analyzing the most recent applications.
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- 2019
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