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[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.

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.

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

[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.

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.

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.

[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.

[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.

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.

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.

[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.

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.

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.

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.

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.

[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.

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.

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.

Urological Note.

[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.

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.

[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).

[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).

[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).

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.