Potential Fields as an External Force and Algorithmic Improvements in Deformable Models

Deformable Models are extensively used as a Pattern Recognition technique. They are curves defined within an image domain that can be moved under the influence of internal and external forces. Some trade-offs of standard deformable models algorithms are the selection of image energy function (external force), the location of initial snake and the attraction of contour points to local energy minima when the snake is being deformed. This paper proposes a new procedure using potential fields as external forces. In addition, standard Deformable Models algorithm has been enhanced with both this new external force and algorithmic improvements. The performance of the presented approach has been successfully proved to extract muscles from Magnetic Resonance Imaging (MRI) sequences of Iberian ham at different maturation stages in order to calculate their volume change. The main conclusions of this paper are the practical viability of potential fields used as external forces, as well as the validation of the algorithmic improvements developed. The feasibility of applying Computer Vision techniques, in conjunction with MRI, for determining automatically the optimal ripening time of the Iberian ham is a practical conclusion reached with the proposed approach

Computer image analysis for intramuscular fat segmentation in dry-cured ham slices using convolutional neural networks

Determination of intramuscular fat (IMF) content in dry cured meats is critical because it affects the sensory quality and consumer's acceptability. Recently, deep learning has become one of the most promising techniques in machine learning for image analysis. However, few applications in food products are found in the literature. This study presents the application of deep learning for the detection of intramuscular fat (IMF) in images of slices of dry cured ham. 8 convolutional neural networks (CNNs) have been studied and compared using segmented images (252 for training, 61 for validation and 62 for testing). The performance was compared to other simple CNNs. CNNs were able to segment IMF with an overall pixel accuracy of 0.99 and a recall and precision rates for fat near 0.82 and 0.84, respectively, using a limited number of training images. However, performance is affected by the quality of the ground truth due to the difficulty of labelling correctly pixels.info:eu-repo/semantics/acceptedVersio

Automatic marbling prediction of sliced dry-cured ham using image segmentation, texture analysis and regression

Dry-cured ham is a traditional Mediterranean meat product consumed throughout the world. This product is very variable in terms of composition and quality. Consumer’s acceptability of this product is influenced by different factors, in particular, visual intramuscular fat and its distribution across the slice, also known as marbling. On-line marbling assessment is of great interest for the industry for classification purposes. However, until now this assessment has been traditionally carried out by panels of experts and this methodology cannot be implement in industry. We propose a complete automatic system to predict marbling degree of dry-cured ham slices, which combines: (1) the color texture features of regions of interest (ROIs) extracted automatically for each muscle; and (2) machine learning models to predict the marbling. For the ROIs extraction algorithm more than the 90% of pixels of the ROI fall into the true muscle. The proposed system achieves a correlation of 0.92 using the support vector regression and a set of color texture features including statistics of each channel of RGB color image and Haralick’s coefficients of its gray-level version. The mean absolute error was 0.46, which is lower than the standard desviation (0.5) of the marbling scores evaluated by experts. This high accuracy in the marbling prediction for sliced dry-cured ham would allow to deploy its application in the dry-cured ham industryThis work has received financial support from the Xunta de Galicia (Centro singular de investigación de Galicia, accreditation 2020– 2023) and the European Union (European Regional Development Fund–ERDF), Project ED431G-2019/04. IRTA’s contribution was also funded by the CCLabel project (RTI-2018- 096883-R-C41) and the CERCA programme from Generalitat de CatalunyaS

Application of non-destructive techniques for the determination of quality parameters and classification of iberian pig carcasses

Tesis por compendio de publicaciones[ES]El cerdo ibérico es una raza autóctona ligada al ecosistema de la dehesa, localizada en el sureste de la Península Ibérica y reconocida por la destacable calidad organoléptica de los productos derivados. La alta demanda de productos ibéricos, junto con una limitada producción de animales cebados en regímenes extensivos alimentados a base de bellota y pasto (montanera), ha dado lugar a la cría de animales en regímenes intensivos y al empleo de cruces con razas mejorantes. La calidad final de la carne de estos animales, y de sus productos derivados, está fuertemente relacionada con diferentes factores como la producción animal, la raza, la alimentación, la edad o el peso en el momento del sacrificio. Son diversos los métodos analíticos que han sido estudiados y aplicados de cara a poder garantizar la autenticidad de la raza y la alimentación suministrada al animal, sin embargo, en el momento actual no existe ningún método analítico oficial. La espectroscopia de infrarrojo cercano (NIR) es una herramienta multiparamétrica que ha sido ampliamente empleada para evaluar características de la carne y calidad de los productos cárnicos. En el sector ibérico, la tecnología NIR ha sido aplicada para la cuantificación de los contenidos en proteína, grasa y humedad, para la predicción del perfil en ácidos grasos y de la dieta del cerdo durante el proceso de engorde. Esta metodología analítica permite obtener los resultados de forma inmediata, individualizada, no destructiva y respetuosa con el medio ambiente. Sin embargo, la interpretación de los espectros obtenidos mediante su aplicación requiere ser complementada con complejos métodos quimiométricos. En esta tesis se propone el uso de la tecnología NIRS con el fin de predecir parámetros determinantes de la calidad de la grasa en cerdo ibérico como el perfil lipídico y la relación isotópica de Carbono (δ13 C). Se aborda así mismo la aplicación de la tecnología NIRS y la espectrometría de movilidad iónica acoplada a la cromatografía de gases (GC-IMS) con fines de clasificación/autentificación. Finalmente, la tesis analiza la viabilidad del uso de equipos portátiles, que facilitan el trabajo en campo, y que han experimentado un claro auge en los últimos años. En el primer artículo incluido en la presente tesis, se estudió la posibilidad de predecir la composición del perfil de ácidos grasos y el valor de δ13 C (‰) en grasa subcutánea intacta usando un equipo NIRS portátil. Los resultados se compararon con los obtenidos aplicando el equipo NIRS de sobremesa tanto en grasa fundida como intacta. En el segundo de los artículos se evalúan los cambios en el perfil lipídico de la grasa y en la relación isotópica de carbono, antes y después de la fase de cebo en montanera, analizándose así mismo la influencia de diferentes tiempos de permanencia en montanera. La existencia de correlaciones entre el isótopo δ13 C (‰) y el perfil lipídico también ha sido estudiada con el fin de poder clasificar el producto en función de la alimentación animal. El tercer artículo evalúa el potencial de clasificación de la tecnología NIRS frente a GC-IMS, en grasa subcutánea, en el momento del sacrificio. El objetivo que se persigue es la clasificación en función de la raza de los animales y los días que han permanecido alimentándose en régimen de montanera. Las conclusiones que derivan de los estudios realizados señalan que la utilización de la espectroscopia NIR, tanto con equipos de sobremesa como portátiles, resulta adecuada para predecir parámetros de calidad en la grasa de cerdo ibérico. Esta tecnología podría reemplazar a los análisis químicos en el laboratorio, más costosos y menos respetuosos con el medio ambiente. La combinación de herramientas quimiométricas con las técnicas de CG-IMS y NIRS ha permitido clasificar la grasa en función del periodo de alimentación en montanera y de la raza. Todo ello apunta al enorme potencial la metodología NIRS para garantizar la autenticidad de las canales en el sector del cerdo ibérico, ofreciendo la posibilidad de conocer los resultados de forma inmediata y de operar de forma rutinaria en las líneas de faenado. [EN]The Iberian pig is an indigenous breed associated with the dehesa ecosystem, which is located in the southwest of the Iberian Peninsula. It is well known for the remarkable organoleptic quality of its derivatives. The high demand for Iberian products, together with the limited production of Iberian pigs reared extensively and fed on acorns and grass (the montanera system), has led to intensive rearing of this breed and also to its crossbreeding with improved breeds. The final quality of the meat from these animals and their products is strongly correlated with different factors such as animal production, the breed, the feeding regime, and the age or slaughter weight. Several analytical techniques have been studied and applied to guarantee the authenticity of the breed and the feeding regime. However, there is currently no official analytical method for the purpose. Near Infrared Spectroscopy (NIR) is a multi-parametric tool which has been widely used to assess meat characteristics and meat product quality. In the sector of the Iberian breed, NIR technology has been applied to quantify protein, fat, and moisture, to predict the fatty acid profile, and to determine the feeding regime during the fattening period. This analytical methodology allows immediate individualised results to be obtained without sample destruction and in an environmentally friendly manner. However, the spectra obtained need to be interpreted by complex chemometric methods. This PhD thesis proposes the use of NIRS technology for predicting parameters which determine the quality of Iberian pig fat, such as the lipid profile and the carbon isotopic ratio δ13 C (‰). The application of NIRS technology and gas chromatography together with ion mobility spectrometry (GC-IMS) for classification/authentication purposes is also addressed. Finally, this study analyses the viability of using portable equipment, which facilitates work in situ and has experienced a boom in recent years. The first article included in the PhD thesis evaluated the feasibility of predicting the lipid profile composition and the δ13 C (‰) of intact subcutaneous fat by using a portable NIRS device. The results were compared with those obtained by using benchtop NIRS equipment on both extracted and intact fat.In the second article, the changes in the lipid profile and the carbon isotope ratio observed before and after the fattening period on the montanera were evaluated. The influence of different montanera times on these parameters was also analysed. Significant correlations between the δ13 C isotope (‰) and the different fatty acids were studied in order to classify the samples according to animal feeding. The third article compares the classification ability of NIRS and GC-IMS technologies when applied at slaughter to subcutaneous fat. The aim was to achieve a correct classification according to the breed and the number of days spent feeding under the montanera system. The conclusions deriving from the present studies indicate that the application of NIR spectroscopy, using both benchtop and portable equipment, is suitable for predicting the quality parameters of Iberian fat. This technology could replace costlier and less environmentally-friendly laboratory chemical analyses. The combination of chemometric tools with NIRS and GC-IMS technologies has made it possible to classify Iberian fat correctly according to the fattening time and the breed. All these results point to the enormous potential of NIRS technology to guarantee the authenticity of Iberian pig carcasses. In fact, it offers the possibility of ascertaining the results immediately which allows for routine operations on the slaughter lines

Control no destructivo e in situ de productos y procesos en la industria del cerdo ibérico usando sensores espectrales de infrarrojo cercano

En esta tesis doctoral, se presentan distintos estudios en los que se ha diseñado, desarrollado, evaluado y optimizado el uso de la tecnología NIRS como sistema de control in situ de procesos y productos y de apoyo a la toma de decisiones en la industria de transformación del sector del cerdo ibérico. El trabajo abarca desde aspectos científicos-técnicos, orientados a las necesidades de la industria y relacionados con la implantación in situ de sensores NIRS portátiles en el control de calidad de productos derivados del cerdo ibérico, como aspectos de investigación básica, relacionados con la propagación de la radiación NIR a través de tejido porcino. Este documento consta de nueve capítulos. El primero de ellos proporciona una introducción y define el marco en el que se desarrolla toda la tesis doctoral. El segundo fija los objetivos a alcanzar. En el tercer capítulo, se recoge una revisión bibliográfica sobre la realidad actual del sector productivo del cerdo ibérico, las últimas investigaciones en el control de calidad de productos derivados de este animal, así como el estado del arte de la tecnología NIRS. El siguiente capítulo describe, de forma general, los materiales y métodos utilizados en los distintos apartados de esta tesis doctoral. El quinto capítulo contiene los resultados generados en esta tesis doctoral, tanto los publicados o enviados a revistas internacionales como los estudios independientes de cada uno de los apartados que constituyen esta sección. Posteriormente, se realiza una reflexión general de todo el trabajo para dar una visión unificada del mismo, asimismo se proporciona algunas recomendaciones y perspectivas para futuros trabajos de investigación, desarrollo e innovación (I+D+i) en la implantación de la tecnología NIRS en el sector del cerdo ibérico. En el séptimo capítulo, se recogen las conclusiones de esta tesis doctoral. El octavo capítulo contiene todas las citas bibliográficas de este documento. Finalmente, en el noveno apartado se agrupan distintas publicaciones presentadas en congresos internacionales y nacionales, así como otros trabajos bibliográficos publicados en revistas internacionales. Además, se incluye un manual sobre el procesamiento de datos procedentes de equipos portátiles MEMS-NIRS, como el evaluado en esta tesis doctoral, así como una guía práctica para el uso y calibración de sistemas de dobles esferas integradoras que se espera que sea de utilidad para futuros investigadores o técnicos en este área. En referencia a las publicaciones, el Artículo 1 (sección 5.1.1) realiza una aportación metodológica para el desarrollo, validación, control y recalibración de modelos NIRS cuantitativos de carne picada de cerdo ibérico. La metodología descrita en este apartado permite, con un coste económico reducido, actualizar modelos NIRS cuantitativos para obtener predicciones fiables en rutina a lo largo del tiempo. Esta misma metodología fue,...This thesis presents several studies in which NIRS technology has been developed, applied, evaluated and validated as an in-situ process and product control system in the iberian pig industry. The work ranges from scientificallytechnical aspects oriented to the industry and related to the implementation of in-situ handheld NIRS sensors for the quality control of iberian pig products and basic research studies related to the NIR radiation propagation through porcine tissues. This document consists of nine chapters. The first one provides an introduction and framework in which the present PhD thesis is developed. The second chapter describes the objectives achieved in this thesis. The third chapter provides a literature review of the current iberian pig production sector, the latest advances in the quality control of iberian pig products, as the state of art of the NIRS technology. The next chapter describes, generally, the materials and methods used in the different sections of this thesis. The fifth chapter contains the results generated in this PhD thesis which have been published or submitted to international journals or written in independent studies in each of the parts of this section. Subsequently, general considerations of the all work are done to provide a general view of the results, also it provides some recommendations and perspectives for future research, development and innovation in the implementation of NIRS technology in the Iberian pig sector. The seventh chapter contains the conclusions, providing a perspective on the future implementation of this technology in the iberian pig sector. The eighth contains all citations of this document. The last chapter, as an annex, comprises the several publications done in national and international conferences, as other reviewed published papers together with two manual: one for data processing of MEMS-NIRS spectral information and other related with the calibration procedure of double integrating spheres systems, which is expected to be useful for future researchers and technicians in this area. Concerning the published papers, Paper 1 (section 5.1.1) describes a methodology for the development, validation, monitoring and recalibration of quantitative NIRS models for routine control of ground iberian pork meat. The methodology described in this section enables, with a reduced economical cost, the update of NIRS models to obtain suitable prediction in routine over time. The same methodology was, later on, applied for the analysis of the main IP products traditionally used in the quality control, melted fat and intact adipose tissue (section 51.2 and 5.1.3, respectively). In these two studies, the monitoring and recalibration of quantitative NIRS models for estimating the main fatty acids of the lipid profile of IP animals is developed and evaluated..