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Taking into account that in the literature on pork-production Life Cycle Assessment (LCA) there are a few studies about the Iberian pig, the present article evaluates an extensive (growing-fattening) Iberian-pig system in Spain, producing meat for Iberian ham and other quality-labelled products. The study has been based on Cumulative Energy Demand (CED), Global Warming Potential (GWP), ReCiPe (midpoint; endpoint) and USEtox (human toxicity; ecotoxicity). The analysis involves feed (for pigs and piglets), transportation, drinking water, straw usage and building materials (concrete). The impacts have been evaluated per kg of live or carcass weight (two functional units). The results show that the total impacts (per kg of live or carcass weight) range from: 1) 22.05 to 28.19 MJprim (CED), 2) 4.37 to 6.19 kg CO2.eq (GWP 20a, 100a and 500a), 3) 0.86 to 1.08 Pts (ReCiPe endpoint single-score, involving Human health, Ecosystems and Resources), 4) 9.9 × 10−6 to 1.2 × 10−5 DALY (ReCiPe endpoint with characterisation), 5) 2.8 × 10−7 to 3.5 × 10−7 (species.yr) (ReCiPe endpoint with characterisation), 6) 10.12 to 12.66 CTUe (USEtox: ecotoxicity). Overall, the results show that the feed for the pigs is responsible for the major part of the environmental impacts. More analytically, maize and soya are the components with the highest environmental impacts due to factors such as transportation, use of fertilisers and diesel fuel. The discussion about pig-production environmental impacts and the role of extensive pig farming is enriched with comparisons with the literature on pig-production LCA. Critical parameters are identified and discussed, with the aim of proposing solutions to reduce pork-production environmental impacts. Finally, the usefulness of the present study and future prospects are presented.

This text delves into the elements on which the notion of quality of a product is built. We believe that, in addition to the standards that regulate a given quality seal, there are other elements that consumers link to the excellence that distinguishes them. In order to deepen these notions, we have chosen two localised agri-food systems (LAS), the first case corresponds to Iberian acorn-ham from Spain and the second to chorizo from Toluca in Mexico. We resorted to a mixed methodology by combining quantitative and qualitative techniques whereby a study of those food systems in two different socio-political contexts was approached. This methodology has allowed us to identify the importance of informal instruments, based not only on institutionalised certification, but on informal mechanisms such as trust and proximity between producers and consumers. The results of this study show how the food quality categories may be guided from various logics depending on the context, categories, and sort of stakeholders involved. Finally, we propose a categorisation of food quality based on the conceptual framework of trust. This categorisation allows the Geographical Indications (GIs) valorisation initiatives to visualise the elements on which they can be guided to work with the different qualities in their LAS.

Infection with Toxoplasma gondii in humans has usually been related to the consumption of raw, undercooked or cured meat. Our study is based on the detection of T. gondii in cured legs and shoulders made from 100% Iberian sows fed mainly with acorn and raised as outdoor livestock in Aracena (Spain), which having been elaborated following a specific curing process (time period and location). An outdoor farm with a total of 636 animals was studied, showing a seroprevalence of 10% for the parasite T. gondii. Twenty individuals were chosen to be experimentally infected and slaughtered 60 days post-infection. Their legs and shoulders were processed to make 100% Iberian ham legs and shoulders. The meat ready to be eaten was analyzed by quantification and viability assays using magnetic capture real-time qPCR and bioassay techniques proving that this specific traditional "Cinco Jotas" curing process 100% Iberian ham is strong enough to eliminate the parasite T. gondii, resulting in a safe product for consumers.

Digital images of food for later analysis tend to be heterogeneous in terms of color and luminosity. Improving these images by using filters is necessary and crucial before further processing. This paper compares the non-use of filters and the use of high-pass filters in the images of hand-cut Iberian ham that will be used in a multifractal analysis for the study of fat and its infiltration. The yielded results show that with the use of a high-pass filter, more accurate fractal dimensions were obtained, which can be featured in predictive techniques of Iberian ham quality.

The potential of headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) to perform non-targeted qualitative analysis of complex samples has led to an unprecedented increase in its popularity in recent years. The operating principle of IMS makes quality control essential to ensure adequate results. Besides this, the suitability of GC-IMS is determined by multiple phenomena that take place before and during IMS detection. The present work discusses a novel GC-IMS quality control protocol for both beginners and experienced users. Likewise, it describes factors that must be taken into account in order to develop a robust GC-IMS qualitative analysis method and, if needed, to achieve the identification of VOCs present in real samples. The developed quality control protocol was successfully employed in our laboratory for the routine analysis of >500 real samples (olive oil and Iberian ham) for 6 months, thus it is recommended for the analysis of a great number of complex samples. Furthermore, the behaviour of the ions produced in the ionisation chamber and the possible reactions between them in GC-IMS qualitative analysis were assessed.

Computer vision algorithms and Magnetic Resonance Imaging (MRI) have been proposed to obtain quality traits of Iberian hams, due to the non-destructive, non-ionizing and innocuous nature of these approaches. However, all the proposals have been based on high-field MRI scanners, which obtain high quality images but also involve very high economical costs. In this paper, low-field MRI devices and three classical texture algorithms were used to predict quality traits of Iberian ham. Prediction equation of quality features were obtained, which estimate the quality parameters as a function of computational textures. The texture features were obtained by applying three well-known classical texture algorithms (GLCM - Gray Level Co-occurrence Matrix, GLRLM - Gray Level Run Length Matrix and NGLDM - Neighbouring Gray Level Dependence Matrix) on low-field MRI. Being the first approach that exploits this type of scanner for this purpose in dry-cured meat, the predicted elements were compared and correlated to the results obtained by means of traditional physico-chemical methods. The obtained correlation were higher than 0.7 for almost all the quality traits, reached very good to excellent relationship. These high correlations between both sets of data (traditional and estimated results) prove that low-field MRI combined with texture algorithms could be used to estimate the quality traits of meat products in a non-destructive and efficient way.

Dry-cured Iberian ham is a meat product prone to be contaminated by ochratoxin A (OTA) because of colonisation by OTA-producing Penicillia on the surface of the product during its ripening. The ability of non-toxigenic moulds to control the growth of indigenous ochratoxigenic strains and OTA accumulation on this product was evaluated. Two protective cultures consisting of the antifungal protein-producing Penicillium chrysogenum RP42C and a mix of selected autochthonous non-toxigenic mould strains were spread on the surface of 45 dry-cured Iberian hams at drying stage and ripened up to 9 additional months. The results showed that the RP42C strain limited the growth of OTA-producing moulds and mainly the OTA accumulation in dry-cured Iberian ham throughout the processing in the meat industry. The use of protective cultures of non-toxigenic mould strains combined with an appropriate HACCP plan holds potential for reducing health hazard of OTA accumulation in dry-cured Iberian ham.

A medida que avanzan los estudios sobre el polisémico ámbito de la alimentación humana, resulta más necesario considerar mayor número de variables para analizar con solvencia el hecho alimentario. Más allá de los estudios sobre las fases de producción y distribución, nuestra propuesta se centra en la fase del consumo y trata de identificar los elementos que explican por qué las sociedades seleccionan y prefieren unos alimentos en detrimento de otros. Actualmente, la selección alimentaria está intrínsecamente presente en el hecho alimentario de las sociedades modernas, relegando a un segundo plano los factores biológicos y fisiológicos, en relación a parámetros dominantes comparados con el placer, la salud y la sociabilidad. Mediante una combinación de técnicas cuantitativas y cualitativas, este estudio propone la relevancia de dimensiones como el placer y la salud como elementos que guían a los consumidores para elegir un determinado producto gourmet, como es el caso del jamón ibérico en España. Palabras clave: Selección de alimentos; Hecho alimentario; Placer; Salud; Sociabilidad; Jamón ibérico. As studies on the polysemic field of human nutrition progress, it is has become necessary to consider a greater number of variables when analysing the reality of food. Our proposal goes beyond studies based on the production and distribution phases, and focuses instead on the consumption phase in an effort to identify the elements that explain why societies choose and prefer some foods over others. Nowadays, food choice is intrinsically present in food as a reality of modern societies, relegating biological and physiological factors in relation to the dominant parameters of pleasure, health and sociability. Through a combination of quantitative and qualitative techniques, this study proposes pleasure and health as elements that guide consumers to choosing a particular gourmet product, as in the case of Iberian ham in Spain.

Objective: To evaluate the impact that the moderate and regular consumption of Cinco Jotas acorn-fed 100% Iberian ham has on overall cardiovascular risk, lipid parameters, blood pressure, and weight. Methods: A longitudinal, analytical, and quasi-experimental clinical study with repeated measures was carried out with 100 randomly selected individuals in primary care. The sample population included men and women (64%) between the ages of 25 and 55 (42.08, SD 9.6) who were not diagnosed with any cardiovascular illness or diabetes, were not undergoing antihypertensive treatment, nor taking lipid-lowering drugs. There were four visits during a 2-week washout period for the first of three phases. Phases 2 and 3 included an 8-week habitual diet phase followed by an 8- week intervention phase when participants consumed 40 g daily of acorn-fed 100% Cinco Jotas Iberian ham. Measurements of cardiovascular risk factors were taken following the SCORE table. These included total cholesterol, high-density lipoproteins cholesterol (HDL-c), low-density lipoproteins cholesterol (LDL-c), triglycerides (TG), and weight. Results: The average vascular risk (SCORE) was 0.20 (SD 0.49) before the consumption phase and 0.18 (SD 0.48) at the end of the study (p > 0.05). An increase in HDL-c of 5 mg/dl was observed while there was a decrease in LDL-c and TG of 10 mg/dl (p < 0.05). There were no differences in total cholesterol levels, blood pressure, or weight; nor were differences observed in average consumption of calories, protein, lipids, carbohydrates, or alcohol (p > 0.05). Conclusions: The daily consumption of 40 g of Cinco Jotas acorn-fed 100% Iberian ham does not increase the risk of cardiovascular disease and has a favorable impact on lipid levels without affecting blood pressure or weight.

In recent years, Gas Chromatography-Ion Mobility Spectrometry (GC-IMS) has been successfully employed in food science as a control technique for the prevention of fraud according to food and labeling regulations. In this work, we propose the use of GC-IMS technique to assess the quality of Iberian ham with regard to the Iberian Pig's diet (either nourished with feed or with acorns). For this purpose, we have acquired a dataset composed of 53 samples of Iberian ham from different food providers using a commercial GC-IMS (FlavourSpec, from G.A.S. Dortmund, Germany). Intensive signal pre-processing for GC-IMS was applied to the raw data. This dataset was employed to create four Partial Least Squares Discriminant Analysis (PLSDA) models corresponding to different train/test partitions of the dataset. Nearly perfect classification rates (above 91 %) were obtained for each partition of the dataset, denoting the high power of GC-IMS to characterize food samples.

This study aims to forecast quality characteristics of Iberian hams by using non-destructive methods of analysis and data mining. Magnetic Resonance Imaging and Computer Vision Techniques were conducted on hams throughout their processing. Physico-chemical parameters were also measured in these products. Information from these analyses was integrated in a database. First, deductive techniques of data mining were applied to these data. Multiple linear regression allows for the estimation of information from Magnetic Resonance Imaging, Computer Vision Techniques and physico-chemical analysis. This enables the completion of the initial database. Then, predictive techniques of data mining were applied. Both, multiple linear regression and isotonic regression achieved the prediction of weight, moisture and lipid content of hams as a function of features obtained by Magnetic Resonance Imaging and Computer Vision Techniques. Thus, data mining, Magnetic Resonance Imaging and Computer Vision Techniques could be used to estimate the quality traits of Iberian hams. This allows for the improvement of the process control without destroying any piece.

Summary This research tries to explain the importance of intangible resources in explaining the international diversification of small and medium sized enterprises (SMEs). Our starting position is that SMEs diversify to leverage their resources across different markets, and therefore a positive relationship is to be expected between technological, human and reputational resources, and diversification. These resources can be held internally by each firm, as proposed by the resource-based view, or, when the SMEs belong to a cluster, they also can be collectively created among neighbouring firms. Empirical evidence was obtained from a sample of 250 SMEs located in the Iberian Ham cluster. The results suggest that SMEs tend to rely on their technological resources and individual reputation to help them become exporters, but when it comes to their diversification through expanding into different overseas markets, collective reputation and human resources become more important.

Dry-cured Iberian ham is one of the most valuable meat products in Spain, with a first-rate consumer acceptance. Visually discernible characteristics of fat and lean, such as marbling, have all effect on the acceptability and palatability of ripened Iberian ham pieces. Important marbling properties include the amount and spatial distribution of intramuscular fat streaks. Chemical processing is the only proved way to determine the fat level of pig meat, but this technique is tedious, destroying and unable to offer information about fat distribution. The determination of Iberian ham sensorial quality has traditionally involved appraisal of marbling characteristics by descriptive analysis methods, which rely heavily on visual evaluation and testing by panels of trained graders. We present a novel method to recognize marbling in Iberian ham images to provide the base for the design of an automatic, non-destroying expert computer system, based on computer vision and pattern recognition techniques, which shall allow food technology industries to evaluate and characterize Iberian ham independently of the subjective and variable criteria of human testers.

Anchovy semipreserves are elaborated in Mediterranean countries with ripened Engraulis encrasicolus obtained by a traditional process. In order to identify those sensory attributes that are most useful as indicators of the ripening stage of Engraulis encrasicolus we performed sensory analyses of anchovy samples obtained at intervals throughout the ripening process. The resulting 90 × 44 sample-by-attribute matrix was analyzed by principal components analysis, leading to the selection of 11 attributes that are reliable indicators of ripening stage and spoilage. The attributes chosen were gray color of the external side; red color of the external side, internal side and backbone mark; the odors Iberian ham and fish meal; the flavors anchovy and bitter; and the texture attributes firmness and juiciness.

Ultrasonic measurements were used to characterize the effect of high pressure treatment (HPT) (600 MPa/6 min) or cold storage (6 °C/120 days) on the textural properties of vacuum packaged dry-cured ham. The ultrasonic velocity, textural properties and fat content were determined in the ham packages. The ultrasonic velocity was related to the ham hardness, which depends on the sample composition. HPT induced molecular alterations which resulted in an average increase in the hardness of lean tissue of 0.2 N and one of 0.3 N in that of fatty tissue. These textural changes give rise to a velocity increase (8 m/s for lean and 17 m/s for fatty tissue). The cold storage of the Iberian hamalso led to an increase in hardness (average 1.10 N) and ultrasonic velocity (average 70 m/s). Therefore, the non-destructive ultrasonic technique could be a reliable method with which to assess the textural changes induced by HPT or cold storage on packaged dry-cured ham., The authors acknowledge the financial support from the "Ministerio de Economia y Competitividad" in Spain (Project RTA 2010-00029-C04-02).

This paper reports the results obtained by analysing some of the most well-known features used in Computer Vision to describe and classify shapes in an appealing real application. We aim to demonstrate the applicability of shape descriptors to classify muscles on Magnetic Resonance Imaging (MRI). The mechanized classification of ham muscles could help the industries to automate the ripening process for Iberian ham. The excellent classification percentages obtained in our experiments suggest the real viability of the feature vector developed in this paper to recognize and classify muscles.

This paper explores the use of MRI (Magnetic Resonance Imaging) in combination with a fully automated Image Analysis method for the recognition of Biceps Femoris and Semimembranosus muscles in Iberian ham. A quantitative description of volume and a study of moisture and weight relationships during the product’s ripening process are included. Three Active Contour methods (Variational Calculus, Dynamic Programming, and Greedy Algorithms) are used to recognize the Biceps Femoris and Semimembranosus muscles by means of Computer Vision techniques. The recognition of both muscles via MRI entails a low error rate (3–10%). A loss of weight in hams during the ripening process is related to a decrease in size ( r 2 = 0.992). The high correlation implies that the information obtained by means of Computer Vision techniques can be used as a non-invasive complement to the traditional processes of ham weighing and moisture estimation.

Active Contours constitute a widely used Pattern Recognition technique, consisting in curves to be moved by minimizing an energy function. Classical active contours are based on different methodologies. This paper proposes a new procedure using Genetic Algorithm to minimize the energy function of the Active Contour. Both techniques are combined to produce a new methodology, called Evolutionary Active Contours. An application has been developed in order to verify the validation of the proposed method. The valid performance of this approach has been demonstrated with both synthetic and real Magnetic Resonance images. Moreover, the algorithm has been used to recognize muscles from Magnetic Resonance images of Iberian ham at different maturation stages in order to calculate their volume change. Our main findings can be summarized as two: The feasible combination of genetic algorithms and active contours, and the automation of optimal ripening points for Iberian ham samples.

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.

Intermuscular Fat Content and its distribution during the ripening process of the Iberian ham is a relevant task from the point of view of technological interest. This paper attempts to study the Iberian ham during the ripening process with images obtained from a MRI (Magnetic Resonance Imaging) device using Pattern Recognition and Image Analysis algorithms, in particular Mathematical Morphology techniques. The main advantage of this method is the non-destructive nature. A concrete algorithm is proposed, which is based on the Watershed transformation. In addition, the results are compared with the Otsu thresholding algorithm. The decreases of the total volume in the ripening process are shown. Also the decrease of the meat percentage and intermuscular fat content are calculated. As a conclusion, the viability of these techniques is proved for the possible future utilization in the meat industries to discover new characteristics in the ripening process.

Acoustic microscopy has been used for many years to image and measure the elastic properties of materials across a wide range of scientific disciplines. However the application of this technique in the food industry is scarce. In this paper we outline the operation of a reflection-mode acoustic microscope and discuss some of the issues relevant to its operation in the food sector. We then present two relevant case studies in which we employ acoustic microscopy to analyse potato cells and the fat structure in Iberian ham and chorizo.