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Nowadays, there is a growing demand for high-quality vegetal protein food products, such as pulses and lentils in particular. However, there is no scientific evidence on the nutritional and morphometric characterization of the main lentil cultivars in the Western Mediterranean area. For this reason, the aim of this work is to carry out a morphometric and nutritional characterization of the main Spanish lentil cultivars. Nutrient content assessment was performed on dry matter. The results showed that all studied cultivars are large and heavy lentils, except for the cultivar “Pardina”. They have high protein levels, ranging from 21% to 25%, which is higher than those found in any other pulse, as well as a high carbohydrate content, greater than 59% in all cases. Fiber content was higher than expected in “Armuña” and “Rubia Castellana” cultivars, ranging from 6% to 6.6%, and exceptionally high in the case of the cultivar “Pardina”, which reached 7.8%. Conversely, very low values were found for fat content, varying between 0.5% and 0.9%. Ca, Fe and Mg levels were remarkably higher (from 550 ppm to 851 ppm, from 98 ppm to 139 ppm and from 790 ppm to 989 ppm, respectively) than those found for other lentil cultivars, especially the high Mg content in the cultivars “Jaspeada” and “Microjaspeada”, both above 955 ppm. Clear differentiation was found between the cultivars “Rubia Castellana”, “Pardina” and those included in the Protected Geographical Indication (PGI) “Lenteja de la Armuña”. Overall, lentil cultivars included in the PGI “Lenteja de la Armuña” showed better morphometric and nutritional characteristics than cultivars “Pardina” or “Rubia Castellana”.
Javier Plaza; M. Morales-Corts; Rodrigo Pérez-Sánchez; Isabel Revilla; Ana Vivar-Quintana. Morphometric and Nutritional Characterization of the Main Spanish Lentil Cultivars. Agriculture 2021, 11, 741 .
AMA StyleJavier Plaza, M. Morales-Corts, Rodrigo Pérez-Sánchez, Isabel Revilla, Ana Vivar-Quintana. Morphometric and Nutritional Characterization of the Main Spanish Lentil Cultivars. Agriculture. 2021; 11 (8):741.
Chicago/Turabian StyleJavier Plaza; M. Morales-Corts; Rodrigo Pérez-Sánchez; Isabel Revilla; Ana Vivar-Quintana. 2021. "Morphometric and Nutritional Characterization of the Main Spanish Lentil Cultivars." Agriculture 11, no. 8: 741.
Currently, there are very few studies in the dairy sheep sector associating milk quality and indicators regarding carbon footprint and their link to grazing levels. For 1 year, monthly milk samples and records related to environmental emissions and management systems were collected through surveys from 17 dairy sheep farms in the region of Castilla y León (Spain), in order to relate this information to the use of natural pastures under free grazing. Indicators were constructed on the collected data and subjected to a multivariate statistical procedure that involved a factor analysis, a cluster analysis and a population canonical analysis. By applying multivariate statistical techniques on milk quality and carbon footprint indicators, it was possible to identify the management system of the farms. From an environmental point of view, farms with a higher grazing level (cluster 4) were more sustainable, as they had the lowest carbon footprint (lower CO2, N2O and CO2 equivalent emissions per sheep and year) and the lowest energy consumption levels, which were gradually lower than those of farms in cluster 3; both indicators were much lower than those of farms in clusters 1 and 2. The milk quality of cluster 1 and 2 farms was significantly lower in terms of total protein and fat content, dry extract, omega-3 fatty acid levels and α-tocopherol content than farms in clusters 3 and 4, which had higher accessibility to grazing resources. In sum, the higher the use of natural resources, the lower the external inputs the farms required and the lower environmental impact and energy costs they have.
Javier Plaza; Isabel Revilla; Jaime Nieto; Cristina Hidalgo; Mario Sánchez-García; Carlos Palacios. Milk Quality and Carbon Footprint Indicators of Dairy Sheep Farms Depend on Grazing Level and Identify the Different Management Systems. Animals 2021, 11, 1426 .
AMA StyleJavier Plaza, Isabel Revilla, Jaime Nieto, Cristina Hidalgo, Mario Sánchez-García, Carlos Palacios. Milk Quality and Carbon Footprint Indicators of Dairy Sheep Farms Depend on Grazing Level and Identify the Different Management Systems. Animals. 2021; 11 (5):1426.
Chicago/Turabian StyleJavier Plaza; Isabel Revilla; Jaime Nieto; Cristina Hidalgo; Mario Sánchez-García; Carlos Palacios. 2021. "Milk Quality and Carbon Footprint Indicators of Dairy Sheep Farms Depend on Grazing Level and Identify the Different Management Systems." Animals 11, no. 5: 1426.
A total of 160 1-day-old medium-growing male chicks (Gallus gallus domesticus) were raised for 120 days in a certified organic farming system. A total of two strains were studied (Coloryield, CY; RedBro, RB). Overall, two weather periods were considered based on the outdoor temperature, being S1 colder than S2. In total, 40 chicks per strain were assigned to each period (n = 80). Chickens were fed ad libitum with the same organic feeds. In the first month, chickens were kept indoors and, from day 30, they had access to the pasture. Slaughter live weight (LW), average daily gains, (ADG), the feed conversion ratio (FCR), and mortality rates did not differ between the two strains. LW was (p < 0.05) higher in the S1 and a trend (p = 0.084) was observed for ADG, which was higher in S1. No differences were found for feed intake, FCR, and mortality rates between weather periods. There were no differences for coefficient of variation (CV) between the strains studied, nevertheless, CV for LW in S2 was increased. Differences in the productive performance between these strains raised in organic production systems were slight. However, chickens raised in S1 had a better performance. It would be preferable to raise chickens in these weather conditions whenever possible.
Ainhoa Sarmiento-García; Isabel Revilla; José-Alfonso Abecia; Carlos Palacios. Performance Evaluation of Two Slow-Medium Growing Chicken Strains Maintained under Organic Production System during Different Seasons. Animals 2021, 11, 1090 .
AMA StyleAinhoa Sarmiento-García, Isabel Revilla, José-Alfonso Abecia, Carlos Palacios. Performance Evaluation of Two Slow-Medium Growing Chicken Strains Maintained under Organic Production System during Different Seasons. Animals. 2021; 11 (4):1090.
Chicago/Turabian StyleAinhoa Sarmiento-García; Isabel Revilla; José-Alfonso Abecia; Carlos Palacios. 2021. "Performance Evaluation of Two Slow-Medium Growing Chicken Strains Maintained under Organic Production System during Different Seasons." Animals 11, no. 4: 1090.
This study investigated the influence of the production system (conventional vs. organic), the grass consumption level and the ageing period (7 and 14 days) on beef quality. Three groups of samples from Limousin × Avileña calves were analysed: F100, formed by animals fed 100% on forage; F74, formed by animals fed on an average amount of forage of 74%; and F35, formed by animals fed on straw fodder (35%) and concentrate (65%). The results showed that the higher the grass content, the lower the fat oxidation and the higher the n-3 content, but also the higher the SFA level, the initial Warner-Bratzler shear force (WBSF), and the more residue it leaves on chewing. As for the effect of production system, organic samples showed higher intramuscular fat content and lower moisture and MUFA content. These samples were darker and showed lower values for flavour quality. Among the organic samples, F100 had higher n-3 and CLA content and higher values for colour, hardness, odour and flavour quality. Increased ageing time may improve the sensory characteristics of the meat, especially in the case of the F100 samples. The results pointed out that F100 samples aged at least 14 days showed the best physico-chemical, nutritional and sensory characteristics.
Isabel Revilla; Javier Plaza; Carlos Palacios. The Effect of Grazing Level and Ageing Time on the Physicochemical and Sensory Characteristics of Beef Meat in Organic and Conventional Production. Animals 2021, 11, 635 .
AMA StyleIsabel Revilla, Javier Plaza, Carlos Palacios. The Effect of Grazing Level and Ageing Time on the Physicochemical and Sensory Characteristics of Beef Meat in Organic and Conventional Production. Animals. 2021; 11 (3):635.
Chicago/Turabian StyleIsabel Revilla; Javier Plaza; Carlos Palacios. 2021. "The Effect of Grazing Level and Ageing Time on the Physicochemical and Sensory Characteristics of Beef Meat in Organic and Conventional Production." Animals 11, no. 3: 635.
The use of insects can be a possible source of protein. This study uses Calliphora sp. larvae (CLM) as a protein source in 320 one-day-old medium-growing male chicks (RedBro) during their first month of life. Chickens were randomly assigned to four dietary treatments. Each group consisted of 10 animals, and a total of 8 replicas. Control group was fed with a certified organic feed. The experimental treatments were supplemented with 5% (T2), 10% (T3), or 15% (T4) of CLM, reducing in each case the corresponding percentage of feed quantity. Productive development and meat quality were analyzed, and near infrared spectroscopy (NIRS) was used as a tool for classifying the samples. Chickens of T4 showed greater final body weight and total average daily gain, but they reduced consumption and feed conversion ratio (FCR). The chicken breast meat of T4 had lower cooking losses and higher palmitoleic acid content (p < 0.01). NIRS classified correct 92.4% of samples according to the food received. CLM is presented as a potential ingredient for the diet of medium-slow growing chickens raised in organic systems.
Ainhoa Sarmiento-García; Carlos Palacios; Inmaculada González-Martín; Isabel Revilla. Evaluation of the Production Performance and the Meat Quality of Chickens Reared in Organic System. As Affected by the Inclusion of Calliphora sp. in the Diet. Animals 2021, 11, 324 .
AMA StyleAinhoa Sarmiento-García, Carlos Palacios, Inmaculada González-Martín, Isabel Revilla. Evaluation of the Production Performance and the Meat Quality of Chickens Reared in Organic System. As Affected by the Inclusion of Calliphora sp. in the Diet. Animals. 2021; 11 (2):324.
Chicago/Turabian StyleAinhoa Sarmiento-García; Carlos Palacios; Inmaculada González-Martín; Isabel Revilla. 2021. "Evaluation of the Production Performance and the Meat Quality of Chickens Reared in Organic System. As Affected by the Inclusion of Calliphora sp. in the Diet." Animals 11, no. 2: 324.
This study has examined the polyunsaturated fatty acid composition of 224 cheeses with variable percentages (0–100%) of milk from different species (cow, ewe’s, and goat) during 6 months of ripening. We analyzed the concentration of ω3 (Σ C20:5 + C22:6 + C18:3), ω6 (ΣC20:4 + C18:2), Σ isomers of the conjugated linoleic acid (CLA), the total of polyunsaturated fatty acids (ω3 + ω6 + CLA), and the ω6/ω3 nutritional relationship of the cheeses. The importance of the animal species, the seasonality, the ripening time, and its influence on the composition of polyunsaturated fatty acids (PUFAs) has been studied. Concerning the species, sheep show a higher concentration of CLA levels and ω6. The seasonality affects above all the levels of CLA and ω3, while ripening only affects the CLA levels. The capacity of NIR technology to predict the concentration of PUFA in cheese by direct application to cheese slices was also assessed. The docosahexaenoic acid relationship (C22:6 ω-3) and the ω6/ω3 relationship presented the most accurate prediction equation (RSQ > 0.7).
Iris Lobos-Ortega; Miriam Hernández-Jiménez; María Inmaculada González-Martín; José Miguel Hernández-Hierro; Isabel Revilla; Ana María Vivar-Quintana. Study of Polyunsaturated Fatty Acids in Cheeses Using Near-Infrared Spectroscopy: Influence of Milk from Different Ruminant Species. Food Analytical Methods 2021, 14, 933 -943.
AMA StyleIris Lobos-Ortega, Miriam Hernández-Jiménez, María Inmaculada González-Martín, José Miguel Hernández-Hierro, Isabel Revilla, Ana María Vivar-Quintana. Study of Polyunsaturated Fatty Acids in Cheeses Using Near-Infrared Spectroscopy: Influence of Milk from Different Ruminant Species. Food Analytical Methods. 2021; 14 (5):933-943.
Chicago/Turabian StyleIris Lobos-Ortega; Miriam Hernández-Jiménez; María Inmaculada González-Martín; José Miguel Hernández-Hierro; Isabel Revilla; Ana María Vivar-Quintana. 2021. "Study of Polyunsaturated Fatty Acids in Cheeses Using Near-Infrared Spectroscopy: Influence of Milk from Different Ruminant Species." Food Analytical Methods 14, no. 5: 933-943.
For Protected Geographical Indication (PGI)-labeled products, such as the dry-cured beef meat “cecina de León”, a sensory analysis is compulsory. However, this is a complex and time-consuming process. This study explores the viability of using near infrared spectroscopy (NIRS) together with artificial neural networks (ANN) for predicting sensory attributes. Spectra of 50 samples of cecina were recorded and 451 reflectance data were obtained. A feedforward multilayer perceptron ANN with 451 neurons in the input layer, a number of neurons varying between 1 and 30 in the hidden layer, and a single neuron in the output layer were optimized for each sensory parameter. The regression coefficient R squared (RSQ > 0.8 except for odor intensity) and mean squared error of prediction (MSEP) values obtained when comparing predicted and reference values showed that it is possible to predict accurately 23 out of 24 sensory parameters. Although only 3 sensory parameters showed significant differences between PGI and non-PGI samples, the optimized ANN architecture applied to NIR spectra achieved the correct classification of the 100% of the samples while the residual mean squares method (RMS-X) allowed 100% of non-PGI samples to be distinguished.
Isabel Revilla; Ana M. Vivar-Quintana; María Inmaculada González-Martín; Miriam Hernández-Jiménez; Iván Martínez-Martín; Pedro Hernández-Ramos. NIR Spectroscopy for Discriminating and Predicting the Sensory Profile of Dry-Cured Beef “Cecina”. Sensors 2020, 20, 6892 .
AMA StyleIsabel Revilla, Ana M. Vivar-Quintana, María Inmaculada González-Martín, Miriam Hernández-Jiménez, Iván Martínez-Martín, Pedro Hernández-Ramos. NIR Spectroscopy for Discriminating and Predicting the Sensory Profile of Dry-Cured Beef “Cecina”. Sensors. 2020; 20 (23):6892.
Chicago/Turabian StyleIsabel Revilla; Ana M. Vivar-Quintana; María Inmaculada González-Martín; Miriam Hernández-Jiménez; Iván Martínez-Martín; Pedro Hernández-Ramos. 2020. "NIR Spectroscopy for Discriminating and Predicting the Sensory Profile of Dry-Cured Beef “Cecina”." Sensors 20, no. 23: 6892.
The potential of a portable Near Infrared spectrophotometer compared with that of NIR benchtop equipment is assessed to determine the13C/12C relationship of stable isotopes and the fatty acid content. 105 samples of subcutaneous fat of Iberian pigs collected at the time of their slaughter have been analyzed. The analysis of stable isotopes and gas chromatography were the methods of reference used. The samples were analyzed without prior handling (portable and benchtop NIR) and after extracting the fat (benchtop NIR). The results show that with the portable equipment it is possible to determine δ13C (‰), 12 fatty acids, and 5 summations of fatty acids (SFA, MUFA, PUFA, w3, and w6), while with the benchtop NIR equipment it is possible to measure δ13C (‰), 16 fatty acids, and the 5 summationsof fatty acids. The correlation coefficients of the portable equipment were slightly lower than those of the NIR benchtop equipment.
María Inmaculada González-Martín; Olga Escuredo; Miriam Hernández-Jiménez; Isabel Revilla; Ana Ma. Vivar-Quintana; Iván Martínez-Martín; Pedro Hernández-Ramos. Prediction of stable isotopes and fatty acids in subcutaneous fat of Iberian pigs by means of NIR: A comparison between benchtop and portable systems. Talanta 2020, 224, 121817 .
AMA StyleMaría Inmaculada González-Martín, Olga Escuredo, Miriam Hernández-Jiménez, Isabel Revilla, Ana Ma. Vivar-Quintana, Iván Martínez-Martín, Pedro Hernández-Ramos. Prediction of stable isotopes and fatty acids in subcutaneous fat of Iberian pigs by means of NIR: A comparison between benchtop and portable systems. Talanta. 2020; 224 ():121817.
Chicago/Turabian StyleMaría Inmaculada González-Martín; Olga Escuredo; Miriam Hernández-Jiménez; Isabel Revilla; Ana Ma. Vivar-Quintana; Iván Martínez-Martín; Pedro Hernández-Ramos. 2020. "Prediction of stable isotopes and fatty acids in subcutaneous fat of Iberian pigs by means of NIR: A comparison between benchtop and portable systems." Talanta 224, no. : 121817.
Dry-cured ham is a high-quality product owing to its organoleptic characteristics. Sensory analysis is an essential part of assessing its quality. However, sensory assessment is a laborious process which implies the availability of a trained tasting panel. The aim of this study was the prediction of dry-ham sensory characteristics by means of an instrumental technique. To do so, an artificial neural network (ANN) model for the prediction of sensory parameters of dry-cured hams based on NIR spectral information was developed and optimized. The NIR spectra were obtained with a fiber-optic probe applied directly to the ham sample. In order to achieve this objective, the neural network was designed using 28 sensory parameters analyzed by a trained panel for sensory profile analysis as output data. A total of 91 samples of dry-cured ham matured for 24 months were analyzed. The hams corresponded to two different breeds (Iberian and Iberian x Duroc) and two different feeding systems (feeding outdoors with acorns or feeding with concentrates). The training algorithm and ANN architecture (the number of neurons in the hidden layer) used for the training were optimized. The parameters of ANN architecture analyzed have been shown to have an effect on the prediction capacity of the network. The Levenberg–Marquardt training algorithm has been shown to be the most suitable for the application of an ANN to sensory parameters
Pedro Hernández-Ramos; Ana María Vivar-Quintana; Isabel Revilla; María Inmaculada González-Martín; Miriam Hernández-Jiménez; Iván Martínez-Martín. Prediction of Sensory Parameters of Cured Ham: A Study of the Viability of the Use of NIR Spectroscopy and Artificial Neural Networks. Sensors 2020, 20, 5624 .
AMA StylePedro Hernández-Ramos, Ana María Vivar-Quintana, Isabel Revilla, María Inmaculada González-Martín, Miriam Hernández-Jiménez, Iván Martínez-Martín. Prediction of Sensory Parameters of Cured Ham: A Study of the Viability of the Use of NIR Spectroscopy and Artificial Neural Networks. Sensors. 2020; 20 (19):5624.
Chicago/Turabian StylePedro Hernández-Ramos; Ana María Vivar-Quintana; Isabel Revilla; María Inmaculada González-Martín; Miriam Hernández-Jiménez; Iván Martínez-Martín. 2020. "Prediction of Sensory Parameters of Cured Ham: A Study of the Viability of the Use of NIR Spectroscopy and Artificial Neural Networks." Sensors 20, no. 19: 5624.
In products from quality labels a sensory analysis is obligatory although this is a slow and expensive process. This study examines the prediction of the sensory parameters of chorizo dry-cured sausage by using NIRS technology and the application of chemometric methods such as MPLS (Modified Partial Least Square regression) and ANN (Artificial Neural Networks). The results show that by applying ANN it is possible to predict the 20 sensory parameters analyzed with RSQ values of from 0.61 to 0.92; these values are always higher than those obtained by prediction using MPLS. Moreover, the combination of NIRS and RMS-X residual discrimination allowed the correct classification of 94.4% of the samples according to whether or not they belonged to a certain Quality Label.
Miriam Hernández-Jiménez; Pedro Hernández-Ramos; Iván Martínez-Martín; Ana M. Vivar-Quintana; Inmaculada González-Martín; Isabel Revilla. Comparison of artificial neural networks and multiple regression tools applied to near infrared spectroscopy for predicting sensory properties of products from Quality Labels. Microchemical Journal 2020, 159, 105459 .
AMA StyleMiriam Hernández-Jiménez, Pedro Hernández-Ramos, Iván Martínez-Martín, Ana M. Vivar-Quintana, Inmaculada González-Martín, Isabel Revilla. Comparison of artificial neural networks and multiple regression tools applied to near infrared spectroscopy for predicting sensory properties of products from Quality Labels. Microchemical Journal. 2020; 159 ():105459.
Chicago/Turabian StyleMiriam Hernández-Jiménez; Pedro Hernández-Ramos; Iván Martínez-Martín; Ana M. Vivar-Quintana; Inmaculada González-Martín; Isabel Revilla. 2020. "Comparison of artificial neural networks and multiple regression tools applied to near infrared spectroscopy for predicting sensory properties of products from Quality Labels." Microchemical Journal 159, no. : 105459.
The sensory characteristics of suckling lamb meat from 40 animals of the Castellana and Churra breeds from both conventional and organic maternal rearing systems were evaluated by a trained panel and texture and colour properties were also assessed by instrumental methods. The fatty acid profile of the feeding milk and the suckling lamb meat was evaluated by gas chromatography. The results showed that meat samples from organic rearing systems had a higher intramuscular fat content than meat samples from the conventional systems, but lower concentrations of saturated fatty acids and higher concentrations of mono- and polyunsaturated fatty acids, both PUFA n-3 and PUFA n-6. Moreover, the Castellana breed samples contained higher concentrations of monounsaturated fatty acids. As for the sensory characteristics, the appearance and the texture were the sensory attributes that were most affected by the rearing system and the breed.
I. Revilla; A.M. Vivar-Quintana; C. Palacios; Isabel Revilla Martín; Miriam Hernández-Jiménez. Effects of rearing system (organic and conventional) and breed (Churra and Castellana) on fatty acid composition and sensory characteristics of suckling lamb meat produced in north-west Spain. Biological Agriculture & Horticulture 2020, 37, 25 -39.
AMA StyleI. Revilla, A.M. Vivar-Quintana, C. Palacios, Isabel Revilla Martín, Miriam Hernández-Jiménez. Effects of rearing system (organic and conventional) and breed (Churra and Castellana) on fatty acid composition and sensory characteristics of suckling lamb meat produced in north-west Spain. Biological Agriculture & Horticulture. 2020; 37 (1):25-39.
Chicago/Turabian StyleI. Revilla; A.M. Vivar-Quintana; C. Palacios; Isabel Revilla Martín; Miriam Hernández-Jiménez. 2020. "Effects of rearing system (organic and conventional) and breed (Churra and Castellana) on fatty acid composition and sensory characteristics of suckling lamb meat produced in north-west Spain." Biological Agriculture & Horticulture 37, no. 1: 25-39.
The acceptance of a food product by the consumer depends, as the most important factor, on its sensory properties. Therefore, it is clear that the food industry needs to know the perceptions of sensory attributes to know the acceptability of a product. There exist procedures that systematically allows measurement of these property perceptions that are performed by professional panels. However, systematic evaluations of attributes by these tasting panels, which avoid the subjective character for an individual taster, have a high economic, temporal and organizational cost. The process is only applied in a sampled way so that its result cannot be used on a sound and complete quality system. In this paper, we present a method that allows making use of a non-destructive measurement of physical–chemical properties of the target product to obtain an estimation of the sensory description given by QDA-based procedure. More concisely, we propose that through Artificial Neural Networks (ANNs), we will obtain a reliable prediction that will relate the near-infrared (NIR) spectrum of a complete set of cheese samples with a complete image of the sensory attributes that describe taste, texture, aspect, smell and other relevant sensations.
Belén Curto; Vidal Moreno; Juan Alberto García-Esteban; Francisco Javier Blanco; Inmaculada González; Ana Vivar; Isabel Revilla. Accurate Prediction of Sensory Attributes of Cheese Using Near-Infrared Spectroscopy Based on Artificial Neural Network. Sensors 2020, 20, 3566 .
AMA StyleBelén Curto, Vidal Moreno, Juan Alberto García-Esteban, Francisco Javier Blanco, Inmaculada González, Ana Vivar, Isabel Revilla. Accurate Prediction of Sensory Attributes of Cheese Using Near-Infrared Spectroscopy Based on Artificial Neural Network. Sensors. 2020; 20 (12):3566.
Chicago/Turabian StyleBelén Curto; Vidal Moreno; Juan Alberto García-Esteban; Francisco Javier Blanco; Inmaculada González; Ana Vivar; Isabel Revilla. 2020. "Accurate Prediction of Sensory Attributes of Cheese Using Near-Infrared Spectroscopy Based on Artificial Neural Network." Sensors 20, no. 12: 3566.
A total of 160 medium-growth male chicks were studied individually from the first day of their lives until slaughter (120 days). The chicks were classified according to the weather of the breeding period (P1 and P2). A total of 80 chickens were used for each breeding period (8 repetitions with a total of 10 chickens per group). The characteristics of the weather period were defined based on the information provided by the Agroclimatic Information System for Irrigation (SiAR); P1 period was colder than P2 period. All birds were given the same diet. After 120 days, the animals were taken to a certified slaughterhouse for organic meat where they were slaughtered. A total of 48 chicks (24 per period) were randomly selected, and subsequently, the breast (Pectoralis major) were extracted to perform the quality analysis. Chicks raised in the colder period (P1) had higher live weights and higher slaughter weights (P < 0.01). The front quarters were not affected (P > 0.05), the weight of the breast was higher in the chicks raised in the warmer period (P < 0.01). Regarding meat quality parameters, the moisture content was significantly lower (P < 0.05) for samples of warmer period but the pH (P < 0.01) and the redness value (a*) (P < 0.05) were higher, while the remainder of the parameters was not affected. It can be concluded that weather conditions in outdoor production systems do not have a direct effect on meat quality.
A. Sarmiento; C. Palacios; I. Revilla; A. M. Vivar-Quintana. The effect of climatic conditions on the quality of medium-growth chicken meat in organic production systems. Organic Agriculture 2020, 10, 109 -116.
AMA StyleA. Sarmiento, C. Palacios, I. Revilla, A. M. Vivar-Quintana. The effect of climatic conditions on the quality of medium-growth chicken meat in organic production systems. Organic Agriculture. 2020; 10 (S1):109-116.
Chicago/Turabian StyleA. Sarmiento; C. Palacios; I. Revilla; A. M. Vivar-Quintana. 2020. "The effect of climatic conditions on the quality of medium-growth chicken meat in organic production systems." Organic Agriculture 10, no. S1: 109-116.
The fat composition is one of the factors which has the greatest influence on cheese. The fatty acids present in the same influence sensory parameters such as color, texture, and flavor (rancid and pungent). They likewise influence the nutritional composition of cheese as different fatty acids have beneficial or harmful effects on human health. On the other hand, the determination of the fatty acids present in cheese has been put forward as a useful tool for distinguishing the various cheeses according to the milk used in their production. Finding a tool which allows the determination of the fatty acids present in cheese in a rapid and non destructive manner is of great interest to the cheese industry. In this study we examine the use of Near-Infrared Spectroscopy (NIRS) technology in the determination of 19 fatty acids in cheese from C8:0 to C20:0 including ∑SFA and ∑UFA. Cheeses were made with known and varying percentages of cow, ewe's, and goat milk (112 samples) and ripening controls were carried out for 6 months. Two ways of recording the spectra are compared, one using a remote reflectance fiber-optic probe on a slice of cheese and another using the fatty extracts obtained from the same cheeses and recorded with cam-lock cells. The regression method used is MPLS. The results obtained reveal that it is possible to predict the fatty acid composition of cheese by means of the use of NIRS, irrespective of the method used to record it. Furthermore, the results obtained in the validation of the method used indicate that the equations obtained allow their application to unknown cheese samples.
M. Inmaculada González-Martín; Ana M. Vivar-Quintana; Isabel Revilla; Javier Salvador-Esteban. The determination of fatty acids in cheeses of variable composition (cow, ewe's, and goat) by means of near infrared spectroscopy. Microchemical Journal 2020, 156, 104854 .
AMA StyleM. Inmaculada González-Martín, Ana M. Vivar-Quintana, Isabel Revilla, Javier Salvador-Esteban. The determination of fatty acids in cheeses of variable composition (cow, ewe's, and goat) by means of near infrared spectroscopy. Microchemical Journal. 2020; 156 ():104854.
Chicago/Turabian StyleM. Inmaculada González-Martín; Ana M. Vivar-Quintana; Isabel Revilla; Javier Salvador-Esteban. 2020. "The determination of fatty acids in cheeses of variable composition (cow, ewe's, and goat) by means of near infrared spectroscopy." Microchemical Journal 156, no. : 104854.
Calibration statistical descriptors for both whole and ground lentils using Near Infrared Spectroscopy (NIRS), combined with fiber-optic probe, are presented and discussed. The models were developed for estimating the weight, size, total raw protein, moisture, total fat, total fiber, and ash. Standard methods were used to determine compositional parameters of 42 samples of different varieties of lentils. The calibration curves show a wide range of validity for all parameters. The results showed excellent predictability for the determination of weight, fiber, and ash in whole lentils. However, size, moisture, and total fat were predicted satisfactorily in ground lentils. The total protein content could be predicted for both whole and ground lentils. Moreover, NIRS and Direct Partial Least Squares (DPLS) were used to determine whether a sample of lentils belonged to the Protected Geographical Indication (PGI) “Lenteja de La Armuña” or not. The results showed that 95 % of the samples were correctly classified as belonging to a PGI. This result demonstrates that this technique allows the differentiation of samples from nearby regions.
I. Revilla; C. Lastras; Isabel Revilla Martín; Ana Maria Vivar Quintana; R. Morales-Corts; M. Ángeles Gómez-Sánchez; Rodrigo Pérez-Sánchez. Predicting the physicochemical properties and geographical ORIGIN of lentils using near infrared spectroscopy. Journal of Food Composition and Analysis 2019, 77, 84 -90.
AMA StyleI. Revilla, C. Lastras, Isabel Revilla Martín, Ana Maria Vivar Quintana, R. Morales-Corts, M. Ángeles Gómez-Sánchez, Rodrigo Pérez-Sánchez. Predicting the physicochemical properties and geographical ORIGIN of lentils using near infrared spectroscopy. Journal of Food Composition and Analysis. 2019; 77 ():84-90.
Chicago/Turabian StyleI. Revilla; C. Lastras; Isabel Revilla Martín; Ana Maria Vivar Quintana; R. Morales-Corts; M. Ángeles Gómez-Sánchez; Rodrigo Pérez-Sánchez. 2019. "Predicting the physicochemical properties and geographical ORIGIN of lentils using near infrared spectroscopy." Journal of Food Composition and Analysis 77, no. : 84-90.
Isabel Revilla; Ana Maria Vivar Quintana. The application of new teaching methodologies. Proceedings of the Sixth International Conference on Technological Ecosystems for Enhancing Multiculturality 2018, 86 -92.
AMA StyleIsabel Revilla, Ana Maria Vivar Quintana. The application of new teaching methodologies. Proceedings of the Sixth International Conference on Technological Ecosystems for Enhancing Multiculturality. 2018; ():86-92.
Chicago/Turabian StyleIsabel Revilla; Ana Maria Vivar Quintana. 2018. "The application of new teaching methodologies." Proceedings of the Sixth International Conference on Technological Ecosystems for Enhancing Multiculturality , no. : 86-92.
Ana María Vivar-Quintana; Isabel Revilla Martín; Isabel Revilla; Eddy Valentín Betances-Salcedo. Determination and quantification of phenolic acids in raw propolis by reversed phase high performance liquid chromatography. Feasibility study for the use of near infrared spectroscopy. Journal of Apicultural Research 2018, 57, 648 -656.
AMA StyleAna María Vivar-Quintana, Isabel Revilla Martín, Isabel Revilla, Eddy Valentín Betances-Salcedo. Determination and quantification of phenolic acids in raw propolis by reversed phase high performance liquid chromatography. Feasibility study for the use of near infrared spectroscopy. Journal of Apicultural Research. 2018; 57 (5):648-656.
Chicago/Turabian StyleAna María Vivar-Quintana; Isabel Revilla Martín; Isabel Revilla; Eddy Valentín Betances-Salcedo. 2018. "Determination and quantification of phenolic acids in raw propolis by reversed phase high performance liquid chromatography. Feasibility study for the use of near infrared spectroscopy." Journal of Apicultural Research 57, no. 5: 648-656.
The results of the present work show the presence of heavy mineral elements, such as Cr, Ni, Cu, Zn and Pb, and pesticide residues like fungicides, herbicides and acaricides in thirty-one commercially processed propolis capsules, tablets, tinctures, candies and syrups originating from Spain, Portugal, Belgium, England, USA and Chile. The determination of the mineral composition of propolis was carried out using Inductively Coupled Plasma Mass Spectrometry (ICP-MS), and contained Cr (0.10–17.7 ppm), Ni (0.01–7.01 ppm), Cu (0.01–6.44 ppm), Zn (0.01–6.44 ppm) and Pb (0.03–7.21 ppm). The pesticides were quantified using Gas Chromatography-Mass Spectrometry (GC–MS), where triadimefon was the main pesticide detected and quantified (between 0.32 and 2.68 mg/kg) and was present in 65% of the samples. The other pesticides found to be present, but to a lesser extent, were quintozene (0.91–1.06 mg/kg), procymidone (0.11 mg/kg), metazachlor (0.63–6.09 mg/kg), folpet (up to 11.31 mg/kg), dichlofluanid (up to 0.29 mg/kg) and chlorfenson (1.05 mg/kg).
Isabel Revilla Martín; I. Revilla; E.V. Betances-Salcedo; A.M. Vivar-Quintana. Pesticide residues and heavy metals in commercially processed propolis. Microchemical Journal 2018, 143, 423 -429.
AMA StyleIsabel Revilla Martín, I. Revilla, E.V. Betances-Salcedo, A.M. Vivar-Quintana. Pesticide residues and heavy metals in commercially processed propolis. Microchemical Journal. 2018; 143 ():423-429.
Chicago/Turabian StyleIsabel Revilla Martín; I. Revilla; E.V. Betances-Salcedo; A.M. Vivar-Quintana. 2018. "Pesticide residues and heavy metals in commercially processed propolis." Microchemical Journal 143, no. : 423-429.
In food products marketing, ensuring to the consumer identical organoleptic properties is vital for maintaining the client fidelity. Systematically achieve it by using as sensory information the valuations of a tasting panel, is unfeasible. Routinely, to assemble a tasting panel involves organizational and economics costs, as well as the sensory fatigue and the subjectivity of the panel members. In this paper is proposed a vitualization strategy or computational model focused on food products quality control, based on cooperation and data exchange between the main agents involved in the process: quality managers, professional tasters, production managers, inspection authorities, etc. Virtualization (digitalization) is supported on a ICatador cloud platform which has intelligent algorithms embedded to predict the food sensory properties. These algorithms have Near InfraRed Spectroscopy data of the product samples as input. As a validation scenario, our virtualization approach has been applied to the ripening cheese elaboration. Thanks to advanced visualization techniques, the quality manager can immediately and systematically know the merit figure related to a product sensory quality. The ICatador solution, has two profitable aspects. Sensory analysis is performed without routinely gathering a professional tasting panel. As a huge amount of data coming from the elaboration process itself are available, the intelligent algorithms are enriched by these data for the adaptation to the product elaboration process. In this way, we will be able to fine-tune continuously the machine-learning algorithms to the particular process and use them intelligently to increase the competitiveness.
Juan Alberto García Esteban; B. Curto; Vidal Moreno; Isabel Revilla Martín; I. Revilla; Ana Maria Vivar Quintana. A digitalization strategy for quality control in food industry based on Artificial Intelligence techniques. 2018 IEEE 16th International Conference on Industrial Informatics (INDIN) 2018, 221 -226.
AMA StyleJuan Alberto García Esteban, B. Curto, Vidal Moreno, Isabel Revilla Martín, I. Revilla, Ana Maria Vivar Quintana. A digitalization strategy for quality control in food industry based on Artificial Intelligence techniques. 2018 IEEE 16th International Conference on Industrial Informatics (INDIN). 2018; ():221-226.
Chicago/Turabian StyleJuan Alberto García Esteban; B. Curto; Vidal Moreno; Isabel Revilla Martín; I. Revilla; Ana Maria Vivar Quintana. 2018. "A digitalization strategy for quality control in food industry based on Artificial Intelligence techniques." 2018 IEEE 16th International Conference on Industrial Informatics (INDIN) , no. : 221-226.
J. A Garcia-Esteban; B. Curto; Vidal Moreno; Isabel Revilla Martín; I. Revilla; Ana Maria Vivar Quintana. A cloud platform for food sensory estimations based on artificial intelligence techniques. 2018 13th Iberian Conference on Information Systems and Technologies (CISTI) 2018, 1 .
AMA StyleJ. A Garcia-Esteban, B. Curto, Vidal Moreno, Isabel Revilla Martín, I. Revilla, Ana Maria Vivar Quintana. A cloud platform for food sensory estimations based on artificial intelligence techniques. 2018 13th Iberian Conference on Information Systems and Technologies (CISTI). 2018; ():1.
Chicago/Turabian StyleJ. A Garcia-Esteban; B. Curto; Vidal Moreno; Isabel Revilla Martín; I. Revilla; Ana Maria Vivar Quintana. 2018. "A cloud platform for food sensory estimations based on artificial intelligence techniques." 2018 13th Iberian Conference on Information Systems and Technologies (CISTI) , no. : 1.