López Maestresalas, Ainara

Last Name

López Maestresalas

First Name

Ainara

person.page.departamento

Ingeniería

person.page.instituteName

IS-FOOD. Research Institute on Innovation & Sustainable Development in Food Chain

ORCID

0000-0001-6636-0752

person.page.observainves

750902

person.page.upna

810716

Full item page

Search Results

Now showing 1 - 10 of 12

Open Access
Near-infrared spectroscopy and hyperspectral imaging for non-destructive quality inspection of potatoes
(2016) López Maestresalas, Ainara; Jarén Ceballos, Carmen; Arazuri Garín, Silvia; Proyectos e Ingeniería Rural; Landa Ingeniaritza eta Proiektuak
La patata (Solanum tuberosum L.) es uno de los cultivos más importantes en el mundo, ocupando el quinto puesto en términos de producción. España es uno de los países europeos con mayor producción y consumo de estos tubérculos. Sin embargo, a pesar de ser un producto altamente valorado, la industria de la patata se enfrenta a la demanda cada vez más creciente de productos de calidad, sanos y libres de daños por parte de consumidores y organismo reguladores. La aceptación en el mercado de estos alimentos depende de varios factores, como son, el aspecto general, textura, color, ausencia de defectos físicos, etc. Resulta imprescindible por tanto suministrar productos de gran calidad que gusten al consumidor final. Con este objetivo, la presente tesis doctoral se centra en ofrecer herramientas para un mayor control de la calidad de manera no destructiva, eficaz y sostenible. Para ello, se presentan diferentes estudios en los cuales se han diseñado, desarrollado y evaluado técnicas espectroscópicas no destructivas para el análisis de calidad en tubérculos de patata. Se ha llevado a cabo en primer lugar una caracterización óptica de los tejidos de patata en el rango visible e infrarrojo (500-1900 nm) mediante el uso de Dobles Esferas Integradoras, para entender los efectos de absorción y dispersión que se producen en los tejidos biológicos y así poder diseñar sensores más eficientes para la evaluación de la calidad de forma no destructiva. Además, se ha realizado una clasificación y determinación de compuestos químicos en patata mediante espectroscopía NIR y el uso de técnicas quimiométricas de análisis multivariante. Por último, se ha diseñado y evaluado un sistema de detección de daños internos en patata, no apreciables a simple vista, mediante análisis de imágenes hiperespectrales obtenidas en el rango visible, de 400 a 1000 nm, e infrarrojo (1000-2500 nm) del espectro. Los resultados obtenidos en estos estudios muestran, por un lado, cómo los espectros de absorción están fuertemente influenciados por la alta concentración de agua de las muestras y, por otro, cómo los tejidos de patata son altamente dispersivos, con unos valores del factor de anisotropía muy cercanos a 1 a lo largo de todo el rango espectral estudiado. Además, se ha conseguido clasificar una colección de 18 cultivares de patata de acuerdo a su contenido en polifenoles, antocianinas y capacidad antioxidante, mediante el empleo de un equipo NIRS con tecnología AOTF, con una precisión de 86.1%. Esto permite la incorporación de estas metodologías en la selección de líneas con alta concentración de los compuestos químicos deseados en programas de mejora genética. De forma similar, se ha logrado estimar la concentración de proteína bruta (R2: 0.86; SEP: 0.68), nitrógeno (R2: 0.86; SEP: 0.11) y polifenoles (R2: 0.83; SEP: 1.33), en un grupo de muestras con alta variabilidad, de manera no destructiva empleando el mismo equipo combinado con análisis de regresión por mínimos cuadrados parciales. Finalmente, los resultados obtenidos en el análisis de imágenes hiperespectrales han permitido discriminar patatas sanas de aquéllas con daño interno con una fiabilidad superior al 98% mediante un análisis discriminante por mínimos cuadrados parciales. Al mismo tiempo, se ha logrado identificar la presencia de daño interno en tubérculos 5 horas después de haberlo inducido, con una precisión de 97.12%. Esto permite localizar tubérculos afectados en las primeras fases de desarrollo del daño y por tanto evitar que lleguen al consumidor final. Los resultados obtenidos en esta tesis doctoral podrían emplearse para una futura implementación de estas técnicas espectroscópicas no destructivas en líneas reales de manipulación y envasado de patata.
Open Access
A review of the application of near-infrared spectroscopy for the analysis of potatoes
(American Chemical Society, 2013) López Maestresalas, Ainara; Arazuri Garín, Silvia; García Ruiz, Ignacio; Mangado Ederra, Jesús; Jarén Ceballos, Carmen; Proyectos e Ingeniería Rural; Landa Ingeniaritza eta Proiektuak; Gobierno de Navarra / Nafarroako Gobernua
Potato (Solanum tuberosum L.) is one of the most important crops in the world being considered as a staple food in many developing countries. The potato industry like other vegetable and fruit industries is subject to the current demand of quality products. In order to meet this challenge, the food industry is relying on the adoption of nondestructive and environmentally friendly techniques to determine quality of products. Near-infrared spectroscopy (NIRS) is currently one of the most advanced nondestructive technologies regarding instrumentation and application, and it also complies with the environment requirements as it does not generate emissions or waste. This paper reviews research progress on the analysis of potatoes by NIRS both in terms of determination of constituents and classification according to the different constituents of the tubers. A brief description of the fundamentals of NIRS technology and its advantages over other quality assessment techniques is included. Finally, future prospects of the development of NIRS technology at the industrial level are explored.
Open Access
Siniestralidad agraria en España (2004 a 2013): factores de riesgo
(Blake & Helsey, 2019) Arnal Atarés, Pedro; Jarén Ceballos, Carmen; López Maestresalas, Ainara; Mangado Ederra, Jesús; Arazuri Garín, Silvia; Ingeniería; Ingeniaritza
Los datos del presente artículo son, en su mayor parte, los resultados encontrados por Pedro Arnal Atarés en el desarrollo de su tesis doctoral 'Análisis de la información sobre accidentes en el sector agrario recogida en los medios de comunicación en el decenio 2004-2013'. Esta tesis fue dirigida por Carmen Jarén Ceballos. Al objeto de conseguir el Doctorado en Prevención de Riesgos Laborales, la tesis citada se defendió el día 5 de septiembre de 2017 en la Universidad Pública de Navarra y obtuvo la calificación de Sobresaliente.
Open Access
Phytochemicals determination and classification in purple and red fleshed potato tubers by analytical methods and near infrared spectroscopy
(Wiley, 2016) Tierno, Roberto; López Maestresalas, Ainara; Riga, Patrick; Arazuri Garín, Silvia; Jarén Ceballos, Carmen; Ruiz de Galarreta, José Ignacio; Proyectos e Ingeniería Rural; Landa Ingeniaritza eta Proiektuak
BACKGROUND: Over the last two decades, the attractive colours and shapes of pigmented tubers and the increasing concern about the relationship between nutrition and health have contributed to the expansion of their consumption and a specialty market. Thus, we have quantified the concentration of health promoting compounds such as soluble phenolics, monomeric anthocyanins, carotenoids, vitamin C, and hydrophilic antioxidant capacity, in a collection of 18 purple- and red-fleshed potato accessions. RESULTS: Cultivars and breeding lines high in vitamin C, such as Blue Congo, Morada and Kasta, have been identified. Deep purple cultivars Violet Queen, Purple Peruvian and Vitelotte showed high levels of soluble phenolics, monomeric anthocyanins, and hydrophilic antioxidant capacity, whereas relatively high carotenoid concentrations were found in partially yellow coloured tubers, such as Morada, Highland Burgundy Red, and Violet Queen. CONCLUSION: The present characterisation of cultivars and breeding lines with high concentrations of phytochemicals is an important step both to support the consideration of specialty potatoes as a source of healthy compounds, and to obtain new cultivars with positive nutritional characteristics. Moreover, by using near infrared spectroscopy a non-destructive identification and classification of samples with different levels of phytochemicals is achieved, offering an unquestionable contribution to the potato industry for future automatic discrimination of varieties.
Open Access
Hyperspectral imaging using notions from type-2 fuzzy sets
(Springer, 2019) López Maestresalas, Ainara; Miguel Turullols, Laura de; López Molina, Carlos; Arazuri Garín, Silvia; Bustince Sola, Humberto; Jarén Ceballos, Carmen; Ingeniería; Ingeniaritza; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
Fuzzy set theory has developed a prolific armamentarium of mathematical tools for each of the topics that has fallen within its scope. One of such topics is data comparison, for which a range of operators has been presented in the past. These operators can be used within the fuzzy set theory, but can also be ported to other scenarios in which data are provided in various representations. In this work, we elaborate on notions for type-2 fuzzy sets, specifically for the comparison of type-2 fuzzy membership degrees, to create function comparison operators. We further apply these operators to hyperspectral imaging, in which pixelwise data are provided as functions over a certain energy spectra. The performance of the functional comparison operators is put to the test in the context of in-laboratory hyperspectral image segmentation.
Open Access
Detection of minced lamb and beef fraud using NIR spectroscopy
(Elsevier, 2019) López Maestresalas, Ainara; Insausti Barrenetxea, Kizkitza; Jarén Ceballos, Carmen; Pérez Roncal, Claudia; Urrutia Vera, Olaia; Beriain Apesteguía, María José; Arazuri Garín, Silvia; Ingeniaritza; Agronomia, Bioteknologia eta Elikadura; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD; Ingeniería; Agronomía, Biotecnología y Alimentación; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
The aim of this work was to investigate the feasibility of near-infrared spectroscopy (NIRS), combined with chemometric techniques, to detect fraud in minced lamb and beef mixed with other types of meats. For this, 40 samples of pure lamb and 30 samples of pure beef along with 160 samples of mixed lamb and 156 samples of mixed beef at different levels: 1-2-5-10% (w/w) were prepared and analyzed. Spectral data were pre-processed using different techniques and explored by a Principal Component Analysis (PCA) to find out differences among pure and mixed samples. Moreover, a PLS-DA was carried out for each type of meat mixture. Classification results between 78.95 and 100% were achieved for the validation sets. Better rates of classification were obtained for samples mixed with pork meat, meat of Lidia breed cattle and foal meat than for samples mixed with chicken in both lamb and beef. Additionally, the obtained results showed that this technology could be used for detection of minced beef fraud with meat of Lidia breed cattle and foal in a percentage equal or higher than 2 and 1%, respectively. Therefore, this study shows the potential of NIRS combined with PLS-DA to detect fraud in minced lamb and beef.
Open Access
Analysis of fire services coverage in Spain
(DYNA, 2018) Echeverría Iriarte, Francisco Javier; González de Audícana Amenábar, María; López Maestresalas, Ainara; Arazuri Garín, Silvia; Ciriza Labiano, Raquel; Jarén Ceballos, Carmen; Ingeniería; Ingeniaritza; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
Previous analysis of the locations of fire stations in Spain and the extent of the areas they cover revealed significant deficiencies with regard to the proportion of communities who would not receive fire service intervention within a reasonable time period. This article discusses and describes the use of Geographic Information Systems and related tools to determine the areas and population covered by existing fire services within a specific response time. This response time by road, is based on a survey of fire service interventions in other European countries. The analysis compares data from a statistical study with georeferenced ones and demonstrates that the areas and communities not covered within this response time is greater than previously believed. The article then describes an analysis an alternative solution to reinforce the current fire stations network with part-time firefighters to cover the areas not covered mainly in rural and remote locations.
Open Access
Hyperspectrum comparison using similarity measures
(IEEE, 2017-08-31) López Molina, Carlos; Marco Detchart, Cedric; Bustince Sola, Humberto; Fernández Fernández, Francisco Javier; López Maestresalas, Ainara; Ayala Martini, Daniela; Automática y Computación; Automatika eta Konputazioa; Proyectos e Ingeniería Rural; Landa Ingeniaritza eta Proiektuak
Similarity measures, as studied in the context of fuzzy set theory, have been proven applicable to many different fields. Surely, their primary role is to model the perceived (dis-) similarity between two fuzzy sets or, equivalently, the linguistic terms they represent. However, the richness of the dedicated study makes the similarity measures portable to other contexts in which quantitative comparison plays a key role. In this work we present the application of similarity measures to hyperspectrum comparison in the context of in-lab hyperspectral imaging for bioengineering.
Open Access
A multi-year analysis of traffic accidents involving agricultural tractors
(AIDIC, 2017) Arnal Atarés, Pedro; López Maestresalas, Ainara; Arazuri Garín, Silvia; Mangado Ederra, Jesús; Jarén Ceballos, Carmen; Proyectos e Ingeniería Rural; Landa Ingeniaritza eta Proiektuak
The agricultural sector in Spain is responsible for a high rate of accidents every year, and many of them are traffic accidents. Tractors are a relatively rare sight on roads, meaning that the incidence of accidents involving these vehicles is relatively low, however, an above-average number of people are seriously injured or killed as a result of such accidents. Tractors are considered responsible for the majority of the occupational accidents in agriculture. Moreover, tractor overturns stand out as the principal cause of fatal accidents mainly because those accidents involved tractors without rollover protective structures (ROPS). Despite the obligation for all tractors of having a protective structure, the incidence rate of accidents with sick leave followed a rising line in the last ten years. Thus, in this study an analysis of the data of traffic accidents involving agricultural tractors in Spain, during the 2004-2013 period, is developed in order to identify the main risk factors that influence them. Official data from the “Statistical Yearbook of Accidents” published annually were used. A total of 2892 accidents were analysed. The results obtained showed that the incidence rate of both accidents and deaths were lower in accidents involving tractors than in general ones, but the consequences were more severe. In addition, the majority of accidents producing victims happened in interurban roads involving two or more vehicles. Defects in the lighting and brake systems were identified as risk of producing an accident. In the majority of the cases, the driver was the only victim of the crash. The total number of victims showed a decreasing tendency while the fatality index remained constant. The age of driver was reported to directly influence the number of accidents, with a high proportion of drivers over 45 years old. The main offences committed by drivers were related to inadequate speed and distracted driving. As much as possible we put our findings in an international context.
Open Access
Non-destructive detection of blackspot in potatoes by Vis-NIR and SWIR hyperspectral imaging
(Elsevier, 2016) López Maestresalas, Ainara; Keresztes, Janos C.; Goodarzi, Mohammad; Arazuri Garín, Silvia; Jarén Ceballos, Carmen; Saeys, Wouter; Proyectos e Ingeniería Rural; Landa Ingeniaritza eta Proiektuak; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
Blackspot is a subsurface potato damage resulting from impacts during harvesting. This type of bruising represents substantial economic losses every year. As the tubers do not show external symptoms, bruise detection in potatoes is not straightforward. Therefore, a nondestructive and accurate method capable of identifying bruised tubers is needed. Hyperspectral imaging (HSI) has been shown to be able to detect other subsurface defects such as bruises in apples. This method is nondestructive, fast and can be fully automated. Therefore, its potential for non-destructive detection of blackspot in potatoes has been investigated in this study. Two HSI setups were used, one ranging from 400 to 1000 nm, named VisibleNear Infrared (Vis-NIR) and another covering the 1000e2500 nm range, called Short Wave Infrared (SWIR). 188 samples belonging to 3 different varieties were divided in two groups. Bruises were manually induced and samples were analyzed 1, 5, 9 and 24 h after bruising. PCA, SIMCA and PLS-DA were used to build classifiers. The PLS-DA model performed better than SIMCA, achieving an overall correct classification rate above 94% for both hyperspectral setups. Furthermore, more accurate results were obtained with the SWIR setup at the tuber level (98.56 vs. 95.46% CC), allowing the identification of early bruises within 5 h after bruising. Moreover, the pixel based PLS- DA model achieved better results in the SWIR setup in terms of correctly classified samples (93.71 vs. 90.82% CC) suggesting that it is possible to detect blackspot areas in each potato tuber with high accuracy.