Jarén Ceballos, Carmen

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Jarén Ceballos

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Carmen

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Ingeniería

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

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0000-0003-3103-7255

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88394

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347

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Now showing 1 - 10 of 36

Open Access
Proyecto Agroinc: prevención del impacto ambiental de incendios provocados por cosechadoras
(Interempresas Media, 2022) Arazuri Garín, Silvia; Mangado Ederra, Jesús; López Maestresalas, Ainara; López Molina, Carlos; Angulo Muñoz, Blanca; Arnal Atarés, Pedro; Jarén Ceballos, Carmen; Ingeniería; Ingeniaritza; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Proyectos e Ingeniería Rural; Landa Ingeniaritza eta Proiektuak; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD; Gobierno de Navarra / Nafarroako Gobernua
Las cosechadoras de cereales, por las condiciones ambientales en las que trabajan, alta temperatura y baja humedad, tanto ambiental como del producto que están cosechando, pueden provocar accidentalmente incendios durante la época de recolección. Los daños económicos y medioambientales que estos incendios suponen pueden ser muy importantes, ya que las condiciones de propagación del fuego son óptimas. Los principales objetivos de este proyecto han sido evaluar el impacto ambiental de los incendios producidos en Navarra en los últimos años y establecer una guía de buenas prácticas para su prevención.
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
Editorial: Mediterranean foods: quality, safety and sustainability
(Frontiers Media, 2024-02-06) Agulheiro-Santos, Ana Cristina; Laranjo, Marta; Jarén Ceballos, Carmen; Ingeniería; Ingeniaritza; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD
In recent years, the Mediterranean diet has been recovered, especially after its recognition as UNESCO's intangible cultural heritage. It involves the use of many plant-based foods common to several Mediterranean countries, such as olive oil, olives, fruits and vegetables, cereals, pulses, nuts, wine, but also meat and fish. The adoption of this diet has favorable and direct implications on health, but also on society and economy, with consequences for the sustainability and resilience of agrifood systems, inherent to production, relevant topics in the current context of climate change and water scarcity. Additionally, these Research Topics are aligned with the 2030 Agenda of the United Nations, mainly contributing to Sustainable Development Goals 2 (Zero Hunger), 3 (Good Health and Wellbeing), and 12 (Responsible Consumption). In this twenty-first century, new challenges have been imposed on all of us involving the food distribution chain, from producers to consumers, including researchers. In parallel with food security, the access to safe food, and the reduction of food loss and waste are also urgent challenges to be addressed. To achieve these worldwide objectives, it is necessary to explore innovative strategies for production of raw materials, to transform unexploited into new food raw materials, to use new manufacturing processes, as well as innovative conservation methods. All these objectives contribute to the availability and accessibility of quality foods that enable an increased adherence to the Mediterranean diet and should be achieved taking environmental concerns into account. The Research Topic on “Mediterranean foods: quality, safety and sustainability” focuses on different Mediterranean diet foods, including their relationship with environmental sustainability and production systems. Among the submitted manuscripts, four research articles were selected by external experts to enter this Research Topic of Frontiers in Nutrition.
Open Access
Mapping acrylamide content in potato chips using near-infrared hyperspectral imaging and chemometrics
(Elsevier, 2025-03-14) Peraza Alemán, Carlos Miguel; López Maestresalas, Ainara; Jarén Ceballos, Carmen; Ruiz de Galarreta, José Ignacio; Barandalla, Leire; Arazuri Garín, Silvia; Ingeniería; Ingeniaritza; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD
This study investigated the potential of near-infrared hyperspectral imaging (NIR-HSI) for the prediction of acrylamide content in potato chips. A total of 300 tubers from two potato varieties (Agria and Jaerla) grown in two seasons and processed under the same frying conditions were analysed. Partial Least Square Regression (PLSR) and Support Vector Machine Regression (SVMR), combined with a logarithmic transformation of the acrylamide levels, were applied to develop predictive models. The most optimal outcomes for PLSR yielded R2 p: 0.85, RMSEP: 201 μg/kg and RPD: 2.53, while for SVMR yielded R2 p: 0.80, RMSEP: 229 μg/kg and RPD: 2.22. Furthermore, the selection of significant wavelengths enabled an 87.95 % reduction in variables without affecting the model’s accuracy. Finally, spatial mapping of acrylamide content was conducted on all chips in the external validation set. This method provides both quantification and visualization capabilities, thus enhancing quality control for acrylamide identification in processed potatoes.
Open Access
Applications of sensing for disease detection
(Springer, 2021) Castro, Ana Isabel de; Pérez Roncal, Claudia; Thomasson, J. Alex; Ehsani, Reza; López Maestresalas, Ainara; Yang, Chenghai; Jarén Ceballos, Carmen; Wang, Tianyi; Cribben, Curtis; Marín Ederra, Diana; Isakeit, Thomas; Urrestarazu Vidart, Jorge; López Molina, Carlos; Wang, Xiwei; Nichols, Robert L.; Santesteban García, Gonzaga; Arazuri Garín, Silvia; Peña, José Manuel; Agronomía, Biotecnología y Alimentación; Agronomia, Bioteknologia eta Elikadura; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Ingeniería; Ingeniaritza; Gobierno de Navarra / Nafarroako Gobernua; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
The potential loss of world crop production from the effect of pests, including weeds, animal pests, pathogens and viruses has been quantifed as around 40%. In addition to the economic threat, plant diseases could have disastrous consequences for the environment. Accurate and timely disease detection requires the use of rapid and reliable techniques capable of identifying infected plants and providing the tools required to implement precision agriculture strategies. The combination of suitable remote sensing (RS) data and advanced analysis algorithms makes it possible to develop prescription maps for precision disease control. This chapter shows some case studies on the use of remote sensing technology in some of the world’s major crops; namely cotton, avocado and grapevines. In these case studies, RS has been applied to detect disease caused by fungi using different acquisition platforms at different scales, such as leaf-level hyperspectral data and canopy-level remote imagery taken from satellites, manned airplanes or helicopter, and UAVs. The results proved that remote sensing is useful, effcient and effective for identifying cotton root rot zones in cotton felds, laurel wilt-infested avocado trees and escaaffected vines, which would allow farmers to optimize inputs and feld operations, resulting in reduced yield losses and increased profts.
Open Access
Fatal tractor accidents in the agricultural sector in Spain during the past decade
(MDPI, 2022) Jarén Ceballos, Carmen; Ibarrola, Alicia; Mangado Ederra, Jesús; Adin Urtasun, Aritz; Arnal Atarés, Pedro; López Maestresalas, Ainara; Ríos Eraso, Alonso; Arazuri Garín, Silvia; Ingeniería; Ingeniaritza; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
Currently, there is a discrepancy between the number of occupational accidents in the agricultural sector reported by Spanish governmental sources and those actually occurring in general. This is mainly due to the official definition of ‘occupational accident’ in the current regulations. In order to be able to analyse all fatal accidents involving tractors, other sources of information must therefore be used. In this study, we have collected the news published in different media during the period 2010–2019. Statistical models that take into account the spatial and temporal dependence of the data were used to estimate the rates of fatal accidents in the provinces of Spain using the Bayesian inference technique INLA (Integrated Nested Laplace Approximation). The results obtained showed that the total number of fatal accidents in that period was 644. The crude rates of fatal accidents per province ranged from 0 to 223.5 fatal accidents per 100,000 registered tractors. In addition, the overall rate for Spain as a whole was 6.87 fatal accidents per 100,000 tractors. As in other EU countries, it was found that the regions with the highest number of accidents were also related to steep terrain, to an older tractor fleet and to horticultural crops and vineyards.
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
Early detection of Esca disease in grapevines using in-field hyperspectral proximal sensing
(Hellenic Society of Agricultural Engineers, 2025) López Maestresalas, Ainara; Ruiz de Gauna González, Jon; Jarén Ceballos, Carmen; León Ecay, Sara; Arazuri Garín, Silvia; Agronomía, Biotecnología y Alimentación; Agronomia, Bioteknologia eta Elikadura; Ingeniería; Ingeniaritza; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD
Esca is one of the most destructive vine diseases in the world. It causes significant economic losses, mainly due to reduced grape yield and quality. Currently, the approved methods of controlling esca include preventive methods such as the use of fungicides on plant wounds or the use of planting systems that do not require intensive pruning, among others. It is therefore advisable to monitor the crop to identify those vines that are susceptible to the disease. For this reason, in this study a proximal hyperspectral camera was used for early detection of esca presence in asymptomatic grapevine leaves. Images of 11 vines of the Tempranillo variety grown in Etxauri (Navarre, Spain) were analysed. Hyperspectral images were acquired using a Specim IQ snapshot camera, mounted on a tripod, working in the range of 400¿1000 nm with a spectral resolution of 7 nm (204 bands), and an image resolution of 512 × 512 pixel including an RGB camera (5 Mpix). The images were taken under natural ambient light conditions on August 21, 2023. From the 11 vines selected, 9 showed visual symptoms of esca and the remaining 2 were asymptomatic to the naked eye. A total of 200 pixels were randomly selected from the dataset, 100 from asymptomatic leaves of asymptomatic vines (class 1) and 100 from asymptomatic leaves of symptomatic vines (class 2). Partial Least Square Discriminant Analysis (PLS-DA) was performed to classify the leaves into the two classes. Classification rates of 97% were achieved in the cross-validation dataset. Models were externally validated at pixel-level using one image of an asymptomatic vine and another of a symptomatic vine. The visualisation of the images confirmed the correct classification of the pixels into the two classes, indicating that by using proximal hyperspectral sensing an early identification of the disease is possible.
Open Access
Imágenes hiperespectrales para el estudio de la respuesta a la deficiencia de nitrógeno de distintos cultivares de patata
(Sociedad Española de Ciencias Hortícolas, 2021) López Maestresalas, Ainara; Jarén Ceballos, Carmen; Ruiz de Galarreta, José Ignacio; Álvarez Morezuelas, Alba; Barandalla, Leire; Arazuri Garín, Silvia; Ingeniería; Ingeniaritza
El cambio climático es uno de los mayores retos de la agricultura moderna. El aumento del rendimiento de los cultivos en el futuro sólo será posible si pueden hacer frente a las consecuencias del cambio climático causado por el aumento de CO2 en la atmósfera. En el cultivo de la patata es muy probable que los estreses abióticos se incrementen considerablemente comprometiendo la sostenibilidad de su producción. A largo plazo, las condiciones de elevado CO2 podrían alterar la toma y transporte de nutrientes, particularmente del nitrógeno (N). Esto conlleva la necesidad de seleccionar cultivares que por sus características genéticas, fisiológicas y agronómicas se adapten mejor a las condiciones del cambio climático global, particularmente a la eficiencia en el uso del N. Para ello, en este estudio, se ha empleado la tecnología de imágenes hiperespectrales con el objetivo de desarrollar modelos de clasificación de variedades más eficientes en el uso del N. Se han muestreado plantas de dos campos experimentales: control y con una reducción del 75% de aporte de N. Se han adquirido imágenes hiperespectrales de 120 hojas de las plantas control y 120 de plantas sometidas a una reducción del 75% de aporte de N. Se han aplicado métodos multivariantes de clasificación para comprobar el potencial de las imágenes hiperespectrales en la identificación de cultivares de patata mejor adaptados a una deficiencia de N, con resultados prometedores. Además, para evaluar la respuesta de las plantas a las diferentes dosis de N, se analizará el contenido total de N, lo que permitirá evaluar la eficiencia en el uso del N en función de la productividad, así como la concentración de metabolitos nitrogenados.
Open Access
Evaluation of mechanical tomato harvesting using wireless sensors
(MDPI, 2010) Arazuri Garín, Silvia; Arana Navarro, Ignacio; Jarén Ceballos, Carmen; Proyectos e Ingeniería Rural; Landa Ingeniaritza eta Proiektuak
The harvesting of processing tomatoes is fully mechanised and it is well known that during harvest, fruits are subjected to mechanical stress causing physical injuries, including skin punctures, pulp and cell rupture. Some wireless sensors have been used for research during recent years with the main purpose of reducing the quality loss of tomato fruits by diminishing the number and intensity of impacts. In this study the IRD (impact recorder device) sensor was used to evaluate several tomato harvesters. The specific objectives were to evaluate the impacts during mechanical harvest using a wireless sensor, to determine the critical points at which damage occurs, and to assess the damage levels. Samples were taken to determine the influence of mechanical harvest on texture, or on other quality characteristics including percentage of damages. From the obtained data it has been possible to identify the critical points where the damages were produced for each one of the five harvester models examined. The highest risk of damage was in zone 1 of the combine—from the cutting system to the colour selector—because the impacts were of higher intensity and hit less absorbing surfaces than in zone 2—from colour selector to discharge. The shaker and exit from the shaker are two of the harvester elements that registered the highest intensity impacts. By adjusting, in a specific way each harvester model, using the results from this research, it has been possible to reduce the tomato damage percentage from 20 to 29% to less than 10%.