Jarén Ceballos, Carmen

Last Name

Jarén Ceballos

First Name

Carmen

person.page.departamento

Ingeniería

person.page.instituteName

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

ORCID

0000-0003-3103-7255

person.page.observainves

88394

person.page.upna

347

Full item page

Search Results

Now showing 1 - 10 of 23

Open Access
On-site identification of esca-affected vines using hyperspectral imaging
(Hellenic Society of Agricultural Engineers, 2025) León Ecay, Sara; Ruiz de Gauna González, Jon; López Maestresalas, Ainara; Jarén Ceballos, Carmen; Arazuri Garín, Silvia; Ingeniería; Ingeniaritza; Agronomía, Biotecnología y Alimentación; Agronomia, Bioteknologia eta Elikadura; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD
Esca represents one of the greatest threats to modern viticulture as it causes large annual economic losses. At present, there is a lack of effective strategies for disease control, so a technique capable of detecting affected vines would allow annual monitoring of disease incidence in the vineyard leading to a better crop management and decision making. This study evaluates close-range hyperspectral imaging for the detection of esca naturally infected vines. Images of 11 vines of the Tempranillo variety grown on plots in Bodegas Otazu, in Etxauri (Navarre, Spain) were acquired. A Specim IQ snapshot hyperspectral camera was used to record the images on August, 21 2023 on the field under natural light conditions. The camera has a spectral resolution of 7 nm (204 wavelengths) and a spatial resolution of 512 x 512 in the 400 ¿ 1000 nm spectral range (Vis-NIR). An individual image was acquired for each vine, of which 9 were symptomatic and 2 asymptomatic. Three classes were analysed: asymptomatic leaves of asymptomatic vines (Class 1), asymptomatic leaves of symptomatic vines (Class 2) and asymptomatic areas of symptomatic leaves of symptomatic vines (Class 3). A total of 300 pixels were randomly selected, 100 per class, for further analysis. Partial Least Square Discriminant Analysis (PLSDA) was used to classify the pixels into the three categories. An accuracy of 86% was achieved in the cross-validation dataset. Models were externally validated using an image of an asymptomatic vine and an image of a symptomatic vine. The visualisation of the images showed that the majority of the pixels of the asymptomatic vine image were classified as class 1, while most of the pixels of the symptomatic vine image were classified as either class 2 or class 3. Hence, this study demonstrated the potential of close-range HSI for the on-site detection of esca.
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
Análisis espacio-temporal de los accidentes mortales con tractor en España durante el período 2010-2019
(Interempresas Media, 2023) Arazuri Garín, Silvia; Ibarrola, Alicia; Mangado Ederra, Jesús; Adin Urtasun, Aritz; Arnal Atarés, Pedro; López Maestresalas, Ainara; Jarén Ceballos, Carmen; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Ingeniería; Ingeniaritza
El sector agrario y el de la construcción son los que presentan los índices de incidencia de accidentes de trabajo mortales más altos de nuestro país, según los datos recogidos por el Instituto Nacional de Seguridad y Salud en el Trabajo (INSST) (2021) dependiente del Ministerio de Trabajo y Economía Social (Cirauqui, 2022). Si tenemos en cuenta la evolución de estos índices, el sector agrario es el único que no ha mejorado dicho índice desde la aparición de la Ley 31/1995 de prevención de riesgos laborales y su siniestralidad continúa aumentando (Fundación Mapfre 2020). Pero, ¿qué ocurre cuando el accidente lo sufren personas que no encajan en la definición legal de trabajador? Estos accidentes no son considerados 'accidente de trabajo' y, por tanto, escapan a todas las estadísticas y datos oficiales del INSST. Este suele ser el caso de muchos accidentes que sufren personas jubiladas, menores de 16 años, familiares colaboradores, etc. que no son personas vinculadas a la actividad laboral tal y como se define en la legislación. Según Arana et al. (2010) de un total de 388 accidentes mortales ocurridos en España con maquinaria agrícola durante los años 2004-2008, solamente el 61,85% de ellos tuvieron carácter oficial. Las personas mayores fueron el sector de la población con un mayor riesgo, seguidos de los niños y las personas ajenas al sector agrario. La mayoría de las muertes fueron debidas al vuelco de tractores sin estructuras de protección.
Open Access
Influencia de factores de cultivo y conservación en el contenido en azúcares reductores en patata
(Universidad de Sevilla, 2023) Jarén Ceballos, Carmen; Peraza Alemán, Carlos Miguel; Mangado Ederra, Jesús; López Maestresalas, Ainara; Arazuri Garín, Silvia; Ingeniería; Ingeniaritza; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD
La patata es uno de los alimentos más importante del mundo y una de las formas más habituales de consumirla es como patatas fritas. Al freírla a altas temperaturas, los azúcares reductores y la asparagina de la patata pueden dar lugar a acrilamidas, por medio de la reacción de Maillard. La acrilamida está clasificada como sustancia probablemente cancerígena para el ser humano. Por eso es importante que las patatas destinadas a fritura tengan un bajo contenido en azúcares reductores. Este contenido depende de factores genéticos, medioambientales, culturales y condiciones de almacenamiento. Por ello, en este trabajo se pretende analizar algunos de esos factores en una variedad rica en azúcares reductores como es Jaerla. Los factores analizados fueron el estrés hídrico durante el cultivo, dos temperaturas de almacenamiento (8 y 13ºC) y tiempo de almacenamiento en las anteriores temperaturas, desde 0 hasta 13 semanas. Las muestras de patatas de cada uno de los tratamientos se liofilizaron y se determinó su contenido en azúcares: glucosa, fructosa y sacarosa. Los datos fueron analizados con R-Studio. Solo se encontraron diferencias significativas en el factor temperatura de conservación para los tres azúcares, obteniéndose los valores más altos en las patatas conservadas a 8ºC.
Open Access
Análisis de la siniestralidad por vuelco de tractor en el período 2017-2021
(Universidad de Sevilla, 2023) Jarén Ceballos, Carmen; Casuso, G.; Mangado Ederra, Jesús; López Maestresalas, Ainara; Arnal Atarés, Pedro; Arazuri Garín, Silvia; Ingeniería; Ingeniaritza; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD
A pesar de los avances que se dan en el ámbito de la seguridad laboral en el sector agrario, los accidentes se siguen produciendo sin que mejore la situación. Los accidentes más graves, por el elevado número de muertos todos los años, son los debidos al vuelco del tractor. En el presente trabajo se ha llevado a cabo el análisis de la influencia de distintas variables continuas y discretas (tamaño de explotación, pendiente, superficie agrícola utilizada (SAU)/número de explotaciones y tipo de cultivo) sobre 63 accidentes graves y mortales sucedidos en España a causa del vuelco. Han destacado las relaciones de los accidentes con las variables pendiente, tamaño y tipo de cultivo, siendo las provincias con mayor tasa de accidentalidad aquellas con explotaciones más pequeñas, situadas en terrenos más escarpados y con cultivos leñosos. Las variables con mayor relación entre sí han sido la pendiente y el tamaño, a su vez con cierta conexión con el tipo de cultivo.
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
Potential of NIRS technology for the determination of cannabinoid content in industrial hemp (Cannabis sativa L.)
(MDPI, 2022) Jarén Ceballos, Carmen; Zambrana, P.; Pérez Roncal, Claudia; López Maestresalas, Ainara; Ábrego Arlegui, Andrés; Arazuri Garín, Silvia; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD
Industrial hemp (Cannabis sativa L.) is a plant native to Asia, and is considered to be a primary source of food, textile fiber, and medicines. It is characterized by containing minimal concentrations of delta-9 tetrahydrocannabidol (THC), which is the main psychoactive chemical component, and cannabidiol (CBD), a non-psychoactive substance. In most European countries, the maximum concentration legally allowed for cultivation is 0.2% of THC, and it is currently under debate whether to increase this level to 0.3%. Moreover, in many countries its production is being regularized and legalized, increasing the need for a rapid analysis method. The present work evaluated the cannabinoid content in hemp (Cannabis sativa L.) using near infrared spectroscopy (NIRS) technology in combination with chemometric techniques. For this, several samples of the Kompolti variety were analyzed. Samples were dried and ground, and the content of total THC (%) and total CBD (%) was determined by high performance liquid chromatography (HPLC) with a diode array detector as reference measurements, and then the spectra were collected by NIRS. Principal component analysis and partial least square regression models were developed. Good coefficients of determination of cross-validation of 0.77 for THC and CBD, and a ratio of prediction to deviation >2 for total THC and CBD, were achieved. The results obtained show that NIRS technology has potential for the quantitative determination of cannabinoids. Therefore, this analytical method would allow a simpler, more robust, precise, and sustainable estimation than the current HPLC approach.
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
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
Predicting the spatial distribution of reducing sugars using near-infrared hyperspectral imaging and chemometrics: a study in multiple potato genotypes
(Elsevier, 2025-08-01) Peraza Alemán, Carlos Miguel; Arazuri Garín, Silvia; Jarén Ceballos, Carmen; Ruiz de Galarreta, José Ignacio; Barandalla, Leire; López Maestresalas, Ainara; Ingeniería; Ingeniaritza; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD
The determination of reducing sugars in potatoes is important due to their impact on product quality during industrial processing. The significant variability of these compounds between genotypes presents a challenge to the development of accurate predictive models. This study evaluated the potential of near-infrared hyperspectral imaging (NIR-HSI) for the prediction of reducing sugars in potatoes. For this, a wide range of genotypes (n=92) from two seasons (2020-2021) was selected. Partial Least Squares Regression (PLSR) and Support Vector Machine Regression (SVMR) methods were used to build the prediction models. Furthermore, interval PLS (iPLS), recursive weighted PLS (rPLS), Genetic Algorithm (GA) and Competitive Adaptive Reweighted Sampling (CARS) were used for relevant wavelength identification to develop less computationally complex models. The best full spectrum model (SNV-PLSR) achieved coefficient of determination and root mean square error values of 0.88 and 0.053% and 0.86 and 0.057%, for calibration and external validation, respectively. Variable selection algorithms successfully reduced the dimensionality of the data without compromising the performance of the models. Robust predicted models were built with only 2.65% (CARS-PLSR) and 3.57% (iPLS-SVMR) of the total wavelengths. Finally, a pixel-wise prediction was performed on the validation set and chemical images were built to visualise the spatial distribution of reducing sugars. This study demonstrated that NIR-HSI is a feasible technique for predicting reducing sugars in several potato genotypes.