Jarén Ceballos, Carmen

Last Name

Jarén Ceballos

First Name

Carmen

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Ingeniería

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

ORCID

0000-0003-3103-7255

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88394

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347

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Now showing 1 - 10 of 37

Open Access
Classification of beef longissimus thoracis muscle tenderness using hyperspectral imaging and chemometrics
(MDPI, 2022) León Ecay, Sara; López Maestresalas, Ainara; Murillo Arbizu, María Teresa; Beriain Apesteguía, María José; Mendizábal Aizpuru, José Antonio; Arazuri Garín, Silvia; Jarén Ceballos, Carmen; Bass, Phillip D.; Colle, Michael J.; García, David; Romano Moreno, Miguel; Insausti Barrenetxea, Kizkitza; Agronomia, Bioteknologia eta Elikadura; Ingeniaritza; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD; Agronomía, Biotecnología y Alimentación; Ingeniería; Gobierno de Navarra / Nafarroako Gobernua Universidad Pública de Navarra / Nafarroako Unibertsitate
Nowadays, the meat industry requires non-destructive, sustainable, and rapid methods that can provide objective and accurate quality assessment with little human intervention. Therefore, the present research aimed to create a model that can classify beef samples from longissimus thoracis muscle according to their tenderness degree based on hyperspectral imaging (HSI). In order to obtain different textures, two main strategies were used: (a) aging type (wet and dry aging with or without starters) and (b) aging times (0, 7, 13, 21, and 27 days). Categorization into two groups was carried out for further chemometric analysis, encompassing group 1 (ngroup1 = 30) with samples with WBSF < 53 N whereas group 2 (ngroup2 = 28) comprised samples with WBSF values 53 N. Then, classification models were created by applying the partial least squares discriminant analysis (PLS-DA) method. The best results were achieved by combining the following pre-processing algorithms: 1st derivative + mean center, reaching 70.83% of correctly classified (CC) samples and 67.14% for cross validation (CV) and prediction, respectively. In general, it can be concluded that HSI technology combined with chemometrics has the potential to differentiate and classify meat samples according to their textural characteristics.
Open Access
Análisis de accidentes de trabajo mortales en España (2000-2020)
(Fundación Internacional ORP, 2022) Ríos Eraso, Alonso; Jarén Ceballos, Carmen; Ingeniería; Ingeniaritza; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD
Los accidentes de trabajo mortales representan la consecuencia máxima del resultado de las estrategias, políticas y acciones de la integración de la seguridad en el trabajo contra la siniestralidad laboral. Este estudio aporta un análisis de los accidentes de trabajo mortales (excluidos los accidentes in itinere), con respecto al total de los accidentes laborales con baja ocurridos en España en el período 2000-2020, señalando las diferencias existentes por sectores de actividad económica, sexo, antigüedad en el puesto de trabajo, edad de los trabajadores, y entre las Comunidades Autónomas de España, para observar el resultado de la aplicación de la Ley 31/1995 de prevención de riesgos laborales, por la transposición de Directivas comunitarias al Derecho español, relativas a la aplicación de promover la mejora de la seguridad y de la salud de los trabajadores en el trabajo.
Open Access
A systematized review on the applications of hyperspectral imaging for quality control of potatoes
(Springer, 2024) Peraza Alemán, Carlos Miguel; López Maestresalas, Ainara; Jarén Ceballos, Carmen; Rubio Padilla, Niuton; Arazuri Garín, Silvia; Ingeniería; Ingeniaritza; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
The application of hyperspectral imaging (HSI) has gained signifcant importance in the past decade, particulary in the context of food analysis, including potatoes. However, the current literature lacks a comprehensive systematic review of the application of this technique in potato cultivation. Therefore, the aim of this work was to conduct a systematized review by analysing the most relevant compounds, diseases and stress factors in potatoes using hyperspectral imaging. For this purpose, scientifc studies were retrieved through a systematic keyword search in Web of Science and Scopus databases. Studies were only included in the review if they provided at least one set of quantitative data. As a result, a total of 52 unique studies were included in the review. Eligible studies were assigned an in-house developed quality scale identifying them as high, medium or low risk. In most cases the studies were rated as low risk. Finally, a comprehensive overview of the HSI applications in potatoes was performed. It has been observed that most of the selected studies obtained better results using linear methods. In addition, a meta-analysis of studies based on regression and classifcation was attempted but was not possible as not enough studies were found for a specifc variable.
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.
Open Access
Exploring the potential of hyperspectral imaging to detect Esca disease complex in asymptomatic grapevine leaves
(Elsevier, 2022) Pérez Roncal, Claudia; Arazuri Garín, Silvia; López Molina, Carlos; Jarén Ceballos, Carmen; Santesteban García, Gonzaga; López Maestresalas, Ainara; Ingeniaritza; Estatistika, Informatika eta Matematika; Agronomia, Bioteknologia eta Elikadura; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD; Ingeniería; Estadística, Informática y Matemáticas; Agronomía, Biotecnología y Alimentación; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
Precise and reliable identification of specific plant diseases is a challenge within precision agriculture nowadays. This is the case of esca, a complex grapevine trunk disease, that represents a major threat to modern viticulture as it is responsible for large economic losses annually. The lack of effective control strategies and the complexity of esca disease expression make essential the identification of affected plants, before symptoms become evident, for a better management of the vineyard. This study evaluated the suitability of a near-infrared hyperspectral imaging (HSI) system to detect esca disease in asymptomatic grapevine leaves of Tempranillo red-berried cultivar. For this, 72 leaves from an experimental vineyard, naturally infected with esca, were collected and scanned with a lab-scale HSI system in the 900-1700 nm spectral range. Then, effective image processing and multivariate analysis techniques were merged to develop pixel-based classification models for the distinction of healthy, asymptomatic and symptomatic leaves. Automatic and interval partial least squares variable selection methods were tested to identify the most relevant wavelengths for the detection of esca-affected vines using partial least squares discriminant analysis and different pre-processing techniques. Three-class and two-class classifiers were carried out to differentiate healthy, asymptomatic and symptomatic leaf pixels, and healthy from asymptomatic pixels, respectively. Both variable selection methods performed similarly, achieving good classification rates in the range of 82.77-97.17% in validation datasets for either three-class or two-class classifiers. The latter results demonstrated the capability of hyperspectral imaging to distinguish two groups of seemingly identical leaves (healthy and asymptomatic). These findings would ease the annual monitoring of disease incidence in the vineyard and, therefore, better crop management and decision making.
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
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
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.