ISFOOD - Institute on Innovation & Sustainable Development in Food Chain

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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
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
Análisis de la siniestralidad por vuelco de tractor en el período 2017-2021
(Interempresas Media, 2023) Casuso, G.; Arazuri Garín, Silvia; Mangado Ederra, Jesús; López Maestresalas, Ainara; Arnal Atarés, Pedro; Jarén Ceballos, Carmen; Ingeniería; Ingeniaritza; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD
Desde que en 1995 se promulgó la Ley 31/1995 (BOE nº269/1995) de Prevención de Riesgos Laborales se ha observado una disminución importante de la siniestralidad laboral en todos los sectores. Sin embargo, en el sector agrario esta disminución no ha sido del calado de otros sectores y, por ejemplo, los índices de mortalidad prácticamente se mantienen en el tiempo. Tal es así, que el sector agrario ha sido calificado por el Observatorio Estatal de Condiciones de Trabajo (OECT) como prioritario para el desarrollo de políticas preventivas eficientes que permitan reducir la siniestralidad en el sector en base al índice de accidentes graves y mortales ajustado por la población afiliada.
Open Access
Application of the elastic curve equation for the verification of structures assimilable to continuous beams
(World Scientific Publishing, 2024) Gimena Ramos, Faustino; Gonzaga Vélez, Pedro; Goñi Garatea, Mikel; Valdenebro García, José Vicente; Senosiain Carasusan, María Aranzazu; Ingeniería; Ingeniaritza; Institute of Smart Cities - ISC; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD
This paper analyzes the beam under isolated and uniform loads, extending this calculation towards the structural type of the continuous beam, by means of a single expression of the elastic curve. A general expression of the bending is proposed, deduced by integrating the different differential equations of the elastica, associated to each section between discontinuities produced by the loads. In this paper, support reactions are incorporated into the load system. Therefore, the continuous beam is understood as a bar made up of sections aligned between discontinuities. With this, the isostatic beam, the hyperstatic beam and the continuous beam can be treated by means of the same integrated expression of the displacement, also called the Macaulay method. Equivalent notations are provided to the expression of bending for the cases of traction-compression and torsion, obtained through the same reasoning and sequence of operations. The formulation of elastic type and the associated operations shown allow us to cover the analysis of the generic structural form, which we can define as the beam of any number of spans, or continuous beam of >n spans. The load system is also generalized, being able to contemplate loads of a different nature and form of distribution, both static and mobile. The examples that have been developed always provide analytical results of solicitation and deformation. They intend to explain the systematic path followed from the approach of the structural problem to its mathematical modelling, and the resolution procedure developed to obtain useful values for the structural verification. In these examples, an increasing degree of complexity and generalization has been followed. The expressions obtained are validated by comparing them with those that are usual in the structural literature for the same or similar problems.
Open Access
Assessment of the main factors affecting the dynamics of nutrients in two rainfed cereal watersheds
(Elsevier, 2020) Hernández García, Iker; Merchán Elena, Daniel; Aranguren Erice, Itxaso; Casalí Sarasíbar, Javier; Giménez Díaz, Rafael; Campo-Bescós, Miguel; Valle de Lersundi, Jokin del; Ingeniaritza; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD; Ingeniería
Nutrient dynamics and factors that control nutrient exports were observed in two watersheds, namely Latxaga and La Tejería, with similar climatic and management characteristics throughout 10 years (2007–2016). Similar patterns were observed in intra-annual and inter-annual dynamics with higher NO3 − concentration and NO3 −-N yield during the humid seasons (i.e., winters and hydrological year 2013). Regarding concentration, Latxaga showed a higher decrease of nitrate due to a higher development of vegetated areas. High discharge events produced nitrate dilution due to the presence of tile-drainage at La Tejeria. At Latxaga, where tile-drainage was not observed, an increase in concentration occurred as a response to high discharge events. Comparing both watersheds, La Tejería presented ca. 73 ± 25 mg NO3 − L−1 while at Latxaga, the concentration observed was almost three times lower, with ca. 21 ± 15 mg NO3 − L−1 throughout the study period. Similar patterns were observed for the NO3 −-N yield, with 32 kg NO3 −-N ha−1 year−1 and 17 kg NO3 −-N ha−1 year−1 at La Tejería and Latxaga, respectively. Regarding phosphorous, the observed concentrations were 0.20 ± 0.72 mg PO4 3− L−1 and 0.06 ± 0.38 mg PO4 3− L−1 at La Tejería and Latxaga, respectively, with PO4 3−-P yields being 71 kg PO4 3−-P ha−1 year−1 and 33 kg PO4 3−-P ha−1 year−1. Annual phosphate-P yield distribution in both watersheds followed similar patterns to those observed for the nitrate-N yield, with higher yields in the humid season. Regarding concentration, highly erosive rainfall that occurred in summer, mobilizing sediments and probably generating desorption of phosphorous in the stream channel, increased phosphate concentration. This research adds to the knowledge base regarding the dynamics of nutrients and the controlling factors in complex agricultural systems with Mediterranean characteristics.
Open Access
Challenges and progresses in the detailed estimation of sediment export in agricultural watersheds in Navarra (Spain) after two decades of experience
(Elsevier, 2023) Barberena Ruiz, Íñigo; Luquin Oroz, Eduardo Adrián; Campo-Bescós, Miguel; Eslava, Javier; Giménez Díaz, Rafael; Casalí Sarasíbar, Javier; Ingeniería; Ingeniaritza; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD
Soil erosion is a very serious environmental problem worldwide, with agriculture considered the main source of sediment in inland waters. In order to determine the extent and importance of soil erosion in the Spanish region of Navarra, in 1995 the Government of Navarra established the Network of Experimental Agricultural Watersheds (NEAWGN), which consists of five small watersheds representative of local conditions. In each watershed, key hydrometeorological variables, including turbidity, were recorded every 10 min, and daily samples were taken to determine suspended sediment concentration. In 2006, the frequency of suspended sediment sampling was increased during hydrologically relevant events. The main objective of this study is to explore the possibility of obtaining long and accurate time series of suspended sediment concentration in the NEAWGN. To this end, simple linear regressions between sediment concentration and turbidity are proposed. In addition, supervised learning models incorporating a larger number of predictive variables are used for the same purpose. A series of indicators are proposed to objectively characterize the intensity and timing of sampling. It was not possible to obtain a satisfactory model for estimating the concentration of suspended sediment. This would be mainly due to the large temporal variability found of the physical and mineralogical characteristics of the sediment, which would be affecting the turbidity value, independently of the sediment concentration, per se. This fact would be particularly important in small river watersheds such as those of this study, and especially if their physical conditions are spatially and temporally radically disturbed by agricultural tillage and by a constant modification of the vegetation cover, as is the case in cereal basins. Our findings suggest that better results could be obtained by including in the analysis variables such as soil texture and exported sediment texture, rainfall erosivity, and the state of vegetation cover and riparian vegetation.
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
Combination of spectral and textural features of hyperspectral imaging for the authentication of the diet supplied to fattening cattle
(Elsevier, 2024) León Ecay, Sara; Insausti Barrenetxea, Kizkitza; Arazuri Garín, Silvia; Goenaga Uceda, Irantzu; López Maestresalas, Ainara; Agronomía, Biotecnología y Alimentación; Agronomia, Bioteknologia eta Elikadura; Ingeniería; Ingeniaritza; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
This study explored the potential of hyperspectral imaging in the near infrared region (NIR-HSI) as a non-destructive and rapid tool to discriminate among two beef fattening diets. For that purpose, a feeding trial was carried out with a total of 24 purebred Pirenaica calves. Twelve of them were fed barley and straw (BS) while 11 animals were finished on vegetable by-products (VBPR). When comparing the reference measurements of the meat coming from those animals, only the total collagen ratio expressed the feeding effect (p-value<0.05). To undertake the authentication procedure, two discrimination approaches were run: partial least squares discriminant analysis (PLS-DA) and radial basis function-support vector machine (RBF-SVM). To precisely extract spectral and textural information from the lean portion of the meat steaks, various techniques were executed, such as principal component (PC) images, competitive adaptive reweighted sampling (CARS) for selecting optimal wavelengths, and gray-level-co-occurrence matrix (GLCM). After hyperspectral imaging and the combination of their own texture features, samples were classified according to feeding diet with an overall accuracy of 72.92% for PLS-DA and 80.56% for RBF-SVM. So, the potential of using HSI technology to authenticate the meat obtained from beef supplied a diet based on circular economy techniques was made in evidence.
Open Access
Convolutional neural networks for the detection of esca disease complex in asymptomatic grapevine leaves
(Springer, 2024-01-24) Carraro, Alberto; Saurio, Gaetano; López Maestresalas, Ainara; Scardapane, Simone; Marinello, Francesco; Ingeniería; Ingeniaritza; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD
The Esca complex is a grapevine trunk disease that significantly threatens modern viticulture. The lack of effective control strategies and the intricacy of Esca disease manifestation render essential the identification of affected plants before symptoms become evident to the naked eye. This study applies Convolutional Neural Networks (CNNs) to distinguish, at the pixel level, between healthy, asymptomatic and symptomatic grapevine leaves of a Tempranillo red-berried cultivar using Hyperspectral imaging (HSI) in the 900¿1700 nm spectral range. We show that a 1D CNN performs semantic image segmentation (SiS) with higher accuracy than PLS-DA, one of HSI data¿s most widely used classification algorithms.
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
A diachronic analysis of a changing landscape on the Duero river borderlands of Spain and Portugal combining remote sensing and ethnographic approaches
(MDPI, 2021) Hearn, Kyle Patrick; Álvarez-Mozos, Jesús; Giza eta Hezkuntza Zientziak; Ingeniaritza; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD; Ciencias Humanas y de la Educación; Ingeniería; Gobierno de Navarra / Nafarroako Gobernua; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
The Arribes del Duero region spans the border of both Spain and Portugal along the Duero River. On both sides of the border, the region boasts unique human‐influenced ecosystems. The borderland landscape is dotted with numerous villages that have a history of maintaining and managing an agrosilvopastoral use of the land. Unfortunately, the region in recent decades has suffered from massive outmigration, resulting in significant rural abandonment. Consequently, the oncemaintained landscape is evolving into a more homogenous vegetative one, resulting in a greater propensity for wildfires. This study utilizes an interdisciplinary, integrated approach of “bottom up” ethnography and “top down” remote sensing data from Landsat imagery, to characterize and document the diachronic vegetative changes on the landscape, as they are perceived by stakeholders and satellite spectral analysis. In both countries, stakeholders perceived the current changes and threats facing the landscape. Remote sensing analysis revealed an increase in forest cover throughout the region, and more advanced, drastic change on the Spanish side of the study area marked by wildfire and a rapidly declining population. Understanding the evolution and history of this rural landscape can provide more effective management and its sustainability.
Open Access
Dissolved solids and suspended sediment dynamics from five small agricultural watersheds in Navarre, Spain: a 10-year study
(Elsevier, 2019) Merchán Elena, Daniel; Luquin Oroz, Eduardo Adrián; Hernández García, Iker; Campo-Bescós, Miguel; Giménez Díaz, Rafael; Casalí Sarasíbar, Javier; Valle de Lersundi, Jokin del; Ingeniaritza; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD; Ingeniería; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
Dissolved solids (DS) and suspended sediment (SS) loads are considered relevant environmental problems. They are related to a wide range of on-site and off-site impacts, such as soil erosion or salinization of water bodies. In this study, the dynamics of DS and SS concentrations and loads were assessed in five small watersheds covering representative agricultural land uses in Navarre (Spain). To this end, discharge, DS and SS concentration data were collected during ten hydrological years at each watershed outlet, and loads were computed from discharge and concentration values. DS concentration followed a seasonal pattern imposed by the availability of water, with higher concentrations recorded in low-flow periods and lower concentration in the high-flow period. SS concentration was extremely variable, with a range of 2–4 orders of magnitude in concentration for any specific discharge. Temporal variations (both intra- and inter-annual) in DS loads were explained by differences in runoff, whereas those of SS were not, being the SS loads associated mainly with specific high flow events. These temporal patterns were observed for both agricultural (this study) and non-agricultural (literature) watersheds. From the data in the Navarrese watersheds and those available in the literature, we inferred that agricultural land use, in general, tends to increase the concentration of both DS and SS. Regarding DS and SS yields, the effects of agricultural land use on DS yields are controlled by the changes in runoff rather than the (small) changes in DS concentration. In this sense, land uses changes expected to increase runoff (i.e., a shift from forested to arable or from rainfed to irrigated agriculture) would increase DS yields. On the other hand, agricultural land use tends to increase SS yields, although the effect is highly variable depending on site-specific factors, both natural (e.g., watershed shape) and anthropogenic (e.g., degree of soil conservation practices). In the Navarrese watersheds, DS yields ranged from 1.1 to 2.2 Mg ha−1 year−1 whereas SS yields ranged from 0.3 to 4.3 Mg ha−1 year−1. DS yields seem to dominate under non-agricultural conditions and in most agricultural land uses at the small watershed scale. On the other hand, SS yields dominate in watersheds with increased soil erosion as a consequence of arable land use over erosion-prone watersheds.
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
Effects of climate change on streamflow and nitrate pollution in an agricultural mediterranean watershed in northern Spain
(Elsevier, 2023) Oduor, Brian Omondi; Campo-Bescós, Miguel; Lana Renault, Noemí; Casalí Sarasíbar, Javier; Ingeniería; Ingeniaritza; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD
Predicting water quality and quantity response to climate change in a watershed is very difficult due to the complexity and uncertainties in estimating and understanding future hydrological conditions. However, hydrological models could simplify the processes and predict future impacts of agricultural activities. This study aimed to evaluate the applicability of the Soil Water Assessment Tool (SWAT) model for climate change prediction of streamflow and nitrate load in an agricultural Mediterranean watershed in northern Spain. The model was first evaluated for simulating streamflow and nitrate load under rainfed agricultural conditions in the Cidacos River watershed in Navarre, Spain. Then, climate change impact analysis on streamflow and nitrate load was conducted in the short-term (2011–2040), medium-term (2041–2070), and long-term (2071–2100) future projections relative to the historical baseline period (1971–2000) under the RCP4.5 and RCP8.5 CO2 emission scenarios. The model evaluation showed a good model performance result during calibration (2000–2010) and validation (2011–2020) for streamflow (NSE = 0.82/0.83) and nitrate load (NSE = 0.71/0.68), indicating its suitability for adoption in the watershed. The climate change projection results showed a steady decline in streamflow and nitrate load for RCP4.5 and RCP8.5 in all projections, with the long-term projection scenario of RCP8.5 greatly affected. Autumn and winter saw a considerable drop in comparison to spring and summer. The decline in streamflow was attributed to the projected decrease in precipitation and increase in temperatures, while the nitrate load decline was consistent with the projected streamflow decline. Based on these projections, the long-term projection scenarios of RCP8.5 indicate dire situations requiring urgent policy changes and management interventions to minimize and mitigate the resulting climate change effects. Therefore, adapted agricultural management practices are needed to ensure sustainable water resource utilization and efficient nitrogen fertilizer application rates in the watershed to reduce pollution.
Open Access
Effects of innovative long-term soil and crop management on topsoil properties of a mediterranean soil based on detailed water retention curves
(European Geosciences Union, 2022) Aldaz Lusarreta, Alaitz; Giménez Díaz, Rafael; Campo-Bescós, Miguel; Arregui Odériz, Luis Miguel; Virto Quecedo, Íñigo; Agronomía, Biotecnología y Alimentación; Agronomia, Bioteknologia eta Elikadura; Ciencias; Zientziak; Ingeniería; Ingeniaritza; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD; Gobierno de Navarra / Nafarroako Gobernua
The effectiveness of conservation agriculture (CA) and other soil management strategies implying a reduction of tillage has been shown to be site-dependent (crop, clime and soil), and thus any new soil and crop management should be rigorously evaluated before its implementation. Moreover, farmers are normally reluctant to abandon conventional practices if this means putting their production at risk. This study evaluates an innovative soil and crop management (including no-tillage, cover crops and organic amendments) as an alternative to conventional management for rainfed cereal cropping in a calcareous soil in a semi-arid Mediterranean climatic zone of Navarra (Spain), based on the analysis of soil water retention curves (SWRCs) and soil structure. The study was carried out in a small agricultural area in the municipality of Garínoain (Navarre, Spain) devoted to rainfed cereal cropping. No other agricultural area in the whole region of Navarre exists where soil and crop management as proposed herein is practiced. Climate is temperate Mediterranean, and the dominant soil is Fluventic Haploxerept. Within the study area there is a subarea devoted to the proposed soil and crop management (OPM treatment), while there is another subarea where the soil and crop management is conventional in the zone (CM treatment). OPM includes no-tillage (18 years continuous) after conventional tillage, crop rotation, use of cover crops and occasional application of organic amendments. CM involves continuous conventional tillage (chisel plow), mineral fertilization, no cover crops and a lower diversity of crops in the rotation. Undisturbed soil samples from the topsoil and disturbed samples from the tilled layer were collected for both systems. The undisturbed samples were used to obtain the detailed SWRCs in the low suction range using a HYPROP©device. From the SWRCs, different approaches found in the literature to evaluate soil physical quality were calculated. The pore-size distribution was also estimated from the SWRCs. Disturbed samples were used in the laboratory to assess soil structure by means of an aggregate-size fractionation and to perform complementary analysis from which other indicators related to soil functioning and agricultural sustainability were obtained. The approaches evaluated did not show clear differences between treatments. However, the differences in soil quality between the two forms of management were better observed in the pore size distributions and by the analysis of the size distribution and stability of soil aggregates. There was an overabundance of macropores under CM, while the amount of mesopores (available water) and micropores were similar in both treatments. Likewise, more stable macroaggregates were observed in OPM than in CM, as well as more organic C storage, greater microbial activity, and biomass. The proposed management system is providing good results regarding soil physical quality and contributing also to the enhancement of biodiversity, as well as to the improvement in water-use efficiency. Finally, our findings suggest that the adoption of the proposed practice would not result in a loss in yields compared to conventional management.
Open Access
EUSEDcollab: a network of data from European catchments to monitor net soil erosion by water
(Nature Research, 2023-08-04) Matthews, Francis; Verstraeten, Gert; Borrelli, Pasquale; Vanmaercke, Matthias; Poesen, J.; Steegen, An; Degré, Aurore; Cárceles Rodríguez, Belén; Bielders, Charles; Franke, Christine; Alary, Claire; Zumr, David; Patault, Edouard; Nadal-Romero, Estela; Smolska, Ewa; Licciardello, Feliciana; Swerts, Gilles; Thodsen, Hans; Casalí Sarasíbar, Javier; Eslava, Javier; Richet, Jean-Baptiste; Ouvry, Jean-François; Farguell, Joaquim; Święchowicz, Jolanta; Nunes, João Pedro; Pak, Lai Ting; Liakos, Leonidas ; Campo-Bescós, Miguel; Żelazny, Mirosław; Delaporte, Morgan; Pineux, Nathalie; Henin, Nathan; Bezak, Nejc; Lana Renault, Noemí ; Tzoraki, Ourania; Giménez Díaz, Rafael; Li, Tailin; Durán Zuazo, Víctor Hugo; Bagarello, Vincenzo; Pampalone, Vincenzo; Ferro, Vito; Úbeda, Xavier; Panagos, Panos; Ingeniería; Ingeniaritza; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD
As a network of researchers we release an open-access database (EUSEDcollab) of water discharge and suspended sediment yield time series records collected in small to medium sized catchments in Europe. EUSEDcollab is compiled to overcome the scarcity of openaccess data at relevant spatial scales for studies on runoff, soil loss by water erosion and sediment delivery. Multi-source measurement data from numerous researchers and institutions were harmonised into a common time series and metadata structure. Data reuse is facilitated through accompanying metadata descriptors providing background technical information for each monitoring station setup. Across ten European countries, EUSEDcollab covers over 1600 catchment years of data from 245 catchments at event (11 catchments), daily (22 catchments) and monthly (212 catchments) temporal resolution, and is unique in its focus on small to medium catchment drainage areas (median = 43 km2, min = 0.04 km2, max = 817 km2) with applicability for soil erosion research. We release this database with the aim of uniting people, knowledge and data through the European Union Soil Observatory (EUSO).
Open Access
Evaluation of near-infrared hyperspectral imaging for the assessment of potato processing aptitude
(Frontiers Media, 2022) López Maestresalas, Ainara; López Molina, Carlos; Oliva Lobo, Gil Alfonso; Jarén Ceballos, Carmen; Ruiz de Galarreta, José Ignacio; Peraza Alemán, Carlos Miguel; Arazuri Garín, Silvia; Ingeniaritza; Estatistika, Informatika eta Matematika; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD; Ingeniería; Estadística, Informática y Matemáticas
The potato (Solanum tuberosum L.) is the world's fifth most important staple food with high socioeconomic relevance. Several potato cultivars obtained by selection and crossbreeding are currently on the market. This diversity causes tubers to exhibit different behaviors depending on the processing to which they are subjected. Therefore, it is interesting to identify cultivars with specific characteristics that best suit consumer preferences. In this work, we present a method to classify potatoes according to their cooking or frying as crisps aptitude using NIR hyperspectral imaging (HIS) combined with a Partial Least Squares Discriminant Analysis (PLS-DA). Two classification approaches were used in this study. First, a classification model using the mean spectra of a dataset composed of 80 tubers belonging to 10 different cultivars. Then, a pixel-wise classification using all the pixels of each sample of a small subset of samples comprised of 30 tubers. Hyperspectral images were acquired using fresh-cut potato slices as sample material placed on a mobile platform of a hyperspectral system in the NIR range from 900 to 1,700 nm. After image processing, PLS-DA models were built using different pre-processing combinations. Excellent accuracy rates were obtained for the models developed using the mean spectra of all samples with 90% of tubers correctly classified in the external dataset. Pixel-wise classification models achieved lower accuracy rates between 66.62 and 71.97% in the external validation datasets. Moreover, a forward interval PLS (iPLS) method was used to build pixel-wise PLS-DA models reaching accuracies above 80 and 71% in cross-validation and external validation datasets, respectively. Best classification result was obtained using a subset of 100 wavelengths (20 intervals) with 71.86% of pixels correctly classified in the validation dataset. Classification maps were generated showing that false negative pixels were mainly located at the edges of the fresh-cut slices while false positive were principally distributed at the central pith, which has singular characteristics.
Open Access
Evaluation of nitrate soil probes for a more sustainable agriculture
(MDPI, 2022) Bellosta Diest, Amelia; Campo-Bescós, Miguel; Zapatería Miranda, Jesús; Casalí Sarasíbar, Javier; Arregui Odériz, Luis Miguel; Agronomía, Biotecnología y Alimentación; Agronomia, Bioteknologia eta Elikadura; Ingeniería; Ingeniaritza; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD; Gobierno de Navarra / Nafarroako Gobernua
Synthetic nitrogen (N) fertilizers and their increased production and utilization have played a great role in increasing crop yield and in meeting the food demands resulting from population growth. Nitrate (NO3−) is the common form of nitrogen absorbed by plants. It has high water solubility and low retention by soil particles, making it prone to leaching and mobilization by surface water, which can seriously contaminate biological environments and affect human health. Few methods exist to measure nitrate in the soil. The development of ion selective sensors provides knowledge about the dynamics of nitrate in the soil in real time, which can be very useful for nitrate management. The objective of this study is to analyze the performance of three commercial probes (Nutrisens, RIKA and JXCT) under the same conditions. The performance was analyzed with respect to electrical conductivity (EC) (0–50 mS/cm) and nitrate concentration in aqueous solution and in sand (0–180 ppm NO3−) at 35% volumetric soil moisture. Differences were shown among probes when studying their response to variations of the EC and, notably, only the Nutrisens probe provided coherent accurate measurements. In the evaluation of nitrate concentration in liquid solution, all probes proved to be highly sensitive. Finally, in the evaluation of all probes’ response to modifications in nitrate concentration in sand, the sensitivity decreased for all probes, with the Nutrisens probe the most sensitive and the other two probes almost insensitive.
Open Access
Evaluation of R tools for downloading MODIS images and their use in urban growth analysis of the city of Tarija (Bolivia)
(MDPI, 2022) Campero Taboada, Milton J.; Luquin Oroz, Eduardo Adrián; Montesino San Martín, Manuel; González de Audícana Amenábar, María; Campo-Bescós, Miguel; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Ingeniería; Ingeniaritza; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
The aim of this study was to compare the available tools in R for downloading and processing Moderate Resolution Imaging Spectroradiometer (MODIS) data, specifically the Enhanced Vegetation Index (EVI) product. The R tools evaluated were the MODIS package, RGISTools, MODISTools, R Google Earth Engine (RGEE) package, MODIStsp, and the Application for Extracting and Exploring Analysis Ready Samples (AppEEARS) application. Each tool was used to download the same product (EVI) corresponding to the same day (3 December 2015), and downloaded data were used to analyze the urban growth of Tarija (Bolivia) as an interesting application. The following features were analyzed: download time and memory used during the download, additional postprocessing time, local memory occupied on the computer, and downloaded file formats. Results showed that the most efficient R tools were those that work directly in the “cloud” or use text queries (RGEE and AppEEARS, respectively) and provide, as a final product, a cropped.tif image according to the area of interest.