THE POTENTIAL OF NEAR INFRARED SPECTROSCOPY AS A METHOD OF DETERMINATION OF THE FAT CONTENT IN

Yogurt is a food product produced by fresh milk as the raw material which is easier to digest and assimilate than fresh milk. Today, it is a very popular food product and is marketed worldwide.Consequently, is important to know its chemical composition. On the other hand, the use of near-infrared technologies is increasing in the last years as it is a fast and easy technique.Nevertheless, studies about its use in yogurts are limited. 141 samples of yogurt were analysed by NIRS. The whole experiment was carried out at 20ºC. 75% of the samples were used for calibration set and the rest were used for validating this model. A NIR Luminar 5030 Miniature “Hand-held” with a spectral range of 1100-2300 nm was used to obtain the spectra, with a sampling interval of 2 nm. The software used for analysis was The Unscrambler. The predictive models were established by using partial least squares (PLS). The information that is used to predict the composition and quantities of the samples is contained into the spectral curves. The pivotal step for spectroscopy technique is to extract quantitative data from them. In this study, PLS algorithm was used to achieve this purpose. 87 samples were chosen as a calibration sample cluster, and PLS mathematic model was built by using NIR-spectroscopy and fat content of each sample (Fig.1). The correlation coefficient between spectral data and fat content of yogurt was 0.965, the standard error of calibration (SEC) was 0.587, and the standard error of prediction (SEP) was 0.642. The fat content of another 33 samples was predicted by a mathematical model (Fig.2). The correlation coefficient of linear regression between predicted and measured values shows a reasonable to excellent prediction performance of 0.929. In conclusion, the results indicated that NIRS could quantitatively analyze fat content of yogurt in a fast and non-destructive way

Difusión de la humedad y cinética del secado de judías: comparación de la validez del modelo de difusión líquida, incluyendo y excluyendo la pérdida de volumen

El objetivo de este trabajo fue ajustar el modelo de difusión líquida para predecir las pérdidas de volumen de grano en el secado de judía (Phaseolus vulgaris L.). Se recolectaron granos de judía con una humedad del 0,92 y se sometieron a un proceso de secado, bajo condiciones controladas, a diferentes temperaturas entre 25 y 55°C y humedades relativas entre 20 y 75%. El volumen de cada grano, considerado como una esfera, fue obtenido utilizando como diámetro el promedio de las tres diagonales principales durante el proceso del secado. Las pérdidas de volumen de grano se determinaron por la relación entre el contenido de agua inicial y final. A partir de los resultados obtenidos, se concluye que el modelo de difusión representa satisfactoriamente la cinética del secado de la judía, y que tiene en cuenta las pérdidas de volumen del grano. El coeficiente de difusión, con valores comprendidos entre 10,8 × 10(-10) y 67,0 × 10(-10) m(2) s(-1), aumenta con la temperatura. La variación del coeficiente de difusión con la temperatura puede ser descrita por la expresión de Arrhenius, con una energía de activación de 40,08 kJ mol(-1).The aim of this work was to compare the results of the liquid diffusion model with respect to bean (Phaseolus vulgaris L.) drying when taking into account or neglecting grain shrinkage. Bean grains were harvested with a moisture content of 0.92 kg water/kg dry matter and dried at air temperatures of 25-55 degrees C and relative humidities of 20-75%. The volume of each grain, understood as a sphere, was determined several times over the drying process, taking the diameter to be the mean length of the three orthogonal axes. Grain shrinkage was determined by examining the relationships between the volume associated with each moisture content and the initial volume. The results show that the liquid diffusion model describes the drying kinetics of beans satisfactorily, and that grain shrinkage can be ignored. The diffusion coefficient increases with air temperature, with values ranging between 10.8 x 10(-10) and 67.0 x 10(-10) m(2) s(-1). This is described by the Arrhenius equation, with an activation energy of 40.08 kJ mol(-1)

Hyperspectral imaging to assess the presence of powdery mildew (Erysiphe necator) in cv. Carignan Noir grapevine bunches

Powdery mildew is a worldwide major fungal disease for grapevine, which adversely affects both crop yield and produce quality. Disease identification is based on visible signs of a pathogen once the plant has already been infected; therefore, techniques that allow objective diagnosis of the disease are currently needed. In this study, the potential of hyperspectral imaging (HSI) technology to assess the presence of powdery mildew in grapevine bunches was evaluated. Thirty Carignan Noir grape bunches, 15 healthy and 15 infected, were analyzed using a lab-scale HSI system (900–1700 nm spectral range). Image processing was performed to extract spectral and spatial image features and then, classification models by means of Partial Least Squares Discriminant Analysis (PLS-DA) were carried out for healthy and infected pixels distinction within grape bunches. The best discrimination was achieved for the PLS-DA model with smoothing (SM), Standard Normal Variate (SNV) and mean centering (MC) pre-processing combination, reaching an accuracy of 85.33% in the cross-validation model and a satisfactory classification and spatial location of either healthy or infected pixels in the external validation. The obtained results suggested that HSI technology combined with chemometrics could be used for the detection of powdery mildew in black grapevine bunches.This research received funding from the Department of Economic Development of the Navarre Government (Project: DECIVID (Res.104E/2017)), by the Spanish Ministry of Economy and Competitiveness (Project TIN2016-77356-P) and by the research services of the Universidad Pública de Navarra. C.P.-R is a beneficiary of postgraduate scholarships funded by Universidad Pública de Navarra (FPI-UPNA-2017 (Res.654/2017))

Fatal tractor accidents in the agricultural sector in Spain during the past decade

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.The authors would like to thank the Public University of Navarra, plan for the promotion of research groups, for co-funding the publication costs

Determinación de precursores de acrilamida en patata por NIRS

Según la Autoridad Europea de Seguridad Alimentaria (EFSA), la presencia de acrilamida en los alimentos incrementa el riesgo de desarrollar determinados tipos de cáncer. Las patatas fritas son una de las principales fuentes de exposición a este contaminante, formado debido a los altos niveles de precursores (azúcares reductores y asparagina) en la patata y a las elevadas temperaturas aplicadas durante la fritura. El objetivo del trabajo es utilizar la tecnología NIRS como método rápido de muestreo y control de los niveles de azúcares reductores en las patatas destinadas para fritura. Se han analizado 494 muestras liofilizadas de patatas obtenidas tanto de diferentes variedades de patatas frescas, como de patatas prefritas congeladas. Se ha empleado como método analítico de referencia el descrito por el Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA) que emplea ácido dinitrosalicílico (DNS) pero utilizando un espectrofotómetro de placas (Synergy HT, BioTek Instruments, Inc., USA). Las medidas en el infrarrojo se han realizado con un espectrofotómetro NIR, Luminar 5030 de Brimrose. El análisis estadístico consiste en la realización de modelos de regresión por mínimos cuadrados parciales (PLSR). Se observó que los errores obtenidos en los modelos de predicción estaban alrededor de 15 mg/g y 22 mg/g, para azúcares reductores y totales (Glucosa, Fructosa y Sacarosa). La técnica se presenta como una herramienta útil para realizar el análisis rápido de muestras de patata liofilizada