39 research outputs found
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
Aplicación de tecnología NIR portátil a la estimación el parcela de la concentración de azúcares en uva
During the 2008 growing season field tests have been carried out on three varieties of wine grape. Over 2500 samples of wine grape berries were scanned with a portable and commercial near infrared (NIR) spectrometer and subsequently processed to determine °Brix using a digital refractometer. The main objectives of this research are to evalúate the potential of a portable NIR equipment to measure the changes in soluble solid contents of grapes during the pre-harvest period, and to establish calibration model for soluble solid contení (°Brix) in grapes, in order to provide a non destructive tool for determining optimal harvest date. A first calibration model has been constructed based on data of three varieties with a R2 of 0.81
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