Short Communication: The potential of portable near infrared spectroscopy for assuring quality and authenticity in the food chain, using Iberian hams as an example

This communication assesses the use of a portable near infrared (NIR) instrument to measure quantitative (fatty acid profile) properties and qualitative (‘Premium’ and ‘Non-premium’) categories of individual Iberian pork carcasses at the slaughterhouse. Acorn-fed Iberian pigs have more unsaturated fats than pigs fed conventional compound feed. Recent advances in miniaturisation have led to a number of handheld NIR devices being developed, allowing processing decisions to be made earlier, significantly reducing time and costs. The most common methods used for assessing quality and authenticity of Iberian hams are analysis of the fatty acid composition of subcutaneous fat using gas chromatography and DNA analysis. In this study, NIR calibrations for fatty acids and classification as premium or non-premium ham, based on carcass fat measured in situ, were developed using a portable NIR spectrometer. The accuracy of the quantitative equations was evaluated through the standard error of cross validation or standard error of prediction of 0.84 for palmitic acid (C16:0), 0.94 for stearic acid (C18:0), 1.47 for oleic acid (C18:1) and 0.58 for linoleic acid (C18:2). Qualitative calibrations provided acceptable results, with up to 98% of samples (n = 234) correctly classified with probabilities ⩾0.9. Results indicated a portable NIR instrument has the potential to be used to measure quality and authenticity of Iberian pork carcasses

Armonización del análisis NIRS de grasa de cerdo ibérico: transferencia de calibraciones de ácidos grasos

El objetivo del presente trabajo es mostrar la posibilidad de transferir ecuaciones de calibración para la determinación de ácidos grasos en grasa de cerdo Ibérico en diferentes instrumentos NIRS, empleando para ello cápsulas no selladas

Multistage and adaptive sampling protocols combined with near-infrared spectral sensors for automated monitoring of raw materials in bulk

A near-infrared (NIR) spectroscopy-based real-time monitoring system is proposed to sample and analyse agro-industrial raw materials transported in bulk in a single stage, easing and optimising the evaluation process of incoming lots at reception of agri-food plants. NIR analysis allows rapid and cost-effective analytical results to be obtained, and hence to rethink current sampling protocols. For this purpose, multistage and adaptive sampling designs were tested in this paper, which have been reported (in soil science and ecology) to be more flexible and efficient than conventional strategies to study patterns of clustering or patchiness, which can be the result of natural phenomena. The additional spatial information provided by NIR has also been exploited, using geostatistical analysis to model the spatial pattern of key analytical constituents in Processed Animal Proteins (PAPs). This study addresses the assessment of two kinds of quality/safety issues in PAP lots – moisture accumulation and cross-contamination. After a simulation study, qualitative and quantitative analyses were carried out to make a performance comparison between sampling designs. Results show that sampling densities below 10–15% demonstrated higher estimation errors, failing to represent the actual spatial patterns, while a stratified adaptive cluster sampling design achieved the best performance

Performance comparison of sampling designs for quality and safety control of raw materials in bulk: a simulation study based on NIR spectral data and geostatistical analysis

This study exploits the potential of near infrared (NIR) spectroscopy to deliver a measurement for each sampling point. Furthermore, it provides a protocol for the modelling of the spatial pattern of analytical constituents. On the basis of these two aspects, the methodology proposed in this work offers an opportunity to provide a real-time monitoring system to evaluate raw materials, easing and optimising the existing procedures for sampling and analysing products transported in bulk. In this paper, Processed Animal Proteins (PAPs) were selected as case study, and two types of quality/safety issues were tested in PAP lots —induced by moisture and cross-contamination. A simulation study, based on geostatistical analysis and the use of a set of sampling protocols, made a qualitative analysis possible to compare the representation of the spatial surfaces produced by each design. Moreover, the Root Mean Square Error of Prediction (RMSEP), calculated from the differences between the analytical values and the geostatistical predictions at unsampled locations, was used to measure the performance in each case. Results show the high sensitivity of the process to the sampling plan used — understood as the sampling design plus the sampling intensity. In general, a gradual decrease in the performance can be observed as the sampling intensity decreases, so that unlike for higher intensities, the too low ones resulted in oversmoothed surfaces which did not manage to represent the actual distribution. Overall, Stratified and Simple Random samplings achieved the best results in most cases. This indicated that an optimal balance between the design and the intensity of the sampling plan is imperative to perform this methodology

Control individualizado de cerdos ibéricos "in vivo" en campo y sobre la canal en matadero mediante tecnología NIRS

El objetivo de este trabajo es la puesta a punto y optimización de la tecnología NIRS para el control del cerdo Ibérico tanto en campo sobre el animal vivo, ya que es una técnica completamente inocua para el animal, como sobre la canal en el matadero, lo cual permitirá consolidar un sistema de trazabilidad basado en sensores no destructivos y rápidos

Miniature near infrared spectroscopy spectrometer and information and communication technologies to guarantee the integrity of the EU high added-value "acorn Iberian pig ham" (IP)

This research is framed within FoodIntegrity, EU sponsored project(7th FP). The main goal of the research to be done is to provide industrials, producers and consumers with a methodology based in low-cost, portable and miniature NIRS sensors and information and communication technologies for process control and voluntary labelling, to guarantee the integrity of the EU high added-value as the “acorn Iberian pig ham”. The present study is focussed in transferring a database (470 samples) of IP tissue - analysed in a FOSS-NIRSystems 6500 (FNS6500) spectrometer, during the seasons 2009-2011 - to a portable/miniature instrument MicroNIR-Onsite, VIAVI (MN1700). A set of 30 samples of adipose tissue was taken from a slaughterhouse during 2015-2016, being analysed in parallel in the satellite (FNS 6500) and master (MN 1700) instruments. Latter on, they were divided in two sets: N = 10 for building the standardization matrices and N = 20 for the validation of the cloning procedure. The algorithm Piece-Wise Direct Standardization (PDS) was applied. The best standardisation matrix was applied to the library of 470 samples taken in the FNS 6500, enabling an excellent fitting between both instruments, as shown the RMSCs statistic calculated in the satellite before and after the standardization and in the master - 108457 vs 22519 vs 17646 μlog 1/R – and the GH distance before and after standardisation between both instruments 437.41 vs 2.06

Hyperspectral Imaging for the Detection of Bitter Almonds in Sweet Almond Batches

A common fraud in the sweet almond industry is the presence of bitter almonds in commercial batches. The presence of bitter almonds not only causes unpleasant flavours but also problems in the commercialisation and toxicity for consumers. Hyperspectral Imaging (HSI) has been proved to be suitable for the rapid and non-destructive quality evaluation in foods as it integrates the spectral and spatial dimensions. Thus, we aimed to study the feasibility of using an HSI system to identify single bitter almond kernels in commercial sweet almond batches. For this purpose, sweet and bitter almond batches, as well as different mixtures, were analysed in bulk using an HSI system which works in the spectral range 946.6–1648.0 nm. Qualitative models were developed using Partial Least Squares-Discriminant Analysis (PLS-DA) to differentiate between sweet and bitter almonds, obtaining a classification success of over the 99%. Furthermore, data reduction, as a function of the most relevant wavelengths (VIP scores), was applied to evaluate its performance. Then, the pixel-by-pixel validation of the mixtures was carried out, identifying correctly between 61–85% of the adulterations, depending on the group of mixtures and the cultivar analysed. The results confirm that HSI, without VIP scores data reduction, can be considered a promising approach for classifying the bitterness of almonds analysed in bulk, enabling identifying individual bitter almonds inside sweet almond batches. However, a more complex mathematical analysis is necessary before its implementation in the processing lines

Cowgotchi: un juego serio para la mejora de la motivación y el aprendizaje en alimentación animal

[ES] El Grupo Docente 44 de la Universidad de Córdoba tiene una amplia experiencia en la incorporación de herramientas innovadoras en la docencia de distintas asignaturas relacionadas con el área de la Producción Animal. En este trabajo se describe la implementación de una nueva herramienta: la gamificación aplicada a los ejercicios de racionamiento animal. El objetivo esta nueva herramienta es la mejora de la motivación y el aprendizaje de los estudiantes de la asignatura “Ingeniería y Tecnología de la Producción Animal”. Se ha desarrollado un juego serio en forma de aplicación Android inspirado en el Tamagotchi® de Bandai, juego muy popular en los años 2000 que se basaba en cuidar y alimentar una mascota virtual para mantenerla viva y obtener diversas bonificaciones. En este caso se trata de calcular raciones adecuadas que permitan mantener viva una vaca lechera, cuidar su salud y maximizar la producción de leche minimizando el coste de la alimentación. Se describe el funcionamiento del juego y los siguientes pasos para mejorar el carácter de juego serio de la aplicación móvil desarrollada.[EN] The Teaching Group no. 44 of the University of Cordoba has extensive experience in incorporating innovative tools in teaching different subjects related to the area of Animal Production. This work describes the implementation of a new tool: gamification applied to animal rationing exercises. The objective of this new tool is to improve the motivation and learning of the students of the subject "Engineering and Technology for Animal Production". A serious game has been developed, in the form of an Android app, inspired by Bandai's Tamagotchi®, a very popular game in the 2000s that was based on caring for and feeding a virtual pet to keep it alive and get different bonuses. In this case, the game is about the calculation of adequate rations to keep a dairy cow alive, take care of its health and maximize milk production while minimizing the cost of feeding. Current game functioning and the planned steps to improve the its characteristics of serious game are described.Maroto Molina, F.; Adame Siles, JA.; Riccioli, C.; Garrido Varo, A.; Pérez Marín, DC. (2021). Cowgotchi: un juego serio para la mejora de la motivación y el aprendizaje en alimentación animal. En IN-RED 2020: VI Congreso de Innovación Educativa y Docencia en Red. Editorial Universitat Politècnica de València. 740-748. https://doi.org/10.4995/INRED2020.2020.12019OCS74074

Near-infrared spectroscopy and geostatistical analysis for modeling spatial distribution of analytical constituents in bulk animal by-product protein meals

Control and inspection operations within the context of safety and quality assessment of bulk foods and feeds are not only of particular importance, they are also demanding challenges, given the complexity of food/feed production systems and the variability of product properties. Existing methodologies have a variety of limitations, such as high costs of implementation per sample or shortcomings in early detection of potential threats for human/animal health or quality deviations. Therefore, new proposals are required for the analysis of raw materials in situ in a more efficient and cost-effective manner. For this purpose, a pilot laboratory study was performed on a set of bulk lots of animal by-product protein meals to introduce and test an approach based on near-infrared (NIR) spectroscopy and geostatistical analysis. Spectral data, provided by a fiber optic probe connected to a Fourier transform (FT) NIR spectrometer, were used to predict moisture and crude protein content at each sampling point. Variographic analysis was carried out for spatial structure characterization, while ordinary Kriging achieved continuous maps for those parameters. The results indicated that the methodology could be a first approximation to an approach that, properly complemented with the Theory of Sampling and supported by experimental validation in real-life conditions, would enhance efficiency and the decision-making process regarding safety and adulteration issues