Avances en la utilización de la tecnología NIRS: aplicaciones en producción animal

La Espectroscopía en el Infrarrojo Cercano se ha consolidado como una verdadera disciplina científica y en la última década ha mostrado su inmenso valor para la industria de la alimentación animal. En el futuro podremos comprobar su contribución científica al entendimiento de los procesos que regulan la utilización del alimento por el animal

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

Fraud Detection in Batches of Sweet Almonds by Portable Near-Infrared Spectral Devices

One of the key challenges for the almond industry is how to detect the presence of bitter almonds in commercial batches of sweet almonds. The main aim of this research is to assess the potential of near-infrared spectroscopy (NIRS) by means of using portable instruments in the industry to detect batches of sweet almonds which have been adulterated with bitter almonds. To achieve this, sweet almonds and non-sweet almonds (bitter almonds and mixtures of sweet almonds with different percentages (from 5% to 20%) of bitter almonds) were analysed using a new generation of portable spectrophotometers. Three strategies (only bitter almonds, bitter almonds and mixtures, and only mixtures) were used to optimise the construction of the non-sweet almond training set. Models developed using partial least squares-discriminant analysis (PLS-DA) correctly classified 86–100% of samples, depending on the instrument used and the strategy followed for constructing the non-sweet almond training set. These results confirm that NIR spectroscopy provides a reliable, accurate method for detecting the presence of bitter almonds in batches of sweet almonds, with up to 5% adulteration levels (lower levels should be tested in future studies), and that this technology can be readily used at the main steps of the production chain

Online NIRS analysis for the routine assessment of the nitrate content in spinach plants in the processing industry using linear and non-linear methods

This study aimed to assess the robustness of the NIRS models developed following different strategies for the routine prediction of nitrate content in spinach plants using an online FT-NIR spectrophotometer. To achieve this, 516 spinach plants from different cultivars, harvest dates, orchards and seasons, were used. Two strategies were followed to make up the calibration and validation sets; the first included in the calibration set those samples belonging to the 2018 and 2019 harvesting seasons, while the second also included in this set part of the population of the 2020 harvesting season. Modified partial least squares quantitative models were initially developed and externally validated. In view of the results and to obtain significant improvements, a non-linear regression technique (the LOCAL algorithm) was applied. The models developed using the non-linear regression technique and considering the greatest possible variability in the training set (samples belonging to 2018, 2019 and 2020 harvesting seasons) reported the best prediction results (R2p = 0.60; SEP = 758 mg/kg), which enabled to classify the product in the main categories or classes established by the official regulations, according to its commercial destination

A Low-Cost IoT-Based System to Monitor the Location of a Whole Herd

Animal location technologies have evolved considerably in the last 60 years. Nowadays, animal tracking solutions based on global positioning systems (GPS) are commercially available. However, existing devices have several constraints, mostly related to wireless data transmission and financial cost, which make impractical the monitorization of all the animals in a herd. The main objective of this work is to develop a low-cost solution to enable the monitorization of a whole herd. An IoT-based system, which requires some animals of the herd being fitted with GPS collars connected to a Sigfox network and the rest with low-cost Bluetooth tags, has been developed. Its performance has been tested in two commercial farms, raising sheep and beef cattle, through the monitorization of 50 females in each case. Several collar/tag ratios, which define the cost per animal of the solution, have been simulated. Results demonstrate that a low collar/tag ratio enable the monitorization of a whole sheep herd. A larger ratio is needed for beef cows because of their grazing behavior. Nevertheless, the optimal ratio depends on the purpose of location data. Large variability has been observed for the number of hourly and daily messages from collars and tags. The system effectiveness for the monitorization of all the animals in a herd has been certainly proved

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

The case method as a tool for teaching and learning Livestock Farming Systems Engineering

Este artículo describe una experiencia en el uso de la herramienta docente conocida como Método del Caso en el Máster de Ingeniería Agronómica de la Universidad de Córdoba. Los estudiantes de la asignatura “Sistemas de Producción Animal: Análisis de Casos” se han enfrentado a un problema real consistente en la necesidad de soluciones de reingeniería para varias instalaciones de un cebadero de terneros. La resolución del caso requirió, por parte de los estudiantes, de la recopilación e integración de diversos conocimientos y habilidades adquiridos en sus estudios de Grado, así como de un ejercicio de pensamiento crítico e ingenio. Los resultados obtenidos fueron positivos en cuanto al fomento del trabajo colaborativo, del espíritu crítico y de la participación activa del alumnado en las actividades de la asignatura, aunque la implementación práctica de la metodología docente presentó algunas dificultades. Concluimos que el Método del Caso es adecuado para estudios de Máster y se debería fomentar su uso en otras asignaturas del título.This paper describes an experience in the use of the teaching and learning tool known as Case Method in a Master Program in Agricultural Engineering of the University of Cordoba. The students of the course “Livestock Farming Systems: Case Studies” have been faced to a real problem consisting of the need of reengineering solutions for several facilities of a beef feedlot. The resolution of the case required from students the compilation and integration of some knowledge and skills acquired in their Undergraduate studies, as well as an effort of critical thinking and ingenuity. The results of the experience were positive in terms of promoting collaborative work, critical thinking and an active participation of the students in course activities, but some difficulties arose in the practical implementation of this teaching and learning methodology. We conclude that the Case Method is an excellent tool for Master studies and its use should be encouraged in other courses of the Master Program in Agricultural Engineering

Fast, Low-Cost and Non-Destructive Physico-Chemical Analysis of Virgin Olive Oils Using Near-Infrared Reflectance Spectroscopy

Near-Infrared (NIR) Spectroscopy was used for the non-destructive assessment of physico-chemical quality parameters in olive oil. At the same time, the influence of the sample presentation mode (spinning versus static cup) was evaluated using two spectrophotometers with similar optical characteristics. A total of 478 olive oil samples were used to develop calibration models, testing various spectral signal pre-treatments. The models obtained by applying MPLS regression to spectroscopic data yielded promising results for olive oil quality measurements, particularly for acidity, the peroxide index and alkyl and ethyl ester content. The results obtained indicate that this non-invasive technology can be used successfully by the olive oil sector to categorize olive oils, to detect potential fraud and to provide consumers with more reliable information. Although both sample presentation modes yielded comparable results, equations constructed with samples scanned using the spinning mode provided greater predictive capacity

Project-based learning as a tool for training on precision livestock farming

Este artículo describe una experiencia en el uso de la metodología docente del aprendizaje basado en proyectos en varias asignaturas de Grado y Máster de la Escuela Técnica Superior de Ingeniería Agronómica y de Montes. Se ha seleccionado el tema de la ganadería de precisión para el desarrollo de los proyectos, en concreto el uso de acelerómetros para la monitorización del movimiento de los animales. Los estudiantes, en grupos de ocho a diez miembros, han diseñado y aplicado un proyecto relativo a las utilidades reales de los datos registrados por collares para vacas que incorporan sensores de posicionamiento y aceleración. Esta metodología ha mejorado la motivación de los estudiantes y algunas de sus habilidades. No obstante, se han encontrado algunos problemas relacionados con la gestión de los grupos de trabajo y con las características de los datos registrados por los collares.This paper describes an experience in the use of the teaching methodology of project-based learning in several undergraduate and postgraduate courses of the Escuela Técnica Superior de Ingeniería Agronómica y de Montes. Precision Livestock Farming was chosen as the main topic of the projects, specifically the use of accelerometers to monitor animal activity. The students, working in groups of eight to ten members, have designed and applied a project relating real-world utilities for data recorded by GPS + accelerometer cow collars. This methodology has improved motivation and some of students’ skills. Nevertheless, some problems have arisen regarding the management of working groups and the characteristics of data recorded by cow collars