International standards for Olive Oil (OO) analysis face challenges, especially with the rampant adulteration of Extra Virgin Olive Oil (EVOO). As demands grow for innovative methods beyond conventional techniques, VIS + NIRS spectroscopy emerges prominently. This study postulates enhanced efficacy through integrating VIS + NIRS with Fluorescence spectroscopy. Addressing challenges like instrument optimization and data security is paramount. Our research evaluates a hand-held multi-mode spectroscopy system combining fluorescence and reflectance. Employing three prototypes, we analyzed EVOO, VOO, and LOO categories. Results, compared against a benchtop instrument, provide insights into tackling EVOO adulteration through advanced spectral sensing.
The European Commission has stablished standards to be applied to all the olive oils subject to international trade. The standards include what is called conformity checks to know the physico-chemical and organoleptic properties, for labelling and category requirements (Delegated Regulation (EU) 2022/2104). However, most of those methods are inaccessible to most producers and retailers. Furthermore, the high cost and time required to obtain the data means that the number of samples inspected per year is very low in relation to the total volume of olive oils produced. There is therefore a growing and urgent demand for novel, fast and low-cost analytical methods to guarantee the authenticity and integrity of olive oils. The present work will provide scientific evidence of the potential of a handheld Linear Variable Filters (LVF) NIRS instrument for the on-site quality control of olive oils.
This work tries to demonstrate the potential of Near Infrared Spectroscopy combined with class-modelling and discriminant methods, for improvement of EVOO authentication. To cover that goal, 209 olive oil samples from the three mentioned categories (68 EVOO, 93 VOO and 48 LOO) were analyzed in a FT-NIR instrument coupled to an in-line fiber optic probe. The best models developed allow to classify correctly 82% of samples as EVOO and 84.93% as VOO. These results show that NIRS technology can be a great instrumental method to replace/complement the Panel Test.
Software tools for chemometric analysis of NIRS data have existed since the first NIRS instruments appeared on the market in the late 1970s. Generally, these software appear attached to a certain instrumentation. Recently, some works have started to use open-source software, such as R and Python, but the development status is still in its infancy, particularly in the case of the latter. This work tries to generate information on the potential of the open-source Python software for the implementation of multivariate algorithms and signal pre-treatment methods for the quantitative and qualitative NIRS analysis of olive oils.
The uptake by the industry of the existing knowledge about the online NIR analysis is being much slower, compared to the acceptance of the at-line analysis. The Research Group of the authors since 2001 has been in close collaboration with the largest Spanish rendering plant to evalate the ability of different for the quality control of animal protein processed by-products. Since 2017, and after several years of research, the company decided to invest in a on-line project. The work done until, for moving from at line to on line analysis in the rendering plant will be summarised in the Conference.
Feeding dairy cows with Total Mixed Rations (TMR) is a cost-effective way to obtain high milk yield. Animal nutritionists are demanding accurate information on the main chemical constituents of TMR to properly feed lactating cows. The use of portable NIRS devices could provide an affordable answer. This work analysed a total of 121 TMR using two portable NIRS instruments for the prediction of dry matter, crude protein and neutral detergent fibre. The paper evaluated whether there were significant differences between the predictive capacities of the models developed from analytical data expressed “ as dry matter” or “ as is basis”.
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