Exploration of Spanish Olive Oil Quality with a Miniaturized Low-Cost Fluorescence Sensor and Machine Learning Techniques
Extra virgin olive oil (EVOO) is the highest quality of olive oil and is characterized by highly beneficial nutritional properties. The large increase in both consumption and fraud, for example through adulteration, creates new challenges and an increasing demand for developing new quality assessment methodologies that are easier and cheaper to perform. As of today, the determination of olive oil quality is performed by producers through chemical analysis and organoleptic evaluation. The chemical analysis requires the advanced equipment and chemical knowledge of certified laboratories, and has therefore a limited accessibility. In this work a minimalist, portable and low-cost sensor is presented, which can perform olive oil quality assessment using fluorescence spectroscopy. The potential of the proposed technology is explored by analyzing several olive oils of different quality levels, EVOO, virgin olive oil (VOO), and lampante olive oil (LOO). The spectral data were analyzed using a large number of machine learning methods, including artificial neural networks. The analysis performed in this work demonstrates the possibility of performing classification of olive oil in the three mentioned classes with an accuracy of 100$\%$. These results confirm that this minimalist low-cost sensor has the potential of substituting expensive and complex chemical analysis.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Physico-chemical properties extraction from the fluorescence spectrum with 1D-convolutional neural networks: application to olive oil
The olive oil sector produces a substantial impact in the Mediterranean's economy and lifestyle. Many studies exist which try to optimize the different steps in the olive oil's production process. One of the main challen…
Dataset of Fluorescence Spectra and Chemical Parameters of Olive Oils
This dataset encompasses fluorescence spectra and chemical parameters of 24 olive oil samples from the 2019-2020 harvest provided by the producer Conde de Benalua, Granada, Spain. The oils are characterized by different …
On the Statistical Efficiency of Reward-Free Exploration in Non-Linear RL
We study reward-free reinforcement learning (RL) under general non-linear function approximation, and establish sample efficiency and hardness results under various standard structural assumptions. On the positive side, …
Reinforcement Learning (RL)$\sqrt{n}$-Regret for Learning in Markov Decision Processes with Function Approximation and Low Bellman Rank
In this paper, we consider the problem of online learning of Markov decision processes (MDPs) with very large state spaces. Under the assumptions of realizable function approximation and low Bellman ranks, we develop an …
Efficient ExplorationReinforcement LearningCollaborative real-time vision-based device for olive oil production monitoring
This paper proposes an innovative approach to improving quality control of olive oil manufacturing and preventing damage to the machinery caused by foreign objects. We developed a computer-vision-based system that monito…