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Assessing statistical neural networks potentiality to distinguish PDO Kalamata and Molaoi olive oil varieties
1 Department of Food Science and Technology, University of Peloponnese, 24100, Kalamata, Greece.
2 Department of Business Administration, University of West Attica, 12241, Athens, Greece.
Research Article
International Journal of Science and Research Archive, 2024, 13(01), 2939–2949.
Article DOI: 10.30574/ijsra.2024.13.1.1997
Publication history:
Received on 08 September 2024; revised on 19 October 2024; accepted on 21 October 2024
Abstract:
Several regional areas in Greece produce high quality olive oil by cultivating certain varieties. Olive oil varieties of Kalamata and Molaoi are of special interest, since they produce extra virgin olive oil. Concretely, Kalamata is a city located in southwestern Greece. Intuitively, Molaoi is a town located in southeastern Greece. Subsequently, both geographic locations are known for their famous olive oil quality. Continually, Protected Designation of Origin (PDO) Kalamata olive oil, established by Council regulation (EC) No 510/2006, is considered an exceptional extra virgin olive oil variety. Specifically, there is a need to distinguish PDO Kalamata olive oil from other olive oil varieties is Greece such as the Molaoi olive oil, since PDO Kalamata olive oil is the main variety exported in the global olive oil market. Distinguishing PDO Kalamata from Molaoi olive oil is possible by incorporating statistical neural networks. Concretely, applying neural network experimentation enables differentiation between variations of certain chemical characteristics observed in certain geographic locations of Greece. In this paper, we use statistical neural networks to distinguish the geographical origin of PDO Kalamata olive oil compared with Molaoi olive oil based on synchronous excitation−emission fluorescence spectroscopy of provided olive oils samples evaluated in the chemical laboratory. Evaluation based on certain experimentation phase and subsequent data visualization of the adopted statistical neural networks are promising for distinguishing the samples of PDO Kalamata olive oil with high values of prediction accuracy. Such ability enables olive oil industry to assess extra virgin olive oil profitable potentiality in global market.
Keywords:
PDO Kalamata olive oil; Molaoi olive oil; Synchronous emission-excitation; Fluorescence spectroscopy; Statistical neural networks; Data visualization
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