This work provides a software based on the combination of a artificial neural network (ANN) approach and a numerical method (called "refining algorithm") for the estimation of the acidity level and of peroxides number of olive oil extracted by a continuous extraction process. The estimation is achieved through the measurement of some agronomical and technological parameters commonly measured by the technicians working at the oil mills. The ANN based approach is able to perform a rough prediction of the two parameters; this prediction is then refined by means of the numerical approach. The devised software, The mean error in estimation of the parameters with the combination of the ANN approach and the refining algorithm, in comparison with the standard chemical analysis, is in the range 6-8% for an oil extraction with a three phases decanting system and about 6-7% for an oil extraction with a two phases decanting system. The maximum error affecting the method (ANN + Refining) described in this work is about 15% for the first case and about 11% for the second one. The system developed in the present work is actually running on the oil mill "TEM Toscana Enologica Mori" of Florence, Italy.The present work has been financed by the Tuscany Regional Agricultural Development and Innovation Office (ARSIA: Azienda Regionale per lo Sviluppo e l'Innovazione dell'Agricoltura) and is a part of a 3-year project whose objective is to create an entirely software + hardware controlled oil mill.
In the present work is described a feasibility assessment for a new approach in virgin olive oil production control system. A predicting or simulating algorithm is implemented as artificial neural network based software, using literature found data concerning parameters related to olive grove, process, machine. Test and validation proved this tool is able to answer two different frequently asked questions by olive oil mill operators, using few agronomic and technological parameters with time and cost saving: – which quality level is up to oil extracted from defined olive lot following a defined process (predicting mode); – which process and machine parameters set would determine highest quality level for oil extracted from a defined olive lot (simulating mode)
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