Use of physicochemical parameters and neural networksin identification of bee honey (Apis mellifera L.) produced in the summer and winter in the microregion of Campos do Jordão, São Paulo
| Autor: | Juliana do Nascimento Bendini, Ricardo de Oliveira Orsi, Hugo do Nascimento Bendini, Silvia Helena Modenese Gorla da Silva |
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| Jazyk: | English<br />Spanish; Castilian<br />Portuguese |
| Rok vydání: | 2010 |
| Předmět: | |
| Zdroj: | Boletim de Indústria Animal, Vol 67, Iss 2, Pp 143-149 (2010) |
| Druh dokumentu: | article |
| ISSN: | 0067-9615 1981-4100 |
| Popis: | The objective of this work was to typify, through physicochemical parameters, honey from Campos do Jordão’s microrregion, and verify how samples are grouped in accordance with the climatic production seasonality (summer and winter). It were assessed 30 samples of honey from beekeepers located in the cities of Monteiro Lobato, Campos do Jordão, Santo Antonio do Pinhal e São Bento do Sapucaí-SP, regarding both periods of honey production (November to February; July to September, during 2007 and 2008; n = 30). Samples were submitted to physicochemical analysis of total acidity, pH, humidity, water activity, density, aminoacids, ashes, color and electrical conductivity, identifying physicochemical standards of honey samples from both periods of production. Next, we carried out a cluster analysis of data using k-means algorithm, which grouped the samples into two classes (summer and winter). Thus, there was a supervised training of an Artificial Neural Network (ANN) using backpropagation algorithm. According to the analysis, the knowledge gained through the ANN classified the samples with 80% accuracy. It was observed that the ANNs have proved an effective tool to group samples of honey of the region of Campos do Jordao according to their physicochemical characteristics, depending on the different production periods. |
| Databáze: | Directory of Open Access Journals |
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