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As for texture, the dried samples were softer and less cohesive as compared to the fresh ones. Mass diffusivity increased with temperature, from 4.4\u00d710\n                    <jats:sup>\u221210<\/jats:sup>\n                    m\n                    <jats:sup>2<\/jats:sup>\n                    \/s at 30\u00b0C to 1.4\u00d710\n                    <jats:sup>\u22129<\/jats:sup>\n                    m\n                    <jats:sup>2<\/jats:sup>\n                    \/s at 60\u00b0C, and so did the mass transfer coefficient, increasing from 3.7\u00d710\n                    <jats:sup>\u221210<\/jats:sup>\n                    m\/s at 30\u00b0C to 7.4\u00d710\n                    <jats:sup>\u22129<\/jats:sup>\n                    m\/s at 60\u00b0C. As to the activation energy, it was found to be 34 kJ\/mol. Neural network modelling showed that all properties can be correctly predicted by feed-forward neural networks. The analysis of the networks\u2019 behaviours input layer weight values also shows which properties are more affected by dehydration or more dependent on variety.\n                  <\/jats:p>","DOI":"10.1515\/ijfe-2012-0135","type":"journal-article","created":{"date-parts":[[2014,5,27]],"date-time":"2014-05-27T08:06:20Z","timestamp":1401177980000},"page":"281-299","source":"Crossref","is-referenced-by-count":24,"title":["Convective Drying of Apples: Kinetic Study, Evaluation of Mass Transfer Properties and Data Analysis using Artificial Neural Networks"],"prefix":"10.1515","volume":"10","author":[{"given":"Raquel P. 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