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      Determining degree of roasting in cocoa beans by artificial neural network (ANN)-based electronic nose system and gas chromatography/mass spectrometry (GC/MS).

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          Abstract

          Roasting is a critical step in chocolate processing, where moisture content is decreased and unique flavors and texture are developed. The determination of the degree of roasting in cocoa beans is important to ensure the quality of chocolate. Determining the degree of roasting relies on human specialists or sophisticated chemical analyses that are inaccessible to small manufacturers and farmers. In this study, an electronic nose system was constructed consisting of an array of gas sensors and used to detect volatiles emanating from cocoa beans roasted for 0, 20, 30 and 40 min. The several signals were used to train a three-layer artificial neural network (ANN). Headspace samples were also analyzed by gas chromatography/mass spectrometry (GC/MS), with 23 select volatiles used to train a separate ANN.

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          Author and article information

          Journal
          J. Sci. Food Agric.
          Journal of the science of food and agriculture
          Wiley
          1097-0010
          0022-5142
          Jan 24 2018
          Affiliations
          [1 ] Department of Food Science and Technology, University of Georgia, Athens, GA, USA.
          Article
          10.1002/jsfa.8901
          29363771
          7cdd569c-534b-433c-bea8-382a1eeac370
          History

          roasting,neural network,electronic nose,cocoa beans
          roasting, neural network, electronic nose, cocoa beans

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