Specifications table
| Subject area | Chemistry |
| More specific subject area | Food Chemistry and Technology |
| Type of data | Table (Microsoft Excel Worksheet) |
| How data was acquired | HS-SPME/GC-qMS: Autosampler for HS-SPME (SPME COMBI PAL System, CTC Analytics AG, Zwingen, Switzerland) – Gas chromatography (GC-2010, Shimadzu Corporation, Kyoto, Japan) coupled with quadrupole mass spectrometer (QP-2010 Plus, Shimadzu Corporation, Kyoto, Japan) E-nose: Portable electronic nose system PEN3 (Airsense Analytics GmbH., Schwerin, Germany) |
| Data format | Raw, analyzed and formatted |
| Experimental factors | Roasting of cocoa beans to obtain the cocoa bean shell (CBS); physical separation of CBSs; grinding of CBSs into a powder with a 250 μm mesh size |
| Experimental features | Semi-quantification (μg 5-nonanol Eq. kg−1 of CBS) of the identified volatile compounds in CBS powders from different geographical origins and cultivars. E-nose sensor responses for CBS powders from different geographical origins and cultivars. |
| Data source location | GC-qMS and E-nose datasets were obtained at Food Technology Laboratory at the Department of Agriculture, Forestry and Food Sciences (DISAFA), University of Turin, Grugliasco, Italy Cocoa beans samples from American countries: Brazil, Colombia, Dominican Republic, Ecuador, Jamaica, Mexico, Peru, Venezuela. Cocoa beans samples from African countries: Cameroon, Congo, Ghana, Ivory Coast, Madagascar, São Tomé, Sierra Leone, Tanzania, Togo, Uganda. The cocoa bean samples were kindly supplied by Silvio Bessone S.r.l., ICAM S.p.A., Ferrero International S.A., Guido Gobino S.r.l., Pastiglie Leone S.r.l., and Venchi S.p.A. |
| Data accessibility | Data are presented in this article and in a Microsoft Excel Worksheet, which is available as supplementary data. |
| Related research article | Barbosa-Pereira, L., Rojo-Poveda, O., Ferrocino, I., Giordano, M., & Zeppa, G. (2019). Assessment of volatile fingerprint by HS-SPME/GC-qMS and E-nose for the classification of cocoa bean shells using chemometrics. Food Research International, 123, 684–696. https://doi.org/10.1016/j.foodres.2019.05.041 |