Analytical Methods Fast and neat – Determination of biochemical quality parameters in cocoa using near infrared spectroscopy Andrea Krähmer a,⇑ , Annika Engel a,b , Daniel Kadow c , Naailah Ali d , Pathmanathan Umaharan d , Lothar W. Kroh b , Hartwig Schulz a a Julius Kühn-Institut, Federal Research Centre for Cultivated Plants, Institute for Ecological Chemistry, Plant Analysis and Stored Product Protection, Königin-Luise-Straße 19, 14195 Berlin, Germany b Institute of Food Technology and Food Chemistry, Berlin University of Technology, Gustav-Meyer-Allee 25, 13355 Berlin, Germany c University of Hamburg, Biocenter Klein Flottbek and Botanical Garden, Crop Science and Applied Ecology, Ohnhorststr. 18, 22609 Hamburg, Germany d Cocoa Research Centre, The University of the West Indies, St. Augustine, Trinidad and Tobago article info Article history: Received 27 November 2014 Received in revised form 26 January 2015 Accepted 17 February 2015 Available online 24 February 2015 Chemical compounds studied in this article: Acetic acid (PubChem CID: 176) Lactic acid (PubChem CID: 612) Epicatechin (PubChem CID: 72276) Caffeine (PubChem CID: 2519) Theobromine (PubChem CID: 5429) Keywords: Cocoa NIR spectroscopy Quantification Quality control PLS prediction abstract The qualitative heterogeneity and increasing consumption of cocoa products require fast and efficient methods for quality assessment of fermented cocoa with regard to fermentation quality and flavor poten- tial. To date, quality control is achieved by visual inspection (e.g., ‘‘cut test’’) and sensory testing. Chromato- graphic methods for quantification of flavor relevant substances are limited in their applicability in stan- dard quality control due to laborious isolation and purification steps. Therefore, the aim of this study was the development of a near infrared spectroscopic (NIRS) method for routine analytical prediction of biochemical quality parameters. Different compound classes like phe- nolic substances (R 2 = 0.93) or organic acids (R 2 = 0.88) as well as individual substances like epicatechin (R 2 = 0.93) or lactic acid (R 2 = 0.87) could be precisely determined just as fermentation time (R 2 = 0.92) and pH value (R 2 = 0.94) presenting NIRS as fast and reliable alternative in routine quality assessment. Ó 2015 Elsevier Ltd. All rights reserved. 1. Introduction With a total global production volume of more than 4 million tons per season (e.g., 4.05 M t 2011/2012) cocoa (Theobroma cacao L.) represents a major agricultural export commodity for several producing countries in West Africa (International Cocoa Organization (ICCO), 2013). It is the key raw material in chocolate manufacturing. Since cocoa deliveries are frequently characterized by a great heterogeneity with regard to their quality attributes, a reliable quality assessment is of great importance for both, produc- ers and purchasers (Rohsius, Elwers, & Lieberei 2010). A key quality attribute of cocoa is the flavor profile. The latter strongly depends on the post-harvest processing i.e., fermentation and drying that the fresh cocoa is subjected to in the countries of origin. Unfermented cocoa does not develop any chocolate flavor during chocolate manufacturing because it does not contain the precursors necessary. Moreover, it is characterized by an unpleas- ant bitterness and astringency. Fermentation results in chocolate flavor precursor formation as well as in the reduction of bitterness and astringency. These changes in the flavor profile go along with a change in color from pale purple (unfermented) to brown (fully fermented) (Kadow, Bohlmann, Phillips, & Lieberei, 2013). http://dx.doi.org/10.1016/j.foodchem.2015.02.084 0308-8146/Ó 2015 Elsevier Ltd. All rights reserved. Abbreviations: ffdm, fat free dry matter; NIR, near infrared; NIRS, near infrared spectroscopy; IR, infrared; HPLC, high performance liquid chromatography; GC, gas chromatography; PLS, partial least square algorithm; PCA, principle component analysis; WMSC, weighted multiple scatter correction; RMSECV, root mean square error of cross validation; RPD, ratio of performance to deviation; SEC, standard error of calibration; SEP, standard error of prediction; STD, standard deviation; SDCV, standard deviation of cross validation; SNV, single normal variate; MSC, multiple scatter correction; MIRS, mid infrared spectroscopy; BR, biological replicate. ⇑ Corresponding author. Tel.: +49 30 8304 2210; fax: +49 30 8304 2503. E-mail address: Andrea.Kraehmer@jki.bund.de (A. Krähmer). Food Chemistry 181 (2015) 152–159 Contents lists available at ScienceDirect Food Chemistry journal homepage: www.elsevier.com/locate/foodchem