|
References [1]. Woolfenden, E., Sorbent-based sampling methods for volatile and semi-volatile organic compounds in air. Part 2. Sorbent selection and other aspects of optimizing air monitoring methods. Journal of Chromatography A, 2010. 1217(16): p. 2685-2694. [2]. Wang, S.-C., Artificial Neural Network, in Interdisciplinary Computing in Java Programming. 2003, Springer US. p. 81-100. [3]. Shimoda, M. and T. Shibamoto, Isolation and identification of headspace volatiles from brewed coffee with an on-column GC/MS method. Journal of Agricultural and Food Chemistry, 1990. 38(3): p. 802-804. [4]. Pérez-Martínez, M., et al., Changes in volatile compounds and overall aroma profile during storage of coffee brews at 4 and 25 C. Journal of agricultural and food chemistry, 2008. 56(9): p. 3145-3154. [5]. Gören*, A.C., et al., Analysis of essential oil of Satureja thymbra by hydrodistillation, thermal desorber, and headspace GC/MS techniques and its antimicrobial activity. Natural product research, 2004. 18(2): p. 189-195. [6]. Helmig, D. and J.P. Greenberg, Automated in situ gas chromatographic-mass spectrometric analysis of ppt level volatile organic trace gases using multistage solid-adsorbent trapping. Journal of Chromatography A, 1994. 677(1): p. 123-132. [7]. Li, C.-H., et al. Using TD-GC-MS to analyze coffee beans aromas of different roast levels. in Nano/Micro Engineered and Molecular Systems (NEMS), 2014 9th IEEE International Conference on. 2014. IEEE. [8]. Fisk, I., et al., Discrimination of roast and ground coffee aroma. Flavour, 2012. 1(1): p. 14. [9]. Witt, K., S. Reulecke, and A. Voss. Discrimination and characterization of breath from smokers and non-smokers via electronic nose and GC/MS analysis. in Engineering in Medicine and Biology Society,EMBC, 2011 Annual International Conference of the IEEE. 2011. [10]. Schaller, E., J.O. Bosset, and F. Escher, ‘Electronic Noses’ and Their Application to Food. LWT - Food Science and Technology, 1998. 31(4): p. 305-316. [11]. Jurs, P.C., G.A. Bakken, and H.E. McClelland, Computational Methods for the Analysis of Chemical Sensor Array Data from Volatile Analytes. Chemical Reviews, 2000. 100(7): p. 2649-2678. [12]. Guo, D., D. Zhang, and L. Zhang, Sparse representation-based classification for breath sample identification. Sensors and Actuators B: Chemical, 2011. 158(1): p. 43-53. [13]. Rui, X. and D. Wunsch, II, Survey of clustering algorithms. Neural Networks, IEEE Transactions on, 2005. 16(3): p. 645-678. [14]. MacQueen, J. Some methods for classification and analysis of multivariate observations. in Proceedings of the fifth Berkeley symposium on mathematical statistics and probability. 1967. California, USA. [15]. Hartigan, J.A. and M.A. Wong, Algorithm AS 136: A k-means clustering algorithm. Applied statistics, 1979: p. 100-108. [16]. Holte, R.C., Very simple classification rules perform well on most commonly used datasets. Machine learning, 1993. 11(1): p. 63-90. [17]. Pham, D.T. and M. Aksoy, An algorithm for automatic rule induction. Artificial Intelligence in Engineering, 1993. 8(4): p. 277-282. [18]. Wu, X., Inductive learning: Algorithms and frontiers. Artificial Intelligence Review, 1993. 7(2): p. 93-108. [19]. Bicego, M., et al., A comparative analysis of basic pattern recognition techniques for the development of small size electronic nose. Sensors and Actuators B: Chemical, 2002. 85(1): p. 137-144. [20]. Gómez, A.H., et al., Evaluation of tomato maturity by electronic nose. Computers and electronics in agriculture, 2006. 54(1): p. 44-52. [21]. Yu, H., et al., Identification of green tea grade using different feature of response signal from E-nose sensors. Sensors and Actuators B: Chemical, 2008. 128(2): p. 455-461. [22]. Shi, Z.-b., et al., Comparison of algorithms for an electronic nose in identifying liquors. Journal of Bionic Engineering, 2008. 5(3): p. 253-257. [23]. GholamHosseini, H., et al. Intelligent processing of E-nose information for fish freshness assessment. in Intelligent Sensors, Sensor Networks and Information, 2007. ISSNIP 2007. 3rd International Conference on. 2007. IEEE. [24]. Martinez, A.M. and A.C. Kak, PCA versus LDA. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 2001. 23(2): p. 228-233. [25]. Fisk, I.D. and A.T. Massey, Composition for Preparing a Beverage or Food Product Comprising a Plurality Insoluble Material Bodies. 2011, Google Patents. [26]. Semmelroch, P. and W. Grosch, Studies on character impact odorants of coffee brews. Journal of Agricultural and Food Chemistry, 1996. 44(2): p. 537-543. [27]. Mancha Agresti, P.D., et al., Discrimination between defective and non-defective Brazilian coffee beans by their volatile profile. Food chemistry, 2008. 106(2): p. 787-796. [28]. Silva, E.A.d., et al., The influence of water management and environmental conditions on the chemical composition and beverage quality of coffee beans. Brazilian Journal of Plant Physiology, 2005. 17(2): p. 229-238. [29]. Risticevic, S., E. Carasek, and J. Pawliszyn, Headspace solid-phase microextraction–gas chromatographic–time-of-flight mass spectrometric methodology for geographical origin verification of coffee. Analytica chimica acta, 2008. 617(1): p. 72-84. [30]. Franca, A.S., et al., A preliminary evaluation of the effect of processing temperature on coffee roasting degree assessment. Journal of food engineering, 2009. 92(3): p. 345-352. [31]. Bhumiratana, N., K. Adhikari, and E. Chambers IV, Evolution of sensory aroma attributes from coffee beans to brewed coffee. LWT-Food Science and Technology, 2011. 44(10): p. 2185-2192. [32]. Gonzalez-Rios, O., et al., Impact of “ecological” post-harvest processing on coffee aroma: II. Roasted coffee. Journal of food composition and analysis, 2007. 20(3): p. 297-307. [33]. Bröhan, M., et al., Influence of storage conditions on aroma compounds in coffee pads using static headspace GC–MS. Food chemistry, 2009. 116(2): p. 480-483. [34]. Fisk, I.D., et al., Gamma-irradiation as a method of microbiological control, and its impact on the oxidative labile lipid component of Cannabis sativa and Helianthus annus. European Food Research and Technology, 2009. 228(4): p. 613-621. [35]. BudryN, G., et al., HS-SPME/GC/MS profiles of convectively and microwave roasted Ivory Coast Robusta coffee brews. Czech J Food Sci, 2011. 29: p. 151-160. [36]. Cantergiani, E., et al., Characterisation of the aroma of green Mexican coffee and identification of mouldy/earthy defect. European Food Research and Technology, 2001. 212(6): p. 648-657. [37]. Holscher, W. and H. Steinhart, Aroma compounds in green coffee. Developments in Food Science, 1995. 37: p. 785-803. [38]. Wu, S., A review on coarse warranty data and analysis. Reliability Engineering & System Safety, 2013. 114(0): p. 1-11. [39]. Dettmer, K. and W. Engewald, Ambient air analysis of volatile organic compounds using adsorptive enrichment. Chromatographia, 2003. 57(1): p. S339-S347. [40]. Holscher, W. and H. Steinhart, Investigation of roasted coffee freshness with an improved headspace technique. Zeitschrift für Lebensmittel-Untersuchung und Forschung, 1992. 195(1): p. 33-38. [41]. Hofmann, T., et al., Model studies on the influence of coffee melanoidins on flavor volatiles of coffee beverages. Journal of agricultural and food chemistry, 2001. 49(5): p. 2382-2386. [42]. Müller, C. and T. Hofmann, Quantitative studies on the formation of phenol/2-furfurylthiol conjugates in coffee beverages toward the understanding of the molecular mechanisms of coffee aroma staling. Journal of agricultural and food chemistry, 2007. 55(10): p. 4095-4102. [43]. Jolliffe, I., Principal component analysis. 2005: Wiley Online Library. [44]. Guo, G., et al., KNN model-based approach in classification, in On The Move to Meaningful Internet Systems 2003: CoopIS, DOA, and ODBASE. 2003, Springer. p. 986-996. [45]. Sarrazin, C., et al., Representativeness of coffee aroma extracts: a comparison of different extraction methods. Food Chemistry, 2000. 70(1): p. 99-106. [46]. Hao, H., et al., Development of a portable electronic nose based on chemical surface acoustic wave array with multiplexed oscillator and readout electronics. Sensors and Actuators B: Chemical, 2010. 146(2): p. 545-553.
|