2016
DOI: 10.1007/s12161-016-0696-y
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Rapid Classification of Coffee Products by Data Mining Models from Direct Electrospray and Plasma-Based Mass Spectrometry Analyses

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Cited by 27 publications
(13 citation statements)
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“…For data mining and model building, we used the R package Rattle (27) and the mean values from triplicate experiments. We applied a hierarchical clustering analysis (HCA) to the filtered data to create metabolic heat maps and evaluated differences in the metabolic profiles (66).…”
Section: Methodsmentioning
confidence: 99%
“…For data mining and model building, we used the R package Rattle (27) and the mean values from triplicate experiments. We applied a hierarchical clustering analysis (HCA) to the filtered data to create metabolic heat maps and evaluated differences in the metabolic profiles (66).…”
Section: Methodsmentioning
confidence: 99%
“…However, an excess of hypoxia stress leads to the expression of CHGs and flavor alteration by the accumulation of fermentative products (Cukrov et al, 2016). As mentioned before, the threshold between conservation and fermentation is highly variable in fruits and vegetables (Beaudry, 1999); therefore, a solution to further monitor this balance is the use of metabolomic fingerprinting by combining state-of-the-art analytical methods, informatics, and agronomical knowledge, as recently shown for coffee (Gamboa-Becerra et al, 2017). The use of tissue or developmental stage-specific promoters to drive the timely expression of RNAi constructs against transcripts of ethylene receptors or fermentative enzymes may also render interesting biotechnological prototypes for fruit conservation technology.…”
Section: Biotechnological Success and Explorationsmentioning
confidence: 99%
“…Apart from these portable MS detectors, a benchtop miniature of the MS system, named Mini 12, was developed. As an ambient ionization source with an MS analyzer, it is capable of producing quantitative data for small volume samples; it is thus able to trace chemical markers in food matrices [62].…”
Section: Gc-ms and Lc-msmentioning
confidence: 99%