2013
DOI: 10.1016/j.jcs.2012.09.012
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Comparative metabolic profiling of pigmented rice (Oryza sativa L.) cultivars reveals primary metabolites are correlated with secondary metabolites

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Cited by 105 publications
(67 citation statements)
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“…In addition, to gain more insight into the differences among samples, the variable importance in the projection (VIP) values were examined. The variables exhibiting a VIP score above a value of 1.0 given by PLS-DA were selected because they were considered to be significantly contributive to the discrimination of geographical origins [47]. As is evident in Fig 4, after data fusion, the variables that play the greatest role in discriminating inner part samples mainly distribute in the regions of 1725–1563, 1201–800 and 565–441 cm -1 , which comprise approximately 68% of the total 475 variables.…”
Section: Resultsmentioning
confidence: 99%
“…In addition, to gain more insight into the differences among samples, the variable importance in the projection (VIP) values were examined. The variables exhibiting a VIP score above a value of 1.0 given by PLS-DA were selected because they were considered to be significantly contributive to the discrimination of geographical origins [47]. As is evident in Fig 4, after data fusion, the variables that play the greatest role in discriminating inner part samples mainly distribute in the regions of 1725–1563, 1201–800 and 565–441 cm -1 , which comprise approximately 68% of the total 475 variables.…”
Section: Resultsmentioning
confidence: 99%
“…In this study, hydrophilic primary metabolites from sweet potatoes were profiled using gas chromatography-time-of-flight mass spectrometry (GC-TOFMS) to determine phenotypic variations and relationships among metabolite contents. A GC-TOFMS-based metabolic profiling analysis facilitates rapid and highly sensitive detection of plant metabolites from the central pathways of primary metabolism (7,8). Carotenoids, flavonoids, anthocyanins, and phenolic acids were quantified as bioactive secondary metabolites to evaluate the quality of three sweet potato varieties.…”
Section: Introductionmentioning
confidence: 99%
“…Heuberger et al (2010) detected 3,097 signals in 10 rice varieties using ultra performance liquid chromatography (UPLC-MS)10. Similarly, using GC-TOF-MS, Lou et al (2011) identified 41 metabolites showing a wide range of variations in 48 distinct rice germplasms11, whilst Kim et al (2012) identified 52 metabolites in seven cultivars by GC-TOF-MS12. Matsuda et al (2012) conducted metabolic quantitative trait loci (mQTL) analysis in rice grains using inbred lines, and determined few loci affecting levels of metabolites13.…”
mentioning
confidence: 99%