The determination of starch content was performed as described by Li et al. [28 (link)]. The remaining precipitate after the extraction with 75% methanol for the determination of sugar and acid was repeatedly cleaned with 80% (v/v) ethanol three times, mixed with 0.1 M KOH and boiled for 30 min to gelatinize the starch. α-amylase at pH 4.5 was added and incubated at 55°C for 1 h. Reducing sugar content was determined by 3, 5-dinitrosalicylic acid (DNS), and then converted to starch content.
Gcms 2010se
The GCMS-2010SE is a gas chromatography-mass spectrometry (GC-MS) system developed by Shimadzu. It combines gas chromatography for sample separation with mass spectrometry for compound identification and quantification. The GCMS-2010SE provides high-sensitivity and high-speed analysis capabilities for a wide range of applications.
10 protocols using gcms 2010se
Comprehensive Analysis of Organic Acids and Sugars
The determination of starch content was performed as described by Li et al. [28 (link)]. The remaining precipitate after the extraction with 75% methanol for the determination of sugar and acid was repeatedly cleaned with 80% (v/v) ethanol three times, mixed with 0.1 M KOH and boiled for 30 min to gelatinize the starch. α-amylase at pH 4.5 was added and incubated at 55°C for 1 h. Reducing sugar content was determined by 3, 5-dinitrosalicylic acid (DNS), and then converted to starch content.
Metabolite Profiling of Plant Leaves
Amino acids were extracted and measured as described previously (Huo et al., 2020b (link)). Briefly, 200 mg of frozen leaf samples were extracted in 2 ml 50% ethanol (including 0.1 M HCl) and centrifuged at 13,000 g for 10 min. The supernatant was added to methanol at a final volume of 10 ml. The samples were filtered through a 0.22 μm filter to analyze the metabolites with a liquid chromatography-mass spectrometry system (QTRAP5500; SCIEX, Concord, ONT, Canada) equipped with an Inertsil ODS-4 C18 column (4.6 × 250 mm, 5 μm) at a flow rate of 0.3 ml/min. The solvent system consisted of water containing 0.1% (v/v) formic acid (A) and acetonitrile (B). Data were quantified by comparing the peak surface areas with those obtained using standard amino acids (Sigma-Aldrich, St. Louis, MO, United States).
Quantitative GC-MS Metabolite Analysis
GC-MS Analysis of Soluble Sugars and Starch
Metabolic Analysis of Seedling Leaves
Metabolite and CO2 Assimilation Analysis
Fatty Acid Composition Analysis
Derivatization and GC/MS Analysis
Genetic Mapping of Fructose Content
A high-density genetic linkage map was used for QTL detection of Fru contents. QTL analysis was conducted with MapQTL 6.0 (Kyazma, Wageningen, Netherlands) and was initially run with interval mapping (IM) computation. After a permutation test with 1000 replicates, a LOD threshold of 3.0 was used to find significant QTLs at the 95% confidence level (Wang et al., 2018) . Multiple QTL model (MQM) mapping was then performed using the loci nearest the QTL peaks as cofactors. The linkage map was graphed by MapChart 2.3 (Wageningen, Netherlands) (Voorrips, 2002) . Designations for QTLs were based on the years (2015 or 2016), parental genetic linkage map names (HC for 'Honeycrisp', QG for 'Qinguan'), and genetic positions (LG number). For LGs that had more than one QTL, the designation also included a dot and number suffix (Wang et al., 2018) .
GC/MS Analysis of Soluble Metabolites
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