High throughput quantitative volatile profiling of melons with silicone rod extraction – thermal desorption – GC–MS for plant breeding line selection. (1st January 2019)

• Record Type: Journal Article
• Authors: Kende, Aniko; Lim, Pei Pei; Lai, Florence; Jessop, Michael; Swindale, Lauraine; Oliver, Marc; Hurr, Brandon; Rickett, Daniel; Baxter, Charles
• Is Part Of: Food chemistry. Volume 270(2019)
• Page Start: 368
• Page End: 374
• Publication Date: 2019-01-01
• Subjects: Volatiles -- Flavor profiling -- Thermal desorption -- GC–MS -- Silicone rod extraction -- Melon -- Plant breeding -- Line selection -- Marker assisted breeding; Food -- Analysis -- Periodicals; Food -- Composition -- Periodicals; 664
• DOI: 10.1016/j.foodchem.2018.07.101
• Languages: English
• ISSNs: 0308-8146

Abstract

Highlights: Use of silicone rods for high throughput volatile profiling of field samples. High quality quantitative data enables differentiation of related melon varieties. Volatile profile is used for breeding selection of melons for desired flavor profile and shelf life. Abstract: Volatile compounds determine the aroma of fruits, giving their unique flavor characteristics. The aim of many plant breeding projects is to improve the consumers' flavor experience when eating fresh produce. Large scale breeding trials produce thousands of samples which need volatile profiling amongst other phenotypes. Despite this interest, current methods have limitations: sampling unsuitable for field conditions, high cost and the inherent issue of highly variable data, which can hinder interpretation. We introduced a simple and robust sampling methodology based on silicone rod extraction, thermal desorption gas chromatography – mass spectrometry (GC–MS) to address these issues. We used differentiated calibration standards to generate quantitative data for metabolites of varying abundance. The method was used to profile 327 melons with high sensitivity (0.05–10 ng/mL, compound dependent), good reproducibility (7%) and differentiate melon varieties based on their volatile profile. The data were then used for line selection for a desired flavor profile.