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Updated: Jun 30, 2026

Fruit Volatile Analysis Using an Electronic Nose
Published on: March 30, 2012
Integrated Volatilomics and Lipidomics Identify Lactones as Correlation Hubs Associated With Lipid Remodeling,
Rui Han1,2, Mingshen Su2,3, Zhengwen Ye2,3
1College of Horticulture, Qingdao Agricultural University, Qingdao, P. R. China.
Abstract:
Melting-flesh nectarines undergo rapid postharvest softening. 1-Methylcyclopropene (1-MCP) effectively delays this process yet may suppress flavor development. Here, we integrated texture parameters, volatile profiles (83 compounds; SPME-GC-MS), and lipid profiles (234 species; LC-MS/MS) from yellow-fleshed nectarines under Control and 1-MCP treatments over an 8-day ambient shelf life. 1-MCP extended the acceptable firmness window and delayed the C6-aldehyde-to-lactone flavor transition. Lipidomic profiling identified 234 lipid species across five classes and 23 subclasses, dominated by glycerolipids (38.9%) and glycerophospholipids (37.2%). During storage, 192 species (82.1%) were differentially accumulated, featuring coupled glycerophospholipid degradation and triacylglycerol accumulation. Double bond index analysis further revealed class-specific unsaturation remodeling. Spearman correlation (|ρ| > 0.8, FDR < 0.05) yielded 454 strong volatile-lipid pairs (62.8% negative) and 70 texture-metabolite pairs. Mantel test, canonical correlation analysis, and Procrustes analysis confirmed robust inter-omics associations. In the correlation network, γ-octalactone and γ-decalactone emerged as hub nodes linking lipid metabolism to flavor dimensions. γ-Decalactone exhibited the strongest firmness correlation among all metabolites (ρ = -0.94), suggesting potential as a nondestructive softening indicator. Unsaturation-stratified analysis revealed that glycerophospholipid monounsaturated fatty acid (MUFA) species (double bond = 1) exhibited the strongest flavor associations, whereas class-level lipid totals were nonsignificant. This highlights molecular species specificity in lipid-flavor linkages. Machine learning identified four consensus markers (d-limonene, monogalactosyldiacylglycerol [MGDG] 36:4, MGDG 36:6, and phosphatidylethanolamine 43:2) that discriminate Control from 1-MCP-treated fruit, providing molecular targets for preservation optimization. PRACTICAL APPLICATIONS: The strong correlation between γ-decalactone and firmness (ρ = -0.94) suggests that gas-sensor or electronic-nose detection of this peach-aroma volatile could enable nondestructive assessment of nectarine softening. The correlation network further suggests that membrane lipid catabolism is closely associated with both lactone-based flavor development and texture loss, providing a mechanistic basis for optimizing 1-methylcyclopropene (1-MCP) dosage and timing to balance firmness retention with flavor preservation. The four consensus markers may additionally serve as molecular references for shelf-life prediction and quality grading. Regarding sensor-based implementation, the wide dynamic range of γ-decalactone observed in this study (<1 to ∼900 ng/g fresh weight) and its high concentration at marketable softening are favorable for electronic nose detection; however, practical deployment would require standardized headspace sampling protocols and cultivar-specific calibration.
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