Assessment and Classification of Volatile Profiles in Melon Breeding Lines Using Headspace Solid-Phase Microextraction Coupled with Gas Chromatography-Mass Spectrometry

Abstract

Cucumis melo L is one of the most commercial and economical crops in the world with several health beneficial compounds as such carotenoids, amino acids, vitamin A and C, minerals, and dietary fiber. Evaluation of the volatile organic compounds (VOCs) in different melon (Cucumis melo L.) breeding lines provides useful information for improving fruit flavor, aroma, and antimicrobial levels. In this study, the VOCs in 28 melon breeding lines harvested in 2019 were identified and characterized using head space solid-phase microextraction (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS). This identified 113 VOCs with significant differences in composition and contents of among the breeding lines, including 15 esters, 27 aldehydes, 35 alcohols, 14 ketones, 4 acids, 10 hydrocarbons, 5 sulfurs, and 3 other compounds. The highest average contents of all the VOCs were found in BL-30 (13,973.07 µg/kg FW) and the lowest were in BL-22 (3947.13 µg/kg FW). BL-9 had high levels of carotenoid-derived VOCs. The compounds with the highest contents were benzaldehyde, geranylacetone, and β-ionone. Quality parameters such as color and sugar contents of melons were also measured. All the melon color readings were within the typical acceptable range. BL-22 and BL-14 had the highest and lowest sugar contents, respectively. Principal component analysis (PCA) produced diverse clusters of breeding lines based on flavor and aroma. BL-4, BL-7, BL-12, BL-20, and BL-30 were thus selected as important breeding lines based on their organoleptic, antimicrobial, and health-beneficial properties.

Latest Improvements and Expanding Applications of Solid-Phase Microextraction

“…A large number of plants own distinctive odors. Analyzing these odors is expected to reveal unique biomarkers for species identification and provide important data for economic valuation. − HS-SPME is an excellent candidate for odor enrichment, and the mixed fibers including DVB/CAR/PDMS, CAR/PDMS, and PDMS/DVB are preferred due to the synergetic effects of absorbents and adsorbents. − It is worth mentioning that the hybrid composites of silica aerogel, preyssler-type polyoxometalate, and MIL-101­(Cr) have been fabricated as a highly porous fiber coating, which has been successfully used for the headspace extraction and identification of Ferulago angulata volatile components. Exerting a magnetic field on the prepared SPME fiber using a permanent magnet substantially improves the extraction efficiency for the volatile components, to an average of 73% …”

Green Extraction Techniques as Advanced Sample Preparation Approaches in Biological, Food, and Environmental Matrices: A Review

“…MEPS is another GreET that has been employed in the analysis of foodstuffs, including the identification of herbicides in rice [100], insecticides in drinking water [101], pesticides in apple juice and coffee [102], antibiotics [103] and steroids [104] in milk, parabens in vegetable oil [105], PAHs in apple [106], caffeine in drinks [107], and polyphenols in baby food [108]. SPME has been widely used to study the volatile composition of several foods, including walnut oils [109], hongeo [110], melon [111], and dairy products [112]. Moreover, this technique has also been used to determine the composition of specific analytes, such as the x-ray induced markers 2-dodecylcyclobutanone and 2-tetradecylcyclobutanone in irradiated dairy products [113], the contaminants 1,4-dioxane and 1,2,3-trichloropropane [114], acrylamide [115], organophosphorus pesticides [116], phthalates [117], synthetic phenolic antioxidants [118], and xanthines [119].…”

Evaluation of Aromatic Characteristics and Potential Applications of Hemerocallis L. Based on the Analytic Hierarchy Process

“…Various analysis models are used for variety breeding under the influence of multiple variables. Among them, the most common one is principal component analysis (PCA), which serves as a multivariate tool to detect correlations between all the breeding lines and VOCs [ 13 ]. In addition, grey relational analysis [ 14 ] and fuzzy comprehensive evaluation [ 15 ] are also utilized to assess the overall quality of varieties based on their traits, aiming to select specific varieties.…”