Integrated E-nose, volatilomics, and transcriptomics analysis of the aroma formation mechanism during pitaya fruit ripening
- 1Guiyang University, Guiyang, China
- 2Guangdong Provincial Key Laboratory of Postharvest Science of Fruits and Vegetables, Engineering Research Center of Southern Horticultural Products Preservation, Ministry of Education, College of Horticulture, South China Agricultural University, Guangzhou, China
Abstract
Pitaya fruit is of high nutritional and economic value, yet the molecular mechanisms governing its aroma formation during ripening remain poorly understood. This study employed an integrated approach combining E-nose, HS-SPME-GC-MS, and transcriptomics to investigate the formation and dynamic changes of volatile organic compounds (VOCs) and their underlying molecular mechanisms in “Zihonglong” pitaya from Guizhou Province, China. A total of 856 VOCs were tentatively identified, among which terpenoids, esters, and ketones were the predominant chemical groups. Based on relative odor activity values (rOAV > 1), 79 compounds were identified as key contributors to aroma perception. Transcriptomic analysis indicated that α-linolenic acid metabolism, terpenoid biosynthesis, and phenylpropanoid biosynthesis were closely associated with volatile formation during ripening. Weighted gene co-expression network analysis (WGCNA) further revealed two major regulatory modules, designated “Turquoise” and “Blue”, which showed strong correlations with the accumulation patterns of characteristic aroma metabolites. Multivariate analysis of E-nose responses successfully distinguished unripe fruit from ripening stages, demonstrating its potential for rapid maturity screening. This study provides mechanistic insights into aroma evolution during pitaya ripening and supports the development of aroma-based quality evaluation strategies.
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BibTeX
@article{ba2026integrated,
title = {{Integrated E-nose, volatilomics, and transcriptomics analysis of the aroma formation mechanism during pitaya fruit ripening}},
author = {Liangjie Ba and Xiaoling Long and Chenglin Luo and Sen Cao and Jianye Chen and Donglan Luo},
journal = {NPJ Science of Food},
year = {2026},
month = jul,
doi = {10.1038/s41538-026-00981-7},
url = {https://doi.org/10.1038/s41538-026-00981-7},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - JOUR
TI - Integrated E-nose, volatilomics, and transcriptomics analysis of the aroma formation mechanism during pitaya fruit ripening
AU - Liangjie Ba
AU - Xiaoling Long
AU - Chenglin Luo
AU - Sen Cao
AU - Jianye Chen
AU - Donglan Luo
PY - 2026
DA - 2026/07/05
JO - NPJ Science of Food
DO - 10.1038/s41538-026-00981-7
UR - https://doi.org/10.1038/s41538-026-00981-7
AB - Pitaya fruit is of high nutritional and economic value, yet the molecular mechanisms governing its aroma formation during ripening remain poorly understood. This study employed an integrated approach combining E-nose, HS-SPME-GC-MS, and transcriptomics to investigate the formation and dynamic changes of volatile organic compounds (VOCs) and their underlying molecular mechanisms in “Zihonglong” pitaya from Guizhou Province, China. A total of 856 VOCs were tentatively identified, among which terpenoids, esters, and ketones were the predominant chemical groups. Based on relative odor activity values (rOAV > 1), 79 compounds were identified as key contributors to aroma perception. Transcriptomic analysis indicated that α-linolenic acid metabolism, terpenoid biosynthesis, and phenylpropanoid biosynthesis were closely associated with volatile formation during ripening. Weighted gene co-expression network analysis (WGCNA) further revealed two major regulatory modules, designated “Turquoise” and “Blue”, which showed strong correlations with the accumulation patterns of characteristic aroma metabolites. Multivariate analysis of E-nose responses successfully distinguished unripe fruit from ripening stages, demonstrating its potential for rapid maturity screening. This study provides mechanistic insights into aroma evolution during pitaya ripening and supports the development of aroma-based quality evaluation strategies.
SN - 2396-8370
ER -