Giménez-Campillo Claudia, Arroyo-Manzanares Natalia, Pastor-Belda Marta, Campillo Natalia, Bodenbender Lukas, Weller Philipp, Viñas Pilar
Department of Analytical Chemistry, Faculty of Chemistry, University of Murcia, Regional Campus of International Excellence "Campus Mare Nostrum", E-30100 Murcia, Spain.
Faculty of Biotechnology, Institute for Instrumental Analytics and Bioanalytics, Technische Hochschule Mannheim, 68163 Mannheim, Germany.
J Agric Food Chem. 2025 Jul 2;73(26):16636-16647. doi: 10.1021/acs.jafc.5c01524. Epub 2025 Jun 23.
In recent years, the quality of peaches has been related to their early harvest, so this work has focused on the characterization of the spectral fingerprint using Fourier transform near-infrared spectroscopy, and headspace gas chromatography (HS-GC) coupled to ion mobility spectrometry (IMS) and mass spectrometry (MS) based on their volatilome or volatile organic compound content, with the aim of identifying the optimum ripening point of peaches. A total of 344 samples of two different varieties at all ripening stages were analyzed. The principal component analysis (PCA) showed a clear tendency for samples at the same stage of ripening to form visible clusters. The groups identified by PCA were used to construct partial least-squares discriminant analysis models that allowed differentiation according to ripening and variety. The overall results were very promising, especially for the volatilomes measured by HS-GC-IMS and HS-GC-MS.
近年来,桃子的品质与其早采有关,因此这项工作专注于利用傅里叶变换近红外光谱法表征光谱指纹,以及基于其挥发物或挥发性有机化合物含量,采用顶空气相色谱(HS-GC)与离子迁移谱(IMS)和质谱(MS)联用的方法,目的是确定桃子的最佳成熟点。对两个不同品种在所有成熟阶段的344个样品进行了分析。主成分分析(PCA)表明,处于同一成熟阶段的样品有明显形成可见聚类的趋势。通过PCA识别出的组用于构建偏最小二乘判别分析模型,该模型能够根据成熟度和品种进行区分。总体结果非常有前景,特别是对于通过HS-GC-IMS和HS-GC-MS测量的挥发物。