Characterization of Key Compounds of Organic Acids and Aroma Volatiles in Fruits of Different Actinidia argute Resources Based on High-Performance Liquid Chromatography (HPLC) and Headspace Gas Chromatography-Ion Mobility Spectrometry (HS-GC-IMS)

Discrimination of coal geographical origins through HS-GC-IMS assisted with machine learning algorithms in larceny case

The process of globalization and industrialization has resulted in a rise in the theft of coal and other related products, thereby becoming a focal point for forensic science. This situation has engendered an escalated demand for effective detection and monitoring technologies. The precise identification of coal trace evidence presents a challenge with current methods, owing to its minute quantity, fine texture, and intricate composition. In this study, we integrated machine learning with the identification of volatiles to accurately differentiate coal geographical origins through the application of headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS). The topographic distribution of volatiles in coals was visually depicted to elucidate the subtle distinctions through spectra and fingerprint analysis. Additionally, four supervised machine learning algorithms were developed to quantitatively predict the geographical origins of natural coals utilizing the HS-GC-IMS dataset, and these were subsequently compared with unsupervised models. Remarkable volatile compounds were identified through the quantitative analysis and optimal Random Forest model, which offered a rapid readout and achieved an average accuracy of 100 % in coal identification. Our findings indicate that the integration of HS-GC-IMS and machine learning is anticipated to enhance the efficiency and accuracy of coal geographical traceability, thereby providing a foundation for litigation and trials.

Investigation of different ingredients affected the flavor changes of Yu-Shiang shredded pork by using GC-IMS and GC-MS combined with E-nose and E-tongue

The objective of this study was to assess and compare the characteristics of Yu-Shiang Shredded Pork made with different ingredients by using physicochemical measurements and intelligent sensory analysis. The study revealed that there were 18 varied amino acids present, with the taste active values (TAVs) of Leu, Glu, Asp, Asn, and Ala all higher than 1.0. Intelligent sensory analysis showed that the samples lacking lettuce and fungus had similar aromas and flavors, while those lacking shredded pork and pickled chillies had distinct aromas and flavors. Moreover, VOCs (volatile organic compounds) were detected in five types of Yu-Shiang Shredded Pork, with 43, 42, 53, 36, and 50 identified in GC-MS (gas chromatography-mass spectrometry), respectively. Olefins (20.62 %-30.93 %) were the most abundant. GC-IMS (gas chromatography-ion mobility spectrometry) detected 68 volatiles flavor compounds, with esters having a significantly higher relative content than other compounds, indicating their significant role in the flavor formation process of Yu-Shiang Shredded Pork. Furthermore, the Orthogonal Partial Least Squares-discriminant analysis (OPLS-DA) model analysis identified 19 marker compounds that could differentiate the five types of Yu-Shiang Shredded Pork. These fundamental results lay the groundwork for future research on the connection between ingredients and the flavor characteristics of Yu-Shiang Shredded Pork.

Evaluation of Loquat Jam Quality at Different Cooking Times Based on Physicochemical Parameters, GC-IMS and Intelligent Senses

The study compared and analyzed the quality of loquat jam with different cooking times through physicochemical parameters, headspace-gas chromatography-ion migration spectroscopy (HS-GC-IMS) and intelligent senses. The results showed that with the prolongation of the cooking time, the color of loquat jam slowly deepened, the energy significantly increased, the adhesiveness, gumminess, hardness and chewiness enhanced, the free amino acid content increased from 22.40 to 65.18 mg/g. The organic acid content increased from 1.64 to 9.82 mg/g. Forty-seven volatile flavor compounds were identified in five types of loquat jam using HS-GC-IMS, among which the relative content of aldehydes was sharply higher than that of other chemical substances, playing an important role in the flavor formation of loquat jam. LJ0, LJ1 and LJ2 had higher aldehyde content, followed by LJ3 and LJ4 had the lowest aldehyde content. The orthogonal partial least squares-discriminant analysis (OPLS-DA) screened 15 marker compounds that could distinguish five types of loquat jam. The E-nose results showed a significant difference in olfactory sense between loquat jam cooked for 100 and 120 min. The E-tongue results corroborated the results of free amino acids (FAAs) and organic acids, indicating that the gustatory sense of loquat jam changed significantly when the cooking time reached 120 min. The results provided a basis for further research on the relationship between the cooking process and quality characteristics of loquat jam.

Flavor Quality Analysis of Ten Actinidia arguta Fruits Based on High-Performance Liquid Chromatography and Headspace Gas Chromatography-Ion Mobility Spectrometry

Actinidia arguta is a fruit crop with high nutritional and economic value. However, its flavor quality depends on various factors, such as variety, environment, and post-harvest handling. We analyzed the composition of total soluble sugars, titratable acids, organic acids, and flavor substances in the fruits of ten A. arguta varieties. The total soluble sugar content ranged from 4.22 g/L to 12.99 g/L, the titratable acid content ranged from 52.55 g/L to 89.9 g/L, and the sugar-acid ratio ranged from 5.39 to 14.17 at the soft ripe stage. High-performance liquid chromatography (HPLC) showed that citric, quinic, and malic acids were the main organic acids in the A. arguta fruits. Headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) detected 81 volatile compounds in 10 A. arguta varieties, including 24 esters, 17 alcohols, 23 aldehydes, 7 ketones, 5 terpenes, 2 acids, 1 Pyrazine, 1 furan, and 1 benzene. Esters and aldehydes had the highest relative content of total volatile compounds. An orthogonal partial least squares discriminant analysis (OPLS-DA) based on the odor activity value (OAV) revealed that myrcene, benzaldehyde, methyl isobutyrate, α-phellandrene, 3-methyl butanal, valeraldehyde, ethyl butyrate, acetoin, (E)-2-octenal, hexyl propanoate, terpinolene, 1-penten-3-one, and methyl butyrate were the main contributors to the differences in the aroma profiles of the fruits of different A. arguta varieties. Ten A. arguta varieties have different flavors. This study can clarify the differences between varieties and provide a reference for the evaluation of A. arguta fruit flavor, variety improvement and new variety selection.