Discrimination of defective dry-cured Iberian ham determining volatile compounds by non-destructive sampling and gas chromatography

Monitoring of the Dry-Curing Process in Iberian Ham Through the Evaluation of Fat Volatile Organic Compounds by Gas Chromatography-Ion Mobility Spectrometry and Non-Destructive Sampling

The current quality control of the dry-curing process in Iberian ham is performed with an olfactory evaluation by ham experts. The present study proposes to monitor the dry-curing process of Iberian ham using an objective analytical methodology that involves non-destructive sampling of the subcutaneous fat of the hams and a volatile profile analysis using gas chromatography-ion mobility spectrometry. Thirty-eight 100% Iberian acorn-fed hams were examined in total, with eighteen hams monitored during the post-salting stage and twenty during the drying-maturation stage. A total of 164 markers were detected in the samples monitored during the post-salting stage, whereas 276 were detected in the hams monitored during the drying-maturation stage. The study of the trends observed in the intensities of the markers throughout the curing process enabled the detection of potential indicators of the end of the post-salting stage. Thus, representative intensity thresholds were established for some markers (3-methylbutanal, pentanal, hexanal, (E)-octen-2-al, 2-hexen-1-ol and heptan-1-ol) to determine the optimal point to specify the end of the post-salting process for hams. These findings provide an objective tool to support the traditional sensory evaluation currently performed in the industry.

Characterization of the flavor profile and dynamic changes in Chinese traditional fish sauce (Yu-lu) based on electronic nose, SPME-GC-MS and HS-GC-IMS

In this study, flavor characteristics and dynamic change of Chinese traditional fermented fish sauce (Yu-lu) with different fermentation time (2, 4, 6, 8, and 12 months) were analyzed. The electronic nose analyses confirmed a notable flavor change in fish sauce samples from different stages. During the 12-months fermentation, the total volatile compounds in fish sauce increased from 3.9 mg/L to 13.53 mg/L. Acids, aldehydes, esters and phenols were the main aroma substances and their contents gradually increased during the fermentation process. The PCA of GC-MS and GC-IMS showed that fish sauce samples from different fermentation periods can be well distinguished. A total of 110 volatile compounds identified by GC-MS, and 102 volatile compounds were detected by GC-IMS. Among them, 13 compounds were identified by both GC-MS and GC-IMS. The most varieties (49) of volatiles appeared after 8 months of fermentation. The odor activity value (OAV) analysis showed that 10 volatile compounds were considered as characteristic flavor in traditional fish sauce. The variable influence on projections (VIPs) in PLS-DA models constructed by GC-MS and GC-IMS identified 5 and 10 volatile compounds as biomarkers, respectively. Our results revealed the dynamic changes of characteristic flavor in fish sauce in combination of GC-MS and GC-IMS, which provides theoretical basis for the production and flavor regulation of fish sauce.

Characteristics of kopyor coconut (Cocos nucifera L.) using sensory analysis and metabolomics-based approach

Kopyor is a coconut with unique characteristics from Indonesia, one of the largest coconut producers in the world. Kopyor is an edible mature coconut with soft endosperm. Although this fruit is one of the most popular coconuts in the world, there are limited studies on its properties, including its sensory attributes and metabolite profiles. This study investigates the characteristics of kopyor using sensory evaluation, a widely targeted metabolomics approach, and multivariate analysis. The liquid (water) and solid (flesh) endosperms were collected as the samples. The results showed that kopyor has characteristics that distinguish it from normal mature and young coconuts. Kopyor water has a milky, creamy, nutty, bitter, and astringent taste with an oily aftertaste and mouthfeel. Kopyor flesh is soft and moist and gives a sandy mouth feel. This study analyzed the sensory attributes of the kopyor endosperm for the first time and compared it with those of normal mature and young coconuts. A gas chromatography mass spectrometry analysis showed that kopyor contained wider variety of metabolites than normal coconuts of the same age. Based on the differential analysis and orthogonal projections to latent structures-regression, kopyor water was characterized by the accumulation of flavor-related metabolites, such as amino acids and organic acids, which contributed to its sensory complexity. This study solidified the effects of maturation and endosperm type on metabolite accumulation in kopyor endosperm. This pioneering information will lead to the future use of kopyor and other unique coconuts worldwide for food, contributing to the sustainability of the coconut industry.

Characterization of Flavor Profile of Sauced Pork from Different Regions of China Based on E-Nose, E-Tongue and Gas Chromatography-Ion Mobility Spectroscopy

This study aimed to investigate the volatile flavor compounds and tastes of six kinds of sauced pork from the southwest and eastern coastal areas of China using gas chromatography-ion mobility spectroscopy (GC-IMS) combined with an electronic nose (E-nose) and electronic tongue (E-tongue). The results showed that the combined use of the E-nose and E-tongue could effectively identify different kinds of sauced pork. A total of 52 volatile flavor compounds were identified, with aldehydes being the main flavor compounds in sauced pork. The relative odor activity value (ROAV) showed that seven key volatile compounds, including 2-methylbutanal, 2-ethyl-3, 5-dimethylpyrazine, 3-octanone, ethyl 3-methylbutanoate, dimethyl disulfide, 2,3-butanedione, and heptane, contributed the most to the flavor of sauced pork (ROAV ≥1). Multivariate data analysis showed that 13 volatile compounds with the variable importance in projection (VIP) values > 1 could be used as flavor markers to distinguish six kinds of sauced pork. Pearson correlation analysis revealed a significant link between the E-nose sensor and alcohols, aldehydes, terpenes, esters, and hetero-cycle compounds. The results of the current study provide insights into the volatile flavor compounds and tastes of sauced pork. Additionally, intelligent sensory technologies can be a promising tool for discriminating different types of sauced pork.

Classification and characterization on sorghums based on HS-GC-IMS combined with OPLS-DA and GA-PLS

Headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) detected 206 and 186 samples of fresh and stored sorghums respectively with three major types in Baijiu industry. The fingerprints showed the differences of volatile compounds among fresh sorghum types by qualitative analysis and artificial recognition. Organic waxy sorghums had more contents of nonanal and 2-ethyl-1-hexanol but fewer ketones. The contents of acetoin in non-glutinous sorghums and organic non-glutinous sorghums were high. On the other hand, genetic algorithm-partial least squares (GA-PLS) selected 19 and 32 characteristic volatile compounds in fresh and stored sorghums. After centering and auto scaling to unit variance, the classification models with three major types of organic waxy sorghum, non-glutinous sorghum and organic non-glutinous sorghum were established based on orthogonal partial least squares-discriminant analysis (OPLS-DA). The goodness-of-fit (R2Y) and the goodness-of-prediction in cross-validation (Q2) in the model of fresh sorghum types all exceeded 0.9, in stored were over 0.8, the correct classification rates of external prediction were 95 % and 100 %, which revealed good performance and prediction. On this basis, the correct classification rates reached 87 % in organic waxy sorghums adulterated over 10 % ratio. GC-IMS combined with chemometrics is applicable in practical production for rapid identification of sorghum types and adulterations.

Meat quality and flavor evaluation of Nanjing water boiled salted duck (NWSD) produced by different Muscovy duck (Cairina moschata) ingredients

Reports on meat quality and flavor evaluation of Nanjing water boiled salted duck (NWSD) produced by different Muscovy duck (Cairina moschata) ingredients are limited. To select a suitable Muscovy duck ingredient for the NWSD processing, six kinds of NWSD products were produced using female (65, 70, and 75 days) and male (75, 80, and 85 days) Muscovy duck ingredients. The meat quality, volatile organic compounds (VOCs), smell and taste were investigated by using colorimeter, texture analyzer, headspace-gas chromatography-ion mobility spectroscopy (HS-GC-IMS), electronic nose (E-nose), electronic tongue (E-tongue), etc. Results exhibited that 32 iconic VOCs were obtained by using partial least squares discrimination analysis (PLS-DA), principal component analysis (PCA), and variable importance projection (VIP) methods. 80-day-old male Muscovy duck showed moderate moisture and protein content, good meat texture and bright color, diverse iconic VOCs and clear differentiation, making it the preferred ingredient for NWSD processing.

Application progress of intelligent flavor sensing system in the production process of fermented foods based on the flavor properties

Fermented foods are sensitive to the production conditions because of microbial and enzymatic activities, which requires intelligent flavor sensing system (IFSS) to monitor and optimize the production process based on the flavor properties. As the simulation system of human olfaction and gustation, IFSS has been widely used in the field of food with the characteristics of nondestructive, pollution-free, and real-time detection. This paper reviews the application of IFSS in the control of fermentation, ripening, and shelf life, and the potential in the identification of quality differences and flavor-producing microbes in fermented foods. The survey found that electronic nose (tongue) is suitable to monitor fermentation process and identify food authenticity in real time based on the changes of flavor profile. Gas chromatography-ion mobility spectrometry and nuclear magnetic resonance technology can be used to analyze the flavor metabolism of fermented foods at various production stages and explore the correlation between flavor substances and microorganisms.

Sensory Properties and Main Differential Metabolites Influencing the Taste Quality of Dry-Cured Beef during Processing

This study adopted widely targeted high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) metabolomics and multivariate data analysis methods to evaluate the correlation between changes in metabolites and their taste formation in dry-cured beef during processing. The physicochemical profile changed significantly in the maturity period (RG), especially due to the continuous hydrolysis and oxidation of proteins. The sensory characteristic of dry-cured beef was highest in saltiness, umami, overall taste, and after-taste in RG. Overall, 400 metabolites were mainly identified, including amino acids, peptides, organic acids, and their derivatives, nucleotides, and their metabolites, as well as carbohydrates. Cysteine and succinic acid were significantly up-regulated during the process of dry-curing beef compared to the control group (CG). Moreover, glutamine and glutathione were significantly down-regulated in the fermentation period (FG) and in RG. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed that glyoxylate and dicarboxylate metabolism, glutathione metabolism, alanine, aspartate, and glutamate metabolism, arginine biosynthesis, taurine, and hypotaurine metabolism were the main metabolic pathways influencing the taste of dry-cured beef during processing. Results of correlation analysis revealed that umami is positively correlated with salty, L-cysteine, L-arginine, inosine, creatinine, and succinic acid. Our study results provide a better understanding of the changes in taste substances and will contribute to quality evaluation of dry-cured beef.