内容: Human milk (HM) not only provides nutrients for infants but also produces volatile odors that can be perceived by newborns, influencing their dietary behavior, flavor learning, and food preferences. Meanwhile, the design of infant formula is gradually getting closer to HM in terms of nutrient composition rather than sensory performance. Volatile compounds in HM are produced upon lipid, protein, and carbohydrate degradation and via Maillard reactions. they primarily consist of fatty acids, terpenes, aldehydes, ketones, alcohols, furans, and pyrans. Moreover, the factors influencing HM flavors are critically involved in dietary intake, HM macronutrients, storage temperature, storage time, and sterilization conditions. this review aimed to summarize the formation, composition characteristics, influencing factors, and analytical techniques of HM odor by summarizing existing studies. relevant conclusions can provide a theoretical basis for future research on the identification, evaluation, and simulation of HM flavor profiles.

内容: Deep learning, a core branch of artificial intelligence, has shown great potential in food flavor analysis, prediction and optimization with its powerful data processing and pattern recognition capabilities. this article reviews deep learning applications in food flavor, discussing various deep learning algorithms and models including artificial neural network, convolutional neural network, recurrent neural network, autoEncoder, graph neural network, and generative adversarial network. besides, the latest progress and development trends of deep learning are discussed in this field. Compared with traditional flavor analysis methods, deep learning methods have obvious advantages and important application prospects in the field of food flavor. With the continuous advancement of technology in the future, it is expected that more deep learning applications will appear in the food industry.

内容: a non-experimental approach based on protein sequences of Takifugu rubripes (a well-known fish for its umami taste) was initially employed using the Procleave database for virtual endogenous enzyme digestion, aimed at screening and identifying novel umami peptides. the potential umami peptides were screened through a dual-strategy approach combining sequence-based analysis and molecular docking techniques. Consequently, five umami peptides (faGDDaPr, HEGEQGQEG, aaPHENatLH, EsHQQtLDD, and GEVED) were selected, synthesized and subjected to comprehensive sensory evaluation, electronic tongue assessment and kinetic analysis using the t1r1-Vft biosensor. sensory evaluation demonstrated that these peptides exhibited low umami thresholds, ranging from 0.195 to 0.281 mg/mL, with primary binding sites at asn150, ser248, arg151, thr154, and Lys155 on the receptor. the kinetic analysis revealed a linear correlation between the kinetic values and peptide concentrations within the range of 10–15–10–5 mg/mL, consistent with sensory evaluation results. therefore, the virtual hydrolysis and screening strategies, designed for the rapid identification of novel umami peptides from T. rubripes, emerge as a practicable and efficient means for the rapid acquisition of peptides and the enrichment of the umami peptides database.

内容: a non-experimental approach based on protein sequences of Takifugu rubripes (a well-known fish for its umami taste) was initially employed using the Procleave database for virtual endogenous enzyme digestion, aimed at screening and identifying novel umami peptides. the potential umami peptides were screened through a dual-strategy approach combining sequence-based analysis and molecular docking techniques. Consequently, five umami peptides (faGDDaPr, HEGEQGQEG, aaPHENatLH, EsHQQtLDD, and GEVED) were selected, synthesized and subjected to comprehensive sensory evaluation, electronic tongue assessment and kinetic analysis using the t1r1-Vft biosensor. sensory evaluation demonstrated that these peptides exhibited low umami thresholds, ranging from 0.195 to 0.281 mg/mL, with primary binding sites at asn150, ser248, arg151, thr154, and Lys155 on the receptor. the kinetic analysis revealed a linear correlation between the kinetic values and peptide concentrations within the range of 10–15–10–5 mg/mL, consistent with sensory evaluation results. therefore, the virtual hydrolysis and screening strategies, designed for the rapid identification of novel umami peptides from T. rubripes, emerge as a practicable and efficient means for the rapid acquisition of peptides and the enrichment of the umami peptides database.

内容: soybean paste has been a prominent condiment in East asia for millennia. Nonetheless, the current methodologies for comprehensively assessing the quality of commercially available soybean paste through sensory evaluation or traditional instruments present significant challenges. in this study, contemporary detection techniques and machine learning methodologies were employed to quantitatively characterize and evaluate the overall quality of soybean paste. sensory evaluations were conducted on 33 varieties of commercial soybean paste using three types of sensors: a colorimeter, an electronic nose (E-nose), and an electronic tongue (E-tongue) for detection purposes. subsequently, machine learning models, including support vector regression (sVr), random forest, extreme gradient boosting, bayesian ridge regression, ridge regression, k-nearest neighbors, and artificial neural network, were developed based on the sensory evaluation data to characterize and assess the overall quality of the soybean paste. the findings from both sensory evaluations and sensor detection indicated notable differences between the various soybean pastes. soybean pastes can be distinguished using three sensors. the quantitative characterization model informed by the sensor data revealed that the sVr model exhibited the highest coefficient of determination (R2) of 0.999 8 for the training set and 0.997 0 for the prediction set, which was close to the ideal value of 1. additionally, the root mean square error for the prediction set was the lowest at 0.535 9. these results suggest that sVr demonstrates superior performance in cross-validation and testing, aligning closely with human sensory perceptions, thereby establishing it as the most effective predictive model. this study underscores the potential of integrating sensor data with modern machine learning techniques to supplement traditional sensory evaluations for comprehensive characterization and assessment of soybean paste quality. the outcomes of this study offer significant insights and guidance for the advancement of the soybean paste industry and the enhancement of soybean paste quality.

内容: the development of innovative products such as ice cider is an important means of adding value to the industry. this research aimed to examine the aroma profiles of late and ice-harvested Changfu No.2 (Cf2) apples, along with their essential phytochemicals. samples were collected at 15-day intervals, starting from the commercial harvest and continuing through to the ice harvest. through gas chromatographymass spectrometry-olfactometry/detection frequency analysis, 21 aroma components were identified as the key odorants of Cf2. the ice-harvested apples were used to make ice cider, and then it was compared with the apple juice produced during the same period. Quantitative analysis using headspace solid phase microextraction gas chromatography-mass spectrometry and subsequent odor activity value analysis revealed increasing trends in most aroma compounds leading up to the ice harvest. Moreover, there are more aroma compounds in ice cider than in apple juice, suggesting that late and ice harvests are beneficial for enhancing the aggregation of apple aroma. these findings establish a scientific foundation for assessing the potential for producing ice cider from late and ice-harvested apples from the Loess Plateau area of China.

内容: to investigate the mechanism of yeast inoculation on aroma improvement of Jinhua ham, microbial succession, myofibrillar protein hydrolysis, enzyme activities, amino acid metabolism, volatile compound evolutions, sensory attributes, and the relationship between key volatiles and sensory attributes were investigated during the processing of Jinhua ham with the inoculation of Rhodotorula mucilaginosa aUMC 9298 (rM), Candida parapsilosis d70a (CP) or Pichia kudriavzevii Xs-5 (PK), respectively, while ham samples without any inoculation were defined as the control group (CK). the inoculation of rM, CP, and PK significantly increased the counts of fungal communities, and the fungal counts of the final products after dry-ripening for 40 days reached 6.65, 6.33, 7.35, and 7.55 (lg (CfU/g)) in CK, PK, rM, and CP groups, respectively; the treatment of rM showed the highest sensory scores in meaty aroma, nutty aroma, and overall acceptance among these groups. the treatment of rM showed the highest capability to degrade myosin and actin. the total contents of free amino acids increased significantly from 2 565.89 mg/100 g of PK to 3 141.46 mg/100 g of rM and 2 714.76 mg/100 g of CP in the final products (P < 0.05), and the most release of free amino acids was observed in rM among these groups. the activities of keto acid decarboxylase, aromatic and branched chain aminotransferase, and branched chain amino acid dehydrogenase in rM were significantly higher than those of CP and PK, which contributed to the metabolism of aromatic and branched chain amino acids. Gas chromatography-mass spectrometry and multivariate statistics demonstrated that benzaldehyde, 3-methylbutanal, 2,5-dimethylpyrazine, and 2,6-dimethylpyrazine were responsible for the improvement of overall acceptance of Jinhua ham with rM inoculation.

内容: adjunct culture can be used to improve typical cheese aroma and contribute to proteolysis during the ripening process. in the present study, some lactobacilli (Lactobacillus casei, Lactobacillus delbrueckii subsp. bulgaricus, Lactiplantibacillus plantarum and two strains of Lactobacillus helveticus) were tested in model cheeses during 120 days of ripening at the temperatures of 8 and 16 °C. it aimed to investigate the effects of these parameters on free amino acid (faa) content, volatile aroma profile, and sensory properties in cheese. Volatile compounds in cheese samples were determined by gas chromatography-mass spectrometry and faa content by high performance liquid chromatography. Principal component analysis, sparse partial least squares-discriminant analysis, and heat map cluster analysis were performed to distinguish different volatile aromas and faas in cheeses according to ripening time and temperature as well as adjunct culture. the predominant faas in the cheese were arg, tyr, Val, Leu, trp, and Lys, regardless of ripening. the highest concentration of Glu was observed in cheeses containing L. bulgaricus, followed by cheeses with L. helveticus and L. plantarum. a total of 41 volatile compounds were identified, with variations noted between the different cheeses; in particular, L. helveticus played a crucial role in flavor development. the ripening temperature also influenced the production of volatile compounds: at 16 °C, cheeses with L. bulgaricus and L. helveticus were characterized by alcohols, esters, and acids, while cheeses with L. plantarum contained mainly, acids, aldehydes, and ketones. for lactobacilli, especially the combination of L. helveticus, L. bulgaricus, and L. plantarum, can be added to the cheese to improve and intensify the flavor. it was seen that the positive effects of selected adjunct cultures on the aroma and taste of model cheeses were related to volatiles and faas.

内容: in this study, headspace solid phase microextraction (SPME), solvent-assisted flavor evaporation (SaFE) and gas chromatography-mass spectrometry were used to detect the changes in aroma components of mandarin orange juice before and after sterilization, the characteristic flavor substances were also analyzed using odor activity value, principal component analysis, and heatmap. The results showed that 149 volatile components were detected, mainly including terpenes, esters, alcohols, aldehydes, and ketones. Compared with unpasteurized juice, the SPME method measured that 38 new volatile components were produced after pasteurization, while 25 volatile components disappeared; the SaFE method measured the production of 34 volatile components after pasteurization, while 18 volatile components disappeared. β-Myrcene, D-limonene, linalool, and p-cymene were important volatile substances in mandarin orange juice. These results provide a reference for further control and detection of mandarin orange juice processing flavors.

内容: Douchi is a fermented food, which has a unique flavor after natural fermentation. However, the correlation between the microbial community and volatile flavor compounds is poorly studied. This study used MiSeq sequencing and headspace solid-phase microextraction-gas chromatography-mass spectrometry techniques to detect the dynamic changes of microbial succession and volatile compounds during fermented douchi and Spearman correlation analysis. The results revealed that a total of 33 key flavor compounds were identified, among which the esters contributing to fruity and floral aromas were the main ones. The dominant strains included Bacillus spp., Millerozyma spp., and Aspergillus spp. Further analysis showed that in the postfermentation stage, various yeast species were highly positively correlated with key flavor compounds such as 2-ethyl-methylbutanoate (fruity) and phenylacetaldehyde (floral). Furthermore, Aspergillus spp. showed a positive correlation with 1-octen-3-one (mushroom). This study provides new insights into the analysis of microbial community succession and the characteristic flavor of Yangjiang douchi, which also offers valuable guidance for quality control and the subsequent screening of potential new starter cultures.