Abstract
Volatile profiles of peas under 9 kinds of different treatments including native, washing, blanching, precooling, freezing, steaming, boiling, frying, and freeze-drying were characterized by GC-IMS and GC-MS. The differences of volatile compounds in different peas were observed from the characteristic fingerprints by GC-IMS. The Venn diagram found that the common flavor substances codetected by GC-IMS and GC-MS were n-hexanal, nonanal, 1-octene-3-ol, benzaldehyde, 6-methyl-5-hepten-2-one, trans-2-octenal, and 2-ethyl-3,5-dimethylpyrazine, which were speculated to be the key flavor substances of peas. The cluster analysis of the heat map conducted towards the differences of volatile components in peas under different treatments; the results indicated that peas could be mainly divided into four groups, which was consistent with the above conclusion of GC-IMS. Eight sensory descriptors were used to evaluate the aroma notes: sweet flowers, fat fragrance, waxy aldehydes, mushroom hay, roasted potato with nuts, vegetable-like bean, spicy dry tar, and bitter almond from the sensory analysis, and the sensory analysis also showed good agreement with the results of GC-IMS and GC-MS. The results indicated that the volatile compounds of peas under different treatments could be visualized and identified quickly via GC-IMS, and the samples could be clearly classified based on the difference of volatile compounds. Practical Application. In the study, fingerprints coupled with cluster analysis were a visualized method for the identification of volatile compounds. Meanwhile, a new method, the Venn diagram with OAV, was used to identify the key-aroma of products. Finally, a rapid method is established to classify products by GC-IMS. In future practical applications, GC-IMS can be used to classify products from different origins and different manufacturers. Similarly, it can identify fake and inferior products and whether the products have deteriorated. In addition, this research will provide a new strategy to find the relationship between flavor compounds and various processed technology towards different cereals.
Highlights
Peas (Pisum sativum L.) are the type of legume most widely used for human consumption, and they are widely cultivated around the world [1, 2]
GC-Ion mobility spectrometry (IMS) was used to analyze the variations in the volatile compositions of peas under different treatments, and the fingerprints were established to confirm the characteristic substance of the peas. e established fingerprints coupled with cluster analysis of GC-MS results would be a visualized and useful method for the identification of volatile compounds in peas and provide a novel alternative method for the classification of various peas products
Experimental data were analyzed statistically using SPSS 16.0 (IBM, Armonk, NY, USA); radar chart and cluster heat map analysis were performed by Origin Pro 8.0 software (Origin Lab Inc., USA). e results were expressed as the mean ± SD of triple measurements. e statistical analyses were calculated using a one-way analysis of variance (ANOVA); differences were considered as significant at a level of p < 0.05
Summary
Peas (Pisum sativum L.) are the type of legume most widely used for human consumption, and they are widely cultivated around the world [1, 2]. Our team previously has studied the effects of three processing methods (oven drying after boiling, frying, and freeze-drying) on aroma components of fresh peas, and a comprehensive analysis showed that the fresh peas by freeze-drying and oven-drying after boiled had better retention of aromatic compounds. GC-IMS is a new hybrid technology, which can analyze the test results quickly, intuitively, and accurately Another instrument, GC-MS, is a widespread and effective method based on solid-phase microextraction, gas phase separation, and mass spectrometry for analyzing volatile compounds in food samples. E established fingerprints coupled with cluster analysis of GC-MS results would be a visualized and useful method for the identification of volatile compounds in peas and provide a novel alternative method for the classification of various peas products GC-IMS was used to analyze the variations in the volatile compositions of peas under different treatments, and the fingerprints were established to confirm the characteristic substance of the peas. e established fingerprints coupled with cluster analysis of GC-MS results would be a visualized and useful method for the identification of volatile compounds in peas and provide a novel alternative method for the classification of various peas products
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