Discrimination of five brands of instant vermicelli seasonings by HS-SPME/GC–MS and electronic nose

Shen, Huishan; Wei, Teng; Zhang, Zhiwei; Zheng, Qianna; Guo, Rui; Jiang, Hao; Zhang, Guoquan; Zheng, Jianmei

doi:10.1007/s13197-020-04454-x

Cited by 16 publications

(2 citation statements)

References 35 publications

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“…E-nose measurement parameters: sampling interval 1 s, rinsing time 100 s, zero adjustment time 8 s, resampling time 5 s, measurement time 260 s, carrier gas flow rate 300 mL/min, injection flow rate 300 mL/min. The response value of the sensor tended to be stable after 255 s; information was acquired at 256, 257, and 258 s; each group of samples was parallelized 5 times; and the results were selected 3 times for data analysis [19]. The types of response substances corresponding to the different sensors of the PEN3 E-nose are shown in Supplementary Materials Table S1 [20].…”

Section: Determination Of the Microstructure Of Breadmentioning

confidence: 99%

Study on the Effect of Microwaved Brewer’s Spent Grains on the Quality and Flavor Characteristics of Bread

Cheng,

Zheng,

Zhao

et al. 2024

Foods

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To enable a wider utilization of co–products from beer processing and minimize the negative effect of added grain on bread quality, flavor, and other attributes, brewer’s spent grains (BSG) are processed through microwave pretreatment, and then the microwave–treated BSG (MW–BSG) is added to bread. So far, there has been no investigation on the effect of microwave–pretreated BSG on bread quality and flavor. In this study, we examined the effects of diverse microwave treatment variables on the physicochemical structure of BSG and explored the consequences of MW–BSG on the quality and flavor of bread. The results showed that soluble dietary fiber and water–soluble protein levels in MW–BSG increased significantly (144.88% and 23.35%) at a 540 W microwave power, 3 min processing time, and 1:5 material–liquid ratio of BSG to water. The proper addition of MW–BSG positively affected the bread texture properties and color, but excessive amounts led to an irregular size and distribution of the bread crumbs. The result of electronic nose and HS–SPME–GC–MS analyses showed that the addition of MW–BSG modified the odor profile of the bread. A sensory evaluation showed mean scores ranging from 6.81 to 4.41 for bread containing 0–10% MW–BSG. Consumers found a maximum level of 6% MW–BSG acceptable. This study endeavors to decrease environmental contamination caused by brewing waste by broadening the methods by which beer co–products can be utilized through an innovative approach.

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Section: Determination Of the Microstructure Of Breadmentioning

confidence: 99%

Study on the Effect of Microwaved Brewer’s Spent Grains on the Quality and Flavor Characteristics of Bread

Cheng,

Zheng,

Zhao

et al. 2024

Foods

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show abstract

“…Instant starch noodles are made from various starch (potato, bean, or cereal starch), water and other ingredients, and processed into dry, no-cooking, convenience food ( 1 ). It usually with the seasonings sprinkled over the starch noodles and are ready to eat after soaked in boiling water for 3–4 min.…”

Section: Introductionmentioning

confidence: 99%

Combining e-nose and e-tongue for improved recognition of instant starch noodles seasonings

Shen²,

Cheng³

et al. 2023

Front. Nutr.

Self Cite

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Seasonings play a key role in determining sensory attributes of instant starch noodles. Controlling and improving the quality of seasoning is becoming important. In this study, five different brands along with fifteen instant starch noodles seasonings (seasoning powder, seasoning mixture sauce and the mixture of powder and sauce) were characterized by electronic nose (e-nose) and electronic tongue (e-tongue). Feature-level fusion for the integration of the signals was introduced to integrate the e-nose and e-tongue signals, aiming at improving the performances of identification and prediction models. Principal component analysis (PCA) explained over 85.00% of the total variance in e-nose data and e-tongue data, discriminated all samples. Multilayer perceptron neural networks analysis (MLPN) modeling demonstrated that the identification rate of the combined data was basically 100%. PCA, cluster analysis (CA), and MLPN proved that the classification results acquired from the combined e-nose and e-tongue data were better than individual e-nose and e-tongue result. This work demonstrated that in combination e-nose and e-tongue provided more comprehensive information about the seasonings compared to each individual e-nose and e-tongue. E-nose and e-tongue technologies hold great potential in the production, quality control, and flavor detection of instant starch noodles seasonings.

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The quality of beef-soybean paste and the relationship between microbial composition and flavor changes during fermentation

Zou,

Xiao,

Wang

et al. 2024

Food Sci Biotechnol

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Discrimination of five brands of instant vermicelli seasonings by HS-SPME/GC–MS and electronic nose

Cited by 16 publications

References 35 publications

Study on the Effect of Microwaved Brewer’s Spent Grains on the Quality and Flavor Characteristics of Bread

Study on the Effect of Microwaved Brewer’s Spent Grains on the Quality and Flavor Characteristics of Bread

Combining e-nose and e-tongue for improved recognition of instant starch noodles seasonings

The quality of beef-soybean paste and the relationship between microbial composition and flavor changes during fermentation

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