Probing into the Mechanism of Adding Tussah Pupa Powder to Improve the Deterioration of a Pork Batter Emulsified Gel
International Journal of Food Science & Technology(2024)
Shenyang Agr Univ
Abstract
The purpose of this experiment was to explore the improvement of tussah pupa powder on the deterioration of pork batter emulsion gel by using proteomics, distribution of moisture, rheological properties and surface hydrophobicity. The results showed that the myosin decomposed as the heating temperature increased; as the increase of the addition proportion of tussah pupa powder at each sterilisation temperature point, compared to the control group, the pH of a pork batter emulsified gel showed a significant increased trend (P < 0.05); the low molecular weight proteins or formed oligomers of tussah pupa powder could be used as fillers to participate in the formation process of gel network; the vitellogenin of tussah pupa powder could form a 'skeleton' in the pork batter system; as the sterilisation temperature at 100 degrees C (30 min) and 110 degrees C (30 min), the surface hydrophobicity was the largest as the addition amount 2%. In short, the tussah pupae powder could improve the deterioration characteristics of the pork batter emulsified gel by influencing the pH, surface hydrophobicity and the formation of gel network of pork batter system. This research provided theoretical support for improving the process property of the meat products.
MoreTranslated text
Key words
Deterioration,gel,proteomics,tussah pupa powder
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined