Neural network-based chilled fresh pork shelf life prediction method
A neural network and prediction method technology, applied in the field of meat quality prediction, can solve the problem of neglecting attention, and achieve the effect of accurate shelf life and quality status
Pending Publication Date: 2021-02-09
WUHAN POLYTECHNIC UNIVERSITY
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Problems solved by technology
At present, the establishment of pork shelf life prediction models in most research reports is based on spoilage microorganism prediction models, and then predicts food shelf life, but ignores the attention to other quality indicators, which makes the research have certain limitations.
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[0034] The present invention will be further described in detail below in conjunction with the embodiments, so that those skilled in the art can implement it with reference to the description.
[0035] Embodiments of the present invention provide a method for predicting the shelf life of chilled fresh pork based on neural networks, including:
[0036] S1, using the neural network model to construct the initial model for predicting the total number of chilled pork colonies; the above-mentioned model can use the existing RBF neural network model, and will not be repeated here;
[0037] S2. Obtain the initial total number of colonies of multiple chilled pork samples and their storage temperature, storage gas environment, storage humidity and storage time data, and detect the final total number of colonies of chilled pork;
[0038] S3, the initial total number of colonies of chilled pork and the data of storage temperature, storage gas environment, storage humidity and storage tim...
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The invention discloses a neural network-based chilled fresh pork shelf life prediction method. The method comprises the steps of constructing a chilled fresh pork colony count prediction initial model, inputting an input sample into the chilled fresh pork colony count prediction initial model for training to obtain a chilled fresh pork colony count prediction model, inputting the count of initialcolony of the chilled fresh pork to be predicted and the storage temperature, the storage gas environment, the storage humidity and the storage time data of the chilled fresh pork into the chilled fresh pork colony count prediction model, and calculating to obtain the predicted chilled fresh pork colony count, and calculating the shelf life of the chilled fresh pork according to the predicted chilled fresh pork colony count to obtain the predicted shelf life of the chilled fresh pork. The invention provides a neural network-based chilled fresh pork shelf life prediction method. The shelf lifeof the chilled fresh pork is predicted according to the storage temperature, the storage gas environment, the storage humidity and the storage time of the chilled fresh pork.
Description
technical field [0001] The invention relates to the field of meat quality prediction. More specifically, the present invention relates to a method for predicting the shelf life of chilled fresh pork based on a neural network. Background technique [0002] At present, there are three main types of pork on the market: cold fresh meat, hot fresh meat and frozen meat. Chilled fresh meat is also called chilled meat. During the whole process of processing and logistics transportation, this kind of pork is always in a low temperature environment of 0-4 ℃. Because of its delicious taste and high nutritional value, cold fresh pork is gradually occupying the market of traditional hot fresh meat and frozen meat, and its consumption ratio is gradually increasing. According to the "2016-2021 China Pork Industry Market Research and Investment Opportunity Research Report" of the China Business Industry Research Institute, the annual growth rate of pork production was 1.88% from 2005 to 2...
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IPC IPC(8): G01N33/12G06N3/04G06N3/08
CPCG01N33/12G06N3/04G06N3/08
Inventor 侯温甫王宏勋艾有伟周敏王丽梅闵婷胥伟
Owner WUHAN POLYTECHNIC UNIVERSITY