A method of joint evaluation of mustard sauce flavor level by using taste system and electronic nose
A mustard sauce and electronic nose technology, which is applied in the field of condiment analysis and identification, can solve the problems of complex chemical index relationship and cannot replace sensory grading, etc., and achieves the effect of comprehensive information, rapid and accurate prediction of simulation effect, and high promotion and application value.
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Embodiment 1
[0038] Example 1: A method for jointly evaluating the flavor level of high-quality green mustard sauce based on the taste system and electronic nose
[0039] Firstly, a scientific sensory evaluation system was established according to the flavor characteristics of the mustard sauce studied. Summarize the descriptions of flavor evaluation factors by experts, and make an objective and fair score. Secondly, electronic nose and electronic tongue detection are carried out on mustard sauce products to obtain sensor characteristic value data. Finally, the data is integrated into the eigenvalues required by the random forest model, and the training samples and test samples are continuously generated by using Matlab language programming, and several decision trees are generated from the training samples to establish the random forest model. The number of variables in the tree nodes of the decision tree and the number of decision trees in the random forest are optimized, and the test...
Embodiment 2
[0042] Example 2: A method for jointly evaluating the flavor level of inferior wasabi based on taste system and electronic nose
[0043] Firstly, a scientific sensory evaluation system was established according to the flavor characteristics of the mustard sauce studied. Summarize the descriptions of flavor evaluation factors by experts, and make an objective and fair score. Secondly, electronic nose and electronic tongue detection were carried out on the mustard sauce product to obtain sensor characteristic value data. Finally, the data is integrated into the eigenvalues required by the random forest model, and the training samples and test samples are continuously generated by using Matlab language programming, and several decision trees are generated from the training samples to establish the random forest model. The number of variables in the tree nodes of the decision tree and the number of decision trees in the random forest are optimized, and the test results are dete...
Embodiment 3
[0046] Example 3: A method for jointly evaluating the flavor level of high-quality mustard hot sauce based on the taste system and electronic nose
[0047] Firstly, a scientific sensory evaluation system was established according to the flavor characteristics of the mustard sauce studied. Summarize the description of each evaluation factor by the experts, and give an objective and fair score for each evaluation factor, and each review item is scored on a 100-point scale. Secondly, electronic nose and electronic tongue detection are carried out on mustard sauce products to obtain sensor characteristic value data. Finally, the data is integrated into the eigenvalues required by the random forest model, and the training samples and test samples are continuously generated by using Matlab language programming, and several decision trees are generated from the training samples to establish the random forest model. The number of variables in the tree nodes of the decision tree and...
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