http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-111208241-B
Outgoing Links
Predicate | Object |
---|---|
classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01N30-8696 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01N30-68 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-04 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-08 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01N30-06 |
classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G01N30-68 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G01N30-86 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-04 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G01N30-06 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-08 |
filingDate | 2020-03-03-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
grantDate | 2021-10-26-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
publicationDate | 2021-10-26-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
publicationNumber | CN-111208241-B |
titleOfInvention | Method for predicting frying oil quality based on combination of electronic nose and artificial neural network |
abstract | On the basis of building a model for volatile components, TPC and polar components subdivision (TGP, ox-TG and THP) of the frying oil, a sample to be tested is subjected to rapid detection of a gas-phase electronic nose and is subjected to neural network modeling by introducing matlab, so that the content of each polar component can be directly and synchronously predicted, the model is well predicted, a convenient and time-saving method is provided for controlling the oil quality on an actual fried food production line, the monitoring of the quality change of the frying oil on the fried food production line is facilitated, and a reliable basis is provided for accurately evaluating the safety of the fried food. |
priorityDate | 2020-03-03-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
type | http://data.epo.org/linked-data/def/patent/Publication |
Incoming Links
Total number of triples: 52.