| Predicate |
Object |
| assignee |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_fa9d66b838a3e187f208c5c40d0d7972 |
| classificationCPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N5-01
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01N21-55
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01N21-33
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01N21-25
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16C20-20
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16C20-70
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01N33-0098 |
| classificationIPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16C20-20
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16C20-70
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G01N21-25
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G01N21-33
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N5-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G01N33-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G01N21-55 |
| filingDate |
2020-11-10-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_58e85fe0d86b339e321b8d29667d6e0d
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_196b63cf426030fece825b7ecfbd284d
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_7056f2eff6d2cb5cd55ad866e4b1dbd5
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_deeaaa6e54a58a15d40d382815378fa9
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_2c47c7f607ee5a8a664a110b3c26c656
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_ced4dfc1bbb380f97b7539cd6ed62a1b
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_a37381db63bad0e0d5fe856ef206552d
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_ca0588b7f6c0425b62233b84b715306f
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_8c89b947380c2fcfa07379f91a810cfb |
| publicationDate |
2021-02-12-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber |
CN-112362812-A |
| titleOfInvention |
A remote sensing inversion model and method for the ratio of chlorophyll carotenoid content in rice leaves based on Lars algorithm |
| abstract |
The invention provides a remote sensing inversion model for the ratio of chlorophyll carotenoid content in rice leaves based on the Lars algorithm. The remote sensing inversion model for the ratio of chlorophyll carotenoid content in rice leaves based on the Lars algorithm is a Python language Lars regression model, and further provides Model parameters for this Lars regression model. It also provides a remote sensing inversion method for the ratio of chlorophyll carotenoid content in rice leaves based on the Lars algorithm. The remote sensing inversion model of the ratio of chlorophyll carotenoid content in rice leaves based on the Lars algorithm of the present invention can quickly and accurately obtain the ratio information of chlorophyll carotenoid content in rice leaves, and overcomes the spectral superposition effect of rice leaves caused by complex rice components. It is difficult to determine the characteristic band of the ratio of chlorophyll carotenoid content, which greatly improves the accuracy of the inversion model of the ratio of chlorophyll carotenoid content in rice leaves. |
| isCitedBy |
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-113945524-A |
| priorityDate |
2020-11-10-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type |
http://data.epo.org/linked-data/def/patent/Publication |