| Title | Sparse reproducible machine learning for near infrared hyperspectral imaging: Estimating the tetrahydrocannabinolic acid concentration in Cannabis sativa L. |
| Publication Type | Journal Article |
| Year of Publication | 2023 |
| Authors | Abeysekera, S.K., Robinson A., Ooi M.P.-L., Kuang Y.C., Manley-Harris M., Holmes W., Hirst E., Nowak J., Caddie M., Steinhorn G., and Demidenko S. |
| Journal | Industrial Crops and Products |
| Volume | 192 |
| Date Published | 2023 |
| ISSN | 09266690 (ISSN) |
| Keywords | Cannabis, Canonical correlations analysis, concentration (composition), Cultivation, data interpretation, estimation method, Hemp, herb, high performance liquid chromatography, Hyperspectral imaging, Infrared devices, infrared imagery, Least squares approximations, Machine learning, Near Infrared, Near-infrared, Near-infrared hyperspectral imaging, Partial least square regression, Performance assessment, Real time, regression, Regression analysis, Reproducibilities, reproduction, Sparsity, Tetrahydrocannabinolic acid, Wavelength |
| URL | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85144472498&doi=10.1016%2fj.indcrop.2022.116137&partnerID=40&md5=407a8ebac8d13bf408152c1273917361 |
| DOI | 10.1016/j.indcrop.2022.116137 |
