Data fusion of XRF and vis-NIR using p-ComDim to predict some fertility attributes in tropical soils derived from basalt

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

hi@scite.ai

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Data fusion of XRF and vis-NIR using p-ComDim to predict some fertility attributes in tropical soils derived from basalt

Cited by 5 publications

References 46 publications

Combination of feature selection and geographical stratification increases the soil total nitrogen estimation accuracy based on vis-NIR and pXRF spectral fusion

Combination of feature selection and geographical stratification increases the soil total nitrogen estimation accuracy based on vis-NIR and pXRF spectral fusion

Optimization of pXRF instrumentation conditions and multivariate modeling in soil fertility attributes determination

Would it be better for partition prediction of heavy metal concentration in soils based on the fusion of XRF and Vis-NIR data?

Contact Info

Product

Resources

About