Application of Support Vector Machine Regression and Partial Least-Square Regression Models for Predicting Sugarcane Leaf Nutrients Content Using Near Infra-Red Spectroscopy,Communications in Soil Science and Plant Analysis

当前位置： X-MOL 学术 › Commun. Soil Sci. Plant Anal. › 论文详情

Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)

Application of Support Vector Machine Regression and Partial Least-Square Regression Models for Predicting Sugarcane Leaf Nutrients Content Using Near Infra-Red Spectroscopy
Communications in Soil Science and Plant Analysis ( IF 1.8 ) Pub Date : 2024-02-04 , DOI: 10.1080/00103624.2023.2265426
Aweke A. Mitku _{1,

2} , Louis Titshall _{3,

4} , Temesgen Zewotir ₁ , Delia North ₁

Affiliation

Near infra-red spectroscopy (NIRS) has been suggested as a rapid, cost-effective, and accurate diagnostic tool for leaf nutrient analysis that could replace more traditional laboratory diagnostics....

中文翻译：