We explored the utilization of both linear regression and machine learning methodology to improve the prediction of leaf chlorophyll content (LCC) in citrus ...
Our findings revealed that using just a few spectral parameters can efficiently estimate LCC in citrus trees, showing substantial promise for implementation in ...
Our findings revealed that using just a few spectral parameters can efficiently estimate LCC in citrus trees, showing substantial promise for implementation in ...
Oct 15, 2020 · This study mainly aimed to assess differences in hyperspectral reflectance to estimate N and Chl contents and enable nondestructive estimation ...
Missing: Utilizing Citrus
Jun 26, 2024 · Hyperspectral remote sensing is one of the most frequently used methods for estimating chlorophyll content. Numerous studies based on data ...
Nov 14, 2023 · In this study, we combined the derivative processing techniques and dimensionality reduction algorithms to improve the hyperspectral estimation ...
We proposed a novel method for estimating the LCC of citrus by combining an ensemble learning regression model based on Hyperopt optimization (H-ELR) with ...
Missing: Utilizing | Show results with:Utilizing
In this study, we analyzed hyperspectral data from grape leaves of different varieties and fertility periods with FOD to monitor the leaves' chlorophyll ...
Jul 2, 2024 · Utilizing hyperspec- tral reflectance and machine learning algorithms for non-destruc- tive estimation of chlorophyll content in citrus leaves.
In this study, we confirmed the high accuracy of using ground hyperspectral data, feature band selection, and the CatBoost model to estimate chlorophyll content ...