高光谱土壤速效钾预测模型数据

可以用于高光谱土壤有效钾预测,输入为土壤样本的光谱401.366nm吸光度，403.609nm吸光度，405.852nm吸光度，输出为土壤有效钾预测。该模型帮助解决了土壤有效钾和土壤光谱吸光度关系建模的问题。使用光谱仪器采集土壤光谱数据，将采集的土壤光谱数据使用传统算法，多元线性回归算法等方式以预测土壤有效钾。该模型通过输入土壤光谱401.366nm吸光度、403.609nm吸光度、405.852nm吸光度，来输出预测的土壤有效钾。

This dataset can be used for hyperspectral prediction of soil available potassium. The input consists of the absorbance values of soil samples at 401.366 nm, 403.609 nm and 405.852 nm, while the output is the predicted soil available potassium. This model resolves the issue of modeling the relationship between soil available potassium and soil spectral absorbance. Soil spectral data are collected using a spectrometer, and traditional algorithms such as multiple linear regression are employed to predict soil available potassium based on the collected soil spectral data. The model takes the absorbance measurements at these three specific wavelengths as input to generate the predicted soil available potassium.