id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
aiti-12683	Jonni Firdaus; Usman Ahmad; I Wayan Budiastra; I Dewa Made Subrata	Estimating Macronutrient Content of Paddy Soil Based on Near-Infrared Spectroscopy Technology Using Multiple Linear Regression	2024	15	.pdf	application/pdf	8249	367	51	Table 7 MLR model calibration and validation result for estimating total potassium with several pretreatment spectra data Model Spectra pretreatment data Number of wavelengths Calibration Validation r R2 RMSE (g/100 g) RPD RMSE (g/100 g) RPD 1 R (raw data) 6 0.90 0.81 0.051 2.3 0.057 2.2 2 Rdg1 4 0.97 0.94 0.029 4.2 0.036 3.6 3 Rdg2 4 0.97 0.93 0.031 3.8 0.037 3.4 4 Rsnv 4 0.95 0.91 0.037 3.2 0.034 3.7 5 Rnorm 4 0.94 0.88 0.042 2.9 0.055 2.3 6 A 4 0.90 0.82 0.051 2.3 0.055 2.3 7 Adg1 4 0.96 0.93 0.032 3.7 0.035 3.8 8 Adg2 4 0.96 0.92 0.034 3.5 0.050 2.6 9 Asnv 4 0.95 0.91 0.036 3.3 0.034 3.6 10 Anorm 4 0.93 0.87 0.044 2.7 0.063 2.0 The best model is written in bold, r: coefficient correlation, R2: coefficient determination, RMSE: The reflectance data undergoes various pretreatment techniques, and MLR models are calibrated using the forward method to achieve correlations exceeding 0.90.	cache/aiti-12683.pdf	txt/aiti-12683.txt