One of the important stages for development an optical
sensor for detection of winter wheat growth
characteristics is determination of significant
wavelengths using multi spectral reflectance data.
Diffuse reflectance of crop leaves was recorded with
other crop variables during growth stages. Multivariate
ana
lysis including partial least squares regression
(PLSR) and stepwise multiple linear regression (SMLR)
procedures were used to determine important
wavelengths. The results showed strong relationships
between predicted and actual crop variables. The best
pr
ediction model built on wavelengths selected by
SMLR so that R2, root mean square and relative error
(RE) for the validation dataset were 0.85, 1.56 and
3.64% for SPAD, 0.89, 413 and 6.21% for grain yield,
and 0.84, 0.56 and 4.85% for protein content
کلید واژگان :
Appropriate Wavelengths - Prediction of Grain Yield - Protein Content
