Abstract
This study aims to estimate the spatial variation of sugarcane Canopy Nitrogen Concentration (CNC) using spectral data, which were measured from a spaceborne hyperspectral image. Stepwise Multiple Linear Regression (SMLR) and Support Vector Regression (SVR) were applied to calibrate and validate the CNC estimation models. The raw spectral reflectance was transformed into a First-Derivative Spectrum (FDS) and absorption features to remove the spectral noise and finally used as input variables. The results indicate that the estimation models developed by non-linear SVR based Radial Basis Function (RBF) kernel yield the higher correlation coefficient with CNC compared with the models computed by SMLR. The best model shows the coefficient of determination value of 0.78 and Root Mean Square Error (RMSE) value of 0.035% nitrogen. The narrow sensitive spectral wavelengths for quantifying nitrogen content in the combined cultivar environments existed mainly in the electromagnetic spectrum of the visible-red, longer portion of red edge, shortwave infrared regions and far-near infrared. The most important conclusion from this experiment is that spectral signals from the space hyperspectral data contain the meaningful information for quantifying sugarcane CNC across larger geographic areas. The nutrient deficient areas could be corrected by applying suitable farm management.
Highlights
Sugarcane (Saccharum spp. hybrid) is a tall-growing perennial crop widely cultivated in the tropical and subtropical regions of the world [1]
The main objective of this study is to estimate the spatial variation of sugarcane mCaaninopoybjeNcittirvoegeonf tChiosnscteundtryatiisonto(CesNtiCm)atferotmhe asnpaEtiOal-1vaHriyaptieornioonf ismugaagrecainne cComanboipnyedNciturlotigveanr Cenovnicreonntmraetinotns.(CTNhCe )cfaropmabailnitEyOo-1f HSMypLeRri-onanimdagSVe iRn-bcoamsebdinaepdpcruolaticvhaersenfovriroensmtimenattsin
The ranges of nitrogen content in the leaf samples are quite small. This is mainly because sugarcane plots in the study areas are in the mature stage (9–10 months)
Summary
Sugarcane (Saccharum spp. hybrid) is a tall-growing perennial crop widely cultivated in the tropical and subtropical regions of the world [1]. In Thailand, sugarcane is mostly used in the sugar and ethanol energy industries. The precise estimation of sugarcane productivity allows the establishment of deliberate policies to balance the amount of sugarcane within sugar and ethanol energy. Nitrogen is considered a key indicator of the physiological susceptibility of water availability, pests, disease and crop nutrient stress, which could potentially affect crop productivity [2]. Nitrogen is one of the primary regulators of several leaf physiological processes, such as photosynthesis, respiration, and transpiration [3]. An increased susceptibility to pests or leaf blades turns a sugarcane leaf from light green to yellow, short, slender stalks and low productivity. To measure the nitrogen concentration using the conventional method, a great number of leaf samples from fields are needed. The conventional method is not appropriate for large areas
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