Raun [13] reported that six of nine sites over two years showed a strong relationship between INSEY and grain yield at harvest (coefficient of determination (r2 = 0.83, P < 0.01). However, Teal [14] found there was no significant increase or decrease in the strength of this relationship when NDVI readings were adjusted by either GDD or days from planting to sensing (DFP) selleck inhibitor when GDD was positive.Several studies have suggested that growth stage, or time of sensing, were important in the ability to predict yield [13,14,16]. Raun [13] and Lukina [16] reported that the strongest relationship between NDVI and winter wheat grain yield was between Feekes 4 to 6, while Teal [14] found that the optimum growth stage for predicting corn yield was at the eight leaf vegetative phase, or between 800�C1,000 GDD.
They found a weak relationship during early growth stages, which was attributed to the yield potential not fully developed. Additionally, they explained the disappearance of this weaker relationship later in the season was due to canopy closure, which resulted in the inability to detect variability associated with differing N-rates. Several reports have shown that an estimate of yield alone is poorly correlated with optimum N rate [17]. However, Raun [11] showed the potential of utilizing a predicted YP as a component of N management scheme. This technology has shown the ability to improve N management decisions in many cropping systems across USA, Canada, Mexico, and other countries [18�C20]. These reports suggest the potential of using yield prediction as an integral part of an N management decision tool to improve recommendations in crop production.
Previous reports have documented the ability of NDVI to estimate sugarcane yield potential, however, most of these reports have been focused on satellite based platforms or passive sensors with few demonstrating the ability of a active ground-based remote sensor to estimate sugarcane yield [21�C25]. Therefore, the objectives of this study were to: (1) determine the ability of an in-season estimation of NDVI to predict sugarcane yield potential; and (2) determine optimum timing for predicting sugarcane in-season yield potential.2.?Experimental SectionResearch was conducted in St. Gabriel (30��15��13��N 91��06��05��W) and Jeanerette (29��54��59��N 91��40��21��W), Louisiana, on several N-rate field trials. Soils utilized for each experiment are as follows: Commerce silt loam (Fine-silty, mixed, superactive, non-acid, thermic Fluvaquentic Endoaquept) for Experiments 1, 2, 3, 4, and 9; Canciene silty clay loam (Fine-silty, mixed, superactive, Batimastat nonacid, hyperthermic Fluv
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