Abstract
Abstract. We evaluate the detection and discriminative strength of three different satellite spectral settings, namely, HyspIRI, the forthcoming Landsat 9 and Sentinel 2-MSI, in mapping tomato (Solanum lycopersicum) plants grown under hydroponic system using humanexcreta derived materials (HEDM), namely, anaerobic baffled reactor (ABR) effluent and nitrified urine concentrate (NUC) and commercial hydroponic fertilizer mix (CHFM) as nutrient sources. Partial least squares – discriminant analysis (PLS-DA) and discriminant analysis (DA) were applied to discriminate tomatoes grown under these different nutrient sources. Results of this study showed that spectral settings of HyspIRI sensor can better discriminate tomatoes grown under different fertilizer regimes when compared to Landsat 9 OLI and Sentinel-2 MSI spectral configurations. For instance, based on DA algorithm, HyspIRI exhibited high overall accuracy of 0.99 and a kappa statistic of 0.99 whereas Landsat OLI and Sentinel-2 MSI exhibited over accuracies of 0.94 and 0.95 as well as kappa statistics of 0.79 and 0.85, respectively. Further, the performance of DA was significantly different (α = 0.05) from that of PLS-DA based on the MaNemar tests. Overall, the performance of HyspIRI, Landsat 9 OLI-2 and Sentinel-2 MSI data seem to bring new opportunities for crop monitoring at farm scale.
Highlights
Food shortage is a large and growing challenge in subSaharan Africa (Mabhaudhi et al 2016, Van Ittersum et al 2016)
Hyperspectral Infrared Imager (HyspIRI), produced high accuracies characterized by kappa statistics of 0.99, whereas the spectral settings of Sentinel-2 multispectral imager (MSI) and Landsat 9 OLI-2’s spectral settings exhibited kappa statistics of 0.85 and 0.79, respectively
The study assessed the performance of Partial least squares – discriminant analysis (PLS-discriminant analysis (DA)) in relation to DA in discriminating tomatoes treated with anaerobic baffled reactor (ABR), nitrified urine concentrate (NUC) and commercial hydroponic fertilizer mix (CHFM)
Summary
Food shortage is a large and growing challenge in subSaharan Africa (Mabhaudhi et al 2016, Van Ittersum et al 2016). The world Bank estimates that in the 2030, nearly 9 in 10 extremely poor people will be living in Sub-Saharan Africa (The-World-Bank 2019). This is exacerbated droughts and soil nutrients deficiencies resulting from limited fertilizer applications (Mabhaudhi et al 2016, Van Ittersum et al 2016). This is in turn associated with high fertilizer and food prices, amongst other factors.
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