Potential of airborne hyperspectral imagery to estimate fruit yield in citrus

By Xujun Ye, K. Sakai, A. Sasao, S. Asada. 2008

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Hyperspectral characterization of freezing injury and its biochemical impacts in oilseed rape leaves (2017, unknown): “PCR reduces data 338 redundancy by transforming a set of highly correlated variables into a new set of 339 uncorrelated principal components variables (Ye et al., 2008).”
‘Extended spectral angle mapping (ESAM)’ for citrus greening disease detection using airborne hyperspectral imaging (2014, background): “airborne visible infrared imaging spectrometer (AVIRIS), and multispectral infrared and visible imaging spectrometer (MIVIS), are now available for precision agriculture applications including yield estimation, fruit detection, environmental impact assessment and crop disease detection (Zhang et al.”
Yield loss caused by huanglongbing in different sweet orange cultivars in São Paulo, Brazil (2011, background): “…for each block of plants, in citrus, neighbour plants show different behavior in the same year, with high yielding N um be r of a sy m pt om at ic fr ui t p er tr ee and low yielding plants, which makes it impossible to forecast the yield based on the previous year’s data (Ye et al. 2008a, b).”
Optical remote sensing and the retrieval of terrestrial vegetation bio-geophysical properties - A review (2015, unknown): “Hansen et al. (2002) and Ye et al. (2007, 2008) applied PLSR for yield prediction purposes.”