Canopy-intercepted light, or photosynthetically active radiation, is fundamentally crucial for quantifying crop biomass development and yield potential. Fractional photosynthetically active radiation (PAR) (fPAR) is conventionally obtained by measuring the PAR both below and above the canopy using a mobile lightbar platform to predict the potential yield of nut crops. This study proposed a feasible and low-cost method for accurately estimating the canopy fPAR using aerial photogrammetry-based canopy three-dimensional models. We tested up to eight different varieties in three experimental almond orchards, including California's leading variety of 'Nonpareil'. To extract various canopy profile features, such as canopy cover and canopy volume index, we developed a complete data collection and processing pipeline called Virtual Orchard (VO) in Python environment. Canopy fPAR estimated by VO throughout the season was compared against midday canopy fPAR measured by a mobile lightbar platform in midseason, achieving a strong correlation (R 2) of 0.96. A low root mean square error (RMSE) of 2% for 'Nonpareil'. Furthermore, we developed regression models for predicting actual almond yield using both measures, where VO estimation of canopy fPAR, as a stronger indicator, achieved a much better prediction (R 2 = 0.84 and RMSE = 195 lb acre-1) than the lightbar (R 2 = 0.70 and RMSE = 266 lb acre-1) for 'Nonpareil'. Eight different new models for estimating potential yield were also developed using temporal analysis from May to August in 2019 by adjusting the ratio between fPAR and dry kernel yield previously found using a lightbar. Finally, we compared the two measures at two different spatial precision levels: per-row and per-block. fPAR estimated by VO at the per-tree level was also assessed. Results showed that VO estimated canopy fPAR performed better at each precision level than lightbar with up to 0.13 higher R 2. The findings in this study serve as a fundamental link between aerial-based canopy fPAR and the actual yield of almonds.
Keywords: aerial photogrammetry; canopy light interception; canopy profile feature; digital elevation model; digital surface model; virtual orchard.
Copyright © 2021 Zhang, Pourreza, Cheung, Zuniga-Ramirez, Lampinen and Shackel.