Zhang Xin, Pourreza Alireza, Cheung Kyle H, Zuniga-Ramirez German, Lampinen Bruce D, Shackel Kenneth A
Department of Biological and Agricultural Engineering, University of California, Davis, Davis, CA, United States.
Kearney Agricultural Research and Extension Center, University of California Agriculture and Natural Resources, Parlier, CA, United States.
Front Plant Sci. 2021 Aug 26;12:715361. doi: 10.3389/fpls.2021.715361. eCollection 2021.
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 ( ) 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 ( = 0.84 and RMSE = 195 lb acre) than the lightbar ( = 0.70 and RMSE = 266 lb acre) 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 . The findings in this study serve as a fundamental link between aerial-based canopy fPAR and the actual yield of almonds.
冠层截留光，即光合有效辐射，对于量化作物生物量发育和产量潜力至关重要。传统上，通过使用移动光条平台测量冠层上下的光合有效辐射（PAR）来获得分数光合有效辐射（fPAR），以预测坚果树作物的潜在产量。本研究提出了一种可行且低成本的方法，利用基于航空摄影测量的冠层三维模型准确估算冠层fPAR。我们在三个实验性杏仁果园中测试了多达八个不同品种，包括加利福尼亚州的主要品种“无与伦比”。为了提取各种冠层轮廓特征，如冠层覆盖率和冠层体积指数，我们在Python环境中开发了一个名为虚拟果园（VO）的完整数据收集和处理管道。将VO在整个季节估算的冠层fPAR与移动光条平台在生长季中期测量的午间冠层fPAR进行比较，得到了0.96的强相关性（ ）。“无与伦比”品种的均方根误差（RMSE）低至2%。此外，我们开发了回归模型，使用这两种测量方法预测实际杏仁产量，其中VO对冠层fPAR的估算作为更强的指标，比光条测量法（“无与伦比”品种的 = 0.70，RMSE = 266磅/英亩）实现了更好的预测（ = 0.84，RMSE = 195磅/英亩）。还通过调整先前使用光条发现的fPAR与干果仁产量之间的比率，利用2019年5月至8月的时间分析开发了八个不同的估算潜在产量的新模型。最后，我们在两个不同的空间精度水平上比较了这两种测量方法：每行和每块。还评估了VO在每棵树水平上估算的fPAR。结果表明，VO估算的冠层fPAR在每个精度水平上都比光条测量法表现更好， 最高高出0.13。本研究的结果是基于航空的冠层fPAR与杏仁实际产量之间的基本联系。
