Quantification of light interception within image-based 3D reconstruction of sole and intercropped canopies over the entire growth season.

BACKGROUND AND AIMS: Light interception is closely related to canopy architecture. Few studies based on multi-view photography have been conducted in a field environment, particularly studies that link 3D plant architecture with a radiation model to quantify the dynamic canopy light interception. In this study, we combined realistic 3D plant architecture with a radiation model to quantify and evaluate the effect of differences in planting patterns and row orientations on canopy light interception. METHODS: The three-dimensional architecture of maize and soybean plants were reconstructed for sole crops and intercrops based on multi-view images obtained at five growth dates in the field. We evaluated the accuracy of the calculated leaf length, maximum leaf width, plant height and leaf area according to the measured data. The light distribution within the 3D plant canopy was calculated with a 3D radiation model. Finally, we evaluated canopy light interception in different row orientations. KEY RESULTS: There was good agreement between the measured and calculated phenotypic traits, with an R2>0.97. The light distribution was more uniform for intercropped maize and more concentrated for sole maize. At the maize silking stage, 85% of radiation was intercepted by approximately 55% of the upper canopy region for maize and by approximately 33% of the upper canopy region for soybean. There was no significant difference in daily light interception between the different row orientations for the entire intercropping and sole systems. However, for intercropped maize, near east-west orientations showed approximately 19% higher daily light interception than near south-north orientations. For intercropped soybean, daily light interception showed the opposite trend. It was approximately 49% higher for near south-north orientations than for near east-west orientations. CONCLUSIONS: The accurate reconstruction of 3D plants grown in the field based on multi-view images provides the possibility for high-throughput 3D phenotyping in the field and allows a better understanding of the relationship between canopy architecture and the light environment.