Research Article | Open Access

Volume 2023 |Article ID 0095 | https://doi.org/10.34133/plantphenomics.0095

Quantification of the Cumulative Shading Capacity in a Maize–Soybean Intercropping System Using an Unmanned Aerial Vehicle

Min Li,¹ Pengcheng Hu,^2,3 Di He,³ Bangyou Zheng,⁴ Yan Guo,¹ Yushan Wu,⁵ and Tao Duan ⁶

¹College of Land Science and Technology, China Agricultural University, Beijing, China
²School of Agriculture and Food Sustainability, The University of Queensland, St Lucia, QLD, Australia
³Agriculture and Food, CSIRO, GPO Box 1700, Canberra ACT 2601, ACT, Australia
⁴Agriculture and Food, CSIRO, Queensland Biosciences Precinct, St Lucia, QLD, Australia
⁵College of Agronomy, Sichuan Agricultural University, Chengdu, China
⁶Institute of Microelectronics of Chinese Academy of Sciences, Beijing, China

Abstract

In intercropping systems, higher crops block direct radiation, resulting in inevitable shading on the lower crops. Cumulative shading capacity (CSC), defined as the amount of direct radiation shaded by higher crops during a growth period, affects the light interception and radiation use efficiency of crops. Previous studies investigated the light interception and distribution of intercropping. However, how to directly quantify the CSC and its inter-row heterogeneity is still unclear. Considering the canopy height differences (Hms, obtained using an unmanned aerial vehicle) and solar position, we developed a shading capacity model (SCM) to quantify the shading on soybean in maize–soybean intercropping systems. Our results indicated that the southernmost row of soybean had the highest shading proportion, with variations observed among treatments composed of strip configurations and plant densities (ranging from 52.44% to 57.44%). The maximum overall CSC in our treatments reached 123.77 MJ m-2. There was a quantitative relationship between CSC and the soybean canopy height increment (y = 3.61 × 10−2×ln(x)+6.80 × 10−1, P < 0.001). Assuming that the growth status of maize and soybean was consistent under different planting directions and latitudes, we evaluated the effects of factors (i.e., canopy height difference, latitude, and planting direction) on shading to provide insights for optimizing intercropping planting patterns. The simulation showed that increasing canopy height differences and latitude led to increased shading, and the planting direction with the least shading was about 90° to 120° at the experimental site. The newly proposed SCM offers a quantitative approach for better understanding shading in intercropping systems.