Analyzing Changes in Maize Leaves Orientation due to GxExM Using an Automatic Method from RGB Images

Abstract

The sowing pattern has an important impact on light interception efficiency in maize by determining the spatial distribution of leaves within the canopy. Leaves orientation is an important architectural trait determining maize canopies light interception. Previous studies have indicated how maize genotypes may adapt leaves orientation to avoid mutual shading with neighboring plants as a plastic response to intraspecific competition. The goal of the present study is 2-fold: firstly, to propose and validate an automatic algorithm (Automatic Leaf Azimuth Estimation from Midrib detection [ALAEM]) based on leaves midrib detection in vertical red green blue (RGB) images to describe leaves orientation at the canopy level; and secondly, to describe genotypic and environmental differences in leaves orientation in a panel of 5 maize hybrids sowing at 2 densities (6 and 12 plants.m −2 ) and 2 row spacing (0.4 and 0.8 m) over 2 different sites in southern France. The ALAEM algorithm was validated against in situ annotations of leaves orientation, showing a satisfactory agreement (root mean square [RMSE] error = 0.1, R 2 = 0.35) in the proportion of leaves oriented perpendicular to rows direction across sowing patterns, genotypes, and sites. The results from ALAEM permitted to identify significant differences in leaves orientation associated to leaves intraspecific competition. In both experiments, a progressive increase in the proportion of leaves oriented perpendicular to the row is observed when the rectangularity of the sowing pattern increases from 1 (6 plants.m −2 , 0.4 m row spacing) towards 8 (12 plants.m −2 , 0.8 m row spacing). Significant differences among the 5 cultivars were found, with 2 hybrids exhibiting, systematically, a more plastic behavior with a significantly higher proportion of leaves oriented perpendicularly to avoid overlapping with neighbor plants at high rectangularity. Differences in leaves orientation were also found between experiments in a squared sowing pattern (6 plants.m −2 , 0.4 m row spacing), indicating a possible contribution of illumination conditions inducing a preferential orientation toward east-west direction when intraspecific competition is low.

Three-Dimensional Modeling of Maize Canopies Based on Computational Intelligence

“…Upon detecting a collision between two 3D phytomers, a mesh deformation method [ 33 ] is employed for collision response. In actual canopies, leaves farther from the stem are more likely to be displaced by external forces upon collision.…”

“…With increased planting density in maize, competition for light resources intensifies, and one plasticity approach is the directional adjustment of leaf azimuth. Therefore, to qualitatively validate the accuracy of the 3D modeling of the maize canopy, the proportion of leaves oriented perpendicular to the row direction in maize plants at different densities is evaluated [ 33 , 34 ]. If the total number of phytomers is N all , and the number of phytomers with azimuth angles (assuming the row direction is north-south) between 60° and 120° is N vert , then the formula for calculating the proportion p of leaf azimuth angles perpendicular to the row direction is as follows: …”