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Table 1 Overview of the phenotyping methodology and trait derived from the corresponding methods in the study. R, Red; G, Green; B, Blue

From: PI-Plat: a high-resolution image-based 3D reconstruction method to estimate growth dynamics of rice inflorescence traits

Phenotyping

Analysis method

Traits extracted

Description

Developing panicle (week 1, 2 and 3 post-fertilization)

Reconstruction of 3D point cloud from multi-view images

Voxel count

Total number of points in 3D reconstructed point cloud, which can be used to estimate the overall volume

Color sum—R, G, B

Sum of color intensities of signals from R, G, and B channels

Color intensity − ratio of R to G

Ratio of intensity in red channel and the intensity in green channel

Multi-view 2D image analysis

Pixel count

Total pixel counts to estimate 2D surface area of the panicle

Mature panicle

Single-view conventional 2D scanning

Projected seed count

Estimation of total number of seeds

Projected surface area

Estimation of total surface area

Seed area

Mean area of all seeds

Seed major and minor axis length

Mean major and minor axis length of all seeds

Manual measurement

Yield-related traits

Total number of seeds, total seed weight, fertility and weight per seed