A Proposed Methodology to Analyze Plant Growth and Movement from Phenomics Data

Abstract

Image analysis of developmental processes in plants reveals both growth and organ movement. This study proposes a methodology to study growth and movement. It includes the standard acquisition of internal and external reference points and coordinates, coordinates transformation, curve fitting and the corresponding statistical analysis. Several species with different growth habits were used including Antirrhinum majus, A. linkianum, Petunia x hybrida and Fragaria x ananassa. Complex growth patterns, including gated growth, could be identified using a generalized additive model. Movement, and in some cases, growth, could not be adjusted to curves due to drastic changes in position. The area under the curve was useful in order to identify the initial stage of growth of an organ, and its growth rate. Organs displayed either continuous movements during the day with gated day/night periods of maxima, or sharp changes in position coinciding with day/night shifts. The movement was dependent on light in petunia and independent in F. ananassa. Petunia showed organ movement in both growing and fully-grown organs, while A. majus and F. ananassa showed both leaf and flower movement patterns linked to growth. The results indicate that different mathematical fits may help quantify growth rate, growth duration and gating. While organ movement may complicate image and data analysis, it may be a surrogate method to determine organ growth potential.

3DeepM: An Ad Hoc Architecture Based on Deep Learning Methods for Multispectral Image Classification

“…For this reason, it possesses mobile panels, position accessories for cameras and illumination and elements made with a 3D printer, such as domes and semidomes. Figure 2 shows four configurations of the dark chamber for different experiments: Figure 2a shows direct illumination to capture an MSI for growth analysis of petunia leaves [24]; Figure 2b allows images to be captured with direct illumination with a dome to avoid the reflection of the illumination subsystem on the grape skin and a semidome to eliminate shadows; Figure 2c shows a direct illumination configuration for the simultaneous visible and IR image capturing, avoiding unwanted brightness; and Figure 2d shows a configuration with back-illumination for the simultaneous visible and IR imaging capture with a big dome to allow for correct light distribution.…”

The Development of a Stereo Vision System to Study the Nutation Movement of Climbing Plants

“…This method is an improvement of their free software "Plant Tracer", which analyzed plant movement using the classic computer vision techniques of object tracking and blob detection. Díaz-Galián et al [14] presented a methodology to analyze the movement of plants using different reference points, which were obtained from image analysis. This methodology included coordinates transformation, curve fitting, and statistical analysis, allowing a comparison between different plant species.…”

Growth charts for small sample sizes using unsupervised clustering: Application to canine early growth

“…Growth curves (GCs) have also been developed for non-human species, including companion animals (Hawthorne et al 2004 ; Salt et al 2017 , 2020 ; Cave et al 2018 ; Alves 2020 ), livestock (Schinckel et al 2004 ; Berry et al 2005 ; Kuhi et al 2010 ; da Silva Marinho et al 2013 ; Luo et al 2015 ; Sogut et al 2016 ), marine animals (Allen et al 1972 ; Frazer and Ladner 1986 ; Hernandez-Llamas and Ratkowsky 2004 ) and plants (Elias and Causton 1976 ; Poorter and Garnier 1996 ; Díaz-Galián et al 2019 ). The rationale for GCs and their potential applications in animals extends beyond flagging any abnormal growth in an individual that requires diagnostic investigations.…”