Three-Dimensional Monitoring of Plant Structural Parameters and Chlorophyll Distribution.

Kenta Itakura,Itchoku Kamakura,Fumiki Hosoi

doi:10.3390/s19020413

Abstract

Image analysis is widely used for accurate and efficient plant monitoring. Plants have complex three-dimensional (3D) structures; hence, 3D image acquisition and analysis is useful for determining the status of plants. Here, 3D images of plants were reconstructed using a photogrammetric approach, called “structure from motion”. Chlorophyll content is an important parameter that determines the status of plants. Chlorophyll content was estimated from 3D images of plants with color information. To observe changes in the chlorophyll content and plant structure, a potted plant was kept for five days under a water stress condition and its 3D images were taken once a day. As a result, the normalized Red value and the chlorophyll content were correlated; a high R2 value (0.81) was obtained. The absolute error of the chlorophyll content estimation in cross-validation studies was 4.0 × 10−2 μg/mm2. At the same time, the structural parameters (i.e., the leaf inclination angle and the azimuthal angle) were calculated by simultaneously monitoring the changes in the plant’s status in terms of its chlorophyll content and structural parameters. By combining these parameters related to plant information in plant image analysis, early detection of plant stressors, such as water stress, becomes possible.

Highlights

Accurate monitoring of plant growth and structural parameters is important for crop yield estimation, species identification, determining vegetative growth, tracking illness, and monitoring insect infestation [1,2,3]
Because 2D projections filter out potentially important information and fail to exploit the full potential of shape analysis, measurement of 3D plant architecture has become very important in plant biology and plant breeding [5,6,7,8]
Chlorophyll content in small areas of leaves was estimated from color information of the 3D plant images and the obtained values were compared with actual values

Summary

Introduction

Accurate monitoring of plant growth and structural parameters is important for crop yield estimation, species identification, determining vegetative growth, tracking illness, and monitoring insect infestation [1,2,3]. A 2D image is obtained by projecting the corresponding three-dimensional (3D) object in one direction; because plants have complex 3D structures, it becomes difficult to accurately estimate their structural parameters. Detection and Ranging) and a photogrammetric approach called “structure from motion” (SfM) Using these methods, plant structural parameters, such as the leaf area index, leaf inclination angle, location, height, and volume, can be estimated [9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28]. The SfM methods are especially useful as they offer detailed 3D models of small plants with affordable cameras if the sample image is clearly taken

Methods

Results

Conclusion