A low-cost open-source imaging platform reveals spatiotemporal insight into leaf elongation and movement.

Abstract

Plant organs move throughout the diurnal cycle, changing leaf and petiole positions to balance light capture, leaf temperature, and water loss under dynamic environmental conditions. Upward movement of the petiole, called hyponasty, is one of several traits of the shade avoidance syndrome (SAS). SAS traits are elicited upon perception of vegetation shade signals such as far-red light (FR) and improve light capture in dense vegetation. Monitoring plant movement at a high temporal resolution allows studying functionality and molecular regulation of hyponasty. However, high temporal resolution imaging solutions are often very expensive, making this unavailable to many researchers. Here, we present a modular and low-cost imaging setup, based on small Raspberry Pi computers that can track leaf movements and elongation growth with high temporal resolution. We also developed an open-source, semiautomated image analysis pipeline. Using this setup, we followed responses to FR enrichment, light intensity, and their interactions. Tracking both elongation and the angle of the petiole, lamina, and entire leaf in Arabidopsis (Arabidopsis thaliana) revealed insight into R:FR sensitivities of leaf growth and movement dynamics and the interactions of R:FR with background light intensity. The detailed imaging options of this system allowed us to identify spatially separate bending points for petiole and lamina positioning of the leaf.

Plant phenotyping relevance

低コスト画像計測プラットフォームとオープンソース解析パイプラインを開発し、葉の伸長・運動・角度を高時間分解能で抽出する方法が研究の中心である。

Code and data availability

The paper's authors publicly deposited their Python image-analysis scripts and R analysis/statistical scripts at the Pierik-Lab GitHub organization, with explicit open-source availability language. The underlying phenotype data, however, is only available on request.