Evaluating Plant Drought Resistance with a Raspberry Pi and Time-lapse Photography

农业工程 计算机科学 云计算 抗性(生态学) 灌溉 树莓皮 元数据 干旱胁迫 生物 拟南芥 作物 园艺 耐旱性 环境科学 农学 突变体 嵌入式系统 遗传学 万维网 工程类 操作系统 物联网 基因
作者
Daniel Ginzburg,Sue Rhee
出处
期刊:Bio-protocol [Bio-Protocol]
卷期号:13 (2)
标识
DOI:10.21769/bioprotoc.4593
摘要

Identifying genetic variations or treatments that confer greater resistance to drought is paramount to ensuring sustainable crop productivity. Accurate and reproducible measurement of drought stress symptoms can be achieved via automated, image-based phenotyping. Many phenotyping platforms are either cost-prohibitive, require specific technical expertise, or are simply more complex than necessary to effectively evaluate drought resistance. Certain mutations, allelic variations, or treatments result in plants that constitutively use less water. To accurately identify genetic differences or treatments that confer a drought phenotype, plants from all experimental groups must be subjected to equal levels of drought stress. This can be easily achieved by growing and imaging plants that are grown in the same pot. Here, we provide a detailed protocol to configure a Raspberry Pi computer and camera module to image seedlings of multiple genotypes growing in shared pots and to transfer images and metadata via the cloud for downstream analyses. Also detailed is a method to calculate percent soil water content of pots while being imaged to allow for comparison of stress symptoms with water availability. This protocol was recently used to uncouple differential water usage from drought resistance in a dwarf Arabidopsis thaliana mutant chiquita1-1/cost1 compared to the wild-type control. It is cost effective, suitable for any plant species, customizable to various biological questions, and requires no prior experience with electronics or basic software programming.
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