ALPHA: A High Throughput System for Quantifying Growth In Aquatic Plants

Abstract

Abstract The need for more sustainable agricultural systems is becoming increasingly apparent. The global demand for agricultural products — food, feed, fuel and fiber — will continue to increase as the global population continues to grow. This challenge is compounded by climate change. Not only does a changing climate make it difficult to maintain stable yields but current agricultural systems are a major source of greenhouse gas emissions and continue to drive the problem further. Therefore, future agricultural systems must not only increase production but also significantly decrease negative environmental impacts. One approach to addressing this is to begin breeding and cultivating new plant species that have fundamental sustainability advantages over our existing crops. The Lemnaceae, a.k.a duckweeds, are one such species that have potential to increase output and reduce the negative environmental impacts of agricultural production. Herein we describe the Automated Lab-scale PHenotyping Apparatus, ALPHA, for high-throughput phenotyping of Lemnaceae. ALPHA is being used for selective breeding of one species, Lemna gibba , toward the goal of creating a new crop for use in sustainable agricultural systems. ALPHA can be used on many small aquatic plant species to assess growth rates in different environmental conditions. A proof of principle use case is demonstrated where ALPHA is used to determine saltwater tolerance of 6 different varieties of L. gibba .

Plant phenotyping relevance

小型水生植物の成長率を高スループットに定量する自動フェノタイピング装置を開発・実証しており、表現型取得法が研究の中心です。

Code and data availability

The authors state that all source code for the phenotyping system, the PlantCV image analysis pipeline, the R growth-curve analysis, 3D models, and the data generated for this study (including PlantCV_Output_Salinity.csv and Barcode_Sample_Map.csv) are publicly available in the ALPHA GitHub repository.