Phenotypic variation of cassava root traits and their responses to drought.

Abstract

Premise of the study The key to increased cassava production is balancing the trade-off between marketable roots and traits that drive nutrient and water uptake. However, only a small number of protocols have been developed for cassava roots. Here, we introduce a set of new variables and methods to phenotype cassava roots and enhance breeding pipelines. Methods Different cassava genotypes were planted in pot and field conditions under well-watered and drought treatments. We developed cassava shovelomics and used digital imaging of root traits (DIRT) to evaluate geometrical root traits in addition to common traits (e.g., length, number). Results Cassava shovelomics and DIRT were successfully implemented to extract root phenotypes, and a large phenotypic variation for root traits was observed. Significant correlations were found among root traits measured manually and by DIRT. Drought significantly decreased shoot dry weight, total root number, and root length by 84%, 30%, and 25%, respectively. High adventitious root number was associated with increased shoot dry weight ( r = 0.44) under drought. Discussion Our methods allow for high-throughput cassava root phenotyping, which makes a breeding program targeting root traits feasible. We suggest that root number is a breeding target for improved cassava production under drought.

Plant phenotyping relevance

キャッサバ根の表現型取得法（shovelomicsとデジタル画像解析DIRT）の開発・適用・相関検証が研究の中心であり、根形質を抽出する高スループット手法として明示されている。

Code and data availability

The authors explicitly deposit the root images and phenotype data supporting this cassava phenotyping study on CyVerse Data Commons under the identifier Saengwilai_Cassava_2019, with a public DOI link. This is a paper-specific, publicly accessible dataset of the plant images and trait measurements used in the analysis.