Kengkanna J, Jakaew P, Amawan S, Busener N, Bucksch A, Saengwilai P.

Appl Plant Sci. 2019 Apr 10; 7(4): e01238. doi: 10.1002/aps3.1238.

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.

See https://www.ncbi.nlm.nih.gov/pubmed/31024782

Fig. 7:

DIRT trait comparison for R5, R9, and R11. The plants were harvested at 12 months after planting in the field under well‐watered conditions (W) and drought conditions (D). (A) WIDTH_MAX, (B) WIDTH_MED, (C) SKL_WIDTH, (D) DIA_STEM, (E) SKL_DEPTH, and (F) AREA traits. Data were made comparable through normalization of mean trait values (Z‐score). Error bars represent the standard error of the mean for each treatment and genotype category that corresponds to a particular trait.