Cluster-based photography and modeling integrated method for an efficient measurement of cassava leaf area.

Leaf area (LA) and biomass are important agronomic indicators of the growth and health of plants. Conventional methods for measuring the LA can be challenging, time-consuming, costly, and laborious, especially for a large-scale study. A hybrid approach of cluster-based photography and modeling was, thus, developed herein to improve practicality.

Effective Metabolic Carbon Utilization and Shoot-to-Root Partitioning Modulate Distinctive Yield in High Yielding Cassava Variety.

Increasing cassava production could mitigate one of the global food insecurity challenges by providing a sustainable food source. To improve the yield potential, physiological strategies (i.e.

AFLP-based transcript profiling for cassava genome-wide expression analysis in the onset of storage root formation.

Cassava (Manihot esculenta Crantz) is a root crop that accumulates large quantities of starch, and it is an important source of carbohydrate. Study on gene expressions during storage root development provides important information on storage root formation and starch accumulation as well as unlock new traits for improving of starch yield. cDNA-Amplified Fragment Length Polymorphism (AFLP) was used to compare gene expression profiles in fibrous and storage roots of cassava cultivar Kasetsart 50.