A Low-Dimensional X-ρ-A Allocation Model for Predicting Light-Dependent Biomass, Protein, and Lipid Dynamics in TAP Batch Cultures of Chlamydomonas reinhardtii CC-400.

Microalgae are promising platforms for producing biomass and biochemicals, but changes in component concentrations may reflect biomass accumulation, shifts in composition, or both. This study developed a low-dimensional X-ρ-A allocation model for jointly describing and predicting dry biomass (X), protein (P), and lipid (L) dynamics. The model was parameterized and evaluated using mixotrophic Tris-acetate-phosphate (TAP) batch cultures of Chlamydomonas reinhardtii strain CC-400. The model uses two composition-derived indices: ρ, the fraction of dry biomass represented by the measured protein-lipid module, and A, the lipid fraction within this module. Model comparison favored a formulation in which ρ was constant over time within each condition. The light-response model was calibrated at 30, 100, and 300 μE m-2 s-1 and evaluated against an independently generated 500 μE m-2 s-1 dataset from the same experimental system to assess predictive performance beyond the calibration range. Validation R2 values were 0.9374, 0.9616, and 0.9321 for dry biomass, protein, and lipid, respectively. Under nitrogen starvation, biomass and protein accumulation were suppressed, whereas A increased, indicating lipid enrichment within the measured protein-lipid module. Within this experimental system, the model provides an interpretable framework for predicting light-dependent biomass, protein, and lipid dynamics and distinguishing biomass-driven increases in component concentrations from shifts in protein-lipid allocation.