Ecologists have often used indirect proxies to represent variables that are difficult or impossible to measure directly. In phytoplankton, the internal concentration of the most limiting nutrient in a cell determines its growth rate. However, directly measuring the concentration of nutrients within cells is inaccurate, expensive, destructive, and time-consuming, substantially impairing our ability to model growth rates in nutrient-limited phytoplankton populations. The red chlorophyll autofluorescence (hereafter "red fluorescence") signal emitted by a cell is highly correlated with nitrogen quota in nitrogen-limited phytoplankton species. The aim of this study was to evaluate the reliability of including flow cytometric red fluorescence as a proxy for internal nitrogen status to model phytoplankton growth rates. To this end, we used the classic Quota model and designed three approaches to calibrate its model parameters to data: where empirical observations on cell internal nitrogen quota were used to fit the model ("Nitrogen-Quota approach"), where quota dynamics were inferred only from changes in medium nutrient depletion and population density ("Virtual-Quota approach"), or where red fluorescence emission of a cell was used as an indirect proxy for its internal nitrogen quota ("Fluorescence-Quota approach"). Two separate analyses were carried out. In the first analysis, stochastic model simulations were parameterized from published empirical relationships and used to generate dynamics of phytoplankton communities reared under nitrogen-limited conditions. Quota models were fitted to the dynamics of each simulated species with the three different approaches and the performance of each model was compared. In the second analysis, we fit Quota models to laboratory time-series and we calculate the ability of each calibration approach to describe the observed trajectories of internal nitrogen quota in the culture. Results from both analyses concluded that the Fluorescence-Quota approach including per-cell red fluorescence as a proxy of internal nitrogen substantially improved the ability of Quota models to describe phytoplankton dynamics, while still accounting for the biologically important process of cell nitrogen storage. More broadly, many population models in ecology implicitly recognize the importance of accounting for storage mechanisms to describe the dynamics of individual organisms. Hence, the approach documented here with phytoplankton dynamics may also be useful for evaluating the potential of indirect proxies in other ecological systems.