BACKGROUNDQuantification of the volumetric oxygen transfer coefficient (k(L)a) is essential to characterize and optimize the oxygen transfer capacity of bioreactors. First order methodologies are commonly used to estimate k(L)a; however, when the delay of the system cannot be neglected, second-order methodologies are required for accurate estimations. Second-order methods are time consuming and hard to reproduce. In this study, we describe an automated algorithm to estimate k(L)a in conventional bioreactors. RESULTSThe simple, four step algorithm developed considers: (1) data smoothing; (2) selection of a high oxygen variation zone; (3) selection of the time period where the instantaneous k(L)a is constant; and (4) k(L)a estimation. The algorithm was coded in MATLAB and four adjustable parameters were fixed heuristically using eight response curves with different hydrodynamic conditions (varying viscosity, agitation and aeration). Compared with manual processing, 80 validation experiments showed that the proposed automatic algorithm yields much more reproducible results in a fraction of the manual processing time. CONCLUSIONThe algorithm is fast and yields, without human intervention, reliable k(L)a estimations under different hydrodynamic conditions; hence, it is useful for designing high throughput k(L)a assessment systems to optimize oxygen delivery in bioreactors. (c) 2016 Society of Chemical Industry