Integration of morphological and physiological data through Principal Component Analysis to identify the effect of organic overloads on anaerobic granular sludge

Morphological parameters, obtained by quantitative image analysis techniques, together with physiological and reactor performance data were inserted in principal components analysis (PCA) to detect operational problems and control of high rate anaerobic reactors during organic overloads. Four lab-scale Expanded Granular Sludge Blanket reactors were used to performed organic overloads of 18 kg.m -3 .day -1 (R1 - HRT of 8h; and, R2 - HRT of 2.5h) and 50 kg.m -3 .day -1 (R3 - fed for 3 days; and, R4 - fed for 16 days). The application of PCA allowed the visualization of the main effects caused by the organic overloads. The first Principal Component (PC) extracted, in each shock load, retains enough information to group observations in agreement with operational conditions (normal or overload). The variables from quantitative image analysis presented high loadings, suggesting that might play an important role in organic overloads control.