DISCRIMINANT FUNCTIONS FOR AQUACULTURE WASTEWATER DILUTIONS IN WELL WATER APPLIED BY NON-SELF-COMPENSATING DRIPPERS

Abstract

ABSTRACT Emitter clogging is the main limitation of drip irrigation systems operating with wastewater. This paper aimed to employ discriminant analysis (DA) to generate classification functions that characterize aquaculture wastewater (AW) dilutions in well water (WA), delivered through non-self-compensating drippers. Five AW dilutions in WA were tested (D1: 100% AW; D2: 75% AW + 25% WA; D3: 50% AW + 50% WA; D4: 25% AW + 75% WA; and D5: 100% WA) to investigate the clogging susceptibility of three non-self-compensating dippers: TS (1.6 L h-1), SL (1.6 L h-1), and NJ (1.7 L h-1) after 160 h of operation. Three hydraulic performance evaluations of the drippers were performed in this period. During the same interval, the quality attributes of the AW dilutions in WA were also quantified. The statistical analyses included correlation matrix and DA. The correlation matrix identified 188 variables with significant correlations. Discriminant functions were constructed for each dripper using DA. These functions revealed Mg2+ as the most significant variable. The classification matrix of these functions achieved a 100% success rate.

Keywords

• multivariate statistics
• agricultural reuse
• emitters
• clogging