Deficit Irrigation Strategies on Tree Physiological and Chemical Properties: Treatment Effects, Prediction Based Model Analyses and Inter-Correlations

Irrigation is a key factor for different physiological aspects of fruit trees. Therefore, such irrigation protocols that can save water consumption during and maintain trees productivity are an essential goal especially under semiarid climate conditions. The aim this 3-year apricot study was to investigate the effect four deficit (DI) treatments (control, moderate regulated irrigation: RDIm, severe RDI: RDIs continuous DI: CDI) on 15 tree properties (chilling requirement—CR, heat requirement—HR, days from end—dormancy until harvest—DEDFH, sum growing degree days—sGDD, total number buds—TNB, flower buds—NFB, vegetative buds—NVB, starting date flowering—SDF, opened buds—NOFB, bud abscission—FBA, set—FS, seasonal growth—SVG, per tree—FNT, weight—FW, yield—FY), two chemical (total soluble carbohydrates—TSC proline content—TPC) cultivars ‘Ninfa’ ‘Canino’ in Egypt. Results showed both DI significantly influenced values CR, HR, TNB, SDF, NOFB, FS, SVG, FNT, FY, TSC, TPC. Values FBA were affected by years treatments, while sGDD cultivars. DEDFH, NFB, FW only cultivars, NVB treatments. RDIm treatment gave most acceptable measured compared fully irrigated control treatment. Prediction based model analysis demonstrated generalized linear models (GLMs) be predictors best goodness-of-fit predicted GLMs reached In all 22 pair-variables (TNB versus (vs.) TNB vs. NFB FW, NOFB FS SVG FNT FY CR HR FBA) correlated Pearson correlation regression analyses. Principal component analyses explained 82% variance PC1, PC2, PC3 23, 21, 15% with FY; FBA, TPC; respectively, indicating strong connections among properties. conclusion, techniques using deficits managed successfully production Mediterranean conditions as one