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

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Department of Horticulture, Faculty of Agriculture, Kafrelshaikh University, Kafr El-Sheikh 33511, Egypt
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Institute of Horticulture, University of Debrecen, Böszörményi út 138, H-4032 Debrecen, Hungary
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Physiology and Breeding of Horticultural Crops Lab (PBHC), Faculty of Agriculture, Kafrelsheikh University, Kafr El-Sheikh 33511, Egypt
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Department of Physical Geography and Geoinformatics, University of Debrecen, H-4032 Debrecen, Hungary
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Department of Horticulture, College of Agricultural Engineering Sciences, Salahaddin University-Erbil, Erbil 46010, Kurdistan Region, Iraq
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Eötvös Loránd Research Network (ELKH), Centre for Agricultural Research, Plant Protection Institute, Herman Ottó út 15, H-1022 Budapest, Hungary
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Author to whom correspondence should be addressed.
Academic Editor: Paola A. Deligios
Agronomy 2021, 11(7), 1361; https://doi.org/10.3390/agronomy11071361
Received: 27 May 2021 / Revised: 30 June 2021 / Accepted: 1 July 2021 / Published: 3 July 2021
Irrigation is a key factor for different physiological aspects of fruit trees. Therefore, such irrigation protocols that can save water consumption during irrigation and maintain fruit trees productivity are an essential goal especially under semiarid climate conditions. The aim of this 3-year apricot study was to investigate the effect of four deficit irrigation (DI) treatments (control, moderate regulated deficit irrigation: RDIm, severe RDI: RDIs and continuous DI: CDI) on 15 tree physiological properties (chilling requirement—CR, heat requirement—HR, days from end—dormancy until fruit harvest—DEDFH, sum of growing degree days—sGDD, total number of buds—TNB, number of flower buds—NFB, number of vegetative buds—NVB, starting date of flowering—SDF, number of opened flower buds—NOFB, flower bud abscission—FBA, fruit set—FS, seasonal vegetative growth—SVG, fruit number per tree—FNT, fruit weight—FW, fruit yield—FY), and on two tree chemical properties (total soluble carbohydrates—TSC and total proline content—TPC) on apricot cultivars ‘Ninfa’ and ‘Canino’ in Egypt. Results showed that both DI treatments and cultivars significantly influenced the values of CR, HR, TNB, SDF, NOFB, FS, SVG, FNT, FY, TSC, and TPC. Values of FBA were significantly affected by years and DI treatments, while sGDD by years and cultivars. Values of DEDFH, NFB, and FW were significantly influenced only by cultivars, while NVB only by DI treatments. The RDIm treatment gave the most acceptable values for most measured properties compared to the fully irrigated control treatment. Prediction based model analysis demonstrated that generalized linear models (GLMs) can be predictors for the measured tree properties in the DI treatments. The best goodness-of-fit of the predicted GLMs was reached for HR, NOFB, FS, SVG, FNT, TSC, and TPC. In all the four DI treatments, 22 pair-variables (TNB versus (vs.) NFB, TNB vs. NOFB, TNB vs. NOFB, NFB vs. NOFB, NFB vs. FNT, NFB vs. FY, NFB vs. FW, NOFB vs. SVG, NOFB vs. FNT, NOFB vs. FY, FS vs. FNT, FS vs. FY, SVG vs. FNT, SVG vs. FY, SVG vs. TSC, FNT vs. FY, FY vs. FW, CR vs. TSC, HR vs. TNB, HR vs. NFB, HR vs. FNT, HR vs. FY, and NOFB vs. FBA) correlated significantly in Pearson correlation and regression analyses. Principal component analyses explained 82% of the total variance and PC1, PC2, and PC3 explained 23, 21, and 15% of the total variance and correlated with the HR, TNB, FS, FNT and FY; FBA, SVG, TSC, and TPC; and NFB, NVB and NOFB, respectively, indicating strong connections among tree physiological and chemical properties. In conclusion, DI techniques using moderate water deficits can be managed successfully in apricot production under semiarid Mediterranean climate conditions such as the one in Egypt. View Full-Text
Keywords: chilling requirement; bud number; shoot growth; flowering; fruit set; yield; soluble carbohydrates; proline content; prediction based GLMs; regression analyses; PCA chilling requirement; bud number; shoot growth; flowering; fruit set; yield; soluble carbohydrates; proline content; prediction based GLMs; regression analyses; PCA
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MDPI and ACS Style

Ezzat, A.; Salama, A.-M.; Szabó, S.; Yaseen, A.A.; Molnár, B.; Holb, I.J. Deficit Irrigation Strategies on Tree Physiological and Chemical Properties: Treatment Effects, Prediction Based Model Analyses and Inter-Correlations. Agronomy 2021, 11, 1361. https://doi.org/10.3390/agronomy11071361

AMA Style

Ezzat A, Salama A-M, Szabó S, Yaseen AA, Molnár B, Holb IJ. Deficit Irrigation Strategies on Tree Physiological and Chemical Properties: Treatment Effects, Prediction Based Model Analyses and Inter-Correlations. Agronomy. 2021; 11(7):1361. https://doi.org/10.3390/agronomy11071361

Chicago/Turabian Style

Ezzat, Ahmed, Abdel-Moety Salama, Szilárd Szabó, Arshad A. Yaseen, Bianka Molnár, and Imre J. Holb. 2021. "Deficit Irrigation Strategies on Tree Physiological and Chemical Properties: Treatment Effects, Prediction Based Model Analyses and Inter-Correlations" Agronomy 11, no. 7: 1361. https://doi.org/10.3390/agronomy11071361

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