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Water-Related Variables for Predicting Yield of Apple under Deficit Irrigation

Riccardo Lo Bianco

Horticulturae · 2019

doi:10.3390/horticulturae5010008 (opens in a new tab)

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Abstract

Predicting apple yield in relation to tree water use is important for irrigation planning and evaluation. The aim of the present study was to identify measurable variables related to tree water use that could predict final fruit yield of apple trees under different strategies of deficit irrigation. Adult ‘Gala’ and ‘Fuji’ apple trees were exposed to conventional irrigation (CI), delivering 100% of crop evapotranspiration; partial root zone drying (PRD), delivering 50% of CI water only on one alternated side of the root-zone; and continuous deficit irrigation (CDI), delivering 50% of CI water on both sides of the root-zone. Integrals of soil (SWDint) and leaf (LWSDint) water deficit along with growth and stomatal conductance (Gsint) were calculated across each season and used to estimate total conductance (GStree) and transpiration (Trtree) per tree, transpiration efficiency on a fruit (GRfruit/Tr) or tree (GRtrunk/Tr) growth basis, and transpiration productivity (Yield/Trtree). ‘Fuji’ trees had higher Yield/Trtree, but had lower GRtrunk/Tr and similar GRfruit/Tr compared to ‘Gala’ trees. In ‘Fuji’, CDI reduced yield, trunk growth, leaf hydration, and gas exchange, while in ‘Gala’, it did not reduce yield and gas exchange. In ‘Fuji’, a linear combination of GRtrunk/Tr, GRfruit/Tr, and Gstree contributed to predicting yield, with GRfruit/Tr explaining nearly 78% of the model variability. In ‘Gala’, a linear combination of LWSDint and Gstree contributed to predicting yield, with Gstree explaining over 79% of the model variability. These results indicate that measuring tree water status or water use may help predict final apple yields only in those cultivars like ‘Gala’ that cannot limit dehydration by closing stomates because of carbon starvation. In more vigorous cultivars like ‘Fuji’, transpiration efficiency based on fruit growth can be a powerful predictor of final yields.

Abstract licence: CC BY

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