HortScience (Feb 2024)
Drought Responses in Three Apple Cultivars Using an Autonomous Sensor-based Irrigation System
Abstract
Irrigation decision support systems evolving in the domestic temperate tree fruit production industry incorporate measures of soil moisture status, which diverges from classic physiological indicators of edaphic stress. This study used an autonomous sensor-based irrigation system to impose a water deficit (soil matric potential targets of –25, –40, –60, and –80 kPa) on ‘Autumn Gala’, ‘CrimsonCrisp’, and ‘Golden Delicious’ apple (Malus domestica) cultivars grafted to ‘Budagovsky 9’ rootstock in the greenhouse (n = 60). It was hypothesized that relationships between physiological plant function, assessed via infrared gas exchange and chlorophyll fluorescence, and the soil matric potential may be used to advance emerging irrigation decision support systems. Complications arising from defoliation by day 11 at –60 and –80 kPa indicate the generation of substrate-specific soil–water relationships in research applications of autonomous sensor-based irrigation systems. ‘Autumn Gala’ carbon assimilation rates at –80 kPa declined from day 0 to day 8 (9.93 and 5.86 μmol⋅m–2⋅s–1 carbon dioxide), whereas the transpiration rate was maintained, potentially reducing observed defoliation as other cultivars increased transpiration to maintain carbon assimilation. Correlation matrices revealed Pearson’s r ≤ |0.43| for all physiological metrics considered with soil matric potential. Nevertheless, exploratory regression analysis on predawn leaf water potential, carbon assimilation, transpiration, stomatal conductance, and nonphotochemical quenching exposed speculatively useful data and data shapes that warrant additional study. Nonlinear piecewise regression suggested soil matric potential may useful as a predictor for the rate of change in predawn leaf water potential upon exposure to a water deficit. The critical point bridging the linear spans, –30.6 kPa, could be useful for incorporating in emerging irrigation decision support systems.
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