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Selected Publication:

Oletic, D; Rosner, S; Zovko, M; Bilas, V.
(2020): Time-frequency features of grapevine's xylem acoustic emissions for detection of drought stress
COMPUT ELECTRON AGR. 2020; 178, 105797 FullText FullText_BOKU

In cultures like grapevine, growth, yield and fruit quality depend on precise regulation of water stress using precision irrigation. In arid climates with seasonal droughts, karst areas and porous stony soils it is difficult to assess irrigation thresholds only based on soil water balance, requiring novel, plant-based techniques of early drought stress detection. In plants, water stress causes an increase in evapotranspiration rate, subjecting the water in the xylem conduits to high tension. This creates cavitations, leading to xylem embolization, loss of hydraulic conductivity and possibly plant death. A promising emerging technology for automated, non-invasive field monitoring of xylem cavitations is acoustic emission (AE) testing. Passive piezoelectric sensors on trunk are used to capture intermittently appearing AE, occurring in ultrasonic frequency-band from 100 kHz to 1 MHz. To make AE suitable as an input for precision irrigation, we present a novel AE time-frequency feature set for discrimination between normal and drought stress conditions. The proposed feature extraction method entails software-compensation of sensor's frequency response, enabling the wide-band frequency-analysis with miniature resonant high-frequency piezoelectrics. The signal analysis revealed three characteristic groups of AEs, differentiated by their spectral composition: single-component, multi-component, and broadband AEs. In conditions of increased water stress, single-component emissions cluster around 200 kHz, and multi-component emissions group between 200 and 600 kHz, forming discriminant time-frequency signatures. The study entails an extensive set of laboratory pot-plant dehydration experiments on four different grapevine cultivars, verifying the selectivity, sensitivity and repeatability of the extracted feature set. It proved sensitive enough for detection of drought stress corresponding to moderate leaf water potentials ranging between -0.7 and -1.2 MPa.
Authors BOKU Wien:
Rosner Sabine

Find related publications in this database (Keywords)
Precision irrigation
Drought stress
Acoustic emission testing
Time-frequency analysis

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