engleski

Hyperspectral imagery as a supporting tool in precision irrigation of karst landscapes

This research was carried out in an experimental vineyard grown in artificially transformed karst terrain (Croatia). The experimental design included four water treatments in three replicates: 1) fully watered or based on 100% evapotranspiration (ETc) application ; 2) regulated deficit irrigation based on 75% and 50% ETc applications ; and 3) non- watered. Hyperspectral images of grapevines were taken in the summer of 2016 using two spectral-radiance (W·sr−1 ·m−2 ) calibrated cameras, covering wavelengths from 409 to 988 nm and 950 to 2509 nm. The four treatments were grouped into two new sets: 1) drought (NO) ; and 2) watered (the remaining three treatments). The watered group was then split into two new sets: 1) 50% treatment ; and 2) 75+ 100% treatment. The images were analyzed using Partial least squares – discriminant analysis (PLS-DA), and Single Vector Machines (SVM). The PLS-DA demonstrated the capability to determine levels of grapevine drought or watered groups with 70 - 80% accuracy. A similar success rate was achieved in distinguishing the 50% group from the 75 +100% group

vineyard, irrigation, water stress, hyperspectral imagery, soil

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