Irrigation scheduling is critical as it affects both fruit yield and composition. We examined the potential to use field-measured hyperspectral remote sensing data (reflectance and transmission over the 350–2500 nm wavelength region) to estimate leaf water content, equivalent water thickness (EWT), and leaf water potential (Ψ) in a commercial vineyard of Vitis vinifera cv. Pinot noir. The data allowed us to evaluate a number of reflectance patterns to estimate vine water status through correlations using two spectral approaches: direct measurement of vegetation indexes (VIs) and continuum removal analysis (CRA). Continuum removal analysis was applied to obtain the maximum band depth (MBD) and the band area (BA) of several absorption features sensitive to water content. Correlations were high for EWT at the leaf level using a modification of the Simple Ratio VI (SR2; R² = 0.916) and for CRA with MBD₉₇₀ (R² = 0.917) and BA₁₁₆₀ (R² = 0.897). Correlations with EWT and water potential at the canopy level for SR2 were nonsignificant, which was characteristic for many VIs. For predawn water potential (ΨPD) and midday stem water potential (Ψstem) at the canopy level, best fits were realized for Modified Triangular VI (MTVI2; R² = 0.360) and Red/Green VI (RGI, R₆₉₅/R₅₅₄; R² = 0.462), respectively. For canopy level water status, the best results were obtained using the difference between the midday stem water potential and the pre-dawn leaf water potential (Ψstem - ΨPD) with R² = 0.619 for RGI and R² = 0.541 for Structure Intensive Pigment Index (SIPI, R₈₀₀-R₄₄₅/R₈₀₀-R₆₈₀), while for CRA R² = 0.477 for BA₁₆₀₀ and R² = 0.509 for MBD₉₇₀. Results suggest that noninvasive monitoring using hyperspectral data could improve current methods for estimating water status in individual vines. Applications of similar measurements could be produced from airborne hyperspectral imagers to provide spatially resolved estimates of water stress for use in water management of large-scale commercial vineyards.
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Pérez et al. (2007) studied this question.
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