Evaluation of the physiological and spectral responses of grapevines (Vitis vinifera L.) under different durations of drought stress under high temperature conditions

Heatwaves and droughts pose a growing threat to viticulture, and it is crucial to identify physiological signs of grapevine stress in order to make effective management decision to mitigate this stress. This study aimed to (i) evaluate the responses of irrigated (C) and non-irrigated (DS) isohydric and anisohydric grapevine (Vitis vinifera L.) cultivars in a hot environment, and, (ii) identify the relevant leaf reflectance spectral regions for early stress detection. We characterised the physiological and spectral responses of potted cv. Grenache and Shiraz (syn. Syrah) grapevines undergoing three or five days of drought stress (DS) in a controlled heated environment. Vine water status and leaf gas exchange were assessed before and after stress imposition. On the same dates, leaf spectral responses were assessed using a portable spectroradiometer. Our results indicated that Grenache maintained its physiological function under well-watered conditions despite decreased leaf stomatal conductance (gs) after five days of high temperature. Under DS conditions, unlike Shiraz, Grenache was unable to recover to its original (pre-stress) levels of leaf net photosynthesis (Pn) and gs after five days of stress. The spectral signatures of the different treatments allowed us to identify wavelength regions that were more sensitive to individual and combined stresses: 650-700 nm, 1400-1500 nm and 1900-2000 nm. The findings of this study suggest that in hot environments, Grenache and Shiraz partially abandon their isohydric and anisohydric behaviours, respectively. Grenache appears more tolerant to high temperature when soil moisture is non-limiting, whereas Shiraz is more resilient to heat when soil moisture is limited. Identifying the leaf spectral regions that are sensitive to drought and heat stresses may allow for the implementation of new protocols and instruments for early stress detection