Using leaf hyperspectral data to early detect before the onset of symptoms in a heavily affected vineyard of Tuscany (Central Italy).

Advanced methods are necessary to improve the detection of flavescence dorée (FD), i.e., one of the most relevant grapevine (Vitis vinifera) diseases in Europe, caused by flavescence dorée phytoplasma (FDp), which is commonly carried out visually by agronomists/winegrowers, so being time-consuming and error prone. The present study demonstrated that full range hyperspectral data (i.e., 400-2,400 nm) collected at leaf level can be used as a tool to rapidly and non-destructively detect FD infection directly in the field. Focusing on a Sangiovese (red grape) vineyard of Tuscany (Central Italy), heavily affected by FD (incidence higher than 75%), we showed that the proposed hyperspectral approach is capable of (i) detecting FDp infection, even before the occurrence of leaf symptoms (accuracy >70%); (ii) discriminating FD-induced leaf symptoms, even between asymptomatic and lightly symptomatic leaves (accuracy: 80%); and (iii) elucidating the complex physiological responses of grapevines to FDp infection, with changes in leaf parameters estimated from spectra suggesting that the disease not only impaired early-season photosynthetic efficiency but also accelerated leaf senescence, potentially impacting grapevine productivity and grape quality. Although the hyperspectral approach proposed here is not intended to replace traditional diagnostic methods (molecular analyses), it could serve as a valuable tool to support the monitoring of plants affected by FD, and may represent a crucial advancement in FD management. Further and broader studies including vineyards less challenged by FD and with other grape varieties (e.g., white ones, showing leaf yellowing instead of reddening) are encouraged.