Tannins-lignin mixed nanoformulations for improving the potential of neem oil as fungicide agent.

Sustainability and circular economy are increasingly pushing for the search of natural materials to foster antiparasitic treatments, especially in the case of economically relevant agricultural cultivations, such as grapevine. In this work, we propose to deliver neem oil, a natural biopesticide loaded into novel nanovectors (nanocapsules) which were fabricated using a scalable procedure starting from Kraft lignin and grapeseed tannins. The obtained formulations were characterized in terms of size and Zeta potential, showing that almost all the nanocapsules had size in the suitable range for delivery purposes (mean diameter 150-300 nm), with low polydispersity and sufficient stability to ensure long shelf life. The target microorganisms were three reference fungal pathogens of grapevine (Botrytis cinerea, Phaeoacremonium minimum, Phaeomoniella chlamydospora), responsible for recurrent diseases on this crop: grey mold or berry rot by B. cinerea and diseases of grapevine wood within the Esca complex of diseases. Results showed that grapeseed tannins did not promote inhibitory effects, either alone or in combination with Kraft lignin. On the contrary, the efficacy of neem oil against P. minimum was boosted by more than 1-2 orders of magnitude and the parasite growth inhibition was higher with respect to a widely used commercial pesticide, while no additional activity was detected against P. chlamydospora and B. cinerea.

Development and Validation of a Mechanistic Model That Predicts Infection by Diaporthe ampelina, the Causal Agent of Phomopsis Cane and Leaf Spot of Grapevines.

Phomopsis cane and leaf spot (PCLS), known in Europe as "excoriose," is an important fungal disease of grapevines caused by Diaporthe spp., and most often by Diaporthe ampelina (synonym Phomopsis viticola). PCLS is re-emerging worldwide, likely due to climate change, changes in the management of downy mildew from calendar- to risk-based criteria that eliminate early-season (unnecessary) sprays, and the progressive reduction in the application of broad-spectrum fungicides. In this study, a mechanistic model for D. ampelina infection was developed based on published information. The model accounts for the following processes: (i) overwintering and maturation of pycnidia on affected canes; (ii) dispersal of alpha conidia to shoots and leaves; (iii) infection; and (iv) onset of disease symptoms. The model uses weather and host phenology to predict infection periods and disease progress during the season. Model output was validated against 11 independent PCLS epidemics that occurred in Italy (4 vineyards in 2019 and 2020) and Montenegro (3 vineyards in 2020). The model accurately predicted PCLS disease progress, with a concordance correlation coefficient (CCC) = 0.925 between observed and predicted data. A ROC analysis (AUROC>0.7) confirmed the ability of the model to predict the infection periods leading to an increase in PCLS severity in the field, indicating that growers could use the model to perform risk-based fungicide applications.