Interaction Between Armenian Clay-based Ceramic and Model Wine

In the last few years the development of HPLC techniques together with multivariate statistical methods allowed to set methodics of large discriminant and classing efficacy in the study of wine-grapes.

Plants in their natural environment are in continuous interaction with large numbers of potentially pathogenic and beneficial microorganisms. Depending on the microbe, plants have evolved a variety of resistance mechanisms that can be constitutively expressed or induced. Phytoalexins, which are biocidal compounds of low to medium molecular weight synthesized by and accumulated in plants as a response to stress, take part in this intricate defense system.1,2
One of the limitations of our knowledge of phytoalexins is the difficulty of analyzing their spatial responsiveness occurring during plant- pathogen interactions under natural conditions.

In this study we have compared the predictive ability of two phenological models: a traditional Thermal Time (TT) and a version of the more recently develop Unified Model (UM).

Il Nebbiolo, uno dei vitigni più rappresentativi della viticoltura piemontese. é caratterizzato da una maturazione tardiva, una elevata vigoria e una bassa fertilità basale. La sua popolazione inoltre presenta una tale variabilità morfologica che é consuetudine suddividere il vitigno in diverse sottovarietà (Lampia, Rosé, Michet, Balla per citare solo quelle dell’areale albese) ognuna con presunte distinte caratteristiche morfologiche e produttive.

Water scarcity, high air temperatures, high vapor pressure deficit, and increasing frequency and intensity of extreme climatic events, namely heat waves, exert huge pressure on viticulture, as is the case of Mediterranean climates. Therefore, farmers rely more and more on irrigation to overcome these constraints. Deficit irrigation is a proved strategy to optimize irrigation efficiency and wine quality. The present study intends to demonstrate the application of precision techniques, namely remote sensing derived vegetation indices (VI) and an open source software, SIMDualKc, to compute crop evapotranspiration using the dual crop coefficient approach (Kcb + Ke), for deficit irrigation management.