Assessing reserve nitrogen at dormancy for predicting spring nitrogen status in Chardonnay grapevines

Current remote sensing strategies rely heavily on reflectance data and energy balance modelling using thermal imagery to estimate crop water use and stress. These approaches show great promise for driving precision management decisions, but still require work to better understand how detected changes relate to meaningful physiological changes. Under water stress, grapevines exhibit a range of responses involving both biological and physical changes within leaves and canopies.

AIM: Lactiplantibacillus plantarum species is wordwide used as starter for malolactic fermentation [1,2]. For the first time, in the present study, the use of L. plantarum (ML PrimeTM, Lallemand wine) to produce white wines with post-fermentative maceration extended until 60 days has been investigated.

Elemental composition, measured as the concentrations of different elements present in a given tissue at a given time point, is a key indicator of vine health and development. While elemental composition and other high-throughput phenotyping approaches yield tremendous insight into the growth, physiology, and health of vines, costs and labor associated with repeated measures over time can be cost-prohibitive. Recent advances in handheld sensors that measure hyperspectral reflectance patterns of leaf tissue may serve as an affordable proxy for other types of phenotypic data, including elemental composition. Here, we ask if reflectance patterns of dried Chambourcin leaf tissue from an experimental grafting vineyard can predict the known elemental composition of those leaves.

A work involving the finding, the description and the recovery of old grapevine varieties from the north and north east of Spain was begun in the CSIC in the year 1987.

Aims: The aims of this study were: (1) to compute recent-past thermal conditions over European vineyards, using state-of-the art bioclimatic indices: chilling portions and growing degree hours; (2) to compute future changes of these thermal conditions using a large ensemble of high-resolution climate models.