Ampelometric Leaf Trait and SSR Loci Selection for a Multivariate Statistical Approach in Vitis vinifera L. Biodiversity Management

Abstract

High estimated heritability values were recently revealed for mature leaf traits in grape (Vitis vinifera L.), thus redeeming ampelography in the era of molecular markers. The “Organisation Internationale de la Vigne et du Vin (OIV)” set a list of hundreds of descriptors for grapevine in order to standardize ampelographic and ampelometric scores. Therefore, the selection and reduction of the number of OIV codes can represent a major goal for leaner biodiversity assessment studies. The identification of ampelometric traits associated with grape diversity allows to construct Classification Trees with chi squared automatic interaction detection (CHAID) algorithm, a stepwise model-fitting method that produces a tree diagram in which at each step the sample pool is splitted based on the independent variables statistically different for the dependent variable. A collection of 100 table and wine grapevines (Vitis vinifera L.) was characterized and evaluated by means of six microsatellites and twenty-two ampelometric traits on mature leaves. Nine ampelometric traits were selected by principal component analysis and employed to build the classification trees based on CHAID algorithm. The strategy can represent an effective tool for grape biodiversity management, right allocations, and identification of new grape genotypes, implemented by a further microsatellite investigation only when unsolved cases occur, allowing faster and cheaper results.