Banca de DEFESA: LUANA KESLLEY NASCIMENTO CASAIS

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
STUDENT : LUANA KESLLEY NASCIMENTO CASAIS
DATE: 18/03/2022
TIME: 08:00
LOCAL: Google meet
TITLE:

NUTRITIONAL BEHAVIOR OF WINE GRAPES IN THE TERROIR OF GARANHUNS, EVALUATED BY X-RAY FLUORESCENCE

KEY WORDS:

Agreste Pernambucano, Artificial Neural Networks, Terroir, Viticulture, XRF.

PAGES: 37
BIG AREA: Ciências Agrárias
AREA: Agronomia
SUBÁREA: Ciência do Solo
SPECIALTY: Fertilidade do Solo e Adubação
SUMMARY:

The cultivation of grapevines in the southern region of Pernambuco has shown
positive results both in terms of productivity and for the final quality characteristics of the
grapes and wine. The soil, climate, exposure and altitude have great influence on a quality
terroir. In managing a terroir, plant nutrition is of paramount importance, as it has a great
influence on the plants, with the leaves being the greatest indicators of deficiencies. The X-
ray fluorescence technique is a method that analyzes samples non-destructively and requires
only a small amount of samples. Aiming to understand how this nutrient availability occurs in
the leaf biomass of grapevines, this study aims to evaluate plant nutrition via X-ray
fluorescence for sampling of nutritional elements in grape leaves. The experiment was
performed in the Municipality of Brejão, at the Instituto Agronômico de Pernambuco (IPA).
The experiment was set up in a randomized block design with five repetitions, and the
treatments were composed of ten grape varieties for the elaboration of fine wines (white wine
- Sauvignon Blanc, Chardonnay and Muscat Petit Grain; red wine - Cabernet Sauvignon,
Pinot Noir, Petit Verdot, Merlot Noir, Malbec, Viognier and Syrah) and eight plants per plot.
The chemical elements (Calcium, Iron, Potassium, Magnesium, Phosphorus, Sulfur and
Rubidium) present in the leaves were analyzed from X-ray Fluorescence Spectrometry (XRF)
method. Artificial Neural Network (ANN) test and Pearson's product-moment correlation
coefficient ρ was applied in association the chemical variations. The data were submitted to
analysis of variance (ANOVA) and the means were compared using Tukey's test at 5%
probability level. The XRF method can be used as a great ally in the foliar diagnosis of
nutrients with fast and accurate response, also when in conjunction with artificial intelligence
methods is a great tool in the identification of varieties. The elements K, Mg, Fe and Ca
determined in grapevine leaves by X-ray fluorescence are strongly associated with soil
chemical and phenological variables of the plants. As for the nutrition of the plant, the Petit
Verdot variety was the one that presented the greatest balance in the concentration of the
elements Ca, Fe and Mg found in its leaves. While the other varieties showed great variation
in the determination of the concentrations. The Syrah variety had the highest degree of
deficiency found. The elements K and Mg were the ones that presented the greatest nutritional
imbalance among the varieties.
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ABSTRACT

Keywords: Agreste Pernambucano, Artificial Neural Networks,

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