Análise da variabilidade espacial e zonas de produtividade em vinhedos de Cabernet Sauvignon e Shiraz, no Vale Central Gaúcho

• Ano de defesa: 2023
• Autor(a) principal: Ferreira, Regiane Aparecida
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Santa Maria; Brasil; Agronomia; UFSM; Programa de Pós-Graduação em Agricultura de Precisão; Colégio Politécnico da UFSM
• Palavras-chave em Português: Índices de vegetação; Aeronave remotamente pilotada; Viticultura de precisão; Vegetation indexes; Remotely piloted aircraft; Precision winemaking; CNPQ::CIENCIAS AGRARIAS::AGRONOMIA
• Link de acesso: http://repositorio.ufsm.br/handle/1/29361

A pilot project for implementing precision viticulture was started at Vinicola Velho Amâncio. The objective of this work was to characterize the spatial variability of vegetation (vines), using geotechnologies applied to precision agriculture, and propose a suggestion of productivity zones/environments. A vineyard of 1.3 ha was used, located in Itaara, RS, Brazil, cultivated with fine vines (Vitis vinifera L.) cv. Shiraz (SH) and Cabernet Sauvignon (CS), conducted in espaliers, with 21 years of implantation. In 2020, a flight was carried out with a remotely piloted aircraft (ARP) to obtain an orthomosaic of the vineyard and define its limits in the geographic information system (GIS) Arc Map. Data collection took place in the years 2021/22, with a grid of 50 sampling points (SP), with up to 3 plants, used for counting vines (productive, unproductive, failures/dead) and bunches of grapes. RGB and multispectral sensors were used in the ARP (Phantom 4 and RedEdge-Mx), and also a spectroradiometer (FieldSpec Hand Held 2 VNIR ASD), for the generation of vegetation indices (VI) (NDVI, NDRE, MPRI, NDWI, PSRI and RED/GREEN). The relative chlorophyll content was determined with a chlorophyll meter (Minolta SPAD502). Productivity was obtained by multiplying the number of bunches by the average weight of the 2023 harvest (SH – 87.51g; CS – 44.11g). Data were analyzed using descriptive statistics, rank comparison analysis, Mann-Whitney test (p=0.05), Spearman correlation (p=0.05) and hierarchical cluster analysis – Cluster. With the Cluster it was possible to group the areas of influence of the PAs, obtained by Voronói polygons in GIS, to generate the initial proposal of productivity zones. The results showed that there was strong heterogeneity and high variability in the data, with high rates of unproductive, failed/dead plants, low productivity, verified in the number of grape bunches and fresh mass (kg), either per plant or per sampling point, with a decrease from the year 2021 to 2022. MPRI and RED/GREEN were the IV that presented moderate correlations with the accumulated productivity (2021/22), 0.67 and -0.66 (p<0.05). Three productivity zones were obtained for the vineyard, 1 – low productivity (group 1: 0.4166 ha; 0.170 kg PA-1), average productivity ( 0.1723 ha; 0.740 kg PA-1), high productivity (0.6239 ha; 1.29 kg PA-1). However, the data suggest a decline in the vines and interventions will be necessary to obtain greater productivity, something that will have to be analyzed by the winery managers, as well as the proposed zoning. The objectives were met by describing the spatial variability of the vines and generating proposals for productivity zones for future phases of the project.