Relationship between the normalized difference vegetation index and leaf area in vineyards

• Autor(a) principal: Junges,Amanda Heemann
• Data de Publicação: 2019
• Outros Autores: Fontana,Denise Cybis, Lampugnani,Cristian Scalvi
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Bragantia
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0006-87052019000200297
• topic: NDVI; Vitis vinifera; Chardonnay; Serra Gaúcha region; Greenseeker

ABSTRACT In vineyards, the monitoring of leaf area is used to guide management practices in order to produce grapes with quality and enological potential. Remote sensing has been used to estimate leaf area by means of vegetation indices. This work aimed at determining the temporal evolution of the Normalized Difference Vegetation Index (NDVI) while associating it with leaf area of vineyards in the Serra Gaúcha region, Brazil. To this end, between 10 and 20 plants were evaluated monthly (September to May) in three vegetative seasons. NDVI data were obtained using the remote sensor Greenseeker while the following leaf area related parameters were obtained non-destructively: unit leaf area (ULA), average number of leaves per branch (NLB), plant leaf area (PLA), leaf area index (LAI) and chlorophyll index (CI). Data correlation was assessed by joint temporal analysis and Pearson correlations (p < 0.05). The results indicated that NDVI variation over time is coherent with the leaf area dynamics and expresses biomass variations due to phenology and management actions. The NDVI evolution pattern is described by a quadratic regression equation: the index increases rapidly at first (September to November), followed by a relative stabilization (December to February), and decreases in the final stage (March to May). The correlations were higher in the initial and final stages of the cycle, especially for NLB (r = 0.73 and 0.77), PLA (r = 0.60 and 0.61) and CI (r = 0.48 and 0.84), which are promising parameters for characterizing leaf area in vineyards by remote sensing.