Daniel Sepulveda-Reyes

Mr. Daniel Sepulveda-Reyes


Research Focus & Metrics

Academic Career Length

11Years (2016-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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7 October 2016 in Remote Sensing
Verified
Journal Article
Open access
PDF file
DSDaniel Sepulveda-Reyes
Daniel Sepulveda-Reyes
Ben IngramBen Ingram
Ben Ingram
MBMatthew Bardeen
Matthew Bardeen
MZMauricio Zúñiga
Mauricio Zúñiga
Samuel Ortega-FariasSamuel Ortega-Farias
Samuel Ortega-Farias
Carlos  Poblete-EcheveriiaCarlos Poblete-Echeveriia
Carlos Poblete-Echeveriia
Aerial and terrestrial thermography has become a practical tool to determine water stress conditions in vineyards. However, for proper use of this technique it is necessary to consider vine architecture (canopy zone analysis) and image thresholding approaches (determination of the upper and lower baseline temperature values). During the 2014–2015 growing season, an experimental study under different water conditions (slight, mild, moderate, and severe water stress) was carried out in a commercial vineyard (Vitis vinifera L., cv. Carménè). In this study thermal images were obtained from different canopy zones by using both aerial (>60 m height) and ground-based (sunlit, shadow and nadir views) thermography. Using customized code that was written specifically for this research, three different thresholding approaches were applied to each image: (i) the standard deviation technique (SDT); (ii) the energy balance technique (EBT); and (iii) the field reference temperature technique (FRT). Results obtained from three different approaches showed that the EBT had the best performance. The EBT was able to discriminate over 95% of the leaf material, while SDT and FRT were able to detect around 70% and 40% of the leaf material, respectively. In the case of canopy zone analysis, ground-based nadir images presented the best correlations with stomatal conductance (gs) and stem water potential (Ψstem), reaching determination coefficients (r2) of 0.73 and 0.82, respectively. The best relationships between thermal indices and plant-based variables were registered during the period of maximum atmospheric demand (near veraison) with significant correlations for all methods.