Ground-Based Remote Sensing for Assessing Tomato Water-Status
AbstractThe objective of this “on farm” research is the evaluation of the remotely surveyed signals in describing crops’ water status dynamics, with the goal of optimizing the tomato irrigation scheduling on a regional level. Attention is given to the surface infra-red (IR) temperature and to the Normalized Differential Vegetation Index (NDVI); both signals were measured from ground platforms in tomato fields over two years, in two localities (Foggia and Rutigliano). The tomato was grown under three soil-water regimes. The water-status of the vegetation was measured at regular intervals through the predawn leaf water potential (PLWP), while IR temperature and NDVI were monitored continuously. The attempts at finding an operative solution to detect the crop’s water-status starting from the IR temperature did not prove to be interesting. The results obtained on NDVI seem to indicate new possibilities in planning irrigation scheduling on a territorial level. In regards to the NDVI, the limitations of its application were represented by the fact that two different crop water conditions could have the same NDVI value. Another limitation consisted in the reduced range in variation of the NDVI. The NDVI values measured during the tomato growth season vary in a little range (between 0.9 and 0.6). Considering the fact that NDVI values are affected by errors innate to the measuring technique, the operative use of NDVI in irrigation scheduling at the moment can not be recommended.
PlumX Metrics provide insights into the ways people interact with individual pieces of research output (articles, conference proceedings, book chapters, and many more) in the online environment. Examples include, when research is mentioned in the news or is tweeted about. Collectively known as PlumX Metrics, these metrics are divided into five categories to help make sense of the huge amounts of data involved and to enable analysis by comparing like with like.
Copyright (c) 2010 Marcello Mastrorilli, Pasquale Campi, Domenico Palumbo, Francesca Modugno
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.