Irrigation Performance Assessment in Table Grape Using the Reflectance-Based Crop Coefficient

In this paper, we present the results of our study on the operational application of the reflectance-based crop coefficient for assessing table grape irrigation requirements. The methodology was applied to provide irrigation advice and to assess the irrigation performance. The net irrigation water requirements (NIWR) simulated using the reflectance-based basal crop coefficient were provided to the farmer during the growing season and compared with the actual irrigation volumes applied. Two treatments were implemented in the field, increasing and reducing the irrigation doses by 25%, respectively, compared to the regular management. The experiment was carried out in a commercial orchard during three consecutive growing seasons in Northern Chile. The NIWR based on the model was approximately 900 mm per season for the orchard at tree maturity. The experimental results demonstrate that the regular irrigation applied covered only 76% of the NIWR for the whole season, and the analysis of monthly and weekly accumulated values indicates several periods of water shortage. The regular management system tended to underestimate the water requirements from October to January and overestimate the water requirements after harvest from February to April. The level of the deficit of water was quantified using such plant physiological parameters as stem water potential, vegetative development (coverage), and fruit productivity. The estimated NIWR was roughly covered in the treatment where the irrigation dose was increased, and the analyses of the crop production and fruit quality point to the relative advantage of this treatment. Finally, we conclude that the proposed approach allows the analysis of irrigation performance on the scale of commercial fields. These analytic capabilities are based on the well-demonstrated relationship of the crop evapotranspiration with the information provided by satellite images, and provide valuable information for irrigation management by identifying periods of water shortage and over-irrigation.