A methodological approach to assess canopy NDVI–based tomato dynamics under irrigation treatments

A tomato field experiment under deficit irrigation treatments was established to assess the feasibility of nonlinear mixed models to predict the change in the canopy Normalized Difference Vegetation Index (NDVI) along the growing season. The irrigation doses were 50, 70, 85, and 100 % of the actual evapotranspiration (ETc). The experiment was performed in the Peruvian Arid Coastal Region (13.10 S, 76.37 W). On-ground destructive plant measurements (7 times) allowed to obtain the leaf area index (LAI) and the canopy equivalent water thickness (EWTcanopy) to validate the experiment. Similarly, volumetric soil moisture was monitored at three hours interval using time-domain reflectometry. High-resolution multispectral imagery was acquired along the growing season (10 times) using an unmanned aerial vehicle. NDVI at plant level was obtained based on oversegmented imagery. The canopy NDVI growth curves were obtained in relation to the irrigation treatments and growing degree days (GDD) using a nonlinear mixed model.Deficit irrigation doses (50, 70 and 85 % ETc) induced lower biomass accumulation and greatly affected LAI and EWTcanopy, attaining lower values (p < 0.05) than the control (100 % ETc). In spite of reaching higher LAI and EWTcanopy values, 70 % ETc was not significantly different from 50 % ETc (p < 0.05) showing the difficulty to accurately discriminate treatments with high deficit irrigation; 85 % ETc produced important differences on EWTcanopy and LAI compared to the other deficit irrigation treatments (p < 0.05) due to a higher leaf area expansion. Deficit irrigation doses led to less vigorous plants resulting in lower NDVI compared to the control. Notwithstanding 50 % ETc obtained lower NDVI values than 70 % ETc, differences were not significant. Volumetric soil moisture was consistent with the irrigation treatments, resulting in a decreased trend with decreasing water application along the growing season. A three-parameter logistic mixed model was found to be well-suited to fit the tomato canopy NDVI growth curves in function of the irrigation treatments (i.e. fixed effects) considering the plant-specific variability (i.e. random effects). At maturity stage, significant differences of the deficit irrigation treatments from the control were obtained (p < 0.05) when cumulative effect of the treatments was well-defined and NDVI reached asymptotic behavior. During the vegetative stage, the inflection point marked the fastest NDVI growth rate for the 100 % ETc treatment whereas the lowest for the 50 % ETc (p < 0.05). The diagnosis plots and the low root mean squared error of the residuals indicated the suitability of using the three-parameter logistic growth curve estimated as a nonlinear mixed model to predict NDVI.