Hybridization of vegetation index with agroclimatic data to improve biomass estimation in tomato for precision N management

Crop biomass is an important parameter to be non-destructively monitored for the proper management of nitrogen (N) fertilization in vegetable cropping systems. The present paper aims at showing the development of an innovative vegetation index that integrates both reflectance measurements and growing degree days (GDDs) for biomass estimation in tomato under different N fertilization treatments. Along five growth stages of tomato plants, both the Green Vegetation Index (GVI) and the plant biomass were monitored. Then the cumulative area under the curve of the GVI of the crop across the GDDs (cIGVI) was calculated per each experimental plot and correlated with tomato biomass. Even though significant weak relationships between GVI and biomass were found at each growth stage, they cannot be used in intermediate periods since they are calibrated for a specific growth stage. The adoption of cIGVI significantly improved the biomass estimation in comparison to the simple GVI-biomass models, and the relationship with tomato biomass was found to follow a Gompertz function. These results suggest that cIGVI may be a promising index for estimating tomato biomass across the entire growing season under different N statuses, and including spectral data in agroclimatic model for estimating biomass can enhance the prediction performances.