Exploring dynamic nitrogen (N) fertigation guided by multispectral sensors: a sustainable optimization of N fertilization in processing tomato

• Dynamic nitrogen management saves 38–60% of N inputs without yield losses. • Fruit size was increased by dynamic N fertigation. • Dynamic fertigation saved 45% of greenhouse gas emissions and 55% of costs. • Experiments are needed to scale up dynamic fertigation guided by satellites. Dynamic management of nitrogen (N) guided by multispectral sensors can help match in-season crop N requirements with precise N supply through fertigation. In the present work, different dynamic strategies to optimize N fertigation in processing tomatoes were explored in two plot experiments across two different years and locations, compared with a well-fertilized control (180 kg N ha -1 , N180). In dynamic N strategies, the green vegetation index (GVI) was monitored with a hand-held multispectral radiometer. Whenever the GVI fell below a critical threshold, N fertilizer was supplied via fertigation. Critical thresholds were developed using different approaches: in the spy plot strategy (N SPY), the N fertilizer was supplied whenever the GVI of the plot was below 90% of the GVI in the spy plot N180. Conversely, absolute threshold GVI values were developed in previous modeling stages based on linear-plateau relationships between the GVI and the relative yield (N THR strategies) or based on the monitoring of the GVI profile of tomatoes under non-limiting N conditions in a previous growing season (N SPY EVO ). In general, the dynamic N strategies saved a significant amount of N fertilizers (with reductions ranging from 38 to 60%), with best performances observed for the N THR and N SPY EVO . Dynamic N strategies did not penalize the marketable yield, thus, the N use efficiency, the fertilizer costs, and the greenhouse gas emission intensity associated with the fertilization were significantly optimized. Furthermore, dynamic N strategies produced fewer but bigger fruits. The present work shows innovative N management strategies to optimize N inputs in processing tomato cultivation, confirming the potential of multispectral sensors in precision agriculture.