Vertical farming offers a sustainable solution for urban food production, but energy optimization remains a critical challenge, with nearly half of the electricity requirements dedicated to artificial lighting. Dynamic adjustment of blue and red light can reduce energy costs, as blue light is more energy-intensive, thereby lowering operating expenses and increasing profitability.
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 optimise N fertigation in processing tomatoes were explored in two plot experiments across two different years and locations, compared with a well-fertilised control (180 kg N ha-1, N180). In dynamic N strategies, the green vegetation index (GVI) was monitored with a hand-held multispectral radiometer.
Hyperspectral imaging is widespread in crop nitrogen (N) monitoring for precision agriculture, although approaches that address the agronomical recommendation of the optimal N rate are still lacking. Here, two approaches are explored in defining the optimal N rate to be supplied in fertigated processing tomatoes through hyperspectral imaging. The first one, called the N uptake approach, focuses on the virtual reproduction of the critical N uptake curve through the estimation of both aboveground biomass and crop N uptake.