Comparison of plant proximal sensing approaches for nitrogen supply detection in crops

Nondestructive proximal sensors can be an efficient source of information N status in crops for localized and rapid adjustment fertilization applications. The aim this study was to compare two transmittance/reflectance-based (SPAD, ASD) a florescence-based sensor (Multiplex) their ability measure content corn (Zea mays L.), spring winter barley (Hordeum vulgare rye (Secale cereale both at the leaf canopy level. Measurements leaves canopies from six field trials 2019 2020 were analyzed establish relationships between laboratory-determined crops. Analyses included linear regression single variables machine learning multivariate approaches, assess relative accuracy N. ASD is time-intensive requires post hoc analyses spectra. However, spectral outputs device clearly correlated with canopies. At level, SPAD showed higher than any Multiplex predict plant performance could improved by combining three its variables. interpolated values best-performing similar accuracy. It concluded that relationship sensor-N species specific. Despite high standard deviation recorded some raw variable, derived indices comparable low deviation. both, levels integrated solution would combine multidimensionality ASD, practicality SPAD.