Hyperspectral Imaging of Adaxial and Abaxial Leaf Surfaces for Rapid Assessment of Foliar Nutrient Concentrations in Hass Avocado

Rapid assessment tools are required for monitoring crop nutrient status and managing fertiliser applications in real time. Hyperspectral imaging has emerged as a promising tool to manage nutrition. This study aimed determine the potential of hyperspectral predicting foliar concentrations avocado trees establish whether different sides leaves affects prediction accuracy. images (400–1000 nm) were taken both surfaces collected from Hass 0, 6, 10 28 weeks after peak anthesis. Partial least squares regression (PLSR) models developed predict mineral using (a) abaxial surfaces, (b) adaxial (c) combined leaf surfaces. Modelling successfully predicted nitrogen (RP2 = 0.60, RPD 1.61), phosphorus 0.71, 1.90), aluminium 0.88, 2.91), boron 0.63, 1.67), calcium 2.86), copper 0.86, 2.76), iron 0.81, 2.34), magnesium 0.87, 2.81), manganese 2.76) zinc 0.79, 2.21) either or surface. Foliar potassium only surface 0.56, 1.54). sodium 0.59, 1.58) In conclusion, showed great rapid nutrition trees, with being most useful concentrations.