Estimating early season growth and biomass of field pea for selection of divergent ideotypes using proximal sensing

The aims of this study were to (i) test ground and aerial-based remote sensing vegetation indices (VIs) for trait-based breeding line selection, (ii) improve our understanding of the association between measured plant traits and readings derived from active and passive sensors and (iii) establish an optimal time for growth assessments in relation to field pea vigour and seed yield. Multispectral sensors were deployed with the handheld Crop Circle (CC) and a sensor mounted on an unmanned aerial vehicle (UAV) to collect data from field trials conducted between 2017 and 2020 at Beulah and Horsham in Victoria and Yenda, Wagga Wagga and Ardlethan in New South Wales in Australia. The result showed that normalised difference vegetation index (NDVI) derived from an aerial-based passive sensor (UAV) was strongly and significantly correlated to NDVI derived from a ground-based active sensor (CC) at both Beulah (R2 = 0.85; n = 1165; p