Non-destructive estimation of individual buckwheat plant biomass using high-throughput phenotyping-derived canopy traits.

Abstract

In this research, we aim to develop a technique for estimating biomass of individual buckwheat from high-throughput phenotyping derived crop traits (HTP-derived crop traits). A tractor-mounted multi-camera phenotyping system was utilised to take images which were processed to generate crop height, volume index and coverage. The accuracy of the imaging system was first validated by comparing image-derived plant height with manual measurements, showing strong agreement with high linear coefficients of determination (R²) of 0.95 and 0.93 for "18sd-1" and "Kitamitsuki", respectively. A biomass estimation model was then developed by relating biomass accumulation to estimated HTP-derived crop traits and compared to that of Monteith-based RUE framework. Biomass estimation was evaluated using one-stage, two-stage, and three-stage models, where the two-stage model separated pre- and post-flowering periods and the three-stage model further divided the pre-flowering period into early and mid-growth stages. The three-stage model improved performance, indicating that developmental stage should be considered when modelling biomass accumulation in buckwheat. Among the evaluated HTP-derived traits, volume index showed the strongest association with measured biomass and showed a similar accuracy as that of the conventional coverage-based RUE framework. These results demonstrate that HTP-derived structural traits, particularly volume index, provide a practical and biologically interpretable approach for repeated, non-destructive estimation of individual-plant biomass in buckwheat.