Aboveground dry matter prediction using Monsi–Saeki theory and 3-D depth camera

— A case study on strawberry production —

Abstract

Intercepted light per plant canopy can be estimated using the Monsi–Saeki theory (MS) or spatial images (SI) and is useful for predicting total dry matter accumulation. This study aimed (1) to predict the total dry matter of strawberry (Fragaria × ananassa Duch. cv. “Benihoppe”) using MS, and (2) to develop a prediction model for total dry matter using SI based on MS. Strawberry plants were grown for 154 days, during which growth data and spatial images were collected. The results demonstrated that (1) MS application yielded accurate predictions of total dry matter (root mean square error [RMSE] = 12.1 g m⁻²), and (2) the model based on SI also provided appropriate predictions (RMSE = 20.5 g m⁻²).