Modelling biomass production and yield of horticultural crops: a review

Abstract

Descriptive and explanatory modelling of biomass production and yield of horticultural crops is reviewed with special reference to the simulation of leaf area, light interception, dry matter (DM) production, DM partitioning and DM content. Most models for prediction of harvest date (timing of production) are descriptive. For DM production many descriptive and explanatory models have been developed. Most explanatory models are photosynthesis-based models. Important components of photosynthesis-based models are leaf area development, light interception, photosynthesis and respiration. Leaf area is predominantly simulated as a function of plant developmental stage or of simulated leaf dry weight. Crop photosynthesis can be calculated as a function of intercepted radiation or more accurately by considering radiation absorption of different leaf layers in combination with a submodel for leaf photosynthesis. In most crop growth models respiration is subdivided into two components: growth and maintenance. There is reasonable consensus concerning the simulation of growth respiration, but the simulation of maintenance respiration is still an area of great uncertainty, which is especially important for large crops grown under winter conditions at relatively high greenhouse temperatures. DM partitioning can be simulated by descriptive allometry, functional equilibrium or sink regulation. The most suitable approach depends on the type of crop studied and the aim of the model. As opposed to most agricultural crops, the DM content of the harvestable product is of great importance to the yield of most horticultural crops. More attention should be paid to the simulation of DM content. It is concluded that the strong features of explanatory crop growth models are the simulation of light interception and gross photosynthesis, while the weak features are the simulation of leaf area development, maintenance respiration, organ abortion, DM content and product quality.