Modelling of Solar Radiation Interception and Biomass Production in an Intercropping System of Rubber with Banana and Pineapple

• Main Author: Jalloh, Mohamadu Boyie
• Format: Thesis
• Language: English; English
• Published: 2003
• Subjects: Solar radiation simulation.; Plant biomass.; Intercropping.
• Online Access: http://psasir.upm.edu.my/id/eprint/10657/1/FP_2003_20.pdf; http://psasir.upm.edu.my/id/eprint/10657/

Simulation modelling is a powerful approach for studying complex intercropping systems in entirety and a complementary tool to conventional field experiments. This study aimed to: 1) construct a dynamic model to simulate the biological productivity of an immature rubber (R), banana (8) and pineapple (P) intercropping system based on the interception and utilisation of incident solar radiation (SR), 2) evaluate growth and yield of the intercrop components using the model, 3) compare production for various cropping scenarios and 4) investigate the likelihood and effects of water stress on crop growth using a simple water budget. A FORTRAN computer model, SURHIS (Sharing and Utilisation of Radiation intercepted in a Hedgerow-Intercropping System), was developed for simulating daily SR interception and growth of R-B-P intercropping system. SR interception was modelled using a modified Monsi-Saeki equation by including a clump factor to account for the loss in intercepted SR resulting from the wide row spacing between the crops. Crop growth was modelled based on the net biomass resulting from the difference between crop photosynthesis and respi ration. Simulation results showed that increments in the leaf area index (LAI) had a greater effect on SR interception by component crops compared to height increments. Changes in height affected only fractional interception, whereas LAI increments affected both fractional and total interception. The crop growth modules were suffiCiently accurate in estimating LAI and dry matter yield (OMY) but less precise for crop height. The girth of rubber was estimated with good accuracy. The general trend in overestimation for later part of the simulation period can be attributed to model assumptions for potential production conditions.