Individual-Based Modelling for Predicting Dry Matter Accumulation in Juveniles of Indian Olive Raised under Different Soil Treatments

Abstract

Dry matter accumulation data for juvenile Indian Olive saplings was modelled using linear and non- linear regression models. The data was gathered bimonthly and for two years i.e., twelve readings. Linear, Quadratic, Power, Sigmoid, and Exponential models performed quite well for cumulative growth data (Adj. R2 > 0.93). The Sigmoid model (Chapman- Richard) demonstrated upper asymptotic values ranged between 179.96- 334.49 grams for all treatments (T0 – T4) suggesting that olive saplings responded positively to different soil treatments. Both, age and size dependent relative growth rates (RGRs) manifested low values and decrease in RGR curve. Age- dependent RGR displayed a smooth decline in function, indicating extended longevity. Low RGR (along with low Specific Leaf Area), is a characteristic feature of slow growing and evergreen species and this trait was observed in Indian Olive growth too. Size- standardized RGR revealed that due to the low rate of decline, T4 had the superior RGR (and maximum dry matter accumulation) followed by other treatments. Moreover, T0 had the sharpest decrease and the lowest dry matter accumulation. Cross- validation of model parameters exhibited statistical stability.