A Model for Predicting Yield of Seeds in Ficus Fruits

Abstract

Ficus is one of the largest plant genus which has an ecological significance due to the presence of “keystone” species. Availability of its sole mutualistic wasp pollinator and the effect of non-pollinator wasps determine the availability of seeds in Ficus fruits to produce the next generation of each species. In most of the previous studies on the yield of seeds of Ficus fruits, seeds have been counted manually, which is a time consuming and hectic process. Therefore, the main objective of this study is to introduce a model for predicting the yield of seeds in two Ficus species. Local polynomial regression, generalized additive models, and Poisson regression models were used for constructing these models to predict the number of seeds per fruit. Two generalized additive models which were constructed for Kandy municipal & Thumpane were best described with lower mean square error values of testing samples and moderately large R2 values when Fruit length was taken as a single predictor for both models. Poisson regression model gives a better result for modeling in Ficus callosa with min-max scaled variables, with a lowest mean square error value of the testing sample. Models which were built up for areas give the best prediction values when the yield of seeds less than 1000. By using local polynomial regression curves, it was identified that both biasedness and variance can be optimized using optimal bandwidth which was calculated by plug in the rule and it gives freedom to the flow of data by keeping non-parametric qualities.