A Novel Approach for Predicting Yield of Seeds in Ficus Fruits Using A Non-Parametric Method. Issue 3 (2nd July 2020)

• Record Type: Journal Article
• Authors: Jayarathna, H.L.D.K.; Nawarathna, Lakshika S.; Karunaratne, W. A. I. P.
• Is Part Of: International journal of fruit science. Volume 20:Issue 3(2020)
• Page Start: 603
• Page End: 619
• Publication Date: 2020-07-02
• Subjects: Ficus -- generalized additive modeling -- poisson regression -- min-max scaling -- yield of seeds; Fruit-culture -- Periodicals; Tree crops -- Periodicals; Fruit trees -- Periodicals; 634
• DOI: 10.1080/15538362.2019.1616653
• Languages: English
• ISSNs: 1553-8362

Abstract

ABSTRACT: Ficus: is one of the largest plant genera which are recognized as keystone species. In the previous studies on Ficus, seeds have been counted manually. The main objective of this study is to introduce a model for predicting the yield of seeds in two monoecious species. Three-dimensional magnitudes were measured, and the numbers of seeds were recorded per each fruit. Generalized additive models (GAM) and Poisson regression models were used for prediction. Fruit length is a significant predictor for both models. Moreover, it is observed that data classification as areas plays an important role in GAM. Poisson modeling of Ficus callosa gives better predictions than Ficus racemosa . Besides, predictions of both models are more accurate when the number of seeds is less than 1000.