AN EVALUATION OF TECHNICAL EFFICIENCY OF RICE FARMS AMONG THE BENEFICIARIES AND NON-BENEFICIARIES OF STATE INTERVENTION PROGRAMMES IN NIGERIA
Publication Type: Journal Article.
Publication Year: 2026
Author(s): Ishola Sarah Oluwakemi; Gbadamosi Fausiyat Yinka; C-Oluatosin Tope; Oludare Olufunke Tomisona and Alao Bashir Idowu.
Journal Name: (IJAEMD)
ABSTRACT
The crown is the centre of physiological activity, crucial for assessing the tree’s vigour. Accurately predicting the crown diameter is crucial in forest management, as it influences tree growth and yield. Diameter at breast height (Dbh) has a strong positive correlation with crown diameter (CD) and forest productivity. This study aimed to develop CD models using linear and nonlinear regression methods for the Department of Forestry and Wildlife, specifically for the Teak and Gmelina plantations at PAAU, Anyigba, Kogi State. Seventeen (17) Temporary Sample Plots of 0.625 ha were randomly laid across two strata identified (Tectona grandis and Gmelina arborea) using simple random sampling techniques at 10% sampling intensity. All tree-related variables were measured using standard procedures. The overall best linear crown prediction equation for the two species is a Multiple Linear-Polynomial model, with standard error of estimate (SEE) and root mean square error (RMSE) values of 1.2049 and 1.1962 for Tectona grandis and Gmelina arborea, respectively. The SEE and RMSE values for these models are 0.433 and 0.4303, respectively. The overall best prediction nonlinear crown prediction equation for Tectona grandis is the Power model, with SEE and RMSE values of 1.2467 and 1.2422, respectively. For Gmelina arborea, the Monomolecular model is the best, with SEE and RMSE values of 0.4385 and 0.4360, respectively. It can be concluded that all the developed models are biologically logical and can be applied to predict the current and future crown diameters of the stand for effective sustainable management, silvicultural treatment, and efficient timber production.
Keywords: technical efficiency, rice production, stochastic frontier analysis, government intervention, agricultural policy, Nigeria