Tropical Plant Research
An International Journal by Society for Tropical Plant Research
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2020, VOLUME 7 ISSUE 1Pages: 137-143
Estimating the leaf area of Khaya senegalensis (Desv.) A. Juss. from linear measurement
Owokotomo Olayinka Oluwatobi
Department of Forestry and Wood Technology, Federal University of Technology, Akure, Nigeria
Abstract:
This study was carried out to develop leaf area prediction models for Khaya senegalensis using linear measurement. The maximum lamina length (L) and lamina width (W) were measured with a graduated ruler (cm), while the actual leaf area (ALA) were measured with a software model WINRHIZO PRO 2005, installed on a computer system with an attached scanning machine. The best fit model was selected based on F-test; mean square error (MSE) and Coefficient of determination (R2). All parameters were positively and significantly correlated at 1% level. The product of length and breadth (LB) had the highest coefficient of Determination of 0.75. Quadratic and linear regression of the data produced eight leaf area models. The best five models were product and sum of length and width while the least four models were derived from single-dimensional measurement of either lamina length or width. The top five models were recommended for leaf area estimation of Khaya senegalensis, but for ease of application model with the highest R2 was preferred for its simplicity- Y= -3E=0.5x3+0.0046x2+1.9839x+7.2194; R2 = 75%.
This study was carried out to develop leaf area prediction models for Khaya senegalensis using linear measurement. The maximum lamina length (L) and lamina width (W) were measured with a graduated ruler (cm), while the actual leaf area (ALA) were measured with a software model WINRHIZO PRO 2005, installed on a computer system with an attached scanning machine. The best fit model was selected based on F-test; mean square error (MSE) and Coefficient of determination (R2). All parameters were positively and significantly correlated at 1% level. The product of length and breadth (LB) had the highest coefficient of Determination of 0.75. Quadratic and linear regression of the data produced eight leaf area models. The best five models were product and sum of length and width while the least four models were derived from single-dimensional measurement of either lamina length or width. The top five models were recommended for leaf area estimation of Khaya senegalensis, but for ease of application model with the highest R2 was preferred for its simplicity- Y= -3E=0.5x3+0.0046x2+1.9839x+7.2194; R2 = 75%.
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