Leaf area prediction models (Uzçelik-I) for different horticultural plants

Abstract

A total of 343 leaves were selected randomly from fifteen different horticultural plants, that are widely grown under Samsun ecological conditions. Lamina width, length and leaf area were measured. The plants were divided into three groups according to lamina shape, plants with similar shapes being put into the same group for developing an equation to predict their leaf areas. The first group of plants included avocado species [1], lotus plum used as persimmon rootstock [2], 52 ÜN 13 selected persimmon type [3], Hayward kiwifruit cultivar [4], Bonica F1 aubergine [5] and Yalova F1 pepper [6]. The second group included GAP F1 cucumber [7], Kara üzüm (Isabella) (Vitis labrusca L.) [8], Narince grape cultivar (Vitis vinifera L.) [9], red-currant species [10], local summer squash type [11] and local Urfa squash type [12]. The third group were selected runner bean type [13], Rubin red raspberry cultivar [14] and blackberry species [15]. The numbers in square brackets represent the plant species (PS) for the equations. The actual leaf area of the plants were measured by PLACOM Digital Planimeter, and multiple regression analysis with EXCEL 7.0 was performed on the groups separately. The leaf area models developed for the first, second and third groups, were LA= -50.63-1.353*L/W*PS+5.347*W+0.06*W 2*PS+5.489*L LA= -114.43-7.31*L/W*PS+0.651*W2+210.86*L/W LA=-148.65-2.39*LLL*PS+2.126*ULL*PS+29.72*LLL respectively, where LA is leaf area, L is leaf length, W is leaf width, ULL is upper leaf lobe length and LLL is lower leaflet length. All R2 values (0.983, 0.986 and 0.988 for the first, second and third group, respectively) and standard errors for all subsets of the independent variables were found to be significant at the p<0.001 level.