关键词: 蓖麻（Ricinus communis L.）, 叶片, 节位, 指标, 回归分析

Abstract: In order to provide theoretical basis for rational leaf picking of castor（Ricinus communis L.）, the regression analysis of leaf node position of main stem and its internode characters, leaf characters and quality characters were conducted from 2018 to 2020 with Dianbima No.2 as experimental material. The results showed that, ①Correlation coefficient analysis showed that there was a very significant positive correlation between different node positions and node length, leaf length, leaf width, petiole length, petiole width and transverse diameter, petiole basal gland length, leaf weight and net leaf weight of castor, and there was a significantly positively correlated with the thick transverse diameter of internode and petiole,there was a significant negative correlation with the number of leaves per kg, and no significant positive correlation with other indicators. ②Analysis of variance showed that there were significant differences between the leaf node of main stem and the node length of main stem, the length of the leaf, the width of the leaf and the length of the petiole. There were significant differences between the leaf node of main stem and the thickness and diameter of the main stem node, the petiole basal gland length and the net quality of the leaf. There was no significant difference between the leaf node of main stem and the other indicators. ③The regression equation fitting between the node position of main stem and main stem characters, leaf characters and quality characters of castor was conformed to the law of quadratic curve. According to the data fitting, when the best node position of main stem leaves is 9.20, the net weight of leaves in the fitting equation reaches 89.15 g at this node position. The effect of the node position on the main stem of castor on the leaf quality of the main stem was as follows, within a certain range of node position, the higher the node position of the leaf on the main stem of castor was, the more significantly the indexes such as leaf length, leaf width, petiole length, petiole width and transverse diameter, petiole basal gland length, leaf quality and leaf net quality increased. The leaf net weight at the ninth node was the highest, which provided a reference for reasonable leaf harvesting.

Key words: castor（Ricinus communis L.）, leaf, section, index, regression analysis