An Experimental Study on the Effect of Cutting Angle on the Growth of Grafted Watermelon Seedlings Using the One-Cotyledon Grafting Method

Author:

Liang Huan,Jiang KaiORCID,Shi Xianfeng,Zhu Juhong,Liu Jiangfeng,Wang Dehuan,Ge Mihong,Zhou Mobing,Shan Feifei

Abstract

The labor-efficient automation of grafting has been recognized as a key factor in the wider adoption of grafting. In growing cucurbits, the root pruned one-cotyledon grafting method is the most commonly used method with grafting machines. The cutting angle, which affects the matching of the rootstock and scion, is key to the survival of the graft seedling. In the production of cucurbit graft seedlings, the cutting parameters are established based on experience, leading to low grafting success. To determine accurate cutting parameters, the watermelon cv. ‘Zaojia84-24′ was used as the scion and the pumpkin cv. ‘Zhenzhuang’ was used as rootstock, and two one-way experiments investigating the cutting angle of the watermelon scion and the rootstock as factors were conducted. The cutting angle of the rootstock and scion had no significant effect on the xylem reconnection rate or the grafting survival rate. A larger cutting angle for the rootstock and scion led to a delay in the reconnection of the phloem. Different cutting angles for the scion significantly affected the growth of the scion after grafting. Compared with a scion graft cutting angle of 10° (SL), graft cutting angles of 14° (SM) and 20° (SS) led to significantly greater scion dry weights, with increases of 16.00% and 18.61%, respectively. Different cutting angles of the rootstock significantly affected the growth of roots after grafting. Compared with a rootstock graft cutting angle of 10° (RL), graft cutting angles of 17° (RM) and 27° (RS) led to significantly greater root dry weights, with increases of 29.33% and 22.54%, respectively. The results of this study can provide a reference for the design of cutting mechanisms for cucurbit grafting robots, improving the cutting precision of grafting robots.

Funder

the BAAFS Innovation Ability Project

the National Nature Science Foundation of China

the Knowledge Innovation Program of Wuhan-Shuguang Project

the Key R&D projects in Hubei Province

the China National Agricultural Research System

Publisher

MDPI AG

Subject

Agronomy and Crop Science

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