Analysis and Testing of Pre-Cut Sugarcane Seed Stalk Sawing Performance Parameters

文献类型： 外文期刊

第一作者： Yan, Bin

作者： Yan, Bin;He, Fengguang;Deng, Ganran;Zheng, Shuang;Cui, Zhende;Zhou, Sili;Dai, Ye;Wang, Xilin;Qin, Shuangmei;Li, Guojie;Li, Ling;Yan, Bin;He, Fengguang;Deng, Ganran;Zheng, Shuang;Cui, Zhende;Zhou, Sili;Dai, Ye;Wang, Xilin;Qin, Shuangmei;Li, Guojie;Li, Ling;Liu, Haitao;Deng, Ganran;Li, Bin

作者机构：

关键词： sugarcane seed stalks; sawing parameters; peak sawing force; sawing surface quality; response surface method

期刊名称：AGRICULTURE-BASEL （ 影响因子：3.3； 五年影响因子：3.5 ）

ISSN：

年卷期： 2024 年 14 卷 6 期

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收录情况： SCI

摘要： Sugarcane is an important economic crop in tropical and subtropical regions. Presawing planting is an important method for achieving automated and precise planting with sugarcane planting machines. The sawing process is a key stage in planting management, affecting not only the germination and survival rates of sugarcane, but also reflecting the mechanical performance of sawing. To reduce the peak sawing force and enhance the sawing surface quality of sugarcane seedlings, this study utilized a central composite experimental design method. Single-factor and multi-factor experiments were conducted with a specially designed sugarcane stalk sawing experimental rig to investigate the impact of factors such as the stalk diameter feeding speed, and sawing speed on the peak sawing force and sawing surface quality. Upon being developed and validated, multivariate mathematical regression models elucidated the relationships among these factors. The experimental results showed that the order of influence of each factor on the peak sawing force was the stalk diameter, feed speed, and sawing speed, while for the sawing surface quality, the sequence was the sawing speed, stalk diameter, and feed speed. Correspondingly, the determination coefficients for the peak sawing force and sawing surface quality prediction models were 0.9708 and 0.9675. With a maximum error of 7.6% for the peak sawing force and an average relative error of 7.1%, and a maximum error of 3.5% for the sawing surface quality and an average relative error of 2.83%, the calculated results from the regression models were in good agreement with the experimental findings. This indicates that the models are capable of quickly and accurately predicting the peak sawing force and sawing surface quality of sugarcane stalks under different conditions. The research findings provide valuable insights for the development and optimization of sugarcane stalk presawing equipment and related experimental studies.

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