Liu 刘海涛 Liu

Mr. Liu 刘海涛 Liu


Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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18 June 2024 in Agriculture
Verified
Journal Article
Open access
PDF file
BYBin Yan
Bin Yan
LLLiu 刘海涛 Liu
Liu 刘海涛 Liu
FHFengguang He
Fengguang He
GDGanran Deng
Ganran Deng
SZShuang Zheng
Shuang Zheng
BLBin Li
Bin Li
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.