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Evaluation of a Pre-Cut Sugarcane Planter for Seeding Performance

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  • Zhikang Peng

    (College of Engineering, South China Agricultural University, Guangzhou 510642, China
    Key Laboratory of Key Technology on Agricultural Machine and Equipment, Guangzhou 510642, China)

  • Fengying Xu

    (College of Engineering, South China Agricultural University, Guangzhou 510642, China
    Key Laboratory of Key Technology on Agricultural Machine and Equipment, Guangzhou 510642, China)

  • Pan Xie

    (College of Engineering, South China Agricultural University, Guangzhou 510642, China)

  • Jinpeng Chen

    (College of Engineering, South China Agricultural University, Guangzhou 510642, China
    Key Laboratory of Key Technology on Agricultural Machine and Equipment, Guangzhou 510642, China)

  • Tao Wu

    (College of Engineering, South China Agricultural University, Guangzhou 510642, China
    Key Laboratory of Key Technology on Agricultural Machine and Equipment, Guangzhou 510642, China)

  • Zhen Chen

    (College of Engineering, South China Agricultural University, Guangzhou 510642, China
    Key Laboratory of Key Technology on Agricultural Machine and Equipment, Guangzhou 510642, China)

Abstract

To investigate the relationship between the seeding performance of a novel pre-cut sugarcane planter designed by South China Agricultural University and operational settings, field seeding tests was conducted with the following protocol: First, the John Deere M1654 tractor’s forward velocity was calibrated, and the planter’s safe loading capacity was determined. Subsequently, eight experimental treatments (A–H) were designed to quantify the relationships between the three performance indicators: seeding density N, the seeding efficiency E and seeding uniformity (coefficient of variation, CV), and three key operational parameters: forward speed of planter v, the discharging sprocket rotational speed n, and the hopper outlet size w. Mathematical models (R20.979) between three key operational parameters with two performance indicators (N, E) was developed through analysis of variance (ANOVA) and regression analysis. The seeding rate per meter was confirmed to follow a Poisson distribution based on Kolmogorov–Smirnov (K–S) tests. When the CV was below 40%, the mean relative error remained within 3%. These findings provide a theoretical foundation for seeding performance prediction under field conditions.

Suggested Citation

  • Zhikang Peng & Fengying Xu & Pan Xie & Jinpeng Chen & Tao Wu & Zhen Chen, 2025. "Evaluation of a Pre-Cut Sugarcane Planter for Seeding Performance," Agriculture, MDPI, vol. 15(13), pages 1-16, July.
    • Handle: RePEc:gam:jagris:v:15:y:2025:i:13:p:1429-:d:1693347
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    References listed on IDEAS

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    1. Sheng Dong & Chun-Shuo Jiao & Shan-Shan Tao, 2017. "Joint return probability analysis of wind speed and rainfall intensity in typhoon-affected sea area," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 86(3), pages 1193-1205, April.
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