Gradient-based method for the identification of multi-nodes in sugarcane

Yang, Rui; Li, Jie; Liu, Qi; Huang, Wenshan; Yin, Kai; Qiao, Xi; Huang, Yiqi

doi:10.1016/j.inpa.2020.01.004

Cited by 4 publications

(3 citation statements)

References 8 publications

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“…X where, denotes the average value of 100-grain weight, kg; M denotes the loading weight of the container, kg; J denotes the number of sugarcane seed per meter; I denotes the number of segments, 100; Χ denotes the planting space of 100 segments of sugarcane seeds, m; l denotes the line spacing of sugarcane seeds, m; q denotes the cumulative number of 100-grain weight when the container is in full load; K denotes the straight line distance when the container is in full load, m; M denotes the operating area when the container is in full load, hm 2 .…”

Section: Figure 3 Structural Diagram Of Key Components Of Rotary Disc...mentioning

confidence: 99%

“…have basically realized mechanized planting. The planting machines are mainly classified into whole-rod type, real-time cutting type and pre-cutting type [2] . In our country, there are usually some problems in mechanized planting, such as large auxiliary labor, high labor intensity, low seeding uniformity, and large amount of seeds, which directly limit the development and promotion of sugarcane mechanized planting technology.…”

Section: Introductionmentioning

confidence: 99%

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Design and experimental research on disc-type seeding device for single-bud sugarcane seeds

Liu¹,

Niu²,

Li³

et al. 2023

International Journal of Agricultural and Biological Engineering

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Mechanized sugarcane seeding is one of the effective technical measures for improving seeding uniformity and operation efficiency. However, the imperfection of supporting equipment limits the promotion and application of this technology. As there are some problems in domestic sugarcane planting machines currently, such as large auxiliary labor, high labor intensity, low seeding uniformity, and large amount of seeds, a disc-type single-bud sugarcane seed metering device was innovatively designed on the basis of the analysis of physical properties of single-bud sugarcane seeds and the combination with agronomic requirements for field planting in this paper. Solidworks was used to simulate and analyze the mechanism, check the theoretical parameters, and process the test prototype. Through single-factor experiments, the effective factors affecting seeding uniformity were determined. A multi-factor orthogonal rotation test was designed, data were collected and then SPSS was used to get the optimal parameters for the seeding uniformity: the advancement speed of machine is 0.22 m/s, the number of disc seeding grooves is 10, the rotating disc speed is 0.18 r/s, and the seeding uniformity is 86.2%; the seeding uniformity was verified by field trial, and the results showed that the average seeding uniformity of the field verification was 83%, with the error 3.2% relative to the optimization result. The relative error is within 10%, indicating that the optimization result is reliable and meets the requirements of seeding uniformity, thus providing theoretical basis for the research and development of the disc-type single-bud seeding device.

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Section: Figure 3 Structural Diagram Of Key Components Of Rotary Disc...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Design and experimental research on disc-type seeding device for single-bud sugarcane seeds

Liu¹,

Niu²,

Li³

et al. 2023

International Journal of Agricultural and Biological Engineering

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“…Jiqing Chen et al [7] initially converted collected sugarcane RGB images into HSV color images, established vertical projection functions for regions of interest, determined the minimum value points of these functions, and preliminarily located sugarcane nodes based on the obtained minimum points. Rui Yang et al [8] proposed a method capable of identifying multiple internodes in a segment of sugarcane by utilizing image stitching and the Sobel operator to obtain gradient images and subsequently identify sugarcane nodes.…”

Section: Introductionmentioning

confidence: 99%

Design and Experimental Evaluation of an Intelligent Sugarcane Stem Node Recognition System based on Enhanced YOLOv5s

Dai,

Luo,

Shi

et al. 2024

Preprint

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The rapid and accurate identification of sugarcane internodes is of great significance for tasks such as field operations and precision management in the sugarcane industry, and it is also a fundamental task for the intelligence of the sugarcane industry. However, in complex field environments, traditional image processing techniques have low accuracy, efficiency, and are mainly limited to server-side processing. Meanwhile, the sugarcane industry requires a large amount of manual involvement, leading to high labor costs. In response to the aforementioned issues, this paper employed YOLOv5s as the original model algorithm, incorporated the K-means clustering algorithm, and added the CBAM attention module and VarifocalNet mechanism to the algorithm. The improved model is referred to as YOLOv5s-KCV. We implemented the YOLOv5s-KCV algorithm on Jetson TX2 edge computing devices with a well-configured runtime environment, completing the design and development of a real-time sugarcane internode identification system. Through ablation experiments, comparative experiments of various mainstream visual recognition network models, and performance experiments conducted in the field, the effectiveness of the proposed improvement method and the developed real-time sugarcane internode identification system were verified. The experimental results demonstrate that the improvement method of YOLOv5s-KCV is effective, with an algorithm recognition accuracy of 89.89%, a recall rate of 89.95%, and an mAP value of 92.16%, which respectively increased by 6.66%, 5.92%, and 7.44% compared to YOLOv5s. The system underwent performance testing in various weather conditions and at different times in the field, achieving a minimum recognition accuracy of sugarcane internodes of 93.5%. Therefore, the developed system in this paper can achieve real-time and accurate identification of sugarcane internodes in field environments, providing new insights for related work in sugarcane field industries.

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