Evidence map›Paper›PMID 38988641›Full record

ArticleFrontiers in plant science2024

A method for measuring banana pseudo-stem phenotypic parameters based on handheld mobile LiDAR and IMU fusion.

Zhou Yang, Qiming Jiang, Jieli Duan, Mohui Jin, Han Fu, Xing Xu

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Article in Frontiers in plant science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Zhou YangGuangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, China.
Qiming JiangGuangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, China.
Jieli DuanGuangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, China.
Mohui JinGuangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, China.
Han FuGuangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, China.
Xing XuCollege of Electronic Engineering (College of Artificial Intelligence), South China Agricultural University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diameter and height are crucial morphological parameters of banana pseudo-stems, serving as indicators of the plant's growth status. Currently, in densely cultivated banana plantations, there is a lack of applicable research methods for the scalable measurement of phenotypic parameters such as diameter and height of banana pseudo-stems. This paper introduces a handheld mobile LiDAR and Inertial Measurement Unit (IMU)-fused laser scanning system designed for measuring phenotypic parameters of banana pseudo-stems within banana orchards. To address the challenges posed by dense canopy cover in banana orchards, a distance-weighted feature extraction method is proposed. This method, coupled with Lidar-IMU integration, constructs a three-dimensional point cloud map of the banana plantation area. To overcome difficulties in segmenting individual banana plants in complex environments, a combined segmentation approach is proposed, involving Euclidean clustering, Kmeans clustering, and threshold segmentation. A sliding window recognition method is presented to determine the connection points between pseudo-stems and leaves, mitigating issues caused by crown closure and heavy leaf overlap. Experimental results in banana orchards demonstrate that, compared with manual measurements, the mean absolute errors and relative errors for banana pseudo-stem diameter and height are 0.2127 cm (4.06%) and 3.52 cm (1.91%), respectively. These findings indicate that the proposed method is suitable for scalable measurements of banana pseudo-stem diameter and height in complex, obscured environments, providing a rapid and accurate inter-orchard measurement approach for banana plantation managers.

Indexed as

3D point cloudbanana pseudo-stem diameterbanana pseudo-stem heightmobile LiDAR systemmulti sensor fusion

Identifiers

PMID38988641
PMCPMC11233685

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