ArticlePlant methods2022
Banana plant counting and morphological parameters measurement based on terrestrial laser scanning.
Article in Plant methods, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- A Review of Optical-Based Three-Dimensional Reconstruction and Multi-Source Fusion for Plant Phenotyping.Sensors (Basel, Switzerland) · 2025Review
- Plant stem and leaf segmentation and phenotypic parameter extraction using neural radiance fields and lightweight point cloud segmentation networks.Frontiers in plant science · 2025Article
- GCASSN: a graph convolutional attention synergistic segmentation network for 3D plant point cloud segmentation.Frontiers in plant science · 2025Article
- An automated phenotyping method for Chinese Cymbidium seedlings based on 3D point cloud.Plant methods · 2024Article
- Accurate LAI estimation of soybean plants in the field using deep learning and clustering algorithms.Frontiers in plant science · 2024Article
- A method for measuring banana pseudo-stem phenotypic parameters based on handheld mobile LiDAR and IMU fusion.Frontiers in plant science · 2024Article
- Feature enhancement guided network for yield estimation of high-density jujube.Plant methods · 2023Article
- Image-Based High-Throughput Phenotyping in Horticultural Crops.Plants (Basel, Switzerland) · 2023Review
- Low-cost and automated phenotyping system "Phenomenon" for multi-sensor in situ monitoring in plant in vitro culture.Plant methods · 2023Article
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6 authors.
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Abstract
backgroundThe number of banana plants is closely related to banana yield. The diameter and height of the pseudo-stem are important morphological parameters of banana plants, which can reflect the growth status and vitality. To address the problems of high labor intensity and subjectivity in traditional measurement methods, a fast measurement method for banana plant count, pseudo-stem diameter, and height based on terrestrial laser scanning (TLS) was proposed.
resultsFirst, during the nutritional growth period of banana, three-dimensional (3D) point cloud data of two measured fields were obtained by TLS. Second, the point cloud data was preprocessed. And the single plant segmentation of the canopy closed banana plant point cloud was realized furtherly. Finally, the number of banana plants was obtained by counting the number of pseudo-stems, and the diameter of pseudo-stems was measured using a cylindrical segmentation algorithm. A sliding window recognition method was proposed to determine the junction position between leaves and pseudo-stems, and the height of the pseudo-stems was measured. Compared with the measured value of artificial point cloud, when counting the number of banana plants, the precision,recall and percentage error of field 1 were 93.51%, 94.02%, and 0.54% respectively; the precision,recall and percentage error of field 2 were 96.34%, 92.00%, and 4.5% respectively; In the measurement of pseudo-stem diameter and height of banana, the root mean square error (RMSE) of pseudo-stem diameter and height of banana plant in field 1 were 0.38 cm and 0.2014 m respectively, and the mean absolute percentage error (MAPE) were 1.30% and 5.11% respectively; the RMSE of pseudo-stem diameter and height of banana plant in field 2 were 0.39 cm and 0.2788 m respectively, and the MAPE were 1.04% and 9.40% respectively.
conclusionThe results show that the method proposed in this paper is suitable for the field measurement of banana count, pseudo-stem diameter, and height and can provide a fast field measurement method for banana plantation management.
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