Relevant bibliographies by topics / Plant skeleton extraction

Academic literature on the topic 'Plant skeleton extraction'

Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Plant skeleton extraction"

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Hu, Yihu, Xinying Luo, Zicheng Gao, Ao Du, Hao Guo, Alexey Ruchay, Francesco Marinello, and Andrea Pezzuolo. "Curve Skeleton Extraction from Incomplete Point Clouds of Livestock and Its Application in Posture Evaluation." Agriculture 12, no. 7 (July 11, 2022): 998. http://dx.doi.org/10.3390/agriculture12070998.

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As consumer-grade depth sensors provide an efficient and low-cost way to obtain point cloud data, an increasing number of applications regarding the acquisition and processing of livestock point clouds have been proposed. Curve skeletons are abstract representations of 3D data, and they have great potential for the analysis and understanding of livestock point clouds. Articulated skeleton extraction has been extensively studied on 2D and 3D data. Nevertheless, robust and accurate skeleton extraction from point set sequences captured by consumer-grade depth cameras remains challenging since such data are often corrupted by substantial noise and outliers. Additionally, few approaches have been proposed to overcome this problem. In this paper, we present a novel curve skeleton extraction method for point clouds of four-legged animals. First, the 2D top view of the livestock was constructed using the concave hull algorithm. The livestock data were divided into the left and right sides along the bilateral symmetry plane of the livestock. Then, the corresponding 2D side views were constructed. Second, discrete skeleton evolution (DSE) was utilized to extract the skeletons from those 2D views. Finally, we divided the extracted skeletons into torso branches and leg branches. We translated each leg skeleton point to the border of the nearest banded point cluster and then moved it to the approximate centre of the leg. The torso skeleton points were calculated according to their positions on the side view and top view. Extensive experiments show that quality curve skeletons can be extracted from many livestock species. Additionally, we compared our method with representative skeleton extraction approaches, and the results show that our method performs better in avoiding topological errors caused by the shape characteristics of livestock. Furthermore, we demonstrated the effectiveness of our extracted skeleton in detecting frames containing pigs with correct postures from the point cloud stream.
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Herrero-Huerta, M., V. Meline, A. S. Iyer-Pascuzzi, A. M. Souza, M. R. Tuinstra, and Y. Yang. "ROOT PHENOTYPING FROM X-RAY COMPUTED TOMOGRAPHY: SKELETON EXTRACTION." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B4-2021 (June 30, 2021): 417–22. http://dx.doi.org/10.5194/isprs-archives-xliii-b4-2021-417-2021.

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Abstract. Breakthrough imaging technologies are a potential solution to the plant phenotyping bottleneck in marker-assisted breeding and genetic mapping. X-Ray CT (computed tomography) technology is able to acquire the digital twin of root system architecture (RSA), however, advances in computational methods to digitally model spatial disposition of root system networks are urgently required.We extracted the root skeleton of the digital twin based on 3D data from X-ray CT, which is optimized for high-throughput and robust results. Significant root architectural traits such as number, length, growth angle, elongation rate and branching map can be easily extracted from the skeleton. The curve-skeleton extraction is computed based on a constrained Laplacian smoothing algorithm. This skeletal structure drives the registration procedure in temporal series. The experiment was carried out at the Ag Alumni Seed Phenotyping Facility (AAPF) at Purdue University in West Lafayette (IN, USA). Three samples of tomato root at 2 different times and three samples of corn root at 3 different times were scanned. The skeleton is able to accurately match the shape of the RSA based on a visual inspection.The results based on a visual inspection confirm the feasibility of the proposed methodology, providing scalability to a comprehensive analysis to high throughput root phenotyping.
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Kang, Hye-Ji, Min-Jung Ko, and Myong-Soo Chung. "Anthocyanin Structure and pH Dependent Extraction Characteristics from Blueberries (Vaccinium corymbosum) and Chokeberries (Aronia melanocarpa) in Subcritical Water State." Foods 10, no. 3 (March 3, 2021): 527. http://dx.doi.org/10.3390/foods10030527.

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This study determines the optimal extraction conditions for the subcritical-water extraction (SWE) of anthocyanin from blueberries and chokeberries and compares the performance using conventional extraction methods. SWE is carried out under different conditions of extraction temperature (110 °C, 130 °C, 150 °C, 170 °C, 190 °C, and 200 °C), extraction time (1, 3, 5, and 10 min), and solvent pH (water and 1% citric acid). The solubility and stability of anthocyanin from blueberries and chokeberries influences the optimal condition for SWE. The presence of more methoxy and hydroxyl functional groups in the basic skeleton of anthocyanin will result in a lower solubility at a high temperature. Water at a higher temperature exhibits a better dissociation reaction, and a solvent has a lower pH at a higher temperature. One percent citric acid is used to reduce the pH of the solvent, which increases the extraction efficiency of anthocyanin in a subcritical water state.
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Concepcion II, Ronnie Sabino, Jonnel Dorado Alejandrino, Sandy Cruz Lauguico, Rogelio Ruzcko Tobias, Edwin Sybingco, Elmer Pamisa Dadios, and Argel Alejandro Bandala. "Lettuce growth stage identification based on phytomorphological variations using coupled color superpixels and multifold watershed transformation." International Journal of Advances in Intelligent Informatics 6, no. 3 (November 13, 2020): 261. http://dx.doi.org/10.26555/ijain.v6i3.435.

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Identifying the plant's developmental growth stages from seed leaf is crucial to understand plant science and cultivation management deeply. An efficient vision-based system for plant growth monitoring entails optimum segmentation and classification algorithms. This study presents coupled color-based superpixels and multifold watershed transformation in segmenting lettuce plant from complicated background taken from smart farm aquaponic system, and machine learning models used to classify lettuce plant growth as vegetative, head development and for harvest based on phytomorphological profile. Morphological computations were employed by feature extraction of the number of leaves, biomass area and perimeter, convex area, convex hull area and perimeter, major and minor axis lengths of the major axis length the dominant leaf, and length of plant skeleton. Phytomorphological variations of biomass compactness, convexity, solidity, plant skeleton, and perimeter ratio were included as inputs of the classification network. The extracted Lab color space information from the training image set undergoes superpixels overlaying with 1,000 superpixel regions employing K-means clustering on each pixel class. Six-level watershed transformation with distance transformation and minima imposition was employed to segment the lettuce plant from other pixel objects. The accuracy of correctly classifying the vegetative, head development, and harvest growth stages are 88.89%, 86.67%, and 79.63%, respectively. The experiment shows that the test accuracy rates of machine learning models were recorded as 60% for LDA, 85% for ANN, and 88.33% for QSVM. Comparative analysis showed that QSVM bested the performance of optimized LDA and ANN in classifying lettuce growth stages. This research developed a seamless model in segmenting vegetation pixels, and predicting lettuce growth stage is essential for plant computational phenotyping and agricultural practice optimization.
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Tarkowská, Danuše. "A Fast and Reliable UHPLC–MS/MS-Based Method for Screening Selected Pharmacologically Significant Natural Plant Indole Alkaloids." Molecules 25, no. 14 (July 18, 2020): 3274. http://dx.doi.org/10.3390/molecules25143274.

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Many substances of secondary plant metabolism have often attracted the attention of scientists and the public because they have certain beneficial effects on human health, although the reason for their biosynthesis in the plant remains unclear. This is also the case for alkaloids. More than 200 years have passed since the discovery of the first alkaloid (morphine), and several thousand substances of this character have been isolated since then. Most often, alkaloid-rich plants are part of folk medicine with centuries-old traditions. What is particularly important to monitor for these herbal products is the spectrum and concentrations of the present active substances, which decide whether the product has a beneficial or toxic effect on human health. In this work, we present a fast, reliable, and robust method for the extraction, preconcentration, and determination of four selected alkaloids with an indole skeleton, i.e., harmine, harmaline, yohimbine, and ajmalicine, by ultra-high performance liquid chromatography coupled with tandem mass spectrometry. The applicability of the method was demonstrated for tobacco and Tribulus terrestris plant tissue, the seeds of Peganum harmala, and extract from the bark of the African tree Pausinystalia johimbe.
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Zheng, Chenxi, Weiliang Wen, Xianju Lu, Wushuai Chang, Bo Chen, Qiang Wu, Zhiwei Xiang, Xinyu Guo, and Chunjiang Zhao. "Three-Dimensional Wheat Modelling Based on Leaf Morphological Features and Mesh Deformation." Agronomy 12, no. 2 (February 7, 2022): 414. http://dx.doi.org/10.3390/agronomy12020414.

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The three-dimensional (3D) morphological structure of wheat directly reflects the interrelationship among genetics, environments, and cropping systems. However, the morphological complexity of wheat limits its rapid and accurate 3D modelling. We have developed a 3D wheat modelling method that is based on the progression from skeletons to mesh models. Firstly, we identified five morphological parameters that describe the 3D leaf features of wheat from amounts of 3D leaf digitizing data at the grain filling stage. The template samples were selected based on the similarity between the input leaf skeleton and leaf templates in the constructed wheat leaf database. The leaf modelling was then performed using the as-rigid-as-possible (ARAP) mesh deformation method. We found that 3D wheat modelling at the individual leaf level, leaf group, and individual plant scales can be achieved. Compared with directly acquiring 3D digitizing data for 3D modelling, it saves 79.9% of the time. The minimum correlation R2 of the extracted morphological leaf parameters between using the measured data and 3D model by this method was 0.91 and the maximum RMSE was 0.03, implying that this method preserves the morphological leaf features. The proposed method provides a strong foundation for further morphological phenotype extraction, functional–structural analysis, and virtual reality applications in wheat plants. Overall, we provide a new 3D modelling method for complex plants.
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Dodd, J., and FD Panetta. "Seed production by skeleton weed (Chondrilla juncea L.) in Western Australia in relation to summer drought." Australian Journal of Agricultural Research 38, no. 4 (1987): 689. http://dx.doi.org/10.1071/ar9870689.

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Seed production in Forms A and C of C. juncea was measured at 11 wheatbelt sites in Western Australia and under glasshouse conditions. Most field-grown plants produced abundant viable seeds, even without substantial summer rainfall. Up to 27.6 x l03 seeds per plant were recorded, and their viability was frequently between 80 and 90%. Even in their first year, some plants produced more than 10000 seeds each. Through the summer, seed production often followed either a positively skewed, or a bimodal curve. Falls of rain in summer did not increase seed output or affect its quality in established plants. Exceptionally high air temperatures appeared to depress seed numbers and/or viability at several, but not all, sites. At the end of summer, when young plants were 9-12 months old, soil water extraction had occurred to 310 cm, indicating root penetration to this depth. Conservative water use by C. juncea during summer was indicated by low values of soil water depletion. In glasshouse-grown plants, simulated drought reduced seed numbers, viability, primary dormancy and seed weight, although the two forms responded differently. Given adequate winter rainfall to recharge soil water storage, C. juncea appears capable of producing large quantities of viable seeds throughout the Western Australian wheatbelt.
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Qi, Jianzhao, Dacheng Wang, Xia Yin, Qiang Zhang, and Jin-Ming Gao. "New Metabolite With Inhibitory Activity Against α-Glucosidase and α-Amylase From Endophytic Chaetomium globosum." Natural Product Communications 15, no. 7 (July 2020): 1934578X2094133. http://dx.doi.org/10.1177/1934578x20941338.

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An efficient bioactive tracking separation strategy based on liquid-liquid extraction and high-speed counter-current chromatography (HSCCC) was developed and used to isolate bioactive natural products from the endophytic fungus Chaetomium globosum residing in Ginkgo biloba. Using HSCCC, the novel metabolite chaetoglobol acid (1) as well as 11 known compounds (2-12), including 6 chlorinated azaphilones and 3 cytochalasans, were successfully isolated. The structure of compound 1 was elucidated through spectroscopic analyses and HRESIMS data. Compound 1 possesses a rare C11-polyketide skeleton. All isolates were evaluated for their α-glucosidase and α-amylase inhibitory activities in vitro. Compound 1 showed high inhibition against α-glucosidase (IC50 = 3.04 μM), 18-fold higher than that of acarbose (IC50 = 54.74 μM), and also displayed moderate inhibitory activity against α-amylase (IC50 = 22.18 μM). As the results indicated that 1 has inhibitory effects against both α-glucosidase and α-amylase, 1 may be a promising candidate for mediating type 2 diabetes.
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Kúsz, Norbert, Dóra Stefkó, Anita Barta, Annamária Kincses, Nikoletta Szemerédi, Gabriella Spengler, Judit Hohmann, and Andrea Vasas. "Juncaceae Species as Promising Sources of Phenanthrenes: Antiproliferative Compounds from Juncus maritimus Lam." Molecules 26, no. 4 (February 13, 2021): 999. http://dx.doi.org/10.3390/molecules26040999.

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Juncaceae family represents an abundant source of phenanthrenes. In continuation of our work aiming at the isolation of biologically active compounds from Juncaceae species, Juncus maritimus Lam. was subjected to phytochemical and pharmacological investigations. The isolation process was carried out by using combined extraction and chromatographic methods. The structures of the obtained chemical compounds were elucidated by spectroscopic analysis, including HRESIMS, 1D (1H, 13C-JMOD), and 2D (1H-1H-COSY, HSQC, HMBC, NOESY) NMR spectra. Four new [maritins A–D (1–4)] and seven known phenanthrenes (5–11) were isolated from the plant, of which two (4 and 11) are phenanthrene dimers composed of effusol monomers. Maritin C (3) has an unusual 4,5-ethanophenanthrene skeleton most likely produced by biosynthetic incorporation of a vinyl group into a cyclohexadiene ring. Compounds 1–11 were tested for their antiproliferative activity on seven human tumor cell lines (HeLa, HTM-26, T-47D, A2780, A2780cis, MCF-7, KCR) and one normal cell line (MRC-5) using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. The dimeric phenanthrenes showed strong antiproliferative activity against T-47D cells with IC50 values of 9.1 and 6.2 µM, respectively.
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Khalid, Ahsan, Zubair Hassan Awaisi, Muhammad Anas Sufian, Zainab Ahmed, Sameera Jamshed, and Umal Asim. "Frequency of Extractions in Various Skeletal Patterns in Orthodontic Nishtar Institute of Dentistry, Multan." Orthodontic Journal of Nepal 10, no. 3 (December 31, 2020): 27–30. http://dx.doi.org/10.3126/ojn.v10i3.35488.

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Introduction: When the 20th century started Orthodontics was first recognized as a science. The removal or extraction of teeth destroys the ideal esthetics and occlusion, which was the base of orthodontic treatment plans. Edward Hartley Angle and his followers were not supporters of extraction due to this reason. Extreme dental or maxillary protrusion leading to facial deformities could be corrected by dental extraction was supported by Calvin Case who was a strong opponent of the Angle., for mainly analyzing the frequency of use of orthodontic extractions after evaluating the changes in the use of extraction in past years. The frequency of extractions was examined in relation to gender and Angle’s malocclusion classification. Materials and Method: This is a retrospective observational study. It was conducted in Orthodontics Department of Nishtar Institute of Dentistry, from 2015 to 2020. In this study records from 1032 patients who reported to orthodontic department in Nishtar institute of dentistry Multan for fixed orthodontic treatment were taken. For data registration SPSS 20 (IBM Chicago Illinois) was used. Frequency of extractions with regards to gender, skeletal pattern and types of extraction pattern was determined. In order to assess the association among variables Chi square test was applied and a P value of less than 0.05 was considered as significant. Result: In respect of extraction group, 222 (41.3%) were males and 316 (58.7%) were female and whereas in nonextraction group, 83 (16.8%) were males and 411 (83.2%) were females. The difference was statistically significant (p<0.001). The frequency of extraction in reference to Angle’s classification was analyzed, and no significant difference was found (p=0.992). Frequency of extraction was highest in class-II division-I malocclusion, and the lowest frequency of orthodontic tooth extraction was seen in class-II division-II malocclusion. Conclusion: It can be concluded from the results of our study that females had higher frequency of extractions as compared to males. Similarly, class II malocclusion patients had highest frequency while lowest frequency was in Class I malocclusions.
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Conference papers on the topic "Plant skeleton extraction"

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Cheng, Zhanglin, Xiaopeng Zhang, and Thierry Fourcaud. "Tree Skeleton Extraction from a Single Range Image." In 2006 International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications (PMA). IEEE, 2006. http://dx.doi.org/10.1109/pma.2006.28.

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Xiaohong, Xu, Lin Shumin, Zeng Qingmao, and Zhu Tonglin. "Skeleton Extraction Algorithm of Plant Lein Based on Watershed." In 2011 International Conference on Intelligent Computation Technology and Automation (ICICTA). IEEE, 2011. http://dx.doi.org/10.1109/icicta.2011.334.

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Regazzoni, Daniele, Andrea Vitali, Caterina Rizzi, and Giorgio Colombo. "A Method to Analyse Generic Human Motion With Low-Cost Mocap Technologies." In ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/detc2018-86197.

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A number of pathologies impact on the way a patient can either move or control the movements of the body. Traumas, articulation arthritis or generic orthopedic disease affect the way a person can walk or perform everyday movements; brain or spine issues can lead to a complete or partial impairment, affecting both muscular response and sensitivity. Each of these disorder shares the need of assessing patient’s condition while doing specific tests and exercises or accomplishing everyday life tasks. Moreover, also high-level sport activity may be worth using digital tools to acquire physical performances to be improved. The assessment can be done for several purpose, such as creating a custom physical rehabilitation plan, monitoring improvements or worsening over time, correcting wrong postures or bad habits and, in the sportive domain to optimize effectiveness of gestures or related energy consumption. The paper shows the use of low-cost motion capture techniques to acquire human motion, the transfer of motion data to a digital human model and the extraction of desired information according to each specific medical or sportive purpose. We adopted the well-known and widespread Mocap technology implemented by Microsoft Kinect devices and we used iPisoft tools to perform acquisition and the preliminary data elaboration on the virtual skeleton of the patient. The focus of the paper is on the working method that can be generalized to be adopted in any medical, rehabilitative or sportive condition in which the analysis of the motion is crucial. The acquisition scene can be optimized in terms of size and shape of the working volume and in the number and positioning of sensors. However, the most important and decisive phase consist in the knowledge acquisition and management. For each application and even for each single exercise or tasks a set of evaluation rules and thresholds must be extracted from literature or, more often, directly form experienced personnel. This operation is generally time consuming and require further iterations to be refined, but it is the core to generate an effective metric and to correctly assess patients and athletes performances. Once rules are defined, proper algorithms are defined and implemented to automatically extract only the relevant data in specific time frames to calculate performance indexes. At last, a report is generated according to final user requests and skills.
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