Proceedings
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| Filter results16 paper(s) found. |
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1. Application Of Hyperspectral Imaging For Rapid And Non-Invasive Quantification Of Quality Of Mulberry FruitThis study investigated the potential of using hyperspectral imaging working in visible and short-wave near infrared region (380-1030 nm) for rapid and non-invasive determination of the total flavonoid in mulberry fruit. Mulberry fruit with its sweet flavor is widely used in jam, pies, tarts, wines, and liquor, and is a delicacy among humans and birds alike. The quality evaluation of mulberry is usually determined by chemical or sensory analysis. However these methods are not capable... L. Huang, H. Jin, Y. He, F. Liu, Y. Zhou |
2. Diagnosis Of Sclerotinia Infected Oilseed Rape (Brassica Napus L) Using Hyperspectral Imaging And ChemomtricsAbstract: Brassica napus L leaf diseases could cause seriously reduction in crop yield and quality. Early diagnosis of Brassica napus L leaf diseases plays a vital role in Brassica napus L growth. To explore an effective methodology for diagnosis of Sclerotinia infected Brassica napus L plants, healthy Brassica napus L leaves and Brassica napus L leaves infected by Sclerotinia were prepared in a controlled circumstance. A visible/short-wave near infrared hyperspectral... N. Chen, F. Liu, L. Jiang, L. Feng, Y. He, Y. Bao |
3. 3-Dimension Reconstruction Of Cactus Using Multispectral ImagesUsing 3D reconstruction result to investigate plant morphology has been a focus of virtual plant. And multispectral imaging has proved to carried biological information in quite a lot work. This paper present a idea to investigate chlorophyll spatial variability of cactus using a bunch of multispectral images. 46 multispectral images are taken at equally distributed angles surrounding the tree and have over 80% overlap. Structure from motion approach has been used... F. Liu, Y. He, Y. Zhang, L. Tan, Y. Zhang, L. Jiang |
4. Application of Semantic Sensor Web in AgricultureIn July 2013, heavy rainstorms across the Midwestern region of the US caused many rivers to breach their banks. Residents of Valley Park, a small town along the Meramec River, Missouri, had to decide whether to rely on a newly constructed levee or abandon their homes for higher ground. Although the levee held, many chose the latter option and fled their homes; it was a chaotic situation that might have been avoided through access to better situational knowledge... Y. Zhang, T. Chen |
5. A Novel Hyperspectral Feature Extraction Algorithm Based On Waveform Resolving For Raisin ClassificationNear infrared hyperspectral imaging technology was adopted in the paper to determine the variety of raisins produced in Xinjiang Uygur Autonomous Region, China. There are 2 varieties of raisins taking part in the research and the wavelengths of the hyperspectral images are from 900nm to 1700nm. A novel waveform resolving method was proposed in the paper to reduce the hyperspectral data and extract features. The waveform resolving method compresses the original hyperspectral data for one pixel... Y. Zhao, X. Xu, Y. Shao, Y. He, Q. Li |
6. Rape Plant NDVI Spatial Distribution Model Based on 3D ReconstructionPlants’ morphology changes in their growing process. The 3D reconstruction of plant is of great significance for studying the impacts of plant morphology on biomass estimation, illness and insect infestation, genetic expression, etc. At present, the 3D point cloud reconstructed through 3D reconstruction mainly includes the morphology, color and other features of the plant, but cannot reflect the change in spatial 3D distribution of organic matters caused by the nutritional status (e.g. chlorophyll... Y. Chen, Y. He |
7. Spotweeds: a Multiclass UASs Acquired Weed Image Dataset to Facilitate Site-specific Aerial Spraying Application Using Deep LearningUnmanned aerial systems (UASs)-based spot spraying application is considered a boon in Precision Agriculture (PA). Because of spot spraying, the amount of herbicide usage has reduced significantly resulting in less water contamination or crop plant injury. In the last demi-decade, Deep Learning (DL) has displayed tremendous potential to accomplish the task of identifying weeds for spot spraying application. Also, most of the ground-based weed management technologies have relied on DL techniques... N. Rai, Y. Zhang, J. Quanbeck, A. Christensen, X. Sun |
8. In-season Diagnosis of Winter Wheat Nitrogen Status Based on Rapidscan Sensor Using Machine Learning Coupled with Weather DataNitrogen nutrient index (NNI) is widely used as a good indicator to evaluate the N status of crops in precision farming. However, interannual variation in weather may affect vegetation indices from sensors used to estimate NNI and reduce the accuracy of N diagnostic models. Machine learning has been applied to precision N management with unique advantages in various variables analysis and processing. The objective of this study is to improve the N status diagnostic model for winter wheat by combining... J. Lu, Z. Chen, Y. Miao, Y. Li, Y. Zhang, X. Zhao, M. Jia |
9. Cotton Yield Estimation Using High-resolution Satellite Imagery Obtained from Planet SkySatSatellite images have been used to monitor and estimate crop yield. Over the years, significant improvements on spatial resolution have been made where ortho images can be generated at 30-centimeter resolution. In this study, we wanted to explore the potential use of Planet SKYSAT satellite system for cotton yield predictions. This system provided imagery data at 50 centimeters resolution, and we collected data 14 times during the season. The data were collected from two different cotton... M. Bhandari |
10. Deep Reinforcement Learning Based Robotic Arm Control for Autonomous HarvestingInverse Kinematics (IK) is a traditional method used for robotic arm manipulation, relying heavily on precise calibration and huge computational demands for arms with higher Degrees of Freedom (DoF). In contrast, Deep Reinforcement Learning (DRL) is an innovative approach to manipulation that exhibits greater tolerance for calibration inaccuracies. It trains using noise added to joint angles, allowing it to learn how to compute accurate trajectories even with inaccuracies in the joint angles.... C. Huang |
11. A Physics-informed Neural Network Approach for Simulating Laminar FlowEfficient and accurate modeling in agricultural fields is critical for advancing precision agriculture. These simulations, often involving the prediction of airflow, temperature, and humidity distributions, directly support decisions related to crop management, greenhouse climate control, and irrigation strategies. Computational Fluid Dynamics (CFD) has been a primary tool for decades, offering reliable and high-fidelity simulations through established numerical methods such as the finite-difference... C. Huang |
12. Disease Symptom Recognition and Severity Assessment for Phalaenopsis OrchidsTraditional disease assessment relies on manual visual inspection, which is subjective and often leads to inconsistent results due to variations in human judgment. To address these challenges, this study proposes an automated approach for disease classification and severity grading in Phalaenopsis orchids using the YOLOv8-seg deep learning model. The system integrates instance segmentation with Lab color space analysis, which was found to outperform HSV in distinguishing healthy and diseased leaf... C. Huang |
13. Quantitative Assessment of Discharge Depth Effects on Lithium-Based Batteries: LTO, LFP, and NCMThis study explores the impact of depth of discharge (DoD) on the performance degradation of three lithium-based battery chemistries: lithium titanate (LTO), lithium iron phosphate (LFP), and nickel cobalt manganese oxide (NCM). The objective is to establish a standardized methodology for evaluating battery health under partial cycling and to quantify the degradation behavior across three DoD ranges: 0–33%, 34–66%, and 67–100%. LFP and NCM cells were cycled at 1C under room temperature,... C. Huang |
14. Modeling the Effects of Greenhouse Environmental Factors on Soft Rot Incidence in PhalaenopsisPhalaenopsis spp. is one of Taiwan’s most important ornamental crops for export. However, during greenhouse cultivation, Phalaenopsis is frequently threatened by bacterial soft rot (Erwinia spp.), particularly under high-temperature and high-humidity conditions that accelerate pathogen spread and cause severe losses in seedlings. This study was conducted in a Phalaenopsis greenhouse located in Houbi District, Tainan, Taiwan. The greenhouse contained 21 planting beds, which were... C. Huang |
15. Cfd Evaluation of Uvc Air-cleaning Integration in Greenhouse Hvac SystemsGreenhouse crops in Taiwan are highly vulnerable to airborne pathogens due to the humid climate and poor ventilation. This study evaluated the integration of UVC air- cleaning devices with the greenhouse HVAC system to reduce pathogen concentrations. A SolidWorks model of the NTU smart greenhouse was constructed, and CFD simulations were conducted to compare three configurations in which four UVC units were placed at the upper, middle, and lower regions of the wet pad. Results showed that the... C. Huang |
16. A Low-cost Multi-view Image to 3d Reconstruction for Plant PhenotypingCurrent 3D plant phenotyping approaches often rely on LiDAR or multi-camera systems, which are costly, require complex calibration, and lack scalability. This study introduces a simple and cost-effective pipeline for 3D plant reconstruction using Hunyuan3D-2.5, a multi-view generative model. Plant samples were photographed directly using a mobile phone, and raw images were processed with a custom Python background-removal pipeline that enhanced plant contours and removed environmental noise. The... C. Huang |