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Showing 1 to 13 of 13 for “"plant phenotyping"”.

  1. Image-based deep learning approaches for plant phenotyping

    The genetic potential of plant traits remains unexplored due to challenges in available phenotyping methods. Deep learning could be used to build automatic tools for identifying, localizing and quantifying plant features based on agricultural images. This dissertation describes the development and …

    ksu Repository record for Image-based deep learning approaches for plant phenotyping (opens in a new tab)

  2. DEVELOPMENT OF A FIELD-BASED MOBILE PLATFORM FOR PLANT PHENOTYPING

    … of an affordable field-based high-throughput plant phenotyping platform for monitoring Canola plants, including both data acquisition/visualization software and measurement system, was the main objective of this research. The primary motivation for this research is the fact that breeders need …

    sask Repository record for DEVELOPMENT OF A FIELD-BASED MOBILE PLATFORM FOR PLANT PHENOTYPING (opens in a new tab)

  3. 3D machine vision system for robotic weeding and plant phenotyping

    … system should be capable of differentiating crop plants and weeds to avoid contaminating crops with herbicide or damaging them with mechanical tools. For the plant genetics industry, automated high-throughput phenotyping technology is critical to profiling seedlings at a large scale to facilitate …

    iastate Repository record for 3D machine vision system for robotic weeding and plant phenotyping (opens in a new tab)

  4. Development of Multifunctional Electrical Impedance Spectroscopy System for Characterization in Plant Phenotyping

    Plant phenotyping plays an important role for the thorough assessment of plant traits such as growth, development, resistance, physiology, etc. Assessing the nutrients and water contents by obtaining the spectroscopy data is essential for plant characterization, and photosynthesis. The conventional …

    sask Repository record for Development of Multifunctional Electrical Impedance Spectroscopy System for Characterization in Plant Phenotyping (opens in a new tab)

  5. Application of unmanned aerial systems and deep learning in high-throughput plant phenotyping

    Plant phenotyping plays an essential role in decision support in precision agriculture and plant breeding. However, traditional phenotyping methods are typically through manually measuring the target traits, which is time-consuming and labor-intensive with sampling bias. Technological innovations …

    ttu Repository record for Application of unmanned aerial systems and deep learning in high-throughput plant phenotyping (opens in a new tab)

  6. Advances in automated plant phenotyping and target-driven visual navigation for breeding candidates

    Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-08-01

    uiuc Repository record for Advances in automated plant phenotyping and target-driven visual navigation for breeding candidates (opens in a new tab)

  7. RGB and NIR Image Registration for Proximal Multiband Imaging

    Accurate monitoring of plant traits is critical to advancing agricultural productivity and sustainability. Multispectral imaging relying on red-green-blue (RGB) and near-infrared (NIR) imagery has become an essential tool in high-throughput plant phenotyping. However, accurate analysis requires …

    sask Repository record for RGB and NIR Image Registration for Proximal Multiband Imaging (opens in a new tab)

  8. Towards Collaborative Scientific Workflow Management System

    … present our proposed method with a use-case of Plant Phenotyping and Genotyping research domain. Recent study shows that the collaborative SWfMSs often different sets of opportunities and challenges. From our investigations on existing research works towards collaborative SWfMSs and findings of …

    sask Repository record for Towards Collaborative Scientific Workflow Management System (opens in a new tab)

  9. Generalizable Canola Seedling Detection in Aerial Field Imagery

    … yield returns of their canola fields. Emergence plant counts are prized as one of the earliest and most useful indicators of crop health. Traditionally, plant population numbers have been estimated by manually counting the number of emerged seedlings at various field locations. Due to the high …

    sask Repository record for Generalizable Canola Seedling Detection in Aerial Field Imagery (opens in a new tab)

  10. Development of Open-Source Gantry-Plus Robot Systems for Plant Science research

    … and readily available automation options for plant research remain scarce, however with the availability of such a system, many research tasks can be streamlined. In this project, we demonstrate a prototype of such an open-source, low-cost, heterogeneous robotic system called Mini T-Rex. We …

    vt Repository record for Development of Open-Source Gantry-Plus Robot Systems for Plant Science research (opens in a new tab)

  11. Evaluation of Yield and Agronomic Performance of Leafed and Semi-leafless Pea Blends

    Field pea has two distinct leaf morphologies: leafed (L) and semi-leafless (SL). The leafed pea is more susceptible to lodging, but it may have high yield potential when lodging is prevented. In contrast, the semi-leafless pea is bred for lodging resistance and has greater yield stability. However, …

    sask Repository record for Evaluation of Yield and Agronomic Performance of Leafed and Semi-leafless Pea Blends (opens in a new tab)

  12. Assessment of the spatial variability of vegetative status in vineyards using non-destructive sensors: Application of remote and proximal sensing technologies in precision viticulture

    Introduction: The vegetative status of grapevines influences yield and grape composition. The assessment of the vineyard spatial and temporal variability in precision viticulture requires a large amount of data. Traditional methods are not suitable, as they are time and labour demanding, making the …

    dialnet Repository record for Assessment of the spatial variability of vegetative status in vineyards using non-destructive sensors: Application of remote and proximal sensing technologies in precision viticulture (opens in a new tab)