Abstract: Seed maturity in peanut ( Arachis hypogaea L.) determines economic return to a producer because of its impact on seed weight, and critically influences seed vigor and other quality characteristics. During seed development, the inner mesocarp layer of the… Read More
Tag: plants
Cross-site learning in deep learning RGB tree crown detection
Abstract: Tree detection is a fundamental task in remote sensing for forestry and ecosystem ecology applications. While many individual tree segmentation algorithms have been proposed, the development and testing of these algorithms is typically site specific, with few methods evaluated… Read More
Breaking down barriers between remote sensing and plant pathology
Abstract: A critical component for enhancing productivity and quality of food and fiber is the ability to quickly detect and monitor plant diseases in order to prevent or minimize losses to agricultural and forest products (Mahlein 2016). The earlier (prior to… Read More
Overcoming Small Minirhizotron Datasets Using Transfer Learning
Abstract: Minirhizotron technology is widely used for studying the development of roots. Such systems collect visible-wavelength color imagery of plant roots in-situ by scanning an imaging system within a clear tube driven into the soil. Automated analysis of root systems… Read More
RhizoVision Crown: An Integrated Hardware and Software Platform for Root Crown Phenotyping
Abstract: Root crown phenotyping measures the top portion of crop root systems and can be used for marker-assisted breeding, genetic mapping, and understanding how roots influence soil resource acquisition. Several imaging protocols and image analysis programs exist, but they are… Read More
Root Identification in Minirhizotron Imagery with Multiple Instance Learning
Abstract: In this paper, multiple instance learning (MIL) algorithms to automatically perform root detection and segmentation in minirhizotron imagery using only image-level labels are proposed. Root and soil characteristics vary from location to location, thus, supervised machine learning approaches that… Read More
Three dimensional reconstruction of plant roots via low energy X-ray computed tomography
Abstract: Plant roots are vital organs for water and nutrient uptake. The structure and spatial distribution of plant roots in the soil affects a plant’s physiological functions such as soil-based resource acquisition, yield and its ability to live under abiotic… Read More
A novel multi-perspective imaging platform (M-PIP) for phenotyping soybean root crowns in the field increases throughput and separation ability of genotype root properties
Abstract: Background: Root crown phenotyping has linked root properties to shoot mass, nutrient uptake, and yield in the field, which increases the understanding of soil resource acquisition and presents opportunities for breeding. The original methods using manual measurements have been… Read More
Multi-camera High-throughput Plant Root Phenotyping System
Abstract: Plant root phenotyping is a key component in plant breeding and selection for desireable root properties. Preferable root traits can not only help a plant to grow faster but also allow for more dense and deep root system architectures… Read More