34,312 research outputs found

    Automated artemia length measurement using U-shaped fully convolutional networks and second-order anisotropic Gaussian kernels

    No full text
    The brine shrimp Artemia, a small crustacean zooplankton organism, is universally used as live prey for larval fish and shrimps in aquaculture. In Artemia studies, it would be highly desired to have access to automated techniques to obtain the length information from Anemia images. However, this problem has so far not been addressed in literature. Moreover, conventional image-based length measurement approaches cannot be readily transferred to measure the Artemia length, due to the distortion of non-rigid bodies, the variation over growth stages and the interference from the antennae and other appendages. To address this problem, we compile a dataset containing 250 images as well as the corresponding label maps of length measuring lines. We propose an automated Anemia length measurement method using U-shaped fully convolutional networks (UNet) and second-order anisotropic Gaussian kernels. For a given Artemia image, the designed UNet model is used to extract a length measuring line structure, and, subsequently, the second-order Gaussian kernels are employed to transform the length measuring line structure into a thin measuring line. For comparison, we also follow conventional fish length measurement approaches and develop a non-learning-based method using mathematical morphology and polynomial curve fitting. We evaluate the proposed method and the competing methods on 100 test images taken from the dataset compiled. Experimental results show that the proposed method can accurately measure the length of Artemia objects in images, obtaining a mean absolute percentage error of 1.16%

    Grading Grain Under the U.S. Grain Standards

    Get PDF
    Crop Production/Industries,

    DIFFERENTIATION AND IMPLICIT PRICES OF U.S. WHEAT EXPORTS

    Get PDF
    This investigation looks at whether the grade determining and official criteria factors identified by the Federal Grain Inspection Service influence the price of wheat for export and, in turn, the competitiveness of United States wheat in the world market. Using data on the transactions price for hard red winter wheat, hard red spring wheat, and soft white wheat and the associated quality characteristics covering the period January 1990 through December 1991 and exported to 63 countries, the results suggest that the test weight, the percentage of shrunken and broken kernels, the protein content, the presence of aflatoxin, the presence of insects, and the falling number are characteristics consistently valued by the market.Demand and Price Analysis, International Relations/Trade,
    • …
    corecore