34 research outputs found

    Genetic improvement of sow longevity and its economic impact on commercial pork production

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    Sow longevity (sow productive lifetime) plays an important role in economically efficient piglet production. Direct selection for sow longevity is not commonly practiced in any pig-breeding program. In recent years, an increased number of peer reviewed articles addressing the economic impact, genetic parameter estimates, and genomic information (including markers and single nucleotide polymorphisms for sow longevity) have been published in the scientific literature. The studies in the literature indicate that sow longevity is a complex trait having economic value and is an animal well-being concern for commercial pork producers. Studies have concluded that sufficient genetic variation exists so that selection to improve sow longevity should be effective. Unlike the dairy industry, the primary parent animal used in the swine industry is a crossbred female, typically F1 (Landrace X Large White or Yorkshire). Sow longevity has shown to be genetically related with prolificacy and leg conformation traits. Sow longevity seems to be the ideal trait to utilize genomic selection when attempting to improve the trait. The genetic correlation between purebred and crossbred sow longevity is low. Since the crossbred sow is the breeding objective, phenotypic data from the crossbred females should ideally be used when estimating the breeding values for sow longevity that are used in the indexes to evaluate nucleus animals. Genomic selection is best suited for sex-limited traits, traits expressed later in life, and many animals do not reach some defined end-point parity, sow longevity seems ideally suited to be evaluated using the latest genome enabled selection technology. Keywords: heritability, leg conformation, selection, sow productive lifetim

    Highly-parallelized simulation of a pixelated LArTPC on a GPU

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    The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 10^3 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype

    Prediction of live body weight using various body measurements in Ugandan village pigs

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    A study to develop body weight prediction equations based on various body measurements was conducted in rural Kamuli district, Uganda. Body weight (kg) and body measurement data (cm) were collected from 411 pigs between 15 and 127 kg from both local and exotic (mainly crossbreds) pigs. Five body measurements; body length, heart girth, height, body width and flank-to-flank were taken from each pig. Prediction models were developed by regressing weight on pig body measurements. The models were developed for pigs categorized as 0.05) and quadratic terms also did not improve accuracy and were not included in any prediction models. These results suggest that live weight could be accurately estimated using two or more pig body measurements. It was concluded that this weight estimation tool would empower Ugandan small scale pig farmers by providing them with an accurate estimate for the animal’s live weight and giving them better bargaining power when selling their pigs
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