RESUMO
Introduction: The African Goat Improvement Network Image Collection Protocol (AGIN-ICP) is an accessible, easy to use, low-cost procedure to collect phenotypic data via digital images. The AGIN-ICP collects images to extract several phenotype measures including health status indicators (anemia status, age, and weight), body measurements, shapes, and coat color and pattern, from digital images taken with standard digital cameras or mobile devices. This strategy is to quickly survey, record, assess, analyze, and store these data for use in a wide variety of production and sampling conditions. Methods: The work was accomplished as part of the multinational African Goat Improvement Network (AGIN) collaborative and is presented here as a case study in the AGIN collaboration model and working directly with community-based breeding programs (CBBP). It was iteratively developed and tested over 3 years, in 12 countries with over 12,000 images taken. Results and discussion: The AGIN-ICP development is described, and field implementation and the quality of the resulting images for use in image analysis and phenotypic data extraction are iteratively assessed. Digital body measures were validated using the PreciseEdge Image Segmentation Algorithm (PE-ISA) and software showing strong manual to digital body measure Pearson correlation coefficients of height, length, and girth measures (0.931, 0.943, 0.893) respectively. It is critical to note that while none of the very detailed tasks in the AGIN-ICP described here is difficult, every single one of them is even easier to accidentally omit, and the impact of such a mistake could render a sample image, a sampling day's images, or even an entire sampling trip's images difficult or unusable for extracting digital phenotypes. Coupled with tissue sampling and genomic testing, it may be useful in the effort to identify and conserve important animal genetic resources and in CBBP genetic improvement programs by providing reliably measured phenotypes with modest cost. Potential users include farmers, animal husbandry officials, veterinarians, regional government or other public health officials, researchers, and others. Based on these results, a final AGIN-ICP is presented, optimizing the costs, ease, and speed of field implementation of the collection method without compromising the quality of the image data collection.
RESUMO
Type 1 polysaccharide storage myopathy caused by genetic mutation in the glycogen synthase 1 gene is present in many breeds including the Noriker and Haflinger horses. In humans, EMG has already been used to document changes in the muscle activity patterns of patients affected by human glycogen storage disorders. Therefore, the aim of the present study was to describe gluteus muscle activity with surface electromyography (sEMG) in Haflinger and Noriker horses with known GYS1 mutation status during walk and trot. Thirty-two horses (11 Haflinger and 21 Noriker horses) with homozygous non-affected (GG), heterozygous affected (GA) and homozygous affected (AA) status of GYS1 mutation without overt clinical signs of any myopathy were selected for the current study. Using surface electromyography gluteus medius muscle activity at walk and at trot was measured, and muscle activity was described in relation to the maximum observed value at the same sensor and the same gait. In order to further describe the signals in detail comprising both frequencies and amplitudes, the crossings through the baseline and the 25, 50 and 75 percentile lines were determined. The result of the relative muscle activity did not show a consistent difference between affected and non-affected horses. Genetically affected (GA and AA) horses showed significantly less density of muscle activity for both gaits and horse breeds except for the crossings per second at the baseline and 75 percentile at walk in the Haflinger horses and 75 percentile at trot in the Noriker horses. The medians of all calculated density values were significantly lower in the GA Haflingers compared to the GG Haflingers (p = 0.012) and also in the AA Norikers compared to the GG Norikers (p = 0.011). Results indicate that the GYS1 mutation reduces the number of functional muscle fibres detected by sEMG measurements even in the absence of overt clinical signs.
