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Using the community-based breeding program (CBBP) model as a collaborative platform to develop the African Goat Improvement Network—Image collection protocol (AGIN-ICP) with mobile technology for data collection and management of livestock phenotypes

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Title Using the community-based breeding program (CBBP) model as a collaborative platform to develop the African Goat Improvement Network—Image collection protocol (AGIN-ICP) with mobile technology for data collection and management of livestock phenotypes
 
Creator Woodward-Greene, Jennifer
 
Contributor Kinser, Jason
Huson, Heather
Sonstegard, Tad
Sölkner, Johann
Vaisman, Iosif
Boettcher, Paul
Masiga, Clet Wandui
Mukasa, Christopher
Guangul, Solomon
Agaba, Morris
Ahmed, Sahar
Maminiaina, Oliver
Getachew, Tesfaye
Gondwe, Timothy
Haile, Aynalem
Hassan, Yassir
Kihara, Absolomon
Kouriba, Aly
Mruttu, Hassan
Mujibi, Denis
Nandolo, Wilson
Rischkowsky, Barbara
D. Rosen, Benjamin
Sayre, Brian
Taela, Maria
Van Tassell, Curtis P.
 
Subject community-based breeding program
african goat improvement network
image collection protocol
livestock phenotypes
 
Description 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.
 
Date 2023-12-29T16:06:15Z
2023-12-29T16:06:15Z
 
Type Journal Article
 
Identifier https://mel.cgiar.org/reporting/download/hash/fb0760256d555f3fab5bd26e4c95cdbe
Jennifer Woodward-Greene, Jason Kinser, Heather Huson, Tad Sonstegard, Johann Sölkner, Iosif Vaisman, Paul Boettcher, Clet Wandui Masiga, Christopher Mukasa, Solomon Guangul, Morris Agaba, Sahar Ahmed, Oliver Maminiaina, Tesfaye Getachew, Timothy Gondwe, Aynalem Haile, Yassir Hassan, Absolomon Kihara, Aly Kouriba, Hassan Mruttu, Denis Mujibi, Wilson Nandolo, Barbara Rischkowsky, Benjamin D. Rosen, Brian Sayre, Maria Taela, Curtis P. Van Tassell. (6/9/2023). Using the community-based breeding program (CBBP) model as a collaborative platform to develop the African Goat Improvement Network—Image collection protocol (AGIN-ICP) with mobile technology for data collection and management of livestock phenotypes. Frontiers in Genetics, 14.
https://hdl.handle.net/20.500.11766/68957
Open access
 
Language en
 
Rights CC-BY-4.0
 
Format PDF
 
Publisher Frontiers Media
 
Source Frontiers in Genetics;14,(2023)