302 Phenomics and its potential impact on livestock development in low income countries: Innovative applications of emerging related digital technology. (30th November 2020) - Ekine, Chinyere; Mrode, Raphael; Marshall, Karen; Chagunda, Mizeck; Muasa, Bridgit; Ojango, Julie; Mwai, Okeyo
Abstract: Infrastructure and institutional frameworks supporting sustainable phenotyping systems are lacking in most developing countries, which are characterized by subsistence agricultural systems with small, highly dispersed farms having few animals, which makes performance recording inefficient, unattractive and expensive. Nevertheless, capturing performance data in near real time using digital devices for livestock improvement is fast gaining ground in many emerging economies around the world because of technological advancements made in the use of information and communications technologies (ICT), mobile devices and a myriad of digital innovations. Several initiatives in developing countries have demonstrated that ICT models for livestock performance recording in small-holder farming systems coupled with appropriate feedback to farmers for improved management and decision making is sustainable. More work needs to be done in developing and designing simple, efficient, inexpensive, non-evasive and sturdy phenotyping devices to support the collection of a range of existing or new quantitative data relating to animal welfare, production, reproduction, product quality, feed efficiency, etc. on farms. Most suitable technologies will be those that will support routine data collection to be transmitted in real time/near real time, but can also function without the internet, and can be easily incorporated into genetic/genomic improvement programs with a community-based breeding program approach. Animal scientists will need to collaborate with an interdisciplinary team of scientists (software developers, engineers, programmers, etc.) to design these next generation of innovative technologies needed for phenotypic data collection. Efficient methods for data collection will generate a lot of data and will need trained scientists to transform this data into information needed for improving animal production systems. Application of these technologies will be critical in attracting youth into agriculture and thus ensure sustainable systems for phenomics in developing countries.