Vol. 11, Special Issue 9 (2022)

Author(s):
Anuradha Panwar, Harshit Kumar, Divya Rajawat, Sonali Sonejita Nayak, Kanika Ghildiyal, Anurodh Sharma, Atul Singh Rajput, Gangula Lokavya Reddy and Manjit Panigrahi

Abstract:
Tremendous progress has been made continually with the over-expanding genomics technologies to uncover and understand animal genomes. However, the impact of genomics data on animal improvement is still far from satisfactory, largely due to the lack of effective phenotypic data; our capacity to collect useful high-quality phenotypic data lags behind the current capacity to generate high-throughput genomics data. Thus, the research bottleneck in animal sciences is shifting from genotyping to phenotyping. High-throughput phenotyping techniques offer a new opportunity to enhance genomic improvement of livestock, especially for novel phenotypes. Together the growing demand for food and the advancement in sensing technology has the potential to make animal farming more centralized, large-scale, and efficient. The use of sensors, big data, artificial intelligence, and machine learning can help animal farmers to lower production costs, increase efficiencies, enhance animal welfare and grow more animals per hectare. One of the most relevant challenges in this context is the handling of large-scale data provided by automated processes such as image collection, continuous real-time sensor-based measurements, and spectroscopy reports, among others. The extraction of biologically relevant features from large datasets generated by automatic devices can be done further by using machine learning algorithms. Many studies have demonstrated the usefulness of advanced remote sensing technologies coupled with machine learning (ML) approaches for the accurate prediction of valuable animal traits. Although AI and ML algorithms have developed so fast, there is a lack of standardization in the collection and sharing of data globally. However, as more farms get connected to technology, AI and sensing technologies will start playing a more decisive role in helping farmers see patterns and solutions to pressing problems in modern animal farming.