USDA grant awarded to Dr. Khaled AhmedDr. Khaled Ahmed received a new grant from the US Department of Agriculture (NationalInstitute of Food and Agriculture). This new federal award, in the amount of $149,960, will support Dr. Ahmed's research project entitled "Artificial Intelligence for Greener Livestock:Educational and Research" for two years. Dr. Ahmed is the PI of this project. Dr. Amer Abu Ghazaleh of the School of Agricultural Sciences serves as the co-PI.
The project summary is as follows:
Methane has negative effects on the climate due to its high global warming potential. Human activities such as agriculture, waste disposal and fossil fuel production produce about 60% of the world's methane emissions that is responsible for at least 25% of today's global warming. Enteric fermentation and manure management are the two processes producing methane in livestock. Wasting part of the feed energy in the form of methane is not only a climate issue but also a production problem. According to the United Nations, the world population is about 7.7 billion in 2019 and expected to grow to around 8.5, 9.7 and 10.9 billion in 2030, 2050 and 2100, respectively. This population growth is the main motivation of the increased demand for livestock products. To meet the growing global demands over the next 50 years, it is estimated that livestock production should increase by 70%. Therefore, methane emissions are expected to continue to increase as the demand for animal productsincreases. Therefore, scientists have been investigating different strategies to reduce methane emissions as communities became more aware of the negative impact of climate change on the environment. Measuring methane emission on a largescale livestock production farm is challenging due to the high costs and the low throughput of the traditional used methods. This project will conduct a number of experiments in lab and field to develop a low cost and a highly efficient system that will be able to monitor and measure methane emission on a larger scale throughout developing computer vision and deep learning techniques. The results of this project will be used for promoting greener livestock and disseminated in a straightforward way to livestock workers through conducting workshop and accessible website. As well as this project will conduct education workshops to animal science students to enrich their skills in using AI technologies in the field of animal science. In conclusion, the expected outcomes of this project will be used by livestock producer for better management practices such as choosing the optimal diet for their herd and manure management practices that will help with reducing methane emission.