This project will enable data-driven decision making for farm vets, by automating the assessment of semen for morphological defects using Artificial Intelligence. This will improve the efficiency by which farm vets perform livestock fertility testing on farm, will improve livestock production rates, and standardises the approach for semen assessment. Currently, vets collect a semen sample during pre-breeding exams, prepare stained sample slides on-farm by using Eosin and spreading the semen sample onto a microscope slide. Then vets usually return to the laboratory with the stained slides, place them under a microscope equipped with high magnification objectives and then count the number of normal cells and abnormal cells on each sample. This takes around 5-10 minutes per sample, and requires significant expertise, preventing young vets to have confidence in their analysis and decisions. In the spring breeding season, UK vets working with beef farms may typically collect 30 samples a day meaning 2.5-5 hours of work for counting morphological defects upon their return to the laboratory. In this project, Dyneval will build an AI platform for simple, fast, and accurate morphology semen assessments to be completed, allowing data-driven decisions to me made. We will use machine learning to develop deep neural network models that automatically classifies both normal cells and cells with morphological defects from microscopy images. This will save significant amount of time to the vets so that they can focus on other tasks for their business, and will allow data-driven decision to be made. Ultimately, we will aim to run the AI platform from images collected with Dyneval's innovative technology, the Dynescan which has been launched to the beef and dairy market in 2022 and uses a unique approach for assessing %motility and cell concentration, the other two key parameters considered within semen quality analysis.

Men's fertility has fallen by 57% since 1973 but no-one knows why. There is insufficient quantitative data because experts still rely on examining a man's semen sample by eye under a microscope. Although obesity, heat and chemicals are known to affect men's fertility there is very little research because there is no convenient and precise method for measurement, until now. My name is Dr Tiffany Wood and I am the CEO co-founder of Dyneval Ltd, a company that launched a new product to the livestock production market in March 2022 to enable farmers, vets and genetics companies to perform measurements on bull semen to improve conception rates. This was based on the invention of my co-founder, Dr Vincent Martinez, who developed an algorithm based on statistical physics to extract key parameters describing semen quality from the fluctuations of light intensity passing through a fresh and motile semen sample. This is now being used successfully in livestock production in the UK, US and Argentina. I am keen to use this Women in Innovation funding to help us prepare for the human fertility market through developing partnerships, generating data and gaining expert advice to help us enter the human fertility market. Being an award winner will help me gain the skills and build the network I require to help our business adapt and grow efficiently.

Dyneval brings to the market a precision technology for monitoring semen quality at any stage of the livestock reproduction process from production by the bull, boar or ram through to artificial insemination in the cow, sow or ewe. Through measurements on a sacrificial straw, farmers will use our artificial intelligence technology to optimise conception rates and eliminate semen that is suboptimal or has been damaged through damage during processing, an insecure cold chain during distribution or storage on farm. Experimental development through this project will enable us to convert our 1st Generation Product (TRL6) to create a robust, lightweight, ergonomic tool, tailored for use on the farm. Long-term, reliable data with predictive capability will improve decision making for artificial insemination. Data will be stored on the cloud for retrieval, data mining and integration with other farming data systems. For cattle, today's conception rates are 20% lower than they were 40 years ago resulting in a suboptimal calving interval that costs farmers €2bn each year across Europe (equivalent to £25k per farm). Dairy cows are estimated to contribute about 20% of total UK atmospheric methane emissions and 25% of total UK ammonia emissions. According to P.C. Garnsworthy (Animal Feed Science and Technology, 112, 211-223, 2004) total herd emissions can be reduced by 20% if conception rates are improved from current levels ~38% to achievable and optimal ~65% (a difference of 27%). Livestock farming contributes 15% of the total global carbon emissions. Deployed globally, our technology has the potential to help farmers reduce global carbon emissions down to 12% and this would be a significant step to helping food production systems reach net zero by 2040 whilst providing sufficient protein for a growing global population. Through eliminating poor quality semen from their batches for artificial insemination, farmers will produce food more efficiently, improve their profitability and resilience on farm and will be able to meet the sustainability goals set by cooperative buyers and supermarkets to help food producers meet their goals for net zero emissions.

Good fertility performance is the cornerstone of a profitable and sustainable livestock enterprise. In the international dairy and beef herd, optimum performance is achieved by maintaining a calving interval (CI) of 365 days. Every day CI increases \>365 days is estimated to directly cost the farmer ~GBP2.07/CAN$3.54/cow, or more for high yielding dairy cows. Fertility drives productivity and in turn the mitigation of greenhouse gas (GHG) emissions through reduced waste and optimising unproductive replacement youngstock inventories. This project will research and develop a number of innovative new technologies and establish national level referral facilities for quality assurance and improvement of bovine germplasm, as an integrated bilateral approach. The outputs of the project will transform genetic progress, through adoption of precision technologies, diagnostics, advanced breeding and big data, leading to more sustainable livestock food production and export opportunities in both UK and Canada.