Cefngwilgy Fawr Project Introduction: Improving herd health through the use of technology

Site: Cefngwilgy Fawr

Address: The Gorn, Llanidloes, Powys, SY18 6LA

Technical Officer: Lisa Roberts

Project Title: Improving herd health through the use of technology


Introduction to project: 

Maintaining herd health and reducing infectious diseases are major drivers in improving the efficiency and profitability of suckler herds. Calf health is one area in which Edward and Kate Jones, Cefngwilgy Fawr, are keen to address following cases of pneumonia in their calves in past years. Pneumonia is caused by a range of factors which include: infectious agents (pathogens), housing environment, management and the immune status of calves. It is estimated that pneumonia can cost up to £82 per affected suckler calf, with costs rising significantly when subsequent treatments are required. 

The suckler herd consists of 50 Limousin-cross and British Blue-cross cows which are mostly spring calving, which calve indoors and are then turned out to pasture. 

This project will focus on improving monitoring of calf health and ensuring early interventions to reduce disease incidence and antibiotic use on farm. An ear tag which measures calf activity and temperature will be used on the spring-born calves to monitor their health. Initial trials on the system have shown that it can detect disease approximately 2 days prior to the appearance of clinical signs. This enables targeted antibiotic usage and has the potential to improve growth rates and reduce calf mortality as disease is detected early. The housing environment will also be monitored through the use of on-farm sensors and LoRaWAN technology. The project objectives are as follows:
Project Objectives:

  • To improve calf health and performance 
  • To identify disease early-on and apply interventions where necessary 
  • To reduce the use of antibiotics

Key Performance Indicators Set:

  • To reduce the overall incidences of pneumonia within the calves from 25% to 5%.
  • To be able to detect at least 90% of potential disease cases 2 days prior to a calf showing clinical signs of illness.