The use of GPS tracking and the LoRaWAN network to improve productivity of grazing dairy cows

Lead Participant: Chalcombe

Abstract

"British milk yields per cow have increased by 50% in the past 20 years (AHDB, 2018). Whilst grazed grass is a cheap, sustainable, high quality feed current grazing systems do not support these increased yields so cows are fed supplements or even housed them over the summer to ensure higher feed intakes. Such actions increase feed costs and environmental problems such as slurry disposal.

Our vision is to develop a system that will collect cow behavioural data in real-time and use artificial intelligence techniques to determine when best to allocate additional pasture to grazed herds resulting in higher intakes and more milk production from grass. To date there has been a market failure in such applied grassland research as there are few established companies in the sector who would financially benefit from promoting such work.

This innovate project will use cow behavioural data to track grazing intensity and determine when best to automatically allocate additional grazing. This will increase milk production from grass and lead to more cows to be grazed more of the time helping to meet society's desire that dairy cows should be grazed at grass.

Small collar-mounted sensors with track the cows using GPS signals and monitor their grazing behaviour through accelerometer data. A small proportion of cows in the herd (5-8%) will wear the collars throughout the grazing season and the collected data will be sent via a low power wide area network (LoRaWAN) to the internet. The LoRaWAN system (2015) has a 10 km range so it can receive data from all fields on a farm and has a low power requirement so that small batteries can be used to power the sensors over a full year. It has been used in the urban sector but not in lowland agriculture.

We will track cows to determine when they move to and from the milking parlour and to monitor their grazing activity in the fields. Group grazing behaviour will be used to determine when best to allocate extra grazing. A signal will be generated to trigger a field gate to open, allowing the herd access to fresh pasture.

Over time the system will build up a database of where the cows have grazed which can be used to quantify the productivity of each field. This information will improve and support pasture management decision making such as the need to re-seed grazed pastures."

Lead Participant

Project Cost

Grant Offer

Chalcombe, Shedfield £144,762 £ 101,333
 

Participant

Rothamsted Research, United Kingdom £32,092 £ 32,092
Wd Farmers £49,870 £ 34,909
Precision Grazing Ltd £11,631 £ 8,142
Hoofprints Technologies Ltd, Feltham £80,608 £ 56,426

Publications

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