Pasture.io was proud to present to a top notch group of Moonlake dairy farm managers who were studying the Diploma unit Analyse and Interpret Production Data. (You can see the slides on this page if you want to see the presentation.)
The purpose of the presentation was to give an overview of the Pasture.io and Milkflow.io platforms and the journey to where they are today.
The journey first started on my family dairy farm on the NW Coast of Tasmania in Flowerdale,back in the year 2005. This was when I was given the responsibility of managing the pasture on our dairy farm. From here I asked a lot of questions such as, how do you know where to graze the herd next? how do you know how much grass is in a paddock? How do you keep trackingof the grazing rotation? How do you know how much a cow can eat?
These questions led me down a rabbit hole of buying a rising plate meter in 2006 and walking the farm once a week collecting pasture covers and growth rates for each of our paddocks. Long story short, without this enquisative nature and determination to record and keep track of data such as grazing records, fert records, pasture records, paddock records, etc we wouldn't have had the know how and speed to developing remote pasture measuring.
By 2009 this data collection was further emboldened with the purchase of a CDax rapid pasture meter. This tool is a pasture meter that is towed behind a quad bike. The CDax provides a good tool for collecting consistent data. This is the exciting part, as this data would form much of the basis for forming a prototype machine learning environment with training data.
The presentation then moved into the collection of weather data and how we were able to integrate this with farm records and satellite imagery for determing pasture biomass and pasture growth rates in each paddock. The important part here is that rubbish data in would equal rubbish data out. This integration of different data streams highlights the steps we have taken over years, and that of fellow farmers, satellite image providers, and governmental weather organisations in making sure the integrity of our data is second to none for further analysis.
The above is crucial in telling the story of analysing and interpreting production data with the crucial aspect of capturing and recording data in such a way that can be utilised for future and often unknown purposes.
- Ollie Roberts, 1 March 2019