This article focusses on the farm system – a fascinating animal-pasture game of matching the ever-changing pasture growth with a livestock business.
I am lucky to have spent time with farmers who are far ahead in thinking: my role has been to understand this thinking and how it can be incorporated into a system. Theirs is a whole story because it includes the battle to get the time to think when everything else is happening – farm succession, regional council consents and farming with your brother…
Helping a farmer involves either supporting them to find the right story and or helping them make the right choices with the story they have chosen. The first is strategy and second is tactics, and this article is about strategy (my next article is about tactics).
Let’s pause for a moment to discuss the animal-pasture game and the size of the prize. In quantifying the value of precise knowledge in pasture management on dairy farms Beukes et al (2019) estimated $385/ha can be gained with improving knowledge of pasture biomass (average 15% error) – also referred to as pasture cover, and a further $155/ha could be achieved with perfect knowledge of paddock biomass, at a price of $6.33/kg of milk solids – a 27% increase in profit.
The study found a 26% increase in pasture production between poor and perfect knowledge. Can we translate this to NZ sheep and beef farms? We can assume an average sheep and beef farmer is dairy’s poor category[1] so the move to perfect knowledge would increase pasture productivity of 6.5tDM/ha by 1.7tDM/ha.
A farmer should be able to convert this into revenue that would double the profit of average hill country sheep and beef farms. And, that is what we see the top farmers are doing in almost every benchmarking scheme I have seen or been part of.
The dairy sector knows exactly how they would use perfect knowledge – using a feed wedge and the Spring Rotation Planner (developed by DairyNZ) to manage grazing rotations. Sheep and beef farms are more complicated with many more mobs all with different metabolic demands running on different landforms with different pasture composition, quality and soil fertility.
So, can a sheep and beef farm double its profit through more perfect knowledge? I think this is theoretically possible and entirely worth the effort. I see three preconditions:
- Pasture cover measurements – easy and accurate
- The farm makes good seasonal decisions – when required, with good measurement
- The farm system is well design – and can adapt to its climatic variability.
Let’s work through these:
1. Pasture cover measurements – easy and accurate
There are great farmers dedicated to measuring their pasture covers paddock by paddock limited only by the accuracy of their technique and state of the technology. But that dedication is beyond the mettle of the remaining 92% of farmers.
Accurate measures of pasture cover on New Zealand sheep and beef farms is extremely important if we want to win the game and double profit. One example is the decisions made in the autumn season. New Zealand farms minimise expensive supplements by accumulating pasture cover to use in winter, while leaving enough to set stock (open the gates) at the start of lambing and calving.
Too little pasture cover pushed forward, and lambs and calves are born underweight on bare pasture – keeping the pasture bare slows regrowth as pastures exhaust their root reserves, reducing annual pasture production by 20%. But the worst effect is that it prolongs the period where mothers cannot wrap their mouths round enough pasture, they roam, and lambs follow an udder that is not full. If a dry summer follows, the farmer starts with poor condition animals.
Too much pasture cover and pastures quickly enter the reproductive phase with too much pasture length: this will mostly be lost to decay and up to 30% of the annual pasture production will not consumed. If the grazing rotations have not been well planned, then the dead and decaying pasture will not be isolated but will instead be through most of grazing area, slowing lamb growth rates.
Getting this right should not be mysterious, it requires good measurement, good information to base predictions and good computation (thinking). Not having an easy and accurate pasture cover measurement and no quantifiable probabilities of future pasture growth rate creates the mystery.
2. The farm makes good seasonal decisions – when required with good measurement
Farms are biological systems and decisions are based on keeping things both alive and thriving. A farmer must manage pasture to keep it vegetative while enabling it to restore root reserves. The complexity comes with maintaining a whole livestock business that supports the management required of pastures.
If a farmer does this without measuring things, they will be on the spectrum between lousy and good.
The good intuitive decision-maker really interests me. In my rather informal study, I have found they look closely at things: for example, they drive over their pastures regularly, perhaps mentally calculating what is coming up in their mental grazing plan. They also have a good memory, particularly for how the farm’s situation compares to previous years and in those situations what they did (or should have done).
The other three quarters of farmers also interest me. Often the other things going on in their story are just too distracting and may be a higher priority.
3. The farm system is well designed – can adapt to its climatic variability
I’m going to discuss this topic in more detail.
Designing for variability is all about understanding the strategy of the game. This is best illustrated to me by farmers who always find variability traumatic. The farm seems to operate well less than half the time. In good years there is a big catch-up to be made and the farm is not setup to capture the onrush of pasture. In poor years stock are not sold in good condition and markets are poor. The solution is usually to invest in thinking – why is the farm so brittle?
The highest value from investing in strategy is in farms with diversity in landforms and variability in climate and who have not yet optimised their systems. This is perhaps half our sheep and beef farming area.
The first step in analysing any farm system is to create a good electronic map of the farm, using this to map out the different landforms. New Zealand has seen many attempts at mapping products but most are designed by people who are not closely engaged with sheep and beef farmers in formulating strategy, so there is no concept of things such as area, effective developable area, effective area excluding scrub, and area in puggable soils.
The next step is matching each area (as above) with its seasonal pasture growth profile. Almost no farmer knows the seasonal growth profile for each landform. Given the size of the prize in winning this game we may be underinvesting.
The next few steps depend on the farmers. They involve looking at changes to the way the livestock policies work, or even replacing these with different stock that the farmer may have no experience with. A moderately complicated sheep and beef farm may have three enterprises, some having several mobs such as ewes, hoggets, sale lambs – so understanding what can feasibly run on a farm is complex.
How do you go into the unknown?
Fortunately for New Zealand farmers in the early 80’s a doctoral student called David McCall went about creating a computer model called Stockpol. Stockpol evolved into the Farmax farm modelling software which supports precisely these questions. Dave’s brilliance was in designing it at the right level of biological complexity to answer most optimisation questions.
But Farmax is only as good as it’s professional user, who may be anywhere on the talent-spectrum from costing a farmer through the resulting bad decisions, through to stories that are transformational.
Good farm modellers have the knowledge to both reduce the number of assumptions made and know where to look for opportunities. The assumption-gap is widest in the knowledge of local pasture growth on each landform. Closing this gap is a worthy cause.
A strategy creates direction, and an example of this would be:
Strategy: Reduce the variability in ewe productivity by managing condition score
Direction: “At weaning we will prioritise getting ewes to 3 condition score and adjust the number of finishing lambs accordingly”
I love it when farmers have bold strategies that are based on solid logic. Such strategies spell out what needs to be measured. These farmers talk in metrics that line up with the decisions they expect to make. I have visited many farmers who are measuring things without knowing what they will do with the results. I like farmers who have these side hobbies, but if they are measuring just because they are guessing at what might be useful, this article is encouraging them to invest in strategy first.
The farmers story is bigger than their farms profitability
Farmers may discount a direction because they have no affinity to it and know they will muck it up: some farmers do not like trading (buying then selling) stock for example. This discount may push it well down the list despite its apparent profitability – I am always amazed but I respect a farmer who is living the dream.
So, how can technology help New Zealand sheep and beef farmers to formulate the strategy needed to double farm profitability? Here are a few things that would excite me:
- Hill country pasture cover measurement
- Calibration of pasture cover measurements
- Pasture database library
- Improved pasture modelling
- Weighing ewes
- Condition scoring ewes
- Hill country pasture cover measurement
As rising plates and other devices are not useable on hill country. You just cannot buy enough remote sensing devices to get accurate measurements for each paddock. Farmers are limited to visual assessment with a sward stick. This takes considerable confidence, is not accurate on diverse landscapes and takes at least a day to do well. If satellite measurement technologies can prove accurate this is the prime candidate.
Pasture cover measurement calibration
No matter how good the RBG satellite image is it will not pick up much of the dead material. This may need some in-paddock calibration. The prime candidate for this is a mobile phone and artificial intelligence to give accurate measures of biomass and the proportion in dead material.
Pasture database library
There were hundreds of pasture growth rate trials during the old MAF and DSIR days and there continues to be more. But it is a grovel to get these data, most is still in hardcopy. It’s good to hear of progress being made to build such a resource.
Improved pasture modelling
The Pasture Growth Forecaster and Farmax simply needs more investment in handling the dynamics of dead and reproductive material across more locations and sward types. Some work is being done here with lucerne but more needs to be done with the gradient from ryegrass/clover to Browntop, Yorkshire fog, kikuyu pastures.
Weighing ewes
New Zealand companies lead the world in yarding, handling, and weighing technologies. The holy grail on the animal side is real-time measurement of liveweight change in a sample of a mob. I do not think this needs to be calibrated to actual grams of liveweight gain but if shepherds could know when animals are going down when they should be going up. There are some exciting satellite based technologies being trialled.
Condition scoring ewes
Condition score is directly related to ovulation rate (and weaning percentage) while human eye assessment of a ewes lightest has been shown to be poorly related. The solution is grasping ewes in the small of the back and feeling how much fat is there – so plenty of room for operator error and very time consuming. Lifting a 2.5 CS ewe to 3 CS is one of the highest return investments on farm – a technology that drafted accurately as sheep flew through the yards would be an exciting development.
References
Beukes PC, McCarthy S, Wims CM, Gregorini P, Romera AJ. 2019. Regular estimates of herbage mass can improve profitability of pasture-based dairy systems. Animal Production Science 59: 359–367
[1] Sheep and beef farmers are limited by accuracy of pasture cover measurements on diverse landforms and in-paddock variability (soils, slope, stock camps).
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