Going round in circles

I’ve just finished refilling my Ecover washing up liquid bottle at work. Here in our shared office facilities our landlord is trying to get us all to go green and so has invested in a large returnable drum of Ecover from which we can all recharge our plastic bottles and avoid yet more plastic into land-fill.

My eco-crusade doesn’t stop there. In the past month we’ve stopped buying milk from the supermarket and I’m now popping into our local dairy farm on the way home and refilling glass bottles from their state-of-the art milk dispensing machine (at twice the price I might add).

Now I haven’t done the carbon calculations on any of this but what I do know is the amount of plastic we are getting through as a family has reduced significantly with just these two simple changes in habit.

At a time when Greta Thunberg is making waves across the Atlantic (literally) and movements like Extinction Rebellion are on the front pages, we simply cannot ignore the fact that the planet is in crisis.

So what does this mean for agriculture?

Those who have far better crystal balls than I do are suggesting that the future of business and the economy will be in what’s known as Circular Design. Unlike our current linear way of living (design, consume, throw away – or at best recycle), Circular Design is based on the rationale of there being no more waste, only the recycling of nutrients with a goal of arresting resource depletion and exploitation. Global sailing icon Ellen MacArthur is one of the big names leading the charge.

If the recycling of nutrients and a sustainable approach to our use of natural resources is the ambition, then agriculture must be central to the mission. And that’s the bit as someone in the agtech sector that excites me.

In an increasingly data-driven world, the opportunities for machine learning and AI to help us rethink the way we do things are growing by the day. As producers of food we are already seeing the norms of food production being challenged – impossible burgers, vertical farming and insect protein to name three. Whether these are truly “circular” I can’t say but they do signal the start of a revolution that is challenging what the farming sector has done for generations – and to traditionalists it feels uncomfortable.

But the truth is there isn’t a future in comfortable. We have such an existential crisis in an environmental sense that the rule book must be ripped up and those that tear the hardest are likely to win out.

To me that means adoption of smart, data-driven tech is an obligation not a privilege. It means we need to start collecting data on farm as a matter of urgency to begin to understand the complex dynamics of food production and resource use, and to deploy the best minds and technologies to redesign how we produce what we eat, how we consume it, and how we recharge the environment throughout this process.

We have such an existential crisis in an environmental sense that the rule book must be ripped up and those that tear the hardest are likely to win out.

Myriad projects could and should emerge that can establish the best production systems optimised by machines (sounds scary but isn’t) that calculate the “circularity” of the on-farm choices being made and that could be tied to market incentives for those that are indeed truly circular.

Imagine a future where data (privacy compliant of course) from your car, home and elsewhere is all linked up to the decisions you make about what you buy. In other words, the way in which you acquire and consume a product (food and non-food) is a dynamic calculation based on its own production history and your subsequent behaviours with it. Your “circularity” could become a badge of honour.

Governments the world over must incentivise the farming sector to make a step change. It is not good enough (in fact shameful) that something like 75% of the UK’s farmers do no electronic data recording at all. That might be fine to run an individual farm but it’s a collective disgrace when you look at the lost opportunity in a sustainability sense. Instrumenting farms and gathering good data is essential.

So as I take my refilled bottle of Ecover home via the milk dispensing machine, I can’t help but wonder what things will look like in five to 10 years from now. If it’s more of the same then we will all have failed. But if I and my children become more enthralled by sharing on social media how “circular” we are rather than obsessing about Snapchat streaks and Instagram likes, then that might suggest the tide has turned.

Or to put it another way, MacArthur won’t be the only one going round in circles!

Time to demonstrate sustainable delivery of human nutrition

As the debate about the carbon footprint of livestock farming rages on, I was encouraged to hear a very persuasive presentation from Professor Michael Lee recently.

Michael heads up the team at UK-based Rothamsted Research’s North Wyke site, a world leading centre for farm-scale ruminant livestock production research.

In the past couple of years, North Wyke has had considerable investment in facilities to support its work and it really is an impressive mix of cutting edge science and pragmatic farming knowledge.

So what was Michael saying when it comes to global warming and livestock production? His argument is many of the figures being bandied about are an oversimplification of a complicated subject. But golly did he do a good job of distilling down the key points. It is true he suggested that when you look at simple measures for global warming potential (GWP) such as C02 equivalent/kg of meat product then the much maligned beef and sheep farming systems do fare rather poorly.

But does one kg of beef have the same nutritional value as a kg of chicken? The answer according to his analysis (actually that of his colleagues Graham McAuliffe et al. he respectfully conceded) is no. And here’s why:

Recommended daily intake

The North Wyke scientists have looked at the recommended daily intake (RDI) nutritional requirements of us humans and mapped this across the nutritional content of the different forms of meat (and systems) to produce a nutrient index based on 10 encouraged and two discouraged nutrients. Then they have compared the typical measure of C02 equivalent/kg of meat with a new measure of C02 equivalent/1% RDI and this rather turns some of the analysis on its head.

As the graph below shows, beef which performed rather poorly from a GWP perspective on the old measure (see top chart), comes out best on the new one. That is to say, for every % of RDI we need in our diet, beef production produces fewer kg of C02 than even chicken!

And while lamb might seem to be lagging even in the new analysis, by looking at arable land used to support the various livestock production systems, lamb does best with chicken again performing rather less well than ruminants on the RDI measure.

The point is not to crash the cause of UK poultry (or even pork) production but to point out that ruminant bashing doesn’t stack up on a RDI basis when measuring C02 equivalency. And while human consumption of plant-based products (as opposed to meat) might be even more sustainable, North Wyke’s work provides a strong argument for grass-based ruminant systems on non-arable land, and that’s even before all the negativities associated with potentially ploughing up swathes of pasture land for arable production and releasing tonnes of sequestered carbon.

So why as a technology provider am I interested in this? Well, if here in the UK rewarding farmers for preserving (even building) “natural capital” is going to become the big game in town, then we need some ways to measure it. Right now, to my knowledge, there isn’t a livestock recording software package out there that measures performance based on (for example) delivery of the human RDI index. This seems an enormous opportunity to start creating a tangible link between human nutrition (society), farm productivity (economy) and the environment through an empirically-based approach. Indeed, these were the three pillars of sustainability that Michael opened his presentation with.

Our own pureFarming livestock recording platform is already a feature-rich white-label tool for organisations helping farmers measure, record and monitor livestock performance but how much better could we make it if we added a new set of sustainability metrics to link on-farm production with the delivery of a healthy diet? That would be bringing farmers closer to meeting the needs of the consumer in a scientifically rigorous way.

I feel a project coming on! Anyone?

Do we really know what’s coming?

One of the questions I am often asked is: “How does farming in NZ compare with the UK”?

Right now I think it’s a slightly loaded question with all the Brexit talk – subsidies and all that. But in reality given the context of the question is usually in the knowledge I head up a UK-based subsidiary of an NZ agri-software business, what many are really asking is: “How will technology change what we are doing, and is NZ ahead of the UK”?

Now this is a harder question to answer. I guess at a high level I would say adoption of technology in the NZ dairy sector is some years ahead of the UK, but equally, there are big advances in UK arable and hort which one might say are further ahead than NZ. One thing I would say is that NZ farmers are, more typically, open to change and innovation and less wedded to the way it is.

But I think there is something bigger going on than simply comparing one country with another. Sure NZ is a focus for our sector just now because of the way it has, in a generation, turned itself into a very globally focused and innovative economy; one that tops the global rankings for ease of doing business (and one that I would say punches well above its weight, and that’s not just the All Blacks!). No. I think we are witnessing the early stages of an utterly transformative period in global agriculture.

And that’s why I ask the question: “Do we really know what’s coming?” By this I mean, how is technology (and maybe digital and data in particular) going to change the sector?

In short, from where I sit, I would say those of us in the tech world do have a good hunch about what’s coming and the potential impact it will have. But I am not at all convinced the “average farmer” (which is a horrid term) does.

To me it is inconceivable that a farming business (whether in the UK or elsewhere) will be in any way competitive without the use of data-driven decision support tools in the future. The level of accuracy and objectivity that data will deliver (and we are seeing this already) simply puts subjective observation in the second tier of good decision making.

That isn’t to say good husbandry and farming experience have no place in the future (of course they do – I know some brilliant, intuitive and innovative farmers) but those who apply that experience with the latest technological tools will become the Premier League while others languish in the lower divisions.

Give me an example I hear you cry? Ok! A couple of weeks ago I sat down with the CEO of an innovative dairy cow data capture company (based in the UK) that is effectively putting Fitbits on cows. The volumes of behavioural data they are collecting from those animals is now substantial. But it’s what they are doing with it that so impressed me.

By using clever algorithms to understand normal and outlier behaviour of animals they are achieving two great things. The first is the ability to provide alerts flagging animals that are not exhibiting typical behaviour. In other words, “go look at those ones, that’s where you should prioritise your time”.

But the second is what really excites me. Who’d have thought that by analysing cow behaviour data it would be possible to identify lameness, mastitis and other disorders days (even weeks) ahead of when the clinical signs might be observed? I don’t care if you are the best herdsman in the world, it is hard to compete with decision support from data that is identifying things well before they are ever observable by the human eye.

This “power” has the potential to transform the way we run our farms. The application of digital technology will not only potentially save time and labour, it will enable better focus on meeting market requirements, predicting and avoiding problems, and increasingly importantly, be able to provide a substantial evidence base to back and improve welfare standards and all sorts of other production areas currently under scrutiny.

But this future is a far cry from where many on our farms sit currently. Sure there are those that are the early adopters, but I think there is a large majority who simply don’t see this massive change coming, or if they do are in denial.

There are many analogies over the years of where technological change has been transformative and where at the time many did not see it coming: Henry Ford and so on. But it’s the sheer scale of change from tech-driven ag that I think we underestimate at our peril.

The upside is that all this talk of agriculture being a high-tech industry that our children and students should be enthused about is not just talk. It is absolutely true. The more we can find demonstrable examples of great (even cool) innovation, the better it will be for our farming sector, not only because we can farm better, but because we can also excite the right people into the industry.

In my 25-plus years in the ag world in the UK and NZ, never have I felt there is a better time and more opportunity for non-farming people to get involved in the industry, whether that’s in agribusiness, science or on the farm.

And if, as I suspect, we see a reasonably aggressive scaling back of direct farm support in the UK (assuming we Brexit!), that could open the door to a new generation of tech-driven farmers, unencumbered by the past and able to deliver from the potential of the land and associated technology alone. They will be the new competition.

Can’t see it coming? The iPhone is only a little over 10 years old. Things will look very different a decade from now in agriculture. That’s really not very far away. Are you on the train or is it leaving without you?

Sounds like DEFRA’s been listening

Back in March I posted an article on LinkedIn arguing the case for future farm support to be channelled into technology solutions that can deliver productivity gains and better deliver of social and environmental goods.
 
Well it seems the UK government is listening. Its publication of the Agriculture Bill last month which will determine farming support for a post-Brexit UK (noting that there will be differences in devolved administrations), caught my eye on three counts:
 
  • The phasing out of direct support payment
  • The introduction of funding for farmer-led R&D and collaboration on productivity innovation
  • A new Environmental Land Management (ELM) scheme
 
Of course the devil is in the detail, but on first glance (and at odds with some farming leaders) I like the look of what’s being proposed. Here’s why:
 
First, phasing out of direct support finally puts an end to the subsidy crutch that for too long has made British farming unproductive. We lag hopelessly behind many of our major competitors on this metric and while transitioning to a brave new world won’t be easy, it is vital to give farming the boot up the backside to become more innovative by necessity.
 
The fact that there may no longer be a requirement to farm to receive progressively reduced payments over seven years is a good thing. It gives farmers wishing to exit a dignified means of doing so, and might even start to make land occupation (rents or purchase) a little more reflective of economic viability – a good thing for innovating farmers and new entrants alike.
 
Second – and the one which in many ways I am most excited about – is the directing of funds towards farmer-led R&D and innovation. This is potentially game changing and totally in tune with a more technology-driven future for the sector. 
 
Back in March I noted the announcement of the Innovate UK Transforming Food Production fund of £90m as being a welcome start, but really just a drop in the ocean. I really hope the government through the Bill is bold enough to provide significant budget into this farmer-led area and not just pay it lip service.  There are some exciting initiatives we are involved in that fall squarely into what the government is driving at here. But this funding MUST encourage innovation that is focused on food production as well as other areas. As I wrote in the spring, more food is needed in the next 50 years than has been consumed in the entire history of humanity! It’s a big challenge that needs big thinking.
 
Third is the ELM scheme. For me there is also a huge technology role here. Delivery of public goods has to be measurable and we are now in the era of big (and small) data, machine learning and AI that could deliver real transformation in ways that can transparently demonstrate public value. The taxpayer should expect nothing less.
 
Moving away from direct support and into the territory of funding innovation and targeted activity is a sea change and something I believe to be a good thing. Ultimately, this approach is about the development of solutions which should, over time, stand on their own two feet. That’s what we are focused on and why so many of our clients come to us asking the question: “How will digital and data help us do the job better?” 
 
So, yes I understand why farm leaders are concerned. But this is not the time to cling onto the past. It is absolutely the time to tear up the rule book, imagine what the future should look like, and back truly innovative thinking and innovative farmers to get us there.  

More than one way to skin the data sharing cat

Last week the UK Agriculture and Horticulture Development Board (AHDB) announced an industry consultation to develop a set of principles (code) to promote the sharing of farm data. Happily, we at Rezare UK have been awarded the contract to run this project based on our unique agridata expertise and our significant experience in developing a code in NZ.

 

Improving the flow of data from farms to other organisations is seen (rightly) by the AHDB as part of the productivity agenda for UK agriculture, but there remain significant barriers to getting the data flowing in practice mainly because of issues around trust and interoperability of disparate sets of data.

 

While the code will go someway towards addressing issues of trust (and start to build some alignment across industry on best practice when it comes to sharing and using farm data), other issues will also need to be addressed going forward beyond the code itself, particularly the more technical aspects of exchanging and using the data.

 

Two really good examples of dealing with this have emerged in the past couple of years – DataLinker in NZ and Agrimetrics in the UK. These two approaches (the latter is one of four UK government agritech centres of excellence) while quite different in nature (and to a degree in objectives), are actually also potentially very complimentary.

 

DataLinker works on a model where no one party becomes the single repository and broker of farm data. Instead, data owners build APIs to standardised schema and do this once only so that permissioned third parties can access that data in a known way. The exchange of data between the owner and user of it (“consumer”) is a bilateral relationship where DataLinker provides the permissioning (tokens) and legal frameworks (templated agreements) to streamline and standardise the process.

 

DataLinker assumes that each potential system is in fact its own “locker” (store of data) with one or more types of data. Users of some sort already interact with those systems, so what DataLinker does is standardise the way of finding which systems have which types of data (the findable F in FAIR data sharing) and in which formats (the interoperable I in FAIR). It specifies the method by which organisations agree data access rules and users provide permission (together, the accessible A of FAIR), with the result that the data is reusable (the R in FAIR). DataLinker has been focused more on the farmer or user-facing sharing of data than for broad data access necessary for researchers for example (at least without organisations explicitly addressing this).

 

Agrimetrics in the UK employs the semantic web whereby publicly available data (published on the web) or private data made available under a licence agreement is organised according to a Resource Description Framework (RDF). Each data entity is described as a “triple” (subject-predicate-object) and in that way stored data becomes machine readable by being linked to other data entities. The data contributed is effectively “held” by Agrimetrics and then exposed through APIs (charged or free) under licence for third parties to use.

 

Agrimetrics is focused on big data and using semantic web is tagging or structuring large datasets in public HTML documents (and other data) in a way that makes it machine recognisable and readable.

 

In essence the two approaches can be differentiated thus:

  • DataLinker is a network approach – a set of protocols and standards that allow myriad parties to exchange and share data in multiple bilateral (albeit mostly templated) arrangements through standardised APIs.
  • Agrimetrics is a hub approach – where data is is shared to the Agrimetrics “centre” where it is stored, manipulated and interpreted before being shared as a more user-friendly asset under licence through APIs.

 

In many ways Agrimetrics is the more comprehensive since it seeks not only to broker data exchange but also to add value to the data by linking it and manipulating it to meet a particular consumer’s need. It can handle structured or unstructured data. This is potentially very powerful as it allows a consumer of the data to draw on Agrimetrics’ technical know-how and capacity to do increasingly clever and machine-learning based activities with the data. In other words, Agrimetrics can offer a one-stop-shop for brokering and adding value to data.

 

However, there are also problems with the approach. It assumes a high degree of integrity and legal rigour being exercised by Agrimetrics since the data sharers are effectively “letting go” of their data to be stored and used by an organisation that is looking to commercialise it. And in the absence of private data holders being prepared to release data, Agrimetrics is only as good as the publicly available (web published) data.

 

DataLinker does not (and is not intended to) become involved in negotiating commercial deals to share data. Nor does it become involved in managing, manipulating or interpreting the data.  It is largely a hand-off approach designed to facilitate the network, not control it. But the adoption of the standardised schemas means there is an IT burden on the data sharers – either in-house or outsourced – to build compliant APIs.
Understanding the DataLinker and Agrimetrics approaches

So is one approach likely to prevail? Most likely not and it’s actually preferable for the two to co-exist and complement each other. Here’s why:

  • First, because culturally the DataLinker approach is more aligned to putting the interests of the farmer first and right now farmer trust in how their data is controlled and used is becoming almost the biggest blocker to progress
  • Second, because it is unlikely industry will want to have all its eggs in the one basket
  • Third, because the horsepower in Agrimetrics is potentially a game changer in terms of releasing real innovation based on farm data and thus demonstrating the value proposition to farmers from sharing their data (another piece of the sharing jigsaw that is missing)
  • Fourth, because the DataLinker approach through its JSON_LD APIs means data can be “readied” for consumption in a semantic way which would complement the success of Agrimetrics
  • And fifth, because the semantic web is likely to be a long-term approach favoured particularly by the research community within the agrifood sector.

 

There are other concepts for farm data sharing that are being considered around the globe.

 

For example, Wageningen University in the Netherlands has proposed a Farm Data Train which effectively creates a number of data lockers (stores), all with the same API and approach to authorisation, which means their interfaces in effect align closely to what is proposed in DataLinker. At present this concept is focused more on plant breeding data but it could easily grow outwards.

 

So what’s my point? Well, as can be seen, there is more than one way to skin the proverbial cat. What’s important is for the sector to provide space for the approaches to breathe so that there is increased opportunity for innovation to deliver against the productivity agenda. That’ll need some collaboration and collaborative thinking and in the UK we shall, in the coming months, discover how its agri sector wants to address these issues.

 

It’s a great time to be involved in agridata and better still that Rezare are in the thick of shaping the future.