PHOTO: NICOLE RABE PHOTO: MATTHEW MCINTOSH
PRECISION FARMING ▶▶▶
Want value from data? Conduct a real experiment
M BY MATTHEW MCINTOSH
ethods of generating value from farm data might differ based on adoption level, but there are some universal truths – namely
the need to employ proper comparison trials and analysis techniques. Indeed, some experts in Ontario, Canada, see the failure of many growers and tech-advocates to conduct proper field trials of precision-ag technologies as a notable barrier to wider adoption.
Take the time to learn “Are you actually going to analyse the data in a timely fashion? Make sure you take the time to learn,” says Dale Cowan, senior agronomist and sales manager with AGRIS and Wanstead Coop- eratives – a grain marketing and farm-input supply company based in the province’s South- west region. As an agronomist specialising in 4R nutrient management and precision-ag tech- nologies (AGRIS and Wanstead Cooperatives operate a wide variety of precision data services for farm clients), Mr Cowan says the first hurdle any successful data-generator must jump is de- termining what they’re trying to do, what data needs to be collected to do it, and from where. This, he says, applies universally – from the most entrenched analogue to the most tech- driven producers. Indeed, Mr Cowan emphasis- es good agronomy should always take top pri- ority in any field crop management system. Data generated in this context will inherently have more value. It’s also important to get help interpreting data, if required, and to keep all raw data. This latter point is particularly impor- tant in preventing data loss as it is transferred through different formats and platforms.
Record keeping crucial Nicole Rabe, land resource specialist with On- tario’s provincial ministry of agriculture (Ontar- io Ministry of Agriculture, Food and Rural Af- fairs), shares Cowan’s view that ag-tech should be driven by agronomy rather than “shiny”
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Proving if a precision technology works starts with remembering trial basics – and taking the time to scrutinise results.
pieces of equipment – many of which she says do not fundamentally fix basic agronomic is- sues, referring to them as “solutions searching for a problem.” Poor record keeping in the first place, by ex- tension, means improvements brought by pre- cision technologies cannot be accurately quantified or realised. “Before you jump in, ask yourself, what shape is my farm in? What are my basic issues and can I fix those first? Then what input do I find the most risky and has a need for better man- agement?” says Ms Rabe. “You need to have a basic understanding of your bottom line.”
Steps for tech-beginners For the late adopter of digital technologies – or those not necessarily engaged in precision farming – Ms Rabe cites three main ways to accrue value from data. The objective being to scale down from a ‘one size fits all’ (macro) approach to a field-by-field profitability (micro) approach. Firstly, centralise all financial notes relating to the cost of production in one place. Use this to identify areas for improvement across the farm and translate that into one or a series of management goals. Secondly, centralise knowledge on each parcel of land being managed (e.g. location, size, crop rotation, soil type, drainage, crop inputs, yield). Identify areas of the farm operation that con- sistently perform poorly, and use fundamental agronomic information to inform new manage- ment approaches for those areas. Then develop field-by-field near-term and long-term man- agement goals, such as a five-year plan to mend drainage systems and address fertility issues. Thirdly – look at equipment. Identify what data is being collected and how it can be used (e.g. fuel efficiency and other fleet information). If
▶ FUTURE FARMING | 1 november 2019
equipment is GPS enabled, centralise any har- vest and spatial data. Training needs should also be identified. Professional advice should be sought to work with the data being gener- ated, as well as to assess historical performance by observing field-by-field trends over time.
Steps for advanced tech-users In contrast to more analogue operations, Ms Rabe says those well-versed in ag-data tech- nologies can gain more value by scaling-up from field-by-field return on investment as- sessment (micro) to a whole farm cost-benefit statement (macro). This, she says, allows pro- ducers to examine what technologies are most advantageous to decision making, and to their bottom line. Growers can use the pre-planting season to analyse a variety of data sets, including those related to historical yield information, soil health assessments (chemical, biological,
Nicole Rabe: “Before you jump in, what’s the shape of my farm? What are my basic issues and can I fix those first?”
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