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Resource Guides 2011
 
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Use common sense when looking at research results

When looking at research results

Written by   
If adding up the predicted returns from crop inputs looks too good to be true, they probably are.
Agricultural science, like all other branches of science, is based on a system that builds on itself. When one discovery is made, researchers focus on perfecting and fine-tuning the information. Fertilizer boosts yields by 10 percent, hybrids by eight percent, grass weed control by 15 percent and so on. Soil scientist, Don Flaten of the Faculty of Agricultural and Food Sciences at the University of Manitoba dubs traditional scientific discovery as a series of 'single input' experiments. He cautions that assuming the single input results are cumulative is dangerous.

"There are almost no comprehensive studies that take into account all inputs," says Flaten. "If growers were to spend the money on the seed, nutrition and crop protection as recommended by science, their economic return would not come close to their expectations based on experiments where only one input is investigated."

One plus one does not equal two
To that end, Flaten delved into the issue and came up with a plan for 'integrated management' of cropping systems. While not intending to target any one input unfairly or specifically, for the sake of discussion, Flaten uses nitrogen as his example.

"Typically, we use marginal returns analyses to determine the optimum rate of applying a single input, such as nitrogen," begins Flaten. "The first step is to gather information on expected yield response to that input. Most growers will calculate the economic return of nitrogen at increasing incremental rates to achieve a maximum economic yield, which is where the spread between revenues and costs is the greatest."

To prove his point that single input experiments can be misleading, he developed a hypothetical canola scenario, where he added up all the yield advantages of additional inputs and their associated costs.

In Flaten's hypothetical scenario (see Table 1), the response for adding each input individually is based on single input research. As the costs continue to build and the expected overall yield becomes unrealistically high, the cost of inputs will inevitably exceed the expected return by a large margin.

Table 1. Hypothetical yield increases and economic returns for production of canola at $5 per bushel.
Yield source or response Yield
(bu/ac)
Revenue
($/ac)
Cost
($/ac)
Margin
($/ac)
Check or base yield* 15 $75 $55 $20
N (100) 20 $100 $30 $70
P (30) 5 $25 $7.50 $17.50
K (30) 4 $20 $15 $5.00
S (25) 6 $30 $6.25 $23.75
B (1) 2 $10 $7.50 $2.50
Zn (5) 3 $15 $12.50 $2.50
Insecticide 15 $75 $15 $60
Herbicide 15 $75 $25 $50
Fungicide 10 $50 $25 $25
Treated hybrid seed 10 $50 $25 $25
Theoretical yield 105 $525 $223.75 $301.25
Realistic yield 35 $157.50 $223.75 -$66.25
*Non-certified seed, machine operating and repair, no fertilizer, no pesticide.
In real field trials conducted by Agriculture and Agri-Food Canada's Dr. Byron Irvine at the Brandon Research Station, Flaten's hypothetical scenario proved to be true. Irvine's actual data shows how the principle of using all recommendations as given may not provide as much profit as expected (see Table 2).

"The misuse of yield responses to single inputs occurs when the individual economic responses are assumed to be meaningful for a farmer's field," explains Flaten. "This overlooks the need for other inputs, such as crop protection or pest control, which can add significant costs to an integrated crop production system."

By examining Tables 1 and 2, growers can see the unrealistic results when response data for single inputs are used for oversimplified economic analyses. What most farmers do instinctively, suggests Flaten, is to employ caution and view inputs interdependently, which is how it should work. The challenge to this type of approach to achieve the necessary comprehensive data is the cost to mount such a complex research project. Further, setting the parameters that will ultimately pay off with useful information adds to the complexity of the research. Therefore, science rarely provides the crop production industry with that kind of information and growers are left to guess. Flaten suggests that, as a consequence, "The results of single input studies cannot be applied directly to whole cropping systems."

Table 2. Average benefit of canola crop inputs when yield responses to those inputs are added individually or as a part of a complete cropping system at Brandon in 2001, 2002 and 2003 (canola priced at $7/bu, data from Dr. Byron Irvine, AAFC Brandon Research Centre).
Yield source or response Yield
(bu/ac)
Revenue
($/ac)
Cost*
($/ac)
Margin
($/ac)
Base yield (med. genetics, no fertilizer or pesticide) 4.3 $30 $75 -$45
Variety response (with all other inputs at high levels)** 4.9 $34 Zero $35
Pesticide response (with all other inputs at high levels) 14.3 $100 $95 $5.00
Fertilizer response (with all other inputs at high levels) 18.8 $132 $74 $58
Theoretical yield if all inputs were additive*** 42.3 $296 $245 $52
Real measured yield with all inputs at high levels 31.4 $220 $251 -$31
*Costs for base yield include pre-seeding glyphosate, seed, machinery, fuel, repairs and other basic costs.
**The higher expense for the high yielding canola variety was offset by planting at a lower seeding rate than for the medium yielding variety and using less seed treatment.
***The benefit of the lower seed treatment costs for the high yielding canola variety is included twice in the theoretical addition of input costs, under-estimating those total input costs, compared to reality.
Blend science with common sense
In the absence of data on fully integrated crop production systems, Flaten recommends that researchers and marketers follow the lead of producers and adopt a more cautious and realistic approach to determining and describing the expected value of crop inputs in a more integrated way.

Flaten suggests that farmers, agronomists and scientists look at crop production inputs as a series of interdependent groups. These would include: Essentials (basic seed, fuel, taxes or costs that cannot be avoided in order to grow a crop); Enhancements (fertilizer and superior genetics that increase yield potential); Repairs (crop protection products that help fix a problem and potentially save yield); and Maintenance (soil conserving equipment, fertilizers added to balance crop removal). Using this approach to planning for maximum economic return allows growers to build on a base of basic needs rather than 'adding on' as needed because no allowance was made for unexpected extras.

Lastly, Flaten recommends that farmers set budgets for a complete cropping system based on low, medium and high input production systems. These budgets should be developed for local growing conditions and should account for all the independent inputs required to reach the goal.

"This examination of how to determine the level of inputs needed to achieve maximum economic yield is not a call to reduce fertilizer use or stop buying certified seed," comments Flaten. "Merely, it is a suggestion to take an approach to planning crop production that integrates what we have learned from single input studies and apply it in real life cropping situations. The benefits and costs for the whole management system should be considered as an entire package."

While most growers know this instinctively and many practice a form of integrating all the information science provides to them, the reality is that it is a somewhat ad hoc approach to meshing all the research into a useful production system. Now that science has fine-tuned many discoveries and has proven that we cannot grow crops successfully without sound crop nutrition, herbicides, high quality seed and good use of mechanical tools, research is needed on how to put everything that has been learned into a useful package.

The integrated crop production package that is selected will vary from farm to farm and year-to-year; there will not be a simple recipe for all situations. However, the process of planning, budgeting and adjusting the entire cropping system will help to reduce the guess work in crop production and improve the odds of maximizing overall net returns. And taking the best knowledge that science has to offer, integrating it into a total crop production package is what farmers know as the 'art' of farming.