Report FAQs

The yield potential model estimates yield assuming perfect management: perfect planting date, winter survival, pest control, no nutrient deficiencies, etc. The only thing that can reduce yield is the availability of water and of sunlight. Temperature plays a subtle role too. To go into details: First, we estimate date of spring greenup when winter dormancy is broken. The model figures out when the crop experiences seven straight days of positive growing degree days (GDDs, base 0oC) and decides that is when dormancy is broken. Then, it uses weather data to figure out how much sunlight is hitting the field from greenup to physiological maturity (yellow peduncle). The user needs to enter date of maturity as the model doesn’t estimate it. Of that sunlight hitting the field, a certain percentage is absorbed by the crop and used to make crop biomass (stem, leaves, tillers, grain, roots). We then say a certain percentage of this biomass is allocated to the grain – a percentage known as harvest index. These key values: the percent of sunlight absorbed by the crop, the efficiency which that sunlight is turned into biomass, and the harvest index, is what separates the Great Lakes YEN model from others. We use actual data collected in Ontario to estimate what these numbers are under perfect management. Details are below. But this lets us calculate sunlight-limited yield potential. We then look at water availability: we add up all rainfall from greenup to maturity. We also consider soil water holding capacity of the field, which is estimated using actual soil texture data. We assume the soil reservoir is full at the start of spring – an assumption generally true in the Great Lakes. We assume that each 560 kg of grain requires 18 mm of moisture availability (rainfall or soil reservoir). If there is not enough soil moisture to support the sunlight-limited yield, the yield potential is downscaled to create water-limited yield potential. We do this by reducing yield potential to ensure that there is 18 mm of moisture for every 560 kg of yield potential. In summary, the model spits out one of two yield potentials for your field: sunlight-limited or water-limited, depending on the weather.

Percentage of incoming sunlight absorbed by the crop: 70% before heading and 95% after heading. Data from M.Sc thesis of Emma Dieleman (2021 and 2022).

Radiation use efficiency: From 20+ years of Ontario Cereal Crop Committee variety performance data (thank you to Ellen Sparry for sharing). We used the 75th percentile of calculated RUE from the OCCC dataset, 1.54 tonnes of biomass per Terajoule of intercepted sunlight.

Harvest Index: From 20+ years of Ontario Cereal Crop Committee variety performance data (thank you to Ellen Sparry for sharing). We used the 75th percentile of calculated harvest index from the OCCC dataset, 58% of all crop biomass is converted to harvested grain.

Water requirements for yield: No good Great Lakes data was available. We use the water use efficiency assumption (18 mm of water) from Sylvester-Bradley and Kindred (2014), two of the scientists involved in the UK YEN. Our final water use efficiency (18 mm per 560 kg yield @0%) is slightly different due to different harvest index values.
Sylvester-Bradley, R., & Kindred, D. (2014). The yield enhancement network: Philosophy and results from the first season. Aspects of Applied Biology, 125, 53–62.

Weather data was sourced from Weather API. This data is integrated into CropTrak and tied to each field, trying to capture the differences in weather between participants. Weather API uses current weather observations from over 50,000 live weather stations, and historical weather data for the past 20+ years sourced from stations, doppler radar, satellite, and atmospheric re-analysis products.

Accurate weather data for your field is difficult to get, short of each farm setting up their own weather station in their field. We believe that this data is reliable enough for crop modelling using temperature and solar radiation. Precipitation more uncertain. For some farms it is very accurate, for others inaccurate. In the 2021-2022 growing season the project team found precipitation varied between farms within the same region. In the future, the YEN team is committed to finding better solutions for more accurately characterizing weather data feeds. Several sources have been reviewed, but none of them are perfect for all farms.

Soil contamination to the leaf tissue samples could result in elevated levels in Al and Fe when analyzed. Soil contamination can occur if plants are laid on the ground and pick up soil particles, placing tissue in a soiled pail or container, or could occur if soil has splashed on the leaf tissue from heavy rainfall.

Crop input cost calculations include the estimated cost of nutrients (N, P, K and S), crop protection chemicals (herbicide, fungicide, insecticide), plant growth regulators and the cost to make each application. The cost of micronutrients was not considered. There are a wide range of products used on farms and with different jurisdictions, it was decided to use a common cost for nutrients, crop protection, plant growth regulators and application expense. This is not intended to get an exact cost of production for each farm, but rather to allow for comparison across farms. Much of the data used to estimate costs was taken from “Publication 60: Field Crop Budgets 2022” published by the Ontario Ministry of Agriculture, Food and Rural Affairs. Prices are listed in Canadian Dollars and USD in parenthesis. See below for how each specific cost was estimated.

The total amount of nitrogen (lb), phosphorus (lb), potassium (lb) and sulfur (lb) applied per acre was calculated for each farm using all forms (dry, liquid) and from all applications including fall and spring. The project team sought input from several sources (Canada and US based) and agreed upon following prices per pound of nutrient:

• Nitrogen: $1.31 ($0.97 USD) per pound
• Phosphorus: $0.91 ($0.67 USD) per pound
• Potassium: $0.80 ($0.59 USD) per pound
• Sulfur: $0.69 ($0.51 USD) per pound

Crop protection applications are typically made with multiple products with varying application rates. A count of each type of application was made to determine the cost. Fungicide cost was broken down into two categories based on timing. Most T1 and T2 applications were generic products that tend to be lower cost. T3 applications tend to be brand name products with higher cost. The following prices were used (these are product costs only ,see application cost estimates below for how application costs were estimated):

• Herbicide: $10.55 ($7.81 USD) per acre
• Fungicide (T1 and T2): $10.50 ($7.77 USD) per acre
• Fungicide (T3): $19.65 ($14.54 USD) per acre
• Insecticide: $3.00 ($2.22 USD) per acre
• Plant Growth Regulators: $14.85 ($10.99 USD) per acre

Due to the fact that oftentimes multiple products and categories are applied together in one pass, it is difficult to precisely apply costs to a crop protection category. So the application cost was calculated independently of specific product applied. Every trip made across the field to apply fertilizer, crop protection products or PGR was counted for each farm and totaled. There are many differences between the costs to make different types of applications (dry vs. liquid, types of equipment, etc.). Here we used a set price for every application that was used for every farm.

• Cost per application: $11.12 ($8.23 USD) per acre (all application types)

Total crop input costs are determined by summing all nutrients, crop protection applications, PGR and the number of trips made across the field. This number is only a partial budget analysis as it does not consider things like drying charges, transportation, taxes, insurance, interest, etc. It is displayed in dollars per acre and is meant to show the range in values across farms in the YEN.

Total crop input costs per bushel are calculated by dividing the Total Crop Input Cost (per acre) by the reported yield. As we look for ways to increase yields, we need to make sure that we are making money, not just yield. Each farm must assess their own purchasing programs to evaluate their costs of production. These two numbers are meant to help you understand the actual costs associated with trying to manage for higher yields.

Not all participants were able to collect all of the data and/or samples needed for the project team to create a complete report. Rather than sending reports to participants with 100% of the data collected, the project team sent reports to all growers that participated in the 2021-2022 growing season and include a report with all of the data collected. If data was missing for your farm, there will be either a blank in the report or it will show only the range in values for everyone else. For example, the boxplots are a graphical representation of the range in values. Your number is represented in each boxplot with a yellow dashed line. If you notice a boxplot without a yellow dashed line, that means that we did not have a valid value in our system for you location, either missing data or contaminated samples that had excessive values as in the case of Fe and Al contaminated tissue samples which would corrupt the entire data set. However, you can still see the range in values and the top 10% of participants in the 2021-2022 Great Lakes YEN.