Agronomic modeling is “…the dynamic simulation of crop growth by numerical integration of constituent processes with the aid of a computer."
Too technical? Then it is the process of creating a definable substitute for a living organism that can be manipulated and scrutinized more easily than the original.
In layman’s terms, you take something complex and decrease the complexity enough that you can make educated forecasts on how a crop, insect or disease will behave given a particular set of circumstances.
When many people hear the term agronomic modeling, it conjures up images of scientists in white lab coats in sterile labs hunched over a computer. While the computer is an integral part of the process, scrap the white coat and sterile lab. Instead, picture a researcher hunched over a crop in the field taking physical measurements. The measurement process may also include high tech weather stations in the field recording such parameters as wind speed and direction, precipitation, humidity and air temperature, and communicating the data via satellite. In other situations, there may simply be a rain gauge (electronic or otherwise) and a data logger recording a select number of weather parameters.
There is a good chance the researcher will be measuring parameters such as crop height, time of flowering, disease pressure or insect presence and feeding damage, in addition to numerous other parameters that may be of interest. The number of factors observed is dependent upon the scope and purpose of the model being developed.
Collected field observations are run in a statistical program along with the collected weather data. Data from multiple locations is used to generate representative data set for a larger area. Models developed with data from multiple locations data tend to be more robust and give a bigger picture view of the situation.
The initial statistical analysis forms the basis of the mathematical representation of the field observations. With the basic model developed, in-season ground proofing is undertaken to fine tune the model as well as understand its limitations. Once ground proofing is complete, the model will best reflect typical conditions in an average year.
Agronomic models are a continual work in progress. It takes dedicated people who care enough about agriculture to try to make production easier and more predictable.
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Cercospora Leaf Spot Forecast for Sugar Beets
Growth Stage is the first company to bring a commercial forecast Daily Infection Value (DIV) model for Cercospora Leaf Spot (CLS) to the marketplace. The Growth Stage CLS model provides forecasted DIV values, indicating the likelihood of infection over the next six days.
Cercospora beticola is the most serious leaf disease of sugar beets in the United States. It causes decreased sugar content and quality as well as decreased quality of stored roots. Significant yield loss occurs when the average incidence of leaf spot exceeds 3% at harvest.
Prior to 2005, growers had to rely on traditional disease control measures including: choosing seed that is resistant to the disease, planting in fields that have not had sugar beets for at least two years and tillage to bury infected residue. In conjunction with these best practices, growers had the opportunity to view historic Cercospora Daily Infection Values (DIVs) on the North Dakota Agricultural Weather Network (NDAWN) Web site. These historical values indicate the level of risk associated with disease infection based on recent weather conditions.
The Growth Stage CLS DIV model is based on forecasted weather patterns giving an advanced look at probable disease pressures. Using both NDAWN and the Growth Stage DIV models, growers can view historic DIVs along with the map of forecasted DIVs to get a better understanding of when the best time is to apply fungicides.
The DIV model is a calculated measurement of favorable weather conditions for spore germination and subsequent infection. A DIV is derived from a combination of daily hours of wetness. Two-day sums of DIVs above a specified threshold indicate a potential for infection. All model results are for guidance only. Management decisions should be based on additional evidence in the field.
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Chickpea and Lentil Models
In 2003 BASF brought HEADLINE®, a new fungicide for chickpeas and lentils, to the marketplace. To help raise awareness of the product and to provide product application assistance to growers, BASF contracted Growth Stage to generate and send Crop Staging Guides.
The Crop Staging Guides Growth Stage developed are unique in the marketplace, as they are the only commercially used chickpea and lentil phenology models in Western Canada.
Development of the models began in 2001, with initial research conducted internally by Growth Stage, to determine the current stage of phenology models for these two crops. The following year, extensive in-field research was undertaken to verify the validity of the models for the Western Canadian marketplace.
In 2003 the models were published in Crop Staging Guides promoting HEADLINE fungicide. In the first year of commercial use, 81% of survey respondents indicated that the lentil and chickpea models were accurate for their location and current conditions. Every year the models are scrutinized to ensure that they are accurately tracking for the current season.
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