As farm businesses continue to expand, crop forecasting becomes increasingly more important in managing the investment made in each crop. The Growing Degree Days (GDD) model is a means of predicting growth of any crop as it develops. The estimates are based on average daily air temperature accumulating to a predefined total GDD. Although it appears to be tricky at first, it is simply based on the fact that temperature directly affects how fast a plant grows. i.e, Where the temperature is cooler than normal, the plant development is slowed.
This model can be used to any growers’ advantage as a planning and forecasting tool, by accurately forecasting harvest dates within a 5 day window. As a crop matures, the accuracy of the model improves by adjusting the forecast using actual temperatures experienced. By having this greater understanding of crop movement, it allows for increased efficiency in crop management.
To best understand this model, we first need to understand the formula used:
GDD = (Tmax + Tmin)/2 – Tbase
Where Tmax is the maximum temperature and Tmin is the minimum temperature on the same day. Tbase is the minimum temperature required for a plant to develop. We can use sweet corn as an example, where one particular sweet corn variety requires 1280 total heat units accumulated from planting to harvest, with base constant of 10°C.
For example: On 20th January 2012 the temperatures were as follows were, Tmax 28°C and Tmin 14°C.
Therefore crop heat units for that day were, (28 + 14)/2 -10 = 11.
This formula is repeated daily, accumulating each days result towards the total requirement of 1280 crop heat unit (CHU).
To use this model as a prediction and forecasting tool, the long term average daily temperatures, for example the data from the past 30 years, are entered into the formula. Planting plans can be accurately developed and as the crop matures the actual heat units are used to increase the accuracy of predicting when the crop would be ready for harvest.
Different stages in a crop can be monitored to increase the accuracy of the forecast, for example with the sweet corn, we can use crop stages such as emergence and silking as prediction markers to further increase accuracy. From silking we know that we require xxx CHU from silking to harvest, with an accuracy of within a 3 day window.
This model can be used across a wide range of other management applications, some being: to understand the suitability of a particular crop to region and the seasons; estimate the growth-stages of crops; predict best timing of fertilizer or pesticide application; estimate the heat stress on crops; plan scheduling of planting dates to produce separate harvest dates.
With the use of the right computer program much of the calculation is done automatically. Information produced in these computer programs ranges from planting requirements to meet market demands, through to yield adjustments flowing through to estimating daily harvest volumes.
On understanding the application of this GDD model, the dynamics of farm management begin to change. The information produced becomes more efficiently available between farm owner and farm manager or any other internal business members.
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