Heat Unit Accumulation
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 farmers 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 20 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 formula is used by plugging in long term average daily temperatures, where it is not unusual to use data from the past 30 years. Planting plans can be accurately developed and as the crop develops the actual heat units are used to increase the accuracy of the forecast.
Different stages in a crop can be monitored to increase the accuracy of the forecast,