Using growing degree days (GDD) to plan early season alfalfa harvests
As spring approaches, alfalfa growers need to keep a plan in mind for optimizing the nutritive value and yield of the first harvest. Now is a good time to review different strategies for in-field prediction of alfalfa nutritive value, and when and how they should be used. Some crop growth predictions are based on environmental information, whereas others are based on direct measurements of the crop in the field. Tracking the accumulation of growing degree days (GDD) is a common approach to estimate the growth and maturity of a crop in the field based on actual temperature conditions rather than calendar days.
Calculating growing degree days (GDD)
Growing degree days are calculated by subtracting a base temperature from the average of daily high (Tmax) and low (Tmin) temperatures as shown to the right. The resulting value is an indicator of how high temperatures were relative to the minimum required temperature for plant growth to occur. This base temperature for alfalfa is 41°F. Therefore, cumulative GDD (the addition of all GDD to date) are an indicator of how much warm weather has accumulated throughout the growing season up to a given point.
In situations where heat is the only limiting factor (ample water and nutrients, no pest pressure, etc.), GDD accumulation is an excellent predictor of crop growth. Consequently, the early growing season leading up to the first harvest (when moisture is not usually limited), is the time of year when GDD estimations are most accurate for alfalfa nutritive value.
Later in the season, estimations of nutritive value should be based on physical measurements of maturity, height, or a combination using the PEAQ system (Predictive Equations for Alfalfa Quality). Descriptions of growth staging methods can be found in the article, In-field assessment of alfalfa quality and information on PEAQ can be found in Estimating alfalfa RFV using PEAQ (University of Wisconsin Extension).
Planning the first cut
Figure 1. Alfalfa neutral detergent fiber (NDF) concentration relative to cumulative growing degree days (Noland et al. 2017).
In the upper Midwest, general recommendations are to plan the first cut near the accumulation of 700-750 GDD (Lee et al. 2010). This is intended to achieve an NDF concentration near 35 percent at harvest, resulting in NDF concentrations near 40 percent (RFV ∼150) when used as feed or sold as hay.
This recommendation is consistent with observed values in an alfalfa trial at Rosemount, MN in 2015 (Figure 1); however, the best approach is to identify the target specific to your production goals and your region. If records are available to compare alfalfa harvest dates and corresponding nutritive value from previous years, online tools such as the Midwest Climate Center tool, cli-MATE, can enable calculation of cumulative GDD values from specific days in previous years. Remember to adjust the base temperature value to 41°F.
When looking back at the number of cumulative GDD at the time of harvest, consider whether desired forage quality was obtained. Understanding the relationship between environmental conditions and forage quality highlights the importance of maintaining farm records that include harvest date, forage nutritive value (NDF, ADF, CP), and yield. These comparisons will indicate whether you harvested too early, too late, or met your goal, and will inform future harvests based on cumulative GDD.
Figure 2. Average accumulation of alfalfa growing degree days (GDD) at Rosemount, MN from 2014-2016 (Noland et al. 2017).
In planning ahead, GDD estimations are available to forecast the date of a given cumulative GDD value. Recent averages from Rosemount, MN indicate GDD accumulation to reach 700 around May 25th (Figure 2). However, with climatic fluctuations each year and different goals among producers, it is important to keep a close eye on current and forecasted conditions in your specific area.
As this information is used, remember that GDD-based estimations of forage nutritive value are most consistent for the first harvest. Later in the season, when other environmental factors become more limiting, direct measurements (growth staging) or destructive sampling (lab analysis) may be required to obtain accurate predictions of nutritive value. Even though these methods can provide useful information, they are labor intensive, time consuming, and seldom adequate for field-scale assessments. Ongoing research at the University of Minnesota is investigating the value of remote sensing technologies to inform predictions of alfalfa nutritive value. These tools have potential to provide timely information at the field scale.
Lee, K., M. Allen, R. Leep. 2010. Predicting optimum time of alfalfa harvest. Michigan State University. http://articles.extension.org/pages/25471/predicting-optimum-time-of-alfalfa-harvest
Martens, D. 2011.Central MN Alfalfa Harvest Alert May 26 Update. University of Minnesota Extension. http://blog-crop-news.extension.umn.edu/2011/05/central-mn-alfalfa-harvest-alert-may-26.html
Noland, R.L., C.C. Sheaffer, and M.S. Wells. 2015. In-field assessment of alfalfa quality: Current tools and future directions. University of Minnesota Extension. http://www.extension.umn.edu/agriculture/forages/utilization/in-field-alfalfa-quality-assessment/
Noland, R.L., M.S. Wells, C.C. Sheaffer. 2017. Integrating canopy reflectance with environmental factors for in-situ estimations of alfalfa nutritive value. Field Crop Res. (in preparation)
Schroeder, J.W. 2010. Timing is important when harvesting alfalfa as feed for dairy cows. North Dakota State University Extension. https://www.ag.ndsu.edu/news/newsreleases/2010/may-17-2010/harvest-alfalfa-at-right-time/
Sulc, R.M, K.A. Albrecht, V.N. Owens, J.H. Cherney. 2014. Update on predicting harvest time for alfalfa. http://fyi.uwex.edu/forage/files/2014/01/alfqualest.pdf