Using performance data to inform Agronomic Management decisions
In 2009, STRI Group pioneered the use of data collection on golf courses as a turf management tool. Since then, around 25,000 golf greens were analysed for a series of performance factors.
These factors included: surface smoothness, surface trueness, green speed, moisture and firmness. In addition to surface performance testing, the soil was also analysed to measure: organic matter at 4 x 20mm depths, pH, available phosphate (P2O5) and potash (K2O).
Whilst on site, agronomic factors were also assessed, including: botanical species content, sward density, soil profile condition and plant health. The combined use of these agronomic factors and the supporting data helps to provide clubs with strategic and sustainable outcomes for their greens.
The large dataset allowed us to interpret data relationships that influence green performance and health. Whilst this information helps to provide pathways to make our golf greens perform better, the data alone may not give a full picture of the reasons behind a golf green performance. That said, the combined use of the data and the agronomic factors is paramount to the success of providing advice to achieve a club's goals and objectives. The performance data informs the agronomic decisions.
This article aims to show some of the data relationships and how they can help to make management of golf greens more sustainable by using the trends that the data provides.
A number of target-based inter-relational trends became apparent. For example, by visually noting ball interactions on a surface, we can conclude that a green on a links course would provide bounce-check release and roll out at firmness levels of 100 gravities or greater - using a clegg impact hammer. This would also typically occur if the soil profiles were managed consistently at moisture levels below 25% VWCs (Volumetric Water Content).
The trends observed in the data sets over time are also important as these will show how a green is changing. For example, moisture content being taken at different times of year, with different weather conditions would show quite a degree of variability depending on whether it was collected on a very dry or wet period. The degree of variability tracked over time can inform if a green was becoming wetter or drier as a result of similar conditions.
Performance Data
Much of the performance data collected provides a snapshot of the conditions and immediate management prior to the data collection. These included smoothness, trueness and green speed. Typically, clubs would set up the green in a similar manner for each data set, but the information provided by this data needs to be carefully assessed in order to assist the agronomic decisions regarding the next few weeks/months of maintenance. Moisture and firmness are less impacted by the immediate maintenance operations, but reflect the weather conditions around the assessment.
Soil testing is useful in reviewing long-term trends because it is less impacted by short-term management. Organic matter, particularly, is useful as it will clearly show how the soil profile is becoming drier through best practice, and therefore more able to support fine turf grasses within the sward. The level of organic matter reflects the weather conditions and management a season earlier and affects, most significantly, firmness and moisture of greens. Greens with low organic matter will vary less in moisture content than a green with a high organic matter.
Graph 1
Organic sampling accuracy is vulnerable to sampling techniques, and so small-scale changes within organic matter should be viewed with caution. It is much better to concentrate on managing the longer-term trends.
Green Performance Relationships
It has long been known that some of the relationships of data collection are inter-related for a number of the performance measures. For example, moisture and firmness (Graph 1) typically shows a straight-line relationship - i.e., the wetter a green, the softer it will be.
It is interesting to observe how the predominant grass species mixture on a green also has an influence. It is clear that meadow-grass dominated species typically will be wetter and therefore softer than a fescue-dominated green.
Graph 2
Green speed and smoothness are very closely related (Graph 2). The Trueness Meter was used to assess smoothness and trueness and provides a clear and accurate measurement of surface performance. A surface that is not smooth would typically be slower. However, speed is also impacted by surface moisture, to some extent the firmness, the height of cut and definitely by the species content. Density can also impact green speed, as the greater number of leaf blades will increase the stickiness or friction of a surface. We would typically look at all of these parameters to see if a low green speed was solely as a result of poor smoothness - or was due to the other factors.
Trueness is interesting in that it does not appear to have a significant impact on the green speed, but it is a particularly important parameter within the ball roll characteristic that would indicate a good ball roll. Trueness gives a measure of the consistency of the ball roll along a desired path, and it should be noted that the higher the green speed the truer a surface is required to be in order to create a playable and consistent surface.
Graph 3
Probably the most important parameter is that of the organic matter (Graph 3). Our data helped to indicate the ideal organic matter in the upper 20mm to achieve appropriate moisture and firmness and hence green performance. Organic matter has the greatest potential influence on many of the other factors, including soil moisture, firmness, potentially green speed and definitely plant health. Organic matter levels predominately are too high and especially in the parkland setting (Graph 4). The trend was broadly downwards in the period from 2009 to 2020, but in the Covid period, when greens maintenance was relaxed, organic matter increased slightly. Research revealed that the ideal level of organic matter was 4-6% in the top 20mm, and then below 4%, below this depth. At these levels, the greens would achieve ideal firmness, moisture content and potentially ideal ball roll characteristics.
Firmness is especially important and is useful as a measure of how a golf ball will interact with a green surface. Firmness is measured using a Clegg Impact Hammer with a rounded golf ball shaped head which measures peak deceleration. We tend to relate the data into two categories, firstly parkland courses which will be typically below 100 gravities, i.e. would be softer, and links which will typically be over 100 gravities. Firmness also gives a clear idea of ball-to-surface interactions and green receptiveness.
Graph 4
Data Influencing Plant Health
The data we collect has some influence on plant health. For example soil pH, if extremely low, it can lead to a locking up of key elements such as Phosphate (P) and Potash (K), but it can also reduce the breakdown of organic matter by soil micro-organisms. The pH therefore is monitored over time to see whether there are risk factors that need addressing, and therefore the agronomic advice would then be adapted to improving those conditions.
Moisture management can be used in prediction or at least management of plant disease. In the UK, the autumn Fusarium Patch (Microdochium nivale) outbreaks tend to occur in the cool conditions where soil moisture is relatively high but also leaf wetness hours are high. Therefore, data can be used to assist in predicting when these outbreaks may occur.
A poor smoothness reading may be related on a softer surface to a high level of a disruption through footprints and pitch marks. If severe and poorly repaired will act as a stress, particularly in meadow grasses and may, if conditions are right, increase disease outbreak.
Using Data to Manage Future Sustainable Surfaces
It is widely understood that the ideal grass species for long-term sustainability would be the fine turf grasses of bentgrasses or fescues. The botanical composition able to be achieved would depend on a number of factors, predominantly that of: dryness and drainage of soils, environmental conditions, green size, tree management and the number of rounds that are currently being played.
In order to develop a fine turf surface, one of the most critical elements would be to ensure the organic matter is as low as possible and certainly within target ranges. We are now seeing a number of clubs, that are reaching the targets, are starting to see increases in the botanical composition of fine turf grasses. Management of these areas would then follow principles such as those discussed many years ago in the 'Disturbance Theory', where the particular chosen fine turf grass would then be managed following the basic principles of theory, reducing disturbance, utilising stress and increasing the chosen grass.
The management of environmental conditions, i.e. reducing shade, creating airflow across green surfaces is key to improving those surfaces in terms of fine turf grasses. There is definite circumstantial evidence from our data over time that fine turf grasses have increased particularly where soil moisture, soil firmness, organic matter levels have reached target points. This could be as a direct consequence of improved environmental conditions around a golf green or tee or following a path to improve profile and appropriate management strategies for the chosen grass type.
