Many golf courses in Japan track the volume of clippings mown off putting greens using this simple technique. A plastic bucket is brought along on the mowing runs, the clippings are placed in the bucket, the bucket is shaken to allow the clippings to settle, and the volume of the clippings is recorded.

This information can be useful to check, track, and improve the management of putting greens, For example, the data can be used to:

ensure that all mowers are set up the same way

measure the effect of fertilizer applications

measure the influence of growth regulators

evaluate the effect of weather and maintenance practices on growth

track clipping yield for special events

Andrew McDaniel is the golf course superintendent at Keya GC in Fukuoka, where the Japan Golf Tour Organization (JGTO) holds the KBC Augusta tournament. Leading up to the tournament, the clipping volume of the korai (Zoysia matrella) greens was generally more than 20 L per day per green with a single cut. Today, on the Wednesday of tournament week, a double cut of the greens is collecting about 5 L of clippings per green. The progression to the tournament target clipping volume has been monitored carefully.

He also used brushes on the mowers in the lead up to the tournament. When two mowers were used on the same green, each mowing the green once, the mower with the brush collected about twice as many clippings as the mower without the brush.

For an even more detailed look at clipping production over time, and different ways I've seen it measured, see my report on clipping yield from putting greens.

I've written about the seductive attractions of metric units and how facility with those units can make turfgrass management easier. I want to explain this a bit more, especially as it is related to fertilizer and to water, first discussing 2 dimensional surfaces.

Last week in Macao (presentation slides and handouts here) this very subject came up. I was discussing turfgrass fertilizer, which is really simple, largely because turf surfaces can be simplified to a 2 dimensional area, square meters (m^{2}) or square feet (ft^{2}) or whatever.

But with landscapes, as we saw at the interior gardens (above) and outdoor gardens and golf course (below) at the Venetian Macao, it is very much an irregular and inconsistent 3 dimensional space.

These landscapes are impressive, but they resist simplification. When applying fertilizer, for example, should we apply it on a per plant basis? Or on a size of plant basis? Or on a gound area basis? Plus there are so many different species, each, presumably, with some different nutrient requirements.

With turfgrass surfaces, we don't really have to consider those complications. Compared to landscape plants, turfgrass surfaces are simple. No matter where we are in the world, and no matter what grass type is being grown, we can express a number of important metrics in 2 dimensional terms.

I like to use one square meter (1 m^{2}) as the base unit in 2 dimensional space. That is, I take a turf surface, such as the zoysia putting green pictured below, and consider it in terms of length (1 dimension) and width (1 dimension). Combining the length and width, we have 2 dimensions, and can consider the flat surface with those dimensions.

This goes for any turfgrass surface. Golf course putting greens, lawns, football fields – we often ignore the rootzone, and ignore the volume of the aboveground plant parts, and simply consider the flat 2 dimensional area.

We then express inputs to the turfgrass surface in terms of mass or volume as applied to a 2 dimensional space. For example, the annual nitrogen amount supplied to a turfgrass area might be 10 g N m^{-2}, which is equivalent to 2 lbs N 1000 ft^{-2}. We would be thinking of how much mass of something is applied per area. Turf is irrelevant here, because we could apply a mass of something to a certain area of parking lot, or of lawn, or of bare soil. It is just mass per area.

That's easy, and we use those units all the time. Irrigation can be thought of in the same way. I often think of water in these terms. The consumptive water use of the grass is the evapotranspiration. In general one needs to supply something similar to the consumptive water use in order to keep grass actively growing. Water use (evapotranspiration) is expressed as a depth (1 dimension), just as precipitation is expressed as a depth (mm). We now have 3 dimensions, because we have a depth applied to an area, but with the metric system this is pretty easy to convert back to a mass or volume per area. No calculator required.

Let's say we have ET of 4 mm, and we want to supply that as irrigation. 4 mm equals 4 L spread across 1 m^{2}, so for a 500 m^{2} area, we would need 2000 L of water.

For topdressing sand, we could do the same type of expression. Topdressing sand may be applied at 100 g m^{-2}. For a 500 m^{2} area, that would require 50 kg of sand.

Fertilizer, water, sand – applied as a mass or volume to a 2 dimensional area – this isn't anything new.

But there is more to it than this, for the turf in reality is growing in a 3 dimensional space. Being able to convert the amount applied at the surface into units that express changes in the 3 dimensional space of the rootzone is quite useful. Being able to relate changes in the rootzone to simple units of how things are usually applied at the surface is also quite useful. Coming up, I'll write about turf in 3 dimensions, and explain how I go about making some of these conversions on the fly, and why I find the metric system so useful in this regard.

The temperature-based turfgrass growth potential (GP) was developed by Wendy Gelernter and Larry Stowell at PACE Turf. Based on only one variable – the actual temperature – one can use the GP equation (below) to produce a number between 0 and 1.

\[GP = e^{-0.5(\frac{t-t_o}{var})^2}\]

where,

GP is growth potential, a value from 0 to 1 e is the base of the natural logarithm, approximately 2.71828 t is the actual mean temperature t_{o} is the optimum temperature, usually set at 20°C for C_{3} grass, 31°C for C_{4} grass var is the variance which adjusts the shape of the curve, 5.5 for C_{3} species and 7 for C_{4} species when using °C.

If the GP is close to 1, then we can think of the growth potential as being high, because the actual temperature is close to the optimum temperature for growth. If the GP is closer to 0, then we can think of the growth potential as being low, because the actual temperature will be much colder or much hotter than the optimum temperature.

Temperature is not the only thing that influences turfgrass growth, however. The four main factors that influence growth are temperature, photosynthetically available light, plant water status, and leaf nitrogen content. For more about this, especially as it relates to the growth of warm-season (C_{4}) grass, see A New Way of Looking at the Weather.

Turfgrass managers are able to modify the plant water status and the leaf nitrogen content, so the two independent and uncontrollable growth factors are temperature and light. The GP equation only accounts for temperature. Would it be improved if a correction for daylength, or shade, or light were included?

I default to a rather extended answer, because there is not a clear answer to this, but it is something I have considered, and my preference at this time is to ignore light and day length when it comes to GP values. Here's why.

1. The GP is not reality. It is only a number that serves as an index of the potential to grow based on temperature. This analysis of clipping yield at various levels of GP shows that there is a general relationship between GP and yield, but not an exact one.

Clipping yield from korai putting greens on a golf course in Japan from mid 2013 to early 2014

2. The GP equation is simple. Providing a numerical value of potential to grow, based only on temperature, can be practically useful in many ways, even though this number is not an exact description of how the grass will actually grow. Because the GP as it is does not predict growth exactly, and is simply an index of potential to grow, I think adding on layers of additional data for day length and/or photosynthetically available light risk complicating this by assigning too much value to the GP number, even though the growth may not exactly match the GP.

3. When I work with GP, my preference is to keep it as simple as possible, as long as the GP values for a particular site match the reality of observed turfgrass growth. GP is only useful when it somewhat approximates reality, so if day length adjustments, or adjustments for photosynthetic radiation, make the GP a more accurate representation of reality at a particular site, then I would look on such adjustments as a good thing.

In response to questions about possible increased fertilizer requirements at high latitudes due to increased day lengths, I have made some comparisons, and I haven't seen that extended day lengths will necessarily correspond with more light energy for growth.

4. If we look, for example, at Malaga and London specifically, along with some other cities from the northern hemisphere, the estimated daily light integral plotted against day length on 15 June looks like this.

That is, even though the day is longer at London in mid-June, because it is at a higher latitude than Malaga, there is still a greater amount of photosynthetic light at Malaga than at London. Why might this be? It is related to the amount of extraterrestrial radiation at any given latitude, combined with the effect of clouds. On an average June day in London, there will be 6.8 hours of bright sunshine (defined as light > 120 W/m^{2}) on a day with 16.3 hours. At Malaga, even though June 15 has a shorter day length than London, with only 14.5 hours, 10.5 of those hours on an average day will be bright sunshine.

With warm-season (C_{4}) grasses we can make the assumption that the grass can use all of the DLI. With cool-season (C_{3}) grasses, that won't be the case when the light is at its greatest intensity.

I have tried to estimate this by taking a maximum value of 1000 micromoles of light per m^{2} per second, for each second of day length, and expressing the estimated DLI as a fraction of that. This chart shows that at Malaga, the amount of light supplied on an average day on 15 June is equal to the maximum amount we expect C_{3} grass to use. At London, even though the day is longer, it appears that on an average day there is less light supplied than the grass can use.

Based on these calculations for June, I don't see a reason to adjust the expected nitrogen use of turf at London to be higher based on day length.

I also looked at this for December, in this chart for estimated DLI on 15 December and this chart for the fraction of usable light that is supplied on average.

In this case, there are again differences in DLI and day length. At Malaga, where there had been nearly 100% of the light that C_{3} grass could potentially use on 15 June, the amount of light supplied on a typical 15 December day is only 50% of that the grass could use.

But for many of these cities, on 15 December, the amount of photosynthetic light is irrelevant, because the temperature is so cold that the grass can't grow. At Milan, for example, the average temperature in mid-December is less than 5°C. When working through these calculations, the temperature will often be the controlling factor.

5. Light does influence the growth, and consequently the nutrient use of grass. In my analyses of this, it seems that temperature plays the controlling role, with light as a secondary factor. I think that this can be accounted for using the GP equation as is, on a site by site basis. For example, at Malaga or Milan or London, one can use the GP to estimate nitrogen requirement as explained in this document.

One only needs to estimate the maximum amount of N that one will use at that location, in the time (day, week, or month) when N use will be at a maximum. The GP can then be used to adjust the N rate over the course of the year. The key is to choose an appropriate maximum N amount for the location, grass species, and soil type. Any light correction can be embedded in the amount of N one chooses as the maximum. My preference is to utilize GP in this way – it is remarkably simple, and provides a good starting template for nutrient requirements.

6. If adjusting by day length or other adjustment to account for light works better at a particular location, then by all means make the adjustment. The objective of the growth potential is to estimate how the grass will actually have the potential to grow at a location. From all the calculations and observations I've made, I'm not convinced that day length or light adjustments improve upon the estimates we can get from temperature alone. Of course, my experience is mostly at latitudes less than 45°, so there may be something I miss at higher latitudes.

Some years ago, on a fine December day, I was at this beautiful golf course in southwestern China. The tees, fairways, and greens are creeping bentgrass. From the tee, I had the view above. But when I got to the fairway, I was surprised to look down and see this pattern.

In fact, there were a lot of cup cutter plugs, lined up one by one, on this fairway.

The mystery is this: why are there cup cutter marks in the fairway?

The correct answer was given in quick succession by @GreatManDan and then soon after by @gossturf.

What I found especially interesting was just how many plugs it took to make this repair. The diagonal across the fairway was about 175 yards in length. With each plug 4.25 inches in diameter, that would require 1482 individual plugs to make the repair.

I really enjoyed today's meeting of the South China Turf Managers Association (SCTMA) in Macau. There is more to share later, but for now, here are the handouts and slides for the two topics I discussed this afternoon.

The second presentation was about nutrient requirements. I explained how the MLSN guidelines can be used as a simple decision making tool.

There are two questions that every turfgrass manager will have when it comes to fertilizer. First, is an element required as fertilizer, or not? Second, if that element is required, how much should be applied? The MLSN guidelines answer both of those questions, for any grass, anywhere. The presentation and associated handout explain how to do this.

After the seminars, we took a tour of the very impressive facilities at The Venetian, then had dinner and lots of turf talk with friends at a poolside reception.

I was excited to read the press release from AGIF and GCSAA last week announcing that Beth Guertal will be teaching in September at events in the Philippines and Vietnam. I've always enjoyed studying the research she does, and these seminars are a great opportunity for learning from one of the world's experts on turfgrass management.

I'm not sure that she will be talking about these particular experiments, but these are three of my favorites (of the many) from her research group.

Potassium Movement and Uptake as Affected by Potassium Source and Placement. "Over the 2 year study potassium application had no beneficial effects on turfgrass performance, and acceptable performance was achieved across a wide gradient of K content in soil and leaf tissue. Regardless of soil test K level, no deficiency symptoms were observed."

Late spring in the Yangtze River Delta. A time of glorious weather before the sultry summer. Tea in classical gardens. Flowering trees have bloomed, and are now in full leaf. On the golf course, grasses are growing a little more rapidly day by day.

That sets the scene for this mystery. A bermudagrass tee, in late spring, in the Yangtze River Delta of East China. In the previous 2 weeks, the lowest temperature was 10°C, and the highest was 31°C.

On the tee, a strip of green. Here is a look from another angle.

A closer look at the turf in the green stripe is here.

And this is what the turf looked like outside of the green stripe.

The mystery is this: what caused the green stripe on this tee?

Congratulations to Jason Goss who got this one exactly correct:

@asianturfgrass they have a skip when they sprayed for transition back to warm season turf?

I think the key for this was recognizing the season and climate. With that type of climate, it is common to overseed bermudagrass tees. But one wants to ensure the bermudagrass can grow with no competition from perennial ryegrass for more than 100 days in the summer. That is necessary to keep healthy bermudagrass. Thus, on this high traffic tee, Monument herbicide (trifloxysulfuron) was used to remove the ryegrass, which will allow the bermudagrass to grow with no competition through late spring and all through the summer.

Mark Hunt's Weatherblog had an interesting statement this week – "why I think the Growth Potential [Optimum] Temperature is wrong for Poa annua." Regarding recent temperatures in Southeast England, he wrote:

For me I think Poa has been under stress for the last two weeks and so the GP model should be showing this with a lowered daily figure, but it’s not and therefore I think the optimum temperature is set too high at 20ºC, it should be more like 18ºC, so that’s what I’m going to change to in 2015.

I think this is a good idea. The objective of the growth potential (GP) model is to generate a number between 0 and 1 that can be an index of potential to grow, or high temperature stress, or low temperature dormancy, and this can be adjusted to fit the conditions and grass species at a particular site.

Jason Haines wrote about his adjustment of the GP to 18ºC for Poa annua greens in Canada. When I was in Iceland last year, I wrote that the 20ºC optimum temperature in the standard GP equation would likely need to be adjusted to fit the observed growth under Icelandic conditions. One of the great things about the GP equation is the ease with which one can adjust it.

Growth potential (GP) curves shift left or right if one changes the optimum temperature in the growth potential equation

Now I don't advise changing this too much if you don't have to. The standard optimum temperatures of 20ºC for cool-season (C_{3}) grass and 31ºC for warm-season (C_{4}) grass work well for most turfgrass species. And it is the simplicity and consistency of the GP concept that makes it so useful.

With C_{3} grasses, I would consider adjusting the optimum temperature down if looking at Poa annua (as Mark wrote) or fine fescue (pictured above in Iceland). With C_{4} grasses, the only one I would adjust is kikuyugrass (Pennisetum clandestinum), which will have an optimum temperature somewhere in the mid-20s. Kikuyugrass thrives in temperatures warmer than optimum for C_{3} grass, but at much cooler temperatures than optimum for other C_{4} grasses.

For example, kikuyugrass is the dominant grass in the mild climate of Kodaikanal (above) in the Palani Hills of Tamil Nadu, just as it is at Real Club de Golf de Las Palmas (below). One would need to adjust the optimum temperature in the growth potential equation for this species in particular.

The first year anniversary of the Global Soil Survey is coming up, and I've been doing a lot of work to analyze the data that has been collected so far. We have received samples from a wide range of soil and grass types. It is interesting to see how the data from these diverse turfgrass growing environments are distributed, and to apply the same analytical procedures that were used to develop the MLSN guidelines to these new data.

Over the next few months, I'll be working with Larry and Wendy from PACE Turf on an annual report with the first year results of the Global Soil Survey (GSS), an update to the MLSN guidelines, a presentation on these results at the 2014 Crop Science Society of America annual meeting, and a technical article about the MLSN guidelines and the supporting GSS.

Empirical cumulative distribution function for soil test phosphorus data from the ATC, Global Soil Survey, PACE Turf, and combined data sets

The process to develop these guidelines can seem a bit complicated, and I was pleased to see a recent article in Golf Course Industry with a simple explanation of the GSS. In the article, Larry Stowell was quoted with a great explanation of this project:

It’s really a common sense approach. We are just trying to develop some tools to make it easier for turfgrass managers to make the applications at the right rates they need to make.

This project is possible because of the many turfgrass managers, golf course superintendents, and golf clubs that have participated in this project by purchasing a kit and submitting data from soils that support good performing turf at their location. I was pleased to see that the article gave a chance for two superintendents who have participated in the survey to speak about this important topic. Here are a few quotes.

Matt Crowther, CGCS from Mink Meadows Golf Club, on fertilizer and one of the reasons he participated in the GSS:

If you’re not being regulated on [nutrients] right now, then you will be soon. It’s sweeping the country. I don’t see how there will be one section that gets away from it. To me, it only seems logical to show an interest in that and try to get ahead of the curve.

Akoni Ganir, from Tokatee Golf Club, on his participation in GSS and philosophy of product application in general:

It’s a very logical approach and aligns with the way I think. I feel like I’m not applying anything to the grass that’s unnecessary. I feel as a turf manager there is a purpose to all of my applications. I’m not putting ‘X’ or ‘Y’ product out there because someone said, ‘Try this because this is great.’ I know why I am putting everything down and for what reason.

This is an ongoing project, and the data collected will benefit everyone in the industry by identifying the nutrient levels that are required for good turf performance. The more sites we collect data from, the more useful the guidelines will be. If you would like to participate, and ensure that data from your growing environment is included in this exciting citizen science project, you can get your survey kit here.

I've had a chance to visit some of the courses that have joined this project, including beautiful Tama Hills GC in Japan (picture of the unique two green system, below). It is really cool to be able to make use of the data that are stored in the soils of every golf course or other turfgrass soil, to combine those data, summarize them, and from those data at actual sites with good-performing turf, to be able to generate guidelines and fertilizer recommendations that can be used by the entire industry. This is really an exciting project, many thanks are due to everyone who has participated so far, and I hope you will join this project so that data from your site can be represented as well.

Manilagrass and creeping bentgrass at Tama Hills GC near Tokyo