MLSN Cheat Sheet
Deﬁnition
MLSN is an initialism for minimum levels for sustainable nutrition. Thisis a method for soil test interpretation and fertilizer recommendations.

MLSN really quick start
If you have Mehlich 3 soil test data, you can directly compare your test
results (in ppm) to the MLSN guideline levels. If your soil is above theguideline, then you don’t need to add that element – today. You can be
conﬁdent that high quality turfgrass can be produced in soils with thatquantity of the element. If your soil is below the guideline, you canhave high quality turfgrass too. But you should be aware that there arefew soils producing high quality turfgrass with nutrient levels that low.
You’ll probably want to add enough of the element to raise it above theMLSN guideline.
That’s only the situation for today. Is your grass alive? We hope so! If it
is, then it is using nutrients. The nutrient content in the soil is going tobe lower tomorrow than it was today – unless your grass is dead ordormant – because the grass uses nutrients. To really use the MLSN
guidelines, you need to look not at today, but into the future. This cheat
sheet is meant to provide all the explanations and calculations you’llrequire.

MLSN quick start
These are the steps to take to get started using MLSN – in the standard
way – immediately. If you don’t know how to get these quantities, don’tworry. The other sections of this cheat sheet show how to ﬁnd thesequantities, and how to make more modiﬁcations to ﬁt your site.
1. Soil test Take soil samples to a depth of 10 cm. Then use theMehlich 3 extractant to ﬁnd soil test K, P, Ca, Mg, and S. Look at
the results in parts per million (ppm). Express the results asmass per area. Call this quantity c.
2. Estimate grass use Find grass use of those elements over a time
duration (t). Express those use estimates as mass per area. Callthis quantity a.
3. Check the MLSN guideline Express the value for each element as
mass per area. Call this quantity b. The MLSN minimum levels foreach element are given in this table.
ElementppmKPCaMgS3721331
47
6

4. Calculate fertilizer requirement The fertilizer amount to apply overtime t is a + b − c.
5. Repeat for each element This process gives a fertilizer requirement
for time t for K, P, Ca, Mg, and S.

Estimating grass use

The soil test amountThe value a is the expected grass use for time t. Here are three ways toget that value.

The soil test amount c is the amount from a Mehlich 3 soil test. Notethat conversion of soil test results from concentration units (ppm) tomass of nutrients per area, depends on the rootzone depth and on thesoil’s bulk density. You can either customize this for your location, oruse the standard conversions.

Estimate from growth One can collect the clippings, express them as amass, and calculate the quantity of nutrients in that mass ofclippings. Clipping volume is a rapid way to estimate the mass.
For every 1 L of clippings m-2 , expect a dry mass of 63 g. Then,calculate nutrient content by considering the elements inhealthy turf. I typically use these numbers.
ElementNKPCaMg
S% in dry leaves
Agrostis & Poa

Cynodon

PaspalumFestuca

42
0.5
0.5
0.2
0.2

32
0.5
0.5
0.2
0.2

3
3
0.5
0.5
0.2
0.2

3
1.5
0.5
0.5
0.2
0.2

If you know that your turf contains different concentrations ofnutrients than shown in this table, please make the adjustments
to ﬁt your site.
Estimate based on N supply The grass cannot grow more than the N
supply. Dividing the N supply by the percentage N in the leaves
gives the maximum clipping yield. One can then work out themaximum use of all the elements. For example, Cynodon
supplied with 15 g N m-2 has a maximum clipping yield of
15= 500 g. To account for N mineralization, I make an
0.03
estimate based on soil organic matter being 5% N and 2.5% ofthat N mineralized in one year (Havlin et al., 1998, p. 109).
Predict based on GP If one doesn’t know clippings or N supply, thetemperature-based growth potential (GP) provides a
straightforward way to get an estimate of N use, andconsequently, of maximum possibly growth. One sets amaximum N rate for any duration (d) of the year, calculates GPfor time intervals of length d, and multiplying maximum N by GP
gives the expected N use (Woods, 2013).

The MLSN guidelines
The MLSN guidelines are given in units of ppm. This is mg of element
per kg of soil. In the calculation of a fertilizer requirement, I express theMLSN guideline amount as b. This amount is added to the amount thegrass uses. This ensures that 100% of grass use, plus the MLSN
minimum amount in the soil, are present in any fertilizer
recommendation.

Converting from ppm to g m-2 , and vice versa
1 m2 to a depth of 10 cm has a mass of 150 kg when the bulk density is1.5 g cm-3 . 1 g (1000 mg) distributed through 150 kg is thus 1000= 6.7150
mg kg-1 . One can ﬁnd the conversion factor for any rootzone depth andany bulk density using this same process.
The conversion factor for 1 kg ha-1 to a 10 cm depth, when the bulk
density is 1.5 g cm-3 , is 0.67. 1 kg is 106 mg. 1 ha with a bulk density of 1.5
and a depth of 10 cm has a mass of 1,500,000 kg. Thus, 1,000,000= 0.67.
1,500,000

Soil tests other than Mehlich 3
We recommend Mehlich 3 soil testing (Mehlich, 1984) when using MLSN.
If you use a different soil testing method, but want to use the MLSN
guidelines, you will have to convert the test results to their expectedvalues in Mehlich 3 – or convert the MLSN guidelines to expected values
in the other extractant. This conversion process introduces an unknown
amount of error into the calculation.
P We’ve calculated an MLSN for the Bray-2 (30 ppm) and Olsen (6 ppm)
extractants. We don’t have information on other extraction
methods for P.
K, Ca, Mg When using 1 N ammonium acetate, or the Morgan
extractant, the approximate MLSN guidelines convert to 30 ppm
for K, 265 ppm for Ca, and 38 ppm for Mg. Alternatively, multiply
the ammonium acetate or Morgan test results by 1.2 and thenuse the unmodiﬁed MLSN guideline.
S No known conversion.

How and why MLSN works
It works by ensuring the grass is supplied with all the nutrients it canuse while keeping a safe amount of each nutrient untouched in the soil
as a reserve. The MLSN calculation identiﬁes the amount of nutrientsthe grass uses at a particular site. It then ensures the grass is either
supplied with 100% of those nutrients from fertilizer, from soil, or froma combination of soil and fertilizer (Woods et al., 2014).
This approach recognizes that grass uses nutrients. Rather than trying
to maintain all the nutrients the grass could ever use, and then some,in a hypothetical optimum soil that doesn’t exist, the MLSN approachmakes a careful estimate of plant use and makes sure the grass issupplied with that much while still keeping a safe amount in reserve,
untouched, in the soil. This approach puts the turfgrass manager incontrol.
“The fundamental principle of successful greenkeeping is
the recognition of the fact that the ﬁnest golﬁng grasses
ﬂourish on poor soil and that more harm is done byover-, rather than underfertilizing” (MacKenzie, 1998).

Why MLSN is needed
Conventional soil test interpretation is based on guidelines that are
higher than required to produce high quality turf. Turner andWaddington (1978) described this problem 40 years ago:
“Unfortunately, turfgrass recommendations appear to bebased on research done with other crops, such asforages, results from turfgrass fertility studies notdesigned to relate to soil testing, and the best judgementof the agronomist making the recommendations.”
Carrow et al. (2001, p. 164) wrote about this problem in their Turfgrass
Soil Fertility book:“In some cases, turfgrasses have been placed in a ‘high’ P
and K requirement category, while pasture grasses werein a ‘low’ category. This decision was based on
economics, not agronomics. The cost of fertilization was
not considered of primary importance for turf.”
The MLSN approach to soil test interpretation is designed to make afertilizer recommendation that is based on supplying the grass all thenutrients that it can use, while ensuring a safe amount remains in thesoil. This solves – or more precisely, avoids – many of the problems of
conventional soil test interpretation.

How MLSN was developed
We studied the nutrient content of thousands of turfgrass soils in whichgood turf was growing at the time the sample was collected. The detailsof this process are described in Woods et al. (2016). After removing
samples with pH < 5.5 and pH > 8.5, and selecting those soils that have
nutrient holding capacities similar to putting green soils, we looked at
the distribution of nutrients in the samples. This is K, as an example.

F−1((p) = αp1−pWhat about micronutrients?

)1/β,p ∈ [0, 1)(2)

The MLSN guideline was selected as the value at which the probabilityof a random variable (X) drawn from this distribution having a valueless than or equal to the MLSN guideline is 0.1. That is, the MLSN
guideline is the value of x where P (X ≤ x) = 0.1, obtained byevaluating the quantile function (Eq. 2) at p = 0.1.
You can work through these, using your soil test values as x in Eq. 1, orchoosing any quantile you want between 0 and 1 as p in Eq. 2. Or let thesustainability index (SI) calculator make the calculation for you:https://asianturfgrass.shinyapps.io/turfsi/.

Frequently asked questions
How do I know the nutrients are available?
You know the nutrients are available because you’ve done a soil test.
That’s what a soil test is – by deﬁnition it produces a nutrient
availability index. If you don’t trust the soil tests, then I suggest
skipping them altogether. Instead, assume the soil can supply nothing,and supply to the grass 100% (or a little more) of its possible use ofeach element. This isn’t the most efﬁcient way to do it, but you won’t
need to worry about availability, and it is guaranteed to supply all thatthe grass can use.

MLSN guideline, target level or minimum level?

All the soils are producing good turf, but the soils contain a wide rangeof K. If the soils with relatively low levels of an element are producing
good turf, then logic tells us that such an amount must be enough toproduce good turf. Having high K in the soil doesn’t make the grass anybetter. It does, however, mean that less K fertilizer is required.
We then used the VGAM package (Yee, 2016) in R (R Core Team, 2017) toidentify the scale (α) and shape (β) parameters for the log-logistic
distribution of each of the elements. These are the parameters of thelog-logistic distributions of the MLSN data.
ElementScale (α)

Shape (β)

KPCaMg
S

73.48
55.07
548.13
83.17
19.37

3.20
2.23
4.85
3.83
2.30

Once α and β are known, one can calculate the cumulative distributionfunction (cdf) for any soil test value. The cdf for a log-logistic
distribution is given by Eq. 1.
xβ
F (x) = β, x ∈ [0, ∞)(1)
α + xβThe quantile function for a log-logistic distribution is given by Eq. 2.

Conventional soil test interpretation may give the impression that there
are target or optimum levels in the soil. The MLSN guideline is aminimum value – minimum is the M in MLSN so we haven’t always
repeated that – that one doesn’t want to drop below. It’s not a level
below which one will have deﬁciency. It’s not a target level that one
ideally will have the soil at. What the MLSN guideline represents is alevel in the soil with enough of that element to produce high quality
turf. There is high quality turf in soils with less of that element too, andthat’s why we are conﬁdent the MLSN guideline is a safe level. But there
aren’t a lot of soils with less, so we suggest keeping the soil fromdropping below the MLSN guideline.

Seriously, the same minimum for every grass, soil, andlocation? No regional customization?
We are conﬁdent that the MLSN guideline is enough to produce highquality turf for every grass, everywhere. MLSN has the ultimate
customization, however, because the grass use of elements is entirely
site speciﬁc. In order to ensure the soil doesn’t drop below the MLSN
guideline, one has to estimate a, the expected plant use over time.
That’s where the customization comes in.

How is this different than conventional soil test
interpretation?
The focus of MLSN is on keeping the soil from dropping below a known
safe level. To do this, one must account for how much the grass usesover time. The MLSN approach explicitly calculates the grass use. The
conventional interpretation (Carrow et al., 2004) is about classifying
based on soil levels.

I don’t worry about them. They are used in tiny amounts by the grass.
The grass uses about 400 times ( 40000) as much N as it does the most100
used micronutrient. The grass probably can get all the micronutrients it
needs from the soil, because it uses such small quantities of them. And
because it uses such small quantities of them, if you are worried about
it, apply micronutrients. It doesn’t cost much and is easy to do.

What about salinity?
Salinity can kill the grass. That’s a major problem. To keep the grassfrom getting killed by high salinity, one needs to leach the salts fromthe soil. I wouldn’t worry much about soil nutrient levels or MLSN if I
have a salinity problem. I would leach the salts, and I would supply
100% or a little more than the grass can use.

Additional resources• MLSN newsletter, www.subscribepage.com/mlsn• PACE Turf MLSN page, & the current guidelines, www.paceturf.
org/journal/minimum_level_for_sustainable_nutrition• Asian Turfgrass Center, www.asianturfgrass.com• MLSN on Facebook, www.facebook.com/mlsnturf• The #MLSN hashtag on Twitter

References
Carrow, R. N., Stowell, L. J., Gelernter, W. D., Davis, S., Duncan, R. R., andSkorulski, J. (2004). Clarifying soil testing: III. SLAN sufﬁciency rangesand recommendations. Golf Course Mgmt., 72(1):194–198.
Carrow, R. N., Waddington, D. V., and Rieke, P. E. (2001). Turfgrass soil
fertility and chemical problems. John Wiley and Sons.
Havlin, J. L., Tisdale, S. L., Nelson, W. L., and Beaton, J. D. (1998). Soil
fertility and fertilizers: an introduction to nutrient management (6thEd.). Prentice Hall, 6th edition.
MacKenzie, A. (1998). The Spirit of St. Andrews. Three Rivers Press.
Mehlich, A. (1984). Mehlich 3 soil test extractant: a modiﬁcation ofMehlich 2 extractant. Comm. Soil Sci. Plant Anal., 15:1409–1416.
R Core Team (2017). R: A Language and Environment for StatisticalComputing. R Foundation for Statistical Computing, Vienna, Austria.
Turner, T. R. and Waddington, D. V. (1978). Survey of soil testing programsfor turfgrasses. Comm. Soil Sci. Plant Anal., 9(1):71–87.
Woods, M. S. (2013). Using temperature to predict turfgrass growthpotential (GP) and to estimate turfgrass nitrogen use. Technicalreport, Asian Turfgrass Center.
Woods, M. S., Stowell, L. J., and Gelernter, W. D. (2014). Just what thegrass requires: using minimum levels for sustainable nutrition. Golf
Course Mgmt., pages 132–138.
Woods, M. S., Stowell, L. J., and Gelernter, W. D. (2016). Minimum soil
nutrient guidelines for turfgrass developed from Mehlich 3 soil test
results. PeerJ Preprints.
Yee, T. W. (2016). VGAM: vector generalized linear and additive models. R
package version 1.0-1.
Prepared by Micah Woods on February 1, 2018, based on the latexsheet templateof Winston Chang.