Effect of clipping height and interval on coastal bermudagrass production

Agricultural Systems 30 (1989) 287-298

Effect of Clipping Height and Interval on Coastal Bermudagrass Production A. R. O v e r m a n Agricultural Engineering Department, University of Florida, Gainesville, Florida 32611, USA

& S. R. W i l k i n s o n US Department of Agriculture, Agricultural Research Service, Southern Piedmont Conservation Research Center, Watkinsville, Georgia 30677, USA (Received 27 September 1988; revised version received 9 November 1988; accepted 23 November 1988)

A BSTRA CT Data from afield study at Plains, Georgia, USA, were used to estimate the effect of clipping height and clipping interval on model parameters for Coastal bermudagrass (Cynodon dactylon ( L ) Pers.). The analysis delineates the relationship of first- and second-order growth functions to harvest interval, clipping height and nitrogen level. Both growth functions follow logistic dependence upon nitrogen. The first-order function shows asymptotic dependence upon clipping height, while the second-order function exhibits a maximum at approximately lOcm (4in). The complex dependence of seasonal yield upon harvest interval, clipping height and applied nitrogen is described.

INTRODUCTION In a previous paper (Overman et al., 1989) a phenomenological model was introduced to simulate yield of Coastal bermudagrass over the season. The model is given by:

y,=AQ, (1) 287 Agricultural Systems 0308-521X/89/$03"50© 1989Elsevier SciencePublishers Ltd, England. Printed in Great Britain

A. R. Overman, S. R. Wilkinson

288

where

+ (2)

y. = ) , Ayl = cumulative yield through nth harvest (tons/ha) i=l

Ayi = yield at ith harvest (tons/ha)

A = yield parameter (tons/ha) Q. = cumulative function 2 c x , Xerf Xi + 1 - erfxi) i=1

_2 / - C(exp ( - X2+ l) -

exp ( - )(2))

}

(3)

where: i = index at beginning of growth increment C = curvature parameter erfX = ~-

x =

exp ( - u 2) du = error function

t-T

(4)

(5)

t = time (weeks) r = mean time of yield distribution (weeks) e = time spread of yield distribution (weeks) Production over the entire season is given by: Yr = AQr

(6)

where Yr is total yield over the entire season and QT is eqn (2) summed over the season. Normalized yield fraction is then given by: F. = Y./YT

(7)

It was shown previously (Overman et al., 1989) that data for F. versus t yield a straight line on probability paper and that Yr versus At (harvest interval) yields a straight line on linear paper up to 6 weeks for Coastal bermudagrass. The phenomenological model is consistent with these observations.

Effect of clipping height and interval on Coastal bermudagrass

289

It may be shown that: At

Qr = 2 + 2Ctr--~

(8)

In previous work (Overman et al., 1989; Overman & Wilkinson, 1989) model parameters were shown to depend upon (1) water status, (2) nitrogen level and (3) harvest interval. The objective of this analysis is to examine the effect of clipping height on yields and model parameters.

DATA ANALYSIS A study was conducted by Ethredge et al. (1973) to evaluate the effects of clipping height, clipping frequency and rate of nitrogen fertilizer on yield of Coastal bermudagrass. Plots utilized established sod on Carnegie sandy loam at Plains, Georgia, USA. Treatments were replicated four times. Average dry matter yields for 1967-68 are shown in Table 1. Plots were harvested at 3, 5 and 7 weeks growth, commencing from 24 April. Individual clipping data were not published. Yields appear to follow linear dependence upon harvest interval up to 6 weeks, consistent with previous results

TABLE 1 Yields a n d Regression Values for Field D a t a for Plains, Georgia, U S A

h N (cm) (kg/ha)

Yr (tons/ha) ° 3

5 (weeks)

7

ct (tons/ ha)

fl (tons/ ha week)

QT 3

5 (weeks)

7

0

0 56 112 448

4'95 7"51 8"44 13"23

5-75 7-80 9"02 14"82

6'66 8"92 11"18 17"08

3"65 6"31 6"12 10'23

0-428 0"352 0"685 0-962

2-70 2"34 2"67 2"56

3"17 2"56 3'12 2"94

3"64 2"78 3"57 3"32

7

0 56 112 448

3"11 5'19 5"95 12"54

4"19 6"78 8"26 14"33

3'74 6"42 7-72 14-77

1-49 2"80 2"48 9"86

0"540 0'795 1"155 0-895

4"17 3"71 4'80 2"54

5"62 4"84 6'66 2"91

-----

14

0 56 112 448

2"55 4"37 5"23 10"14

3-00 5"85 6-49 12'60

3"38 5"79 6"79 11.90

1'88 2"15 3"34 6"45

0"225 0"740 0"630 1"230

2"71 4"06 3"13 3"14

3"19 5.44 3"89 3"91

-----

° D a t a from Ethredge et al. (1973).

290

A. R. Overman, S. R. Wilkinson

(Overman & Angley, 1987; Overman et al., 1989). Regression coefficients are also shown in Table 1 for the linear function: YT = ~ + fl At

(9)

where: At = harvest interval (weeks) Yr = seasonal total yield (tons/ha)

= intercept (tons/ha) fl - slope (tons/ha week) At 0 cm clipping height, all three harvest intervals were used in regression analyses. Values of Q r listed in Table 1 were calculated from: (10)

Qr = 2 a + f l a t

where 0t and fl appropriate to each clipping height (h) and nitrogen level (N) were used. Parameter values for the growth model are given in Table 2. Since clipping data were not reported by Ethredge et al. (1973), tr could not be calculated directly. Estimates were made from a study at Tifton, Georgia, U S A (Overman & Angley, 1987). This, of course, assumed that tr was independent of clipping height. Values of A were calculated from eqn (6), while C was calculated from eqn (8). Then each value of A C was calculated from corresponding A and C. Dependence of A and A C on N

The next step was to relate A and A C to N for each clipping height. Logistic equations were used for this purpose, viz. Ao~ __ A

1 =exp

(

(11) N'

J

where: A~ = upper limit of A (tons/ha) N'U2 = nitrogen for half response (A = A ~/2) (kg/ha) N' = response coefficient (kg/ha) and: A~C~ AC

1 = exp

--

N"~ ' 1 / 2

(12)

Effect of clipping height and interval on Coastal bermudagrass

291

TABLE 2 Parameter Values for the Model N

(kg/ha)

0

At tra (weeks) (weeks)

3 5 7

3 5

7 (cm)

14

0

7 (cm)

14

0

7 (crn)

14

5.00

1.83 1-81 1-83 1-82

0.746 0.746 -0.746

0'941 0.940 -0"940

0'825 0"827 0"828 0"827

2-56 2'56 -2'56

0.84 0.84 -0-84

1.51 1.49 1'52 1.50

1'90 1"90 -1"90

0.79 0-79 -0-79

5"21

3.21 3'05

1"40 1"40

1"08 1.08

0"418 0"412

2.10 2-10

2.53 2.53

1.35 1.25

2"94 2"94

2-73 2.73

3.21 3.16

-1.40

-1.08

0"410 0-413

-2.10

-2.53

1.32 1.30

-2"94

-2.73

5-39

3-16 2-89 3-13 3'06

1'24 1"24 -1-24

1.67 1-67 -1.67

0"85 0'85 0"85 0'85

3-55 3.55 -3.55

1"44 1.44 -1.44

2-69 2-46 2.66 2-60

4"40 4"40 -4"40

2-40 2-40 -2-40

6.02

5.17 5.04 5.14 5-12

4.94 4.92 -4-93

3'23 3"22 -3"22

0"80 0'80 0-80 0-80

0.77 0.77 -0-77

1.62 1.62 -1.62

4.14 4'03 4'11 4.09

3'80 3'80 -3"80

5.23 5"23 -5.23

7

Avg 112

3 2 7

Avg 448

3 2 7

Avg a Calculated from

AC (tons~ha)

C

0

Avg 56

A (tons~ha)

study at Tifton, Georgia, USA (Overman & Angley,

1987).

where: AooC® = upper limit of A C (tons/ha) N~'/2 = nitrogen for half response (AC = A o~Co~/2) (kg/ha) N" = response coefficient (kg/ha)

The procedure was to select Aoo to provide the best line for (A~o/A - I) on semilog paper and then to perform regression analysis for eqn (11). A similar procedure was used for A C to obtain A ooC®. Dimensionless graphs are shown for A versus N (Fig. 1) and for A C versus N (Fig. 2). The lines are drawn from eqns (11) and (12), respectively. It may be seen that the logistic equations provide adequate correlation between A and N and between A C and N. This agrees with results from Overman & Angley (1987). Dependence of eoellieients on h The various coefficients from nitrogen correlations are summarized in Table 3. The challenge is to develop correlations of these coefficients with h that

A. R. Overman, S. R. Wilkinson

292

10

Symbol Height, ×

cm

7

×

I

0.1

0.01

O. 001 -4

I

I

-2

I

I

I

I

0

2

N

-

I

I

I

4

Nl't2

N'

Fig. I. Dependence of reduced A on reduced N and clipping height. can be used to estimate the coefficients for use in eqns (11) and (12). The process necessarily involves some uncertainty due to limited data. The following set of functions seems to provide a reasonable compromise:

Aoo= 5.20(1 + 0.075h)exp ( - 12-~) N'~/2= 1 4 0 ( 1 - e x p ( h 2 . ~ l ) ) N' = 140

(13) (14) (15)

Effect of clipping height and interval on Coastal bermudagrass

293

In ~

i

l

Symbol HeiSt. II

cm

]4

I

Q.O:

O. OOl

-4

I

I

-2

I

I

0

I

2

I

I

4

I

6

N - NI"~ N'"

Fig. 2.

Dependence of reduced AC on reduced N and clipping height.

AooC~= N~/2=

(h)

4.10(1 + 0-15h)exp - 1-5-8.8

(16)

70

(17)

N"=70

(18)

Estimates of the nitrogen coefficients from eqns (13)-(18) are given in Table 4. Some criterion is needed to evaluate the utility of these values. We now proceed to achieve this goal. Estimates of growth model parameters from eqn (11) and (12) with coefficients from Table 4 are graphed in Fig. 3 to show dependence on N for

A. R. Overman, S. R. Wilkinson

294

TABLE 3

Coefficients from N Correlations h

(cm)

A~

(tons~ha)

0 7 14

N'u2

N'

(kg/ha)

(kg/ha)

49 270 137

96 177 127

5'20 4'50 3"50

A~Co~

(tons~ha) 4"10 5"50 5-25

N'~/2

N"

(kg/ha)

(kg/ha)

59 39 64

91 55 94

h cm

7

14

20 0

J

o

0 tO 0 ~J

7

4

14

2O

00

i

I

I,

I

I

I

100

200

30Q

400

500

600

700

N AppliQd, kg/ha Fig. 3.

Dependence of A and AC on nitrogen and clipping height.

Co

0'79 1"22 1-50

Effect of clipping height and interval on Coastal bermudagrass

295

TABLE 4 Estimates of N Coefficients h

(cm)

A~o

N'1/2

(tons~ha)

0 7 14

5"20 4"53 3"48

N'

(kg/ha)

(tons~ha)

55 134 140

140 140 140

N =

44B

A~C~

N'~/2

(kg/ha)

N"

(kg/ha)

4"10 5'39 5'24

70 70 70

70 70 70

kg/ho

Z o

4~

4

112

0 c"

¢" 0

4

E

r

J

J

I

J

5

10

15

20

25

C l I p p l n 9 H~19ht,

Fig. 4.

C~

(kg/ha)

30

cm

Dependence of A and AC oh clipping height and nitrogen.

0-79 1"19 1'50

A. R. Overman, S. R. Wilkinson

296

20 h = 14 cm

448

kglhn

15

]]2

10

56 0 0

0 r-

C 0

o

0

448

h =7

1

/

15 112

I

10

56 ×

C 0 0 0 U'I

O

5 o

0 h = 0

448

I# ~

15 112 10

55 0

5

O/

0

I

1

1

I

2

4

6

8

Horvest

]ntervo],

10

weeks

Fig. 5. Estimates of seasonal yield in relation to harvest interval, clipping height and nitrogen.

various clipping heights. Dependence of the parameters on h for various nitrogen levels is graphed in Fig. 4. Note that the first-order growth parameter (A) decreases toward zero with increased clipping height, as expected intuitively. The second-order growth parameter (AC) increases through a maximum, then decreases toward zero, as expected. Maximum second-order growth occurs at approximately 7.5 cm (3 in). (Overman & Wilkinson (1989) have shown that second-order growth corresponds to stem mass.) According to this analysis, maximum stem mass is produced at this clipping height.

Effect of clipping height and interval on Coastal bermudagrass

297

Estimates of seasonal yields Seasonal yields are now estimated from coefficients listed in Table 4 coupled with eqns (11)-(18). Results are graphed in Fig. 5. In general, agreement between estimated and measured yields is rather close. This constitutes the criterion for estimating the utility of these equations. Application of these results may now be illustrated. Equations (6) and (8) may be combined to give the yield function: 2ACAt

y r = 2A + r = - ~x/2

(19)

Equations (13)-(18) are used to estimate influence of clipping height on various coefficients in eqns (11) and (12). Equations (11) and (12) are then used to estimate A and A C for given clipping height and nitrogen application. An appropriate value for tr is chosen for the nitrogen application, as discussed by Overman & Angley (1987). For a chosen clipping interval, values are inserted in eqn (19) to estimate dry matter production.

CONCLUSIONS Data from a field study at Plains, Georgia, USA, have been utilized to characterize the interaction among clipping height, clipping interval and applied nitrogen level. Parameters in the model were evaluated with the data. Graphs were developed to show the dependence of the 1st and 2nd order functions upon clipping height and nitrogen. The 1st order function showed an asymptotic decrease with height, while the 2nd order function reached a maximum at about 10cm (4in) and then declined toward zero. Both functions showed logistic dependence upon nitrogen. Both data and model showed decreased dry matter as clipping height was increased. Wilkinson et al. (1968) observed this same effect at Watkinsville, Georgia, USA, with both Coastal bermuda and tall fescue. Holt & Lancaster (1968) measured greater yields at lower stubble height, also. The model accounted for the effects of clipping height, harvest interval and nitrogen level rather well.~" These results can be used to assess the impact of management practices upon forage production and environmental control. ~fWhile uncertaintyexists in the parameters due to limiteddata, the analysis does provide insight into interactions among various managementfactors.

298

A. R. Ooerman, S. R. Wilkinson ACKNOWLEDGEMENT

This paper is published as Florida Agricultural Experiment Station Journal Series No. 9165.

REFERENCES Ethredge, J., Beaty, E. R. & Lawrence, R. M. (1973). Effects of clipping height, clipping frequency, and rates of nitrogen on yield and energy content of Coastal Bermudagrass. Agronomy Journal, 65, 717-19. Holt, E. C. & Lancaster, J. A. (1968). Yield and stand survival of 'Coastal' Bermudagrass as influenced by management practices. Agronomy Journal, 60, 7-11. Overman, A. R. & Angley, E. A. (1987). Simulation model for Coastal Bermudagrass. III. Validation of the mechanistic model. Agricultural Engineering Department, University of Florida, Gainesville. April, 1987. Overman, A. R. & Wilkinson, S. R. (1989). Partitioning of dry matter between leaf and stem in Coastal bermudagrass. Agricultural Systems, 30(1), 35-47. Overman, A. R., Angley, E. A. & Wilkinson, S. R. (1989). A phenomenological model of Coastal bermudagrass production. Agricultural Systems, 29(2), 137-148. Wilkinson, S. R., Welch, L. F., Hillsman, G. A. & Jackson, W. A. (1968). Compatability of tall fescue and Coastal Bermudagrass as affected by nitrogen fertilizer and height of clip. Agronomy Journal, 60, 359-62.