simulation of herbicide persistence in soil .iii. propyzamide in different soil types

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Pestic. Sci. 1976, 7, 59-64 Simulation of Herbicide Persistence in Soil III. Propyzamide in Different Soil Types Allan Walker National Vegetable Research Station, Wellesbourne, Warwick CV35 9EF (Manuscript received 19 September 1975) The effects of soil temperature and soil moisture content on the rate of degradation of propyzamide in five soils were examined under controlled laboratory conditions. Half-lives in soils incubated at field capacity varied from 23 to 42 days at 25°C and from 63 to 112 days at 15°C. The variation in half-life at 25°C and 50% of field capacity was from 56 to 94 days. When the laboratory data were used in conjunction with the relevant meteorological records and soil properties in a computer simulation program, predicted degradation curves for propyzamide in four of the soils ip micro- plots were in close agreement with those observed. Use of the program to predict residues of propyzamide in the fifth soil at crop maturity in a series of field experi- ments concerned with continuity of lettuce production gave values fairly close to those observed when appropriate corrections were made for initial recoveries. 1. Introduction The computer program for simulation of herbicide persistence described by Walker' has been shown to predict the degradation pattern of propyzamide in the same soil in seven separate field experiments.2 The model is specific to the soil type in which measurements of herbicide degradation rates are made under controlled conditions, and includes an empirical method for simulating surface soil moisture contents from meteorological records. Although the moisture contents simulated by the model are in good agreement with measurements,' it is possible that the empirical method may also be specific to the soil type for which it was developed initially. The present experiments were therefore made to test the model with propyzamide in soils with contrasting properties to gain further information on the persistence of propyzamide in relation to soil type, and to determine whether the empirical equations used to simulate soil moisture content would apply to other soils. Because propyzamide is used as a pre-emergence herbicide for weed control in lettuce, the extent to which the model would predict residue levelsof propyzamide in soil at harvest was also examined in a series of field experiments concerned with continuity of lettuce production.3 2. Experimental 2.1. Materials Soils from five fields at the National Vegetable Research Station were used in this work. Their properties are shown in Table 1. Four of these soils were prepared in microplots constructed from concrete slabs sunk in the ground. Three replicate plots, each 1.25 x 2.5 m, were filled to a depth of about 25 cm with each of soils 2 to 5 (Table 1). After filling, the surfaces of the plots were forked and raked level, and the soils then left for about 8 weeks to equilibrate. The fifth soil (soil 1, Table 1) was from the field used for experimental plots at the Research Station during summer 1974. The herbicide used was a commercial wettable powder formulation of propyzamide (50% a.i.). 59

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Page 1: Simulation of herbicide persistence in soil .III. Propyzamide in different soil types

Pestic. Sci. 1976, 7, 59-64

Simulation of Herbicide Persistence in Soil III. Propyzamide in Different Soil Types

Allan Walker

National Vegetable Research Station, Wellesbourne, Warwick CV35 9EF

(Manuscript received 19 September 1975)

The effects of soil temperature and soil moisture content on the rate of degradation of propyzamide in five soils were examined under controlled laboratory conditions. Half-lives in soils incubated at field capacity varied from 23 to 42 days at 25°C and from 63 to 112 days at 15°C. The variation in half-life at 25°C and 50% of field capacity was from 56 to 94 days. When the laboratory data were used in conjunction with the relevant meteorological records and soil properties in a computer simulation program, predicted degradation curves for propyzamide in four of the soils ip micro- plots were in close agreement with those observed. Use of the program to predict residues of propyzamide in the fifth soil at crop maturity in a series of field experi- ments concerned with continuity of lettuce production gave values fairly close to those observed when appropriate corrections were made for initial recoveries.

1. Introduction

The computer program for simulation of herbicide persistence described by Walker' has been shown to predict the degradation pattern of propyzamide in the same soil in seven separate field experiments.2 The model is specific to the soil type in which measurements of herbicide degradation rates are made under controlled conditions, and includes an empirical method for simulating surface soil moisture contents from meteorological records. Although the moisture contents simulated by the model are in good agreement with measurements,' it is possible that the empirical method may also be specific to the soil type for which it was developed initially.

The present experiments were therefore made to test the model with propyzamide in soils with contrasting properties to gain further information on the persistence of propyzamide in relation to soil type, and to determine whether the empirical equations used to simulate soil moisture content would apply to other soils. Because propyzamide is used as a pre-emergence herbicide for weed control in lettuce, the extent to which the model would predict residue levelsof propyzamide in soil at harvest was also examined in a series of field experiments concerned with continuity of lettuce production.3

2. Experimental 2.1. Materials Soils from five fields at the National Vegetable Research Station were used in this work. Their properties are shown in Table 1. Four of these soils were prepared in microplots constructed from concrete slabs sunk in the ground. Three replicate plots, each 1.25 x 2.5 m, were filled to a depth of about 25 cm with each of soils 2 to 5 (Table 1). After filling, the surfaces of the plots were forked and raked level, and the soils then left for about 8 weeks to equilibrate. The fifth soil (soil 1, Table 1 ) was from the field used for experimental plots at the Research Station during summer 1974.

The herbicide used was a commercial wettable powder formulation of propyzamide (50% a.i.).

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60

Table 1. Soil properties

A. Walker

Soil

Moisture content at

Organic 100 cm matter Clay Sand suction

Texture ( %) ( %) ( %) PH ( %)

1 Gravel Pits Sandy loam 1.75 16 70 6.1 12.4

3 Soakwaters Clay loam 1.38 29 61 6.1 16.8 4 Gallas Leys Clay 2.90 34 62 6 . 9 23.8 5 Water Meadows Clay loam 5.32 41 47 1 . 2 23.4

2 Little Cherry Sandy loam 1.38 13 73 6 .8 12.0

2.2. Laboratory experiments About 6 kg soil was removed from the surface of each microplot and the three samples from the replicate plots of the same soil were bulked, air-dried and passed through a 2 mm mesh sieve. A sample of soil from the field plot area was treated similarly. Suspensions of propyzamide in 250 ml water were mixed into separate 15 kg quantities of each soil to give a final concentration of 6.4 pg/g dry soil. Subsamples (2.5 kg) from each treatment were weighed into polyethylene bags and sufficient water was added to give the required soil moisture contents. Duplicate treatments were prepared at nominal soil moisture contents of 50 and 100% of field capacity (Table 1) for incubation at 25"C, and at 100% of field capacity for incubation at 15°C. Immediately after preparation and on four occasions during the subsequent 80-90 days, 500 g soil was removed from each treatment and the herbicidal activity remaining determined using a bioassay based on the shoot growth of ryegrass (Loliurnperenne L.).4 A subsample from each soil was dried at 110°C to determine the soil moisture content at each sampling time. Moisture losses from the soils in the bags were replaced by adding water when necessary.

2.3. Microplot experiments The soil in the microplots was raked level and mildly compacted to give a smooth, even surface. Two plots of each soil type were sprayed with the equivalent of 4.0 kg a.i. propyzamide in 1100 litres water/ha. Immediately after spraying and at intervals during the next 21 weeks, 20 cores (2.5 cm diameter x 7.5 cm deep) were removed at random and bulked for each plot. The samples were sieved (2 mm) and the weights of sieved soil recorded. The amounts of propyzamide in the samples were determined using the ryegrass bioassay. The third plot of each soil was used for measurements of soil moisture content. Samples from the surface 2.5 cm of each soil were taken at intervals during the first 70 days of the experiment and dried at 110°C for 48-72 h.

2.4. Field experiments with lettuce A series of field experiments was carried out by the Plant Physiology Section at Wellesbourne during summer 1974. Lettuce (Luctucu sutivu L.) was sown on seven different dates from 11 April to 25 July. The plots were all treated pre-emergence with propyzamide at the equivalent of 1.96 kg a.i./ha. A small area (about 4 x 1.5 m) of the guard bed of each experiment was sampled immediately after spraying and the same area again sampled at lettuce maturity. On each occasion, 40 cores (2.5 cm diameter x 7.5 cm deep) were removed from each plot, bulked, sieved and their herbicide content determined as before.

3. Results and discussion 3.1. Laboratory experiments Previous experiments with propyzamide have shown that degradation under controlled laboratory conditions corresponds with first-order kinetics.2. 4 9 The present data confirmed this and the

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Propyzamide persistence in various soils 61

results, expressed as half-lives, are shown in Table 2. The effects of temperature on the rates of degradation were similar in the different soils-a change in temperature from 25 to 15°C increased the half-life by a factor of between 2 and 3. The activation energies for propyzamide degradation

Table 2. Half-lives for propyzamide in different soils

25°C 25°C 15°C Constants for -

Moisture Half- Moisture Half- Moisture Half- equation (1) Activation content life content life content life - - energy

(%) (days) (%) (days) (%) (days) A E (kJ/mol)

Gravel Pits 11.9 32 4.1 60 11.7 76 132.5 0.572 61.7 Little Cherry 12.1 30 4 . 0 72 12.0 70 217.3 0.797 60 .4 Soakwaters 16.3 23 6 . 4 56 17.8 63 327.3 0.952 71.9 Gallas Leys 16.7 42 6 .2 94 16.7 112 414.0 0.813 70. I Water Meadows 29.1 35 14.8 49 29 .5 85 187.5 0.498 63 .3

calculated from the Arrhenius equation are shown in Table 2, and the values calculated for the different soils were similar. The effects of soil moisture content on degradation rates were more variable between soils, with a reduction from 100% of field capacity to 50% of field capacity increasing the half-life by a factor varying between 1.4 and 2.5. Previous results with propyzamide2 have shown that an empirical equation can be used to relate the half-life ( H ) with soil moisture content ( M ) :

in which A and B are constants. The values for the constants A and B calculated from the present data are shown in Table 2.

H= A M-B (1)

3.2. Simulation of persistence in microplots The required weather data from March to October 1974 (soil temperature at 10 cm, rainfall (mm/ day) and evaporation from an open water surface (mm/day)) were combined with the appropriate constants (Table 2) in the computer program.1 The rates of loss of propyzamide from the four soils in the microplots are shown in Figures 1 and 2 in which the activity remaining, expressed as a percentage of that present initially, is plotted against time. Also shown are the simulated degrada- tion curves. The simulation model gave good approximations to the patterns of degradation in the four soil types and distinguished between Soakwaters, in which the residue at 147 days was 8 % of that found initially, and the other three soils in which the final residue varied from 21 to 32 %.

Although the model uses empirical methods of simulating surface soil temperatures and moisture contents, the results suggest that the values predicted are of sufficient accuracy for the purpose intended. The simulated soil moisture contents compared with those determined are shown for the four soils in Table 3. With each soil, there were discrepancies between predicted and observed values, but the general pattern of the fluctuation in surface soil moisture content was simulated satisfac- torily by the method employed.

Although the data in Figures 1 and 2 show that the simulation model predicts the degradation curves for propyzamide in the different soils, the degradation curve for each soil was simulated from laboratory measurements of the rates of herbicide loss in the same soil. The usefulness of the simulation model would be greatly improved if some correlation could be found between the rate of degradation under a standard temperature and moisture regime in different soils and some measurable soil parameter. In a study of the degradation of picloram in 11 soils, Meikle et al.7 showed that good relationships could be obtained between its rate of degradation in any one soil and soil temperature and soil moisture content but that only 26% of the variations between soils

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62 A. Walker

0 o+o oj O O

Q.0 Oo

0 0 O O O + ; O 0 00 ooooooo

A I I I I I I I 0 2 0 4 0 60 80 ICO 120 140 160

Time (days1

Figure 1. The persistence of propyzamide in Little Cherry (a) and Soakwaters (b) soil. 0, Observed; 0, simulated. Time O = 18 April 1974.

100

80

60

0

E 40

: ; g 20 z I20 0

0 -

100

6 ,\" 80

60

40

20

" O O O

t o O t O o i

( a 1

* I I I I I I 1 I

oo4000 1 I I I I 1 I I

20 4 0 60 00 100 120 140 160 Time (days1

Figure 2. The persistence of propyzamide in Gallas Leys (a) and Water Meadows (b) soil. 0 , Observed: 0, simulated. Time O = 18 April 1974.

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Propyzamide persistence in various soils 63

Table 3. Simulation of surface soil moisture content

Soil moisture content (%) in the surface 2.5 cm

Little Cherry

Time (days) Simulated Observed

0 4 7

12 22 25 36 41 50 60 70

7.1 4.3 3.1 3.6 3.4 4.6 5.0 9.2 8.2

12.0 11.0 10.1 10.7 3.6 2.9 9.3 10.2 7.6 8.2

13.2 12.1

-

Soakwaters

Simulated Observed

- 7.8 7.7 5.7 7.6 5.4 9.7 7.6

14.9 13.1 17.9 12.0 14.4 16. I 8.8 8.4

14.5 13.0 13.0 11.8 17.7 16.2

Gallas Leys

Simulated Observed

- 8.4 8.3 5.7 8.2 6.3

11.6 7.9 17.3 13.1 20.6 17.0 21.1 16.0 10.7 11.9 18.5 17.1 15.9 13.6 25.2 22.9

Water Meadows

Simulated Observed

- 9.8 9.7 9.3 9.6 11.2

12.5 7.6 19.0 13.9 22.8 21.8 20.5 20.5 11.3 13.0 19.3 17.3 16.9 11.7 24.8 22.6

could be accounted for by a multiple linear regression with soil properties. They concluded that much of the variation was due to biological factors which, at present, have not been studied.

Propyzamide degradation in soil is considered to be chemical rather than biological in nature,5 but with this herbicide also, Yih et aL5 reported no obvious correlation between its rate of loss and the various physical or chemical properties of different soils.

3.3. Prediction of residues in soil at lettuce maturity The results from the field experiments with lettuce are shown in Table 4. The soil residues predicted by the model were consistently higher than those observed. The main reason for this is apparent in

Table 4. Prediction of propyzamide residues in soil at lettuce harvest

Residue (kg/ha)

Initial Predicted Days to recovery

Date sprayed maturity ( %) Observed Corrected Uncorrected ~~

11 April 85 68.4 0.69 0.79 1.15 30 April 72 59.3 0.71 0.66 1 . 1 1 24 May 66 114.0 0.70 1.23 1.08 3 June 74 69.5 0.83 0.65 0.94

17 June 64 76.8 0.65 0.73 0.96

25 July 68 78.0 0.62 0.89 1.14 11 July 60 109.2 I .03 1.26 1.15

the data for initial recovery of the applied herbicide. This varied between different times of applica- tion from 59 to 114 % of the nominal dose.

Previous experiments with simazine and prometryneo have shown that differences in initial recoveries from replicate plots of the same treatment are often reflected in final residue levels, and that correction for these differences can greatly improve agreement between replicates. Correction of the present simulated data for initial recoveries also markedly improved agreement between predicted and observed values (Table 4). The uncorrected predicted residue levels were similar for

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64 A. Walker

the different sowing dates although the time between herbicide application and lettuce maturity varied from 60 to 85 days. This probably reflects a similarity in the effects of soil temperature on lettuce growth rate and herbicide degradation rate, both of which will increase as the soil tempera- ture increases.

The residue levels at lettuce harvest (Table 4) were relatively large, and although the rate applied (1.96 kg a.i./ha) is somewhat higher than the normal dose (1.12 to 1.68 kg/ha), the data show that careful choice in subsequent cropping is important with propyzamide. The data of Leistra et al.8 also showed propyzamide to be a relatively persistent herbicide, with the time required for 50% loss following application in spring varying between soils from 33 to 75 days.

4. Conclusions

The simulation model gave good approximations to the observed degradation patterns of propy- zamide in four soils of contrasting properties and the data further demonstrate the usefulness of the simulation technique to predict the persistence of certain herbicides. When used in the practical situation, difficulties were encountered because of the unevenness of the initial application, so that the predicted residues showed little correspondence with those observed unless corrections were made for initial recoveries.

Acknowledgements

Thanks are expressed to Dr D. Gray for allowing use of the guard beds in his experiments, to Mr D. A. Stone for measuring the moisture release characteristics of the different soils, and to Mrs D. Y. McLeman and Miss P. A. Brown for technical assistance. The interest and advice given by Mr H. A. Roberts is also gratefully acknowledged.

References

1 . 2.

3. 4. 5. 6. 7.

8.

Walker, A. J. Environ. Quality 1974, 3, 396. Walker, A. In Proceedings European Weed Research Council Symposium, Herbicides and the Soil Paris, 1973, p. 240. Gray, D. Rep. natn. Veg. Res. Stn for 1974 1975, p. 77. Walker, A . Pestir. Sci. 1970, 1, 237. Yih, R. Y . ; Swithenbank, C.; McRae, D. H. Weed Sci. 1970, IS, 604. Walker, A. Pestic. Sri. 1976, 7 , 41. Meikle, R. W.; Youngson, C. R.; Hedlung, R. T.; Goring, C. A. 1.; Hamaker, J. W. ; Addington, W. W. Weed Sci. 1973, 21, 549. Leistra, M . ; Smelt, J. H.; Verlaat. J. G. ; Zandvoort, R. Weed Res. 1974, 14, 87.