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III. Modeling Crop Residue Decomposition

III. Modeling Crop Residue Decomposition

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In 1989, Stroo et al. published a mechanistic-based model for surface-managed

wheat residue decay in the field. The model simulates decay under constant environmental conditions using C and N dynamics. It then determines the impact of

environmental conditions, calculating the fraction of an optimum “decomposition

day” occurring in a4-h period. Information concerning initial residue C and N pool

availability is required for this model. The model was developed from mechanistic relationships developed in the laboratory and a series of field decomposition

studies in different climatic zones (Stott el al., 1990).

Once the theoretical model for crop residue decomposition was developed, the

next step was to simplify the model for use as a component in an expert system on

residue management (RESMAN) (Stott and Rogers, 1990; Stott et al., 1988; Stott,

1991). The goal in developing RESMAN was to incorporate residue decomposition knowledge with site- and situation-specific tillage considerations including

residue burial. Inputs for the expert system needed to be relatively simple and readily available to a wide variety of users.. Another feature was a user-specified need

for quick run times; thus, the expert system was unable to deal with the complexity of a true research model.

Since its release in 1990, RESMAN has been used widely by industry personnel, extension and soil conservation advisors, and private consultants throughout

the United States, Canada, and several other countries to develop crop residue

management strategies for soil conservation. Due to its wide acceptance, the theory

and equations used in RESMAN were incorporated into several erosion models

being developed by the USDA, including Revised Universal Soil Loss Equation

(RULSE), Revised Wind Erosion Equation (RWEQ), Water Erosion Prediction

Project (WEPP), and Wind Erosion Prediction System (WEPS), RUSLE was

implemented by the USDA-NRCS in its southeastern field offices in 1995 and will

be implemented in the remainder of the United States in 1996. RWEQ is to be implemented in late 1996. WEPP and WEPS, utilizing new erosion prediction technologies, are expected to be completed and implemented by the end of the decade.



To simulate the decomposition process, the decomposition day concept as presented by Stroo et al. (1989) for winter wheat residue decomposition was used as

a basis for the residue mass loss calculation. The Stroo et al. (1989) model simulates residue decay under constant environmental conditions using C and N dynamics based on Knapp et al. ( 1983a,b)and Bristow er nl. (1986). The residue C is

split into three pools based on availability for use by the soil microbial population

and chemically defined. This information is not readily available for a wide variety



of crops, thus in the RESMAN model the equations describing the C and N dynamics were replaced with the following single equation (Stott and Barrett, 1994):

M, = M y * e - (Rapt . EF),


where M,is the residue mass per unit area remaining on the surface today, Myis the

mass per unit area left on the ground the previous day, Ropt is a decomposition constant for a given residue type for the amount of mass lost in I day under optimum

conditions for microbial activity, and EF is the environmental factor determining the

fraction of a decomposition day that has occurred during day t. The value for Ro

for a given crop can be calculated from the more mechanistic Stroo et al. (1984)

model if the nutrient data are available. Alternatively, Ropt can be estimated from

field or laboratory studies measuring rates of residue mass loss. In the field, residue

decomposition rates are controlled by environmental factors (Martin and Haider,

1986). Especially important are the residue water content and temperature (Pam and

Papendick, 1978).The effects of water content and temperature on the rate of residue

decomposition were assumed to be independent of one another (Strooet al., 1989;

Stott et al., 1986).To estimate the influence of these factors on residue decomposition in the field, the following relationship was used (Stott and Barrett, 1994):

EF = Minimum (WFC, TFC),


where EF is the environmental factor used in Eq. (l), and WFC and TFC are water and temperature factors, respectively, with normalized values between 0 and 1.

The changes in the water content and temperature within the soil and residue layers are calculated with a simplified version of the Bristow er af. (1986) model. Bristow et al. (1986) divided the residue into five layers and the soil into three layers.

Temperature and moisture fluctuations were calculated for each layer at 4-h time intervals. In the RESMAN model, three residue and five soil layers are used, and calculations are done at 24-h time intervals. The data needed to calculate the temperature and water content for the soil and residue layers include daily maximum and

minimum air temperatures and precipitation. It is assumed that most of the residue

decomposition occurs in the bottom residue layer that interfaces with the soil surface. Thus, WFC and TFC are calculated using the temperature and water content

for the bottom residue layer. RUSLE, RWEQ, and WEPP do not calculate the temperature or moisture within the residue layer; therefore, WFC is estimated based on

the water content in the top soil layer and TFC is estimated from the air temperature.

The water function (WFC) is calculated as (Linn and Doran, 1984):


WFC= - i f @ < @




orWFC= - i f @ > O o p t ,



where 0 is the actual water content (g water kgg ') of the residue or soil, and Oopt

is the optimum water content. The latter value was set at 3500 g water kg- residue

as determined by Stroo et al. (1989) from data published by Stott et al. ( 1 986).

This residue water content is equivalent to a water potential of -33 kPa, which is




considered optimal for microbial activity (Sommers et al., 1981). RESMAN assumed that the soil texture was silt loam. For that soil textural class, a -33 kPa water potential is equivalent to approximately 60%water-holding capacity. Assuming

a bulk density of 1.2 and 50% porosity, Qopt for the soil layers was set at 833 g water kg- soil. The submodel used in WEPP allows for variations in soil texture and

water absorptive capacities of the soil. This includes changes in the amount of pore

space within the soil as compaction and tillage occur. The temperature function

(TFC) is based on an equation for photosynthetic activity (Taylor and Sexton, 1972):




+ A)2(Tm + A)* - (T + A)4


+ A)4


where T is the average temperature in "C, T, is the optimum temperature, and A is

an experimentally derived constant. T is calculated as the mean of the daily minimum and maximum temperatures. If T is plotted against TFC, T, is the temperature at which TFC equals 1. TFC equals 0 at two points-the first where the average daily temperature is too low for microbial activity, and the second where it is

too high for activity. The constant, A, is equal to the absolute value of the lower of

the two TFC zero values. Stroo et al. (1989) used Tm = 33"C, and A = 6.1"C for

calculating TFC at 4-h time intervals. RESMAN uses average daily temperature for

T rather than 4-h averages; thus a T,,, of 30°C and an A of 0°C were used based on

laboratory data from Stott et al. (1986) and personal unpublished field data. Because Eq. (4) is a quartic formula, TFC was set to 0 when T < 0.0 or T > 42.4.

Each operation or pass through a field with a tillage implement inverts residue

under the soil surface, reducing erosion protection. Modeling the effects on percentage residue cover of all possible tillage procedures is difficult because each

tillage pass not only turns some of the residue under but also can, in a few cases,

return some of the previously buried residue to the surface. Depth and speed of the

equipment operation impacts the amount of residue buried, as does the amount of

residue present at time of tillage. For a specific piece of equipment, the shallower

the operating depth, the greater the amount of residue left on the surface, whereas

deeper operating depths will bury more residue. Additionally, slower operating

speeds tend to leave more residue on the surface. In RESMAN (Version 2.0) and

the erosion models, the tillage burial coefficients used were derived from the

USDA-SCS-EM1 tillage implement list (1992).

The effectiveness of a residue layer in protecting the soil against water erosion

is dependent on the percentage of the soil surface covered. Because residue decomposition is calculated in terms of residue mass per unit area, a conversion from

residue mass to percentage cover is needed. The equation used in RESMAN and

the erosion models for this conversion is based on the following one published by

Gregory ( 1982):

C, = tOO * ( I







where the percentage surface are covered (C,)is a function of the M,from Eq. (1)

and a constant ( K ) that is dependent on crop type and represents the area covered

by a specific mass of residue.

C, is the critical value for determining that adequate erosion protection will be

achieved using a given management practice. The amount of erosion and sediment

loss occurring is very sensitive to changes in this value. Because accurate predictions are essential for planning erosion control measures, we are attempting to gain

a better understanding of how soil biological and environmental characteristics impact the plant residue decay process as well as the mass-to-cover relationship.


Brian et al. (195 1) showed that the metabolic products from some saprophytic

rhizosphere microorganisms could adversely affect plant root development. Woltz

( 1978) said that saprophytic deleterious rhizobacteria usually live outside their

hosts and inhibit plant growth through the production of a water-soluble toxin. Salt

( 1979) felt that some rhizosphere microorganisms not normally considered

pathogens may decrease crop yields. Suslow and Schroth (1982) called them deleterious rhizobacteria (DRB). They postulated that these organisms are a significant

pathogen group that limits plant growth and yield and influence other hostpathogen interactions at the root surface. Schippers et al. (1987) defined these organisms as deleterious rhizosphere microorganisms that were minor pathogens affecting plants by their metabolites without parasitizing plant tissues; both bacteria

and fungi are included in this definition.

We conducted several studies on the relationship of DRB, primarily pseudomonads, on winter wheat (Triticurn aestivum L.) growth. Pseudomonads were isolated from the surface of winter wheat roots. Large numbers of these isolates were

inhibitory to winter wheat root growth (Elliott and Lynch 1984b). Incidence of the

organisms appeared to correlate with poor winter wheat growth when it had been

no-till seeded into heavy residues from the previous crop. The organisms inhibited wheat root growth by the production of a toxin (Fredrickson and Elliott, 1985a).

The organisms grew well at 5°C and were detectable on wheat roots in early spring

(Elliot and Lynch, 1985) or after prolonged cold and wet periods in late fall and

early winter (Rovira et af., 1990). Inoculation of wheat seed, which was no-till

seeded into residues, resulted in severe inhibition of crop growth (compare Fig. 3

with the uninoculated check in Fig. 4). When wheat straw was inoculated with a

wheat DRB at 1 X I O8 organisms per square meter and wheat was no-till seeded

into the residues, severe stand loss and stunting occurred (Fig. 5 ; plots on left inoculated; uninoculated check on right). When seedlings were dug from the plots

and compared, the three plants on the right were severely stunted when compared

with the plant on the left (Fig. 6).There were no obvious effects, such as discol-

Figure 3 Loss o f a no-till seeded winter wheat stand caused by bacterization of the winter wheat

seed with a DRB at I X IOh organisms per seed (the three center pairs of rows were bacterized).

Figure 4 Growth of no-till seeded winter wheat seed with nonbacterized seed.

Figure 5 The effect o f a DRB on the growth of no-till seeded winter wheat. The straw on the plot

on the left was sprayed with 1 X IDx DRB organisms per square meter before no-till planting. whereas the plot on the right was lightly sprayed with water only.

Figure 6 The plants on the right were dug from the plot that was sprayed with DRB before planting. whereas the plant on the left was from a nonsprayed plot.



oration on the roots-just reduced growth. The severity of the stunting that can be

caused by DRB is shown in Fig. 7 with the inoculated roots on the right.

Pseudomonads isolated from winter wheat roots and incubated at 5°C or in a medium containing NO; showed significantly greater numbers of TOX+ isolates than

those incubated at 20°C in the absence of NO;. Possibly, nutrification of ammo-

Figure 7 An uninoculated check (left) compared with winter wheat plants (right) growing in soil

inoculated with a DRB. Reprinted from Soil Biology and Biochemistry 20(2), H. F. Stroo, L. F. Elliott,

and R. 1. Papendick, Growth, survival, and toxin production of root-inhibitory pseudomonads on crop

residues, pp. 201-207, 1988, with kind permission from Elsevier Science Ltd, The Boulevard, Langford Lane, Kidlington OX5 IGB, UK.



Table I

Effect of Root Zone Temperature and Soil Q p e on Root Populations

of Inhibitory Pseudomonads

Rhizoplane population

(cfu mg-' dry root X



Temperature ("C)

Time" (days)














88 rif'"



I .o




LSD 0.05


NTIS rif'"

I .7







Note. Reprinted from Soil Biology and Biochemistry 19(2), J. K. Fredrickson, L. F. Elliott, and

J. C. Engibous, Crop residues as substrates for host-specific inhibitory pseudomonads, pp. 127-134,

1987. with kind permission from Elsevier Science Ltd, The Boulevard, Langford Lane, Kidlington

0x5 IGB, UK.

"Length of time required at the given temperature to reach the two-leaf stage (Fredrickson and

Elliott, 198Sa).

nia fertilizer and the overwinter cold induces toxin expression by the inhibitory

pseudomonads (Rovira et al., 1990). The pseudomonads produced a toxin that reduced winter wheat root and Escherichia coli C l a growth. However, this antibiosis toward E. coli and wheat seedling root inhibition in agar was reversed by Lmethionine (Fredrickson and Eliott, 1985a,b). No correlation between plant root

amino acid exudation and plant susceptibility to the toxin could be demonstrated

(J. Fredrickson and L. Elliott, unpublished data). Studies were conducted on the

wheat root colonization potential of rifampicin resistant mutants of two inhibitory pseudomonads as affected by temperature and soil type (Table I). Temperature

did not affect winter wheat root populations of isolates B8 riflm or NT15

but soil type did. The organisms colonized the wheat roots more vigorously in the

Ritzville than in the Palouse soil. The Ritzville soil is much lower in total C

(0.73%)and microbial biomass (1 1 4 6 pg biomass C g-' soil) than the Palouse

soil (2.09% C and 450490 pg biomass C g- soil). However, when the soils were

pasteurized, wheat root colonization by the mutants B8 riflm and NT15 rif" was

still significantly greater in the Ritzville than in the Palouse soil (Frederickson and

Elliott, 1985a). The main difference between the two soils is C content, whereas

physical and chemical properties are similar. These data show that the inhibitory

bacteria were very aggressive root colonizers in view of the number that colonized

the roots under nonpasteurized conditions. Colonization increased approximately




I log phase when the soil was pasteurized showing that there was competition from

the residual microbial biomass. However, the effect was proportional, which may

indicate that size of the microbial biomass is the controlling factor. Unfortunately, we have no measure of population diversity.

Evidence is accumulating that DRB are affected by crop rotation (Schippers et

a/., 1987; Rovira et a/., 1990). Schippers et af. (1987) found that yields of wheat

and especially potatoes (Solanum tuberosum) were sensitive to the frequency of

the rotation but were unable to attribute the low yields to known soil-home

pathogens and postulated that the yield reductions resulted from nonspore-forming DRB. Studies in the Pacific Northwest on DRB pseudomonads indicated that

as the frequency of winter wheat in the rotation increased, the populations of DRB

(pseudomonads) increased on the wheat rhizoplane (Rovira er af., 1990). Other

causes of the plant growth retardation cannot be ruled out, and the direct effect of

the DRB cannot be established in natural soil with current technology. Additional

studies are needed to determine factors favoring DRB because the presence or ahsence of these organisms could be an important measure of sustainability of a cropping system.

In related studies, the colonization potential and root inhibition by NT15 rifIo0

and B8 rif'* on winter wheat, spring wheat, winter and spring barley (Hordeum

vufgare L.), oats (Avena saliva L.), lentils (Lens culinaris L.), and peas (Pisum

sutivum L.) were compared (Table 11). Root growth of winter wheat was most severely inhibited by the bacteria followed by spring wheat and winter barley, where-

Table I1

Wheat Rhizoplane Populations of Inhibitory Pseudomonads

and Their Influence on Crop Root Growth

NT15 rifItMknu


~8 ripin)<,

Root length

(% of control)


(log cfu mg-'

dry root)

















Root length

(% of control)

(log cfu mg

dry root)




Winter wheat

Spring wheat

Winter barley

Spring barley




LSD (0.05)
















0.4 I

"Resistant to rifamipicin at 100 p g ml-l [(from Fredrickson and Elliott (198%) with permission].



as spring barley, oats, lentils, and peas were either not significantly different from

the controls or only slightly inhibited. The magnitude of rhizoplane colonization

did not correlate with root inhibition (Fredrickson et al., 1987). Other studies have

shown that the inhibitory effect resulted from the production of a toxin that exhibited plant specificity (Fredrickson and Elliott, 1985b), which agrees with the

colonization data in Table 11. The toxin appeared to be unique from toxins produced by recognized plant pathogenic bacteria (Bolton et al., 1989).

It was mentioned previously that the organisms appeared to be associated with

no-till seeding into heavy crop residues. Evidence is accumulating that some of

these detrimental organisms may be closely associated with the previous crop

residue, especially when the residue remains on the soil surface. When nonsterile

winter wheat straw was inoculated with a rifampicin-resistant inhibitory pseudomonad at 1/1000th the population of the native bacterial flora and incubated at 5

and 15"C, the organism multiplied rapidly to almost the same numbers as the native bacterial flora. Fairly high proportions of the introduced rifampicin-resistant

mutant were also obtained from growth on pea residue, winter barley straw and

chaff, and winter wheat chaff (Fredrickson et ul., 1987). Another series of studies

were conducted to determine the association of the inhibitory pseudomonads with

crop residues in the laboratory and field. A nonfluorescent rifampicin-resistant

Pseudomonas sp. capable of producing a toxin inhibitory to the growth of wheat

roots was inoculated onto nonsterile wheat straw at lo4 or lo6 colony-forming

units (cfu) g-' dry weight and incubated at several water potentials. Water potential between -0.6 and -0.9 MPa appeared optimum for the introduced microorganisms, which reached populations in excess of 1O'O cfu g-I within 6 days of incubation and accounted for up to 80% of the bacteria recovered on tryptic soy agar.

These data show the highly competitive ability of these organisms to colonize

straw. Bacteria inoculated onto barley residues in the field in October maintained

populations greater than lo6 cfu g-' straw throughout the winter and declined in

mid-March when the residues dried (Fig. 8). Populations on residues in the no-till

plots were approximately 10-fold higher than those in the tilted plots. It was also

found that the organism B8, sprayed on the straw, colonized the rhizoplane of the

winter wheat no-till seeded into the residues and the plants showed root growth inhibition (Stroo et al., 1988). These data show crop residues have the capability of

carrying and transmitting these organisms. The results also indicate that residue

management will dramatically affect populations of inhibitory microorganisms.

Although the organisms showed specificity toward the plants tested, they had a

broad antimicrobial activity (Bolton et ul., 1989). The aggressive growth of these

organisms on plant roots and residues indicates that they compete well for available substrate. In other studies, a pseudomonad inhibitory to winter wheat growth,

RC 1, was mutagenized with the Tn5 transposon to obtain TOX- mutants. TOX(loss of inhibition to both E. coli C l a and wheat root growth) and partial TOXf

(partial loss of inhibition of E. coli Cla and wheat root growth) Tn5 mutants were









Figure 8 Numbers of rifampicin-resistant pseudomonads on barley residue in tilled and no-till

plots at varying times after inoculation of the residue (from Stroo et al., 1988).

isolated to be compared with a TOX rifampicin-resistant spontaneous mutant.

When the RC1 rif (rifampicin TOX+ spontaneous mutant) was coinoculated with

the TN5 mutant, colonization proportions remained roughly the same (Table 111).

The wild-type mutant ratios changed somewhat but one would have to conclude

that, in this case, toxin production by these organisms is not their primary mechanism of competitive advantage for root colonization (Kennedy et al., 1992). The

data also indicate that the TOX- bacteria could be used to alleviate the deleterious effect of these types of inhibitory bacteria because the TOX+ rif-TOX- combination did not inhibit plant growth.

It appears that the effects of these organisms will have to be considered during

the development of sustainable cropping systems because they can decrease the

efficiency of the system. The organisms are predominately associated with heavy

crop residues and no-till seeding. It is possible that these organisms will become

more of a problem as crop rotations are decreased. Changing tillage to no-till affects C sequestration in the system and also changes the system ecology. Hendrix

et al. (1986) showed that the no-till system was dominated by fungi and earthworms, whereas the biota of the conventional till was dominated by bacteria, nematodes, and enchytraeids in studies of Georgia soil. Kennedy (Turco et al., 1994)

showed that substrate utilization patterns of microorganisms varied depending on

the history of the soil from which they were isolated. Substrate utilization patterns

were different when no-till seedings were compared with conventional tilled seed+

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