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2008 Plant Management Network.
Accepted for publication 2 January 2008. Published 17 March 2008.


Biomass Yield Reductions in Switchgrass Due To Smut Caused by Tilletia maclaganii


Paige M. Thomsen, Research Assistant, Department of Plant Pathology, Iowa State University, Ames 50011; and E. Charles Brummer, Professor, Department of Crop and Soil Sciences, University of Georgia, Athens 30602; and John Shriver, Research Associate, and Gary P. Munkvold, Associate Professor, Department of Plant Pathology, Iowa State University, Ames 50011


Corresponding author: Gary P. Munkvold. munkvold@iastate.edu


Thomsen, P. M., Brummer, E. C., Shriver, J. M., and Munkvold, G. P. 2008. Biomass yield reductions in switchgrass due to smut caused by Tilletia maclaganii. Online. Plant Health Progress doi:10.1094/PHP-2008-0317-01-RS.


Abstract

Switchgrass (Panicum virgatum) is an attractive biomass crop for renewable energy, but there is little information on disease losses. Tilletia maclaganii causes a smut disease of switchgrass that results in stunting, premature flowering, and replacement of seeds by fungal sori. We conducted a study in naturally-infested fields to describe the impact of smut on biomass yield. Ten fields were sampled; smut incidence, stand density, and biomass yield were determined. Disease incidence varied from 0.7 to 55.4% (26% overall) and biomass varied from 174 to 617 g/m. Mean biomass/tiller was significantly reduced by the disease in each field, by 38 to 82%. Yield loss was calculated based on the ratio of mean biomass/tiller for samples (actual yield) and mean biomass/tiller for healthy tillers (attainable yield). Yield loss estimates ranged from 1.7 to 40.1% among the fields. There was a strongly linear relationship (R = 0.95) between disease incidence and yield loss, and regression analysis estimated a 0.66% reduction in yield for every 1% increase in disease incidence. According to this model, yield loss for all sampled fields was estimated at 17.0%. This disease is having a significant impact on biomass production in Iowa, and there is a critical need for research on management approaches if switchgrass is to be successful as a feedstock for lignocellulosic ethanol production.


Introduction

Switchgrass (Panicum virgatum L.) is a native perennial warm-season prairie grass in which cultivars have been developed for use as forage and biomass crops. In 1991, the United States Department of Energy (DOE) chose switchgrass as a model species for its Bioenergy Feedstock Development Program (19). Since that time, DOE and the USDA have partnered with a variety of collaborators to conduct evaluations of switchgrass as a bioenergy crop in a number of locations across North America (2,16,17,18,20,23,27,33) and on other continents (5,22). Evaluations have included analyses of switchgrass biomass for combustion and as a feedstock for lignocellulosic biofuel production through pre-treatment and fermentation.

Switchgrass is currently grown in southern Iowa primarily for forage or as part of a demonstration project coordinated by Chariton Valley Resource Conservation and Development (CVRC&D), a USDA-sponsored non-profit organization. The goal of this project is to test the co-firing of biomass from switchgrass with coal at an electricity generating station near Ottumwa, IA (4). Switchgrass production for forage or bio-fuel is a desirable land use in southern Iowa because the soil environment is less suitable for row cropping; switchgrass is adapted to many different soil types (21), and can be more cheaply established than alfalfa, reed canary grass, or big bluestem. Approximately 1,600 ha have been committed to switchgrass for this project in southern Iowas Chariton Valley, which occupies parts of Lucas, Monroe, Wayne, and Appanoose counties. It is anticipated that switchgrass cultivation will expand as the economics improve for lignocellulosic ethanol production.

Like all crop production systems, the viability of switchgrass production, either as a biofuel feedstock or a forage crop, is yield dependent. The biomass yield potential of switchgrass populations and cultivars has been characterized extensively. Yields of the most productive cultivars in DOE-collaborator trials ranged from 10.7 to 23.0 Mg/ha (20). Switchgrass cultivars can be classified as "upland" and "lowland types, with upland types most suited for northern latitudes. One of the most productive upland cultivars for Iowa and surrounding areas is Cave-in-Rock (20). Cave-in-Rock has become the predominant cultivar grown in Iowa, and has been planted in most of the biomass fields in the Chariton Valley. Cave-in-Rock is recommended for southern Iowa because of its adaptability, producing consistent yields across many soil and environmental conditions in the region. Yields of Cave-in-Rock have been reported from various states, including Iowa (16,33), North Dakota (1), South Dakota (24), Oklahoma (9), the southeastern US (8), various other US states (7), and Italy (28), with mean yields ranging from approximately 2.0 to 12.6 Mg/ha. Reported yields for other cultivars have been similar or somewhat higher, especially in the southern US or under irrigation (3,5,28). Yields in southern Iowa tend to be slightly lower than the Iowa average (16), ranging from approximately 2.5 to 9 Mg/ha (10).

Switchgrass yields can exhibit significant spatial and temporal variability (9,15,24,32). Virgilio (32) reported yield variability of 3 to 20 Mg/ha within a 5-ha field. Lee and Boe (15) reported Cave-in-Rock yields varied from <2.0 to >9.0 Mg/ha over a 4-year period within a location. Precipitation, persistence, stand density, soil properties, and competition from other plant species were mentioned as sources of variability, but none of these reports considered disease occurrence as a potential source of yield variability.

Switchgrass can be afflicted by a variety of diseases caused by fungi (11,30), but there has been little research on management of switchgrass diseases. There have been a small number of surveys (11,14,30), and diseases of possible economic importance were reviewed by Parrish and Fike (26). Among these are rust, caused by Puccinia emaculata, Barley yellow dwarf virus, Helminthosporium spot blotch (Bipolaris sorokiniana), and smut (Tilletia maclaganii). Some research has been conducted on cultivar responses to diseases, including rust (13) and smut (29), but other management tactics have not been explored.

Switchgrass smut, caused by the fungus Tilletia maclaganii (Berk.) G.P. Clinton, is a widespread, apparently endemic disease in native stands of switchgrass (30). It has been reported from Connecticut, Iowa, Illinois, Kansas, Nebraska, and New York (6). Switchgrass producers in Iowas Chariton Valley experienced declining biomass and seed yields in some fields during the late 1990s, with some fields dropping to about half the expected yield. This led to the recognition of T. maclaganii as a significant problem on switchgrass in southern Iowa (11,12). Smut was present in 15 of 17 fields surveyed in 1999, and an estimated 50 to 82% of the sampled area was infested with T. maclaganii. Incidence in the individual fields ranged from 0 to 70% (12). The disease continues to be a concern for biomass and seed production in southern Iowa.

Fig. 1. Switchgrass plant infected with Tilletia maclaganii showing symptoms and signs just after flowering. Panicles display a purple pigment and brick-red teliospores are exuding from flowers.

 

Smut infection alters the physiology of the switchgrass plant, causing stunted tillers, premature flowering, and replacement of seeds with fungal sori (Figs. 1, 2, and 3). The disease cycle has not been thoroughly investigated, but may be similar to that of Tilletia controversa, the dwarf bunt pathogen of small grains. T. controversa survives as teliospores in the soil or on seed, infects plants through the roots, and grows systemically until flowering, at which time all the kernels of the infected plant are replaced by teliospores. It is not clear whether T. maclaganii also infects by secondary sporidia, but infection can be initiated by incorporating teliospores into the soil in established switchgrass stands (29). Infected panicles emerge in early to mid-June, about a month before healthy ones. A healthy switchgrass plant may reach more than 3 m in height. Height of infected plants is significantly less, and can be less than 1 m tall (Figs. 2 and 3) (11), reducing biomass yields. Some switchgrass seed fields in southern Iowa were a total loss for seed production when infested by smut in 1999 (12). Observations indicated that the profitability of switchgrass production for seed or biomass was noticeably affected by the occurrence of smut, but the extent of this impact was not clear. Therefore, our objectives were to quantify the yield impact of switchgrass smut in fields with naturally occurring epidemics, and to describe the relationship between disease incidence and yield loss. This information, coupled with survey data, can be used to estimate the overall economic impact of the disease.


   

Fig. 2. Switchgrass plant infected with Tilletia maclaganii showing symptoms and signs several weeks after flowering. Teliospores are dark brown and the tiller has senesced prematurely.

   

Fig. 3. Switchgrass plants infected with Tilletia maclaganii (bottom) are stunted and prematurely senescent. Panicles of healthy plants can be seen at top.


Field Sampling and Yield Measurement

In 2002, ten fields (Table 1; Fig. 4) in the Chariton Valley area were selected in order to quantify the effect of switchgrass smut on biomass yields. The fields were selected to represent a range of smut incidence levels, based on prior knowledge (11). All ten fields were planted with the cultivar Cave-in-Rock.


 

Fig. 4. Locations of Iowa switchgrass fields sampled for estimation of yield loss due to smut (Tilletia maclaganii).

 

Table 1. Iowa switchgrass fields evaluated for yield impact of Tilletia maclaganii, 2002.

Field County Township Section number Hectares Date
sampled
1 Lucas Benton 12 22.3 25 Sep
2 Wayne Union 14,15,22,23 50.6 25 Sep
3 Wayne Union 23 10.5 27 Aug
4 Wayne Corydon 12 9.3 24 Sep
5 Wayne Union 27 6.5 24 Sep
6 Appanoose Chariton 9 25.1 27 Aug
7 Lucas Otter 23 19.8 22 Aug
8 Lucas Warren 29 10.5 28 Aug
9 Wayne Union 27 1.6 24 Sep
10 Wayne Washington 13 15.8 28 Aug

Samples were collected from each field to assess smut incidence and biomass yield. Five samples were collected from within each field. A sample consisted of three 1-m subsamples, collected at the center and ends of arbitrarily selected, 50-m transects. At each subsample site, all plant biomass was clipped 15 cm from the soil surface and collected in a large plastic bag. The three subsamples from each transect were combined for data analysis. The samples were transported to the ISU campus and stored in a cold room at 4C until smut determinations could be made. The number of healthy tillers and the number of tillers with smut were counted for each sample. Tilletia maclaganii was identified according to its symptoms and teliospore characteristics, as we described previously (11,12), and according to the key published by Vanky (31). Smut incidence was calculated as the percentage of tillers in each sample that showed disease symptoms. Healthy and diseased tillers were separated and dried at 60C for four days. The dry biomass was recorded and the mean biomass per tiller was calculated for both healthy and diseased tillers. Mean biomass for all tillers in each sample was calculated based on the total dry biomass and total number of tillers. Percent yield loss (25) for each sample was determined using the following formula:

 

yield loss = 100 (1        mean biomass for all tillers     ) [1]
mean biomass for healthy tillers


This definition assumes that there is no yield compensation and the mean yield of healthy plants represents the attainable yield in the absence of disease. It is standardized for variability in stand density among samples.

Data were subjected to analysis of variance (PROC GLM, SAS Institute Inc., Cary, NC), using a nested model structure, to determine differences among field means for stand density (tillers/m), biomass/tiller, and biomass yield (g/m). Mean separations were made using Fishers Protected LSD (α = 0.05). T-tests were conducted to contrast biomass/tiller for healthy and diseased tillers within each field. Linear correlations among the measured variables were assessed using SAS PROC CORR. In order to describe the direct relationship between disease incidence and yield loss per sample, a linear regression analysis was conducted, of the form

                                   Yi =  B0 + B1Zi1 + ui                             [2]

In which Yi is the yield loss for the i-th sample, as calculated in equation 1; Zi1 is the incidence of smutted tillers in the i-th sample; B0 and B1 are the intercept and slope coefficient, respectively; and ui is the i-th error term. A separate linear regression model was developed to describe the yield contributions of healthy and diseased tillers, following the example of Madden et al. (19) (equation 7), when disease incidence data are available. The form of the model is:

                               Yi = B1Zi1 + B2Zi2 + ui                           [3]

in which Yi is the biomass yield of the i-th sample, Zi1 is the number of smutted tillers in the i-th sample, Zi2 is the number of healthy tillers in the i-th sample, B1 and B2 equal the biomass yield per tiller for diseased and healthy tillers, respectively, and ui is the i-th error term. The regression feature of SPSS Ver 14.0 (SPSS Inc., Chicago, IL) was used for regression analysis.


Relationships Among Stand Characteristics, Disease Incidence, and Yield

There are two main components of biomass yield: biomass/tiller and stand density (tillers/m). Both of these components differed significantly among fields. Mean biomass/tiller ranged from 1.6 to 3.5 g/tiller overall and from 1.9 to 4.2 g/tiller for healthy tillers. Stand density ranged from 101 to 266 tillers/m. Growing conditions most likely were responsible for this variation, as all ten fields were the same cultivar. Overall, stand density in all the fields was low compared to some other published reports. Sharma et al. (28) reported a range of 540 to 2868 tillers/m in one- to three-year-old stands of switchgrass in Italy. Most other reports are given in plants/m, with a range of 10 to 20 plants/m considered desirable (26). This plant density would correspond to approximately 300 to 600 tillers/m if plants average 30 tillers/plant, although tillers/plant also is quite variable (27).

Biomass yield also differed significantly, ranging from 174 to 617 g/m (Table 2), which corresponds to 1.74 to 6.17 Mg/ha. The two fields with the highest stand density, Fields 7 and 10, also had the highest yields. Smut occurred in all ten fields, ranging in incidence from 0.7 to 55.4%. Overall, 26% of all tillers found in the sampling areas displayed signs of T. maclaganii infection. The level of disease in the switchgrass fields did not appear to be related to location (Fig. 4). Tillers with smut yielded significantly less than healthy tillers in each field (Table 2; Fig. 5). Yield loss varied from 0.6% to 40.1% among fields (Table 2).


Table 2. Stand density, biomass yield, smut incidence, and impact of Tilletia maclaganii on biomass/tiller and biomass yield for ten southern Iowa switchgrass fields in 2002.

Field Stand density (tillers
/m)
Yield (g/m) Smut incidence (%) Mean biomass/tiller
(g)
Biomass
reduction
/tiller
y
(%)
Yield lossz
(%)
mean std dev healthy diseased overall
1  126 bcx 344 cde 2.2   1.7  2.8 c 0.6 2.7 b 78   1.7
2  129 bc 351 cd 3.2   1.8  2.7 cd 0.5 2.7 b 81   2.6
3  123 c 265 defg 2.4   2.1  2.2 de 1.3 2.1 bc 38   0.9
4  107 c 383 c 0.7   1.2  3.6 b 0.6 3.5 a 82   0.6
5  130 bc 242 fg 9.1   4.3  1.9 e 0.4 1.8 c 79   7.2
6  157 b 252 efg 55.4   7.9  2.7 c 0.7 1.6 c 72 40.1
7  266 a 516 b 51.5   10.2  2.7 c 1.3 1.9 c 53 27.0
8  124 c 330 cdef 49.7   12.5  4.2 a 1.0 2.8 b 75 37.5
9  101 c 174 g 50.8   22.4  2.7 c 0.8 1.9 c 68 34.7
10  237 a 617 a 12.6   8.3  2.9 c 0.9 2.6 b 71   8.9

 x Values in a column followed by the same letter are not significantly different according to Fishers Protected LSD test (α = 0.05).

 y Biomass reduction/tiller = 100 (1 mean biomass of diseased tillers / mean biomass of healthy tillers)

 z Yield loss (%) = 100 (1 mean biomass yield for all tillers / mean biomass yield for healthy tillers)


 

Fig. 5. Dried switchgrass bundles from four subsampling areas: diseased tillers are on the left, healthy tillers at right.

 

There was a strong linear relationship between disease incidence and yield loss, with a slope of 0.66 (standard error = 0.021) and adjusted R = 0.95 (Fig. 6). Confidence interval (95%) for the regression slope was 0.61 to 0.70. The intercept parameter was not significantly different from zero. Therefore, the simple yield loss regression model can be expressed as

                                               L = 0.66 D                                         [4]

In which L represent yield loss (% of biomass) and D represents smut incidence (% of tillers). Yield loss was not correlated with total biomass yield or stand density (data not shown). The yield regression model estimated yield per diseased and healthy tiller as B1 = 1.09 (SE = 0.203), and B2 = 2.76 (SE = 0.106), respectively, with an adjusted R =  0.96.


 

Fig. 6. Relationship between disease incidence and biomass yield loss for smut caused by Tilletia maclaganii in switchgrass, based on 50 strip plot yields from 10 fields in southern Iowa in 2002. Each data point represents the mean of three 1-m subsamples.

 

Our results demonstrate that switchgrass smut significantly affects biomass/tiller. Mean biomass was significantly (P ≤ 0.05) lower for diseased tillers than healthy tillers in each field. This reduction was fairly consistent across eight of the ten fields (68 to 82%). This is consistent with the slope coefficient of the yield loss regression (95% CI = 0.61 to 0.70), indicating that diseased tillers typically yielded only 30 to 39% as much as healthy tillers. The reduction in biomass/tiller was not as severe for fields #3 and #7. Possibly in these fields, some plants were in the early stages of infection and their growth was not yet affected. Based on the mean biomass reduction/tiller and the yield loss regression slope, it is probable that switchgrass growers with advanced-stage smut outbreaks will experience a disease incidence-yield loss relationship ≥ 0.66.

Conversely, we do not have evidence that T. maclaganii affects stand density; there was no relationship between smut incidence and stand density, which suggests that the disease does not reduce stand. Some fields had relatively high yield in spite of a high incidence of smut. Field 7 had the 2nd highest smut incidence but also ranked 2nd for yield because it had the highest stand density among the sampled fields (266 tillers/m). However, our data were not collected in a way to adequately address the potential effect of smut infection on plant survival, and the potential long-term impact of T. maclaganii on stand density warrants additional investigation.


Conclusions and Outlook

This analysis revealed that smut caused by T. maclaganii is having a significant impact on biomass yields of switchgrass in the Chariton Valley, and that yield loss is linearly related to smut incidence. Based on the overall incidence of smut in the sampled fields (26%) and the slope of the disease incidence-yield loss linear regression (0.66), yield loss in 2002 to smut in the sampled fields was 17.0%. A survey conducted in 1999, representing switchgrass production throughout the Chariton Valley, found an overall smut incidence of 10.1% (12). Our analysis estimates that a 6.6% yield loss occurred in Chariton Valley switchgrass production in 1999 due to T. maclaganii.

For several years switchgrass smut has progressively reduced yields in seed production and fields used in biomass production, and it continues to do so. The disease cycle for T. maclaganii is poorly documented, but because switchgrass is a perennial species, it is likely that affected fields will experience chronic disease losses, and little information is available regarding disease management. Stuteville et al. (29) found that the cultivar Kanlow appeared to be resistant to T. maclaganii in a small field trial. Kanlow may have promise as a source of resistance but as a lowland type, it is not attractive for widespread planting in the north-central US. Other sources of resistance should be investigated. Other potential switchgrass smut management tactics include seed sanitation or treatment, and prescribed burning. However, more information is needed on the etiology of this disease in order to understand whether these tactics might be effective, and to develop an overall management strategy for this potentially yield-limiting factor in switchgrass production for biomass.


Acknowledgments

We are grateful to John Sellers, who was instrumental in establishing the sampling locations and collecting data, and to Dr. Lori Carris (Washington State University) and Dr. Lisa Castlebury (USDA-ARS), for assistance with identification of T. maclaganii. This research was supported by Chariton Valley Resource Conservation and Development and the US Department of Energy.


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