Morphology And Physiological Functions Of Plants

Published Date: 02 Nov 2017

Switchgrass (Panicum virgatum L.) cultivars, Shawnee (upland) and Kanlow (lowland) were evaluated for yield response to simulated leaf-mass consumption. The data showed no significant effect of up to 80% simulated insect defoliation on the yield of switchgrass under suitable weather conditions. During the first year of the study with abundant rainfall, a significant reduction in leaf area index (LAI) did not result in a significant effect on switchgrass yield. However, the following year, drought occurred and resulted in significant yield reduction along with reductions in LAI and percent light interception.

Switchgrass cultivars (Shawnee and Kanlow) were tested for their photosynthetic response to simulated leaf injury. Mechanical defoliation with different insect feeding patterns was applied to individual leaves to determine the effect on photosynthetic rates. No significant differences among various patterns of tissue removal were recorded in Kanlow. However, during 2011, double edge cutting treatment significantly reduced the photosynthetic rates in Shawnee. Significant temporal effects were recorded in Kanlow for both years. Photosynthetic rates between the years differed significantly even prior to treatment application likely as a result of water stress in the second year.

The actual feeding rates of nymphs and adults of red-legged grasshopper, Melanoplus femurrubrum (DeGeer) (Orthoptera: Acrididae) were quantified. The average leaf area consumed and the weight gained by each stage of grasshopper were measured after three days of feeding. The results of the study indicated that the third instar of M. femurrubrum consumed the maximum amount per unit of body weight per day while, the maximum weight gain was observed in adults and the fifth instars. These results may explain the higher metabolic rates and digestive efficiencies of immature grasshoppers. The study results suggest control of grasshoppers at early stages is needed to avoid potential economic losses.

Switchgrass: General Introduction

Interest in warm season grasses is increasing for biofuel production (Hopkins et al. 1995). For the last decade, maize (Zea mays L.), sugarcane (Saccharm officinarum L.) and wood have been used for ethanol and bioenergy (Petrulis et al. 1993; Pimentel and Patzek 2005; Tammisola 2010). The cellulose and hemicellulose contents of bioenergy crops are converted into ethanol and the renewable energy characteristics of these crops make them better than fossil fuels (Kim and Dale 2004). In North America, switchgrass (Panicum virgatum L.) has received increasing attention for many reasons (Mitchell et al. 2010). Switchgrass, as a perennial crop, has the capability to regrow following harvest. Moreover, it has the ability to adapt to varied environments and can tolerate a wide range of temperatures, rainfall and humidity (Porter 1966).

Switchgrass, a warm season grass with C4 photosynthetic pathway (Sanderson and Adler. 2008), is native to North America and widely grown in eastern United States (Fig. 1). During the period when cool season grasses are not available, switchgrass serves as rangeland forage for many grazers. However, pre-flowering grazing is best for higher production of switchgrass (Heidman and Riper 1967). Cattle can safely graze on switchgrass while, horses, goats and sheep face problems after grazing on switchgrass because of their increased light sensitivity and disturbance to liver functions (USDA-NRCS 2002).

Switchgrass is classified into upland and lowland cultivars based on its habitat, morphology and genetics (Porter 1966). These cultivars are distinguished from each other by growth requirements (Vogel et al. 1985) particularly of water. Lowland cultivars have better ability to establish in flooded soils while upland cultivars require moderate to dry soil conditions (Hefley 1937; Porter 1966). Lowland varieties are taller and thicker with higher biomass (dry matter) production than upland cultivars (Porter 1966). Both types of switchgrass also differ in nitrogen requirements but this difference is not as great as moisture requirement differences (Vogel 2004). Other variations include the use of soil nutrients such as carbon, potassium, phosphorus and soil pH differences. Upland switchgrass has been successfully grown on less alkaline soil with lower clay content, less phosphorus and higher organic carbon with exchangeable potassium (Porter 1966; Vogel et al. 1985; McLaughlin et. al. 1999). The morphological differences between switchgrass ecotypes were suggested to be related to soil features; however, Porter (1966) found no relationship between soil types and the differences in switchgrass ecotypes.

Figure 1: Switchgrass production regions in The United States (Walsh et al. 2003).

Planting methods for switchgrass vary according to the requirements and land features. Generally, three methods are used for its establishment: 1) conventional tillage with drill planting, 2) no-till planting and, 3) frost seeding method (Rinehart 2006). For the first two methods, dormant or non-dormant seeds can be used but for frost seeding, dormant seeds are planted in late winter or early spring. Seed dormancy is a limiting factor in switchgrass establishment and several methods like stratification and winter seed planting can be used to overcome seed dormancy (Rinehart 2006). Seed size and structure is another hindrance to switchgrass establishment because seeds are too small to connect to the soil (Aiken and Springer 1995). Weed competition in switchgrass fields is another problem that makes seeding success poor (Mitchell et al. 2010).

Switchgrass has high value forage characteristics and soil conservation qualities (Moser and Vogel 1995). It has also been used as an ornamental grass in Europe and America (Elbersen et al. 2001). High cellulosic content of switchgrass may result in higher and better quality biomass and ethanol production (Schmer et al. 2008). Switchgrass requires lesser inputs and production cost when compared with maize. Because of high lignocellulose contents, it has also been used for paper production. When compared to other crops used for ethanol production in North America, switchgrass produces 700% more output than input along with 540% more renewable energy and 94% less CO2 gas emission (Schmer et al. 2008). Switchgrass absorbs soil phosphorus and nitrogen that helps control the excessive nitrification (Kiniry et al. 2005). Furthermore, it reduces soil erosion and plays an important role in native prairie restoration (Alderson and Sharp 1994). Carbon sequestration is another important characteristic of switchgrass (Liebig et al. 2008).

Establishment of Switchgrass

Several factors are involved in successful establishment of switchgrass. For example; field preparation, soils characteristics, physical factors and cultivar selection. To establish switchgrass, a field must be free from the perennial weeds and excessive soil moisture. The suitable soils for switchgrass growth have moderate fertility and texture, are well-drained and have pH ranges between 5.5 and 6.5 (Douglas et al. 2009). Proper maintenance of soil pH using appropriate fertilizers is a useful practice for switchgrass growth (Douglas et al. 2009).

The no tillage planting method has become the most commonly used method for seed planting. For a successful switchgrass stand, seeds are planted at a depth of 0.6 to 1.25 centimeters because of smaller seed size (Aiken and Springer 1995). Seed quality, cultural practices, planting rates and planting dates are also critical for switchgrass establishment. To control weeds, pre-emergence herbicides are often applied before and at the seeding stage.

Being a perennial grass, switchgrass stands have a life span of almost 10 years (Parrish and Fike 2005; Fike et al. 2006). Although switchgrass has the ability to grow in a variety of environmental conditions and lower soil fertility, selection of cultivars is an important factor for successful establishment and production in specific environments (Lemus et al. 2002). Several studies demonstrated the potential differences of productivity among upland and lowland cultivars, for example; Caddo, Alamo, Cane-In-Rock, Dacotah, Trailblazer, Shawnee and various genotypes including SL931, SL932, SL941 and NU942, grown at various locations in the United States (Lemus et al. 2002; Cassida et al. 2005; Lee and Boe 2005; McLaughlin and Kszos 2005) produced substantial differences in yield and varied by harvesting seasons (Adler et al. 2006).

Among physical factors, light interception is critical for production and it ranges from 0% to 100%, where all light photons are utilized in photosynthesis. Reduced light interception causes yield losses in crops (Higley 1992), thus seed spacing to reduce competition among seedling is also critical. In addition, biotic factors including diseases like rust and smut have been reported on switchgrass in different areas of the United States (Stuteville et al. 2001; Gustafson et al. 2003). Some insect pests have also been reported in switchgrass including armyworm, Mythimna unipuncta (Haworth) (Prasifka et al. 2011a), stem boring caterpillars, Blastobasis repartella (Dietz) and Haimbachia albescens Capps (Prasifka et al. 2011b), aphids and grasshoppers (Holguin et al. 2010). The control of these pests is very important because during initial years of establishment, switchgrass is very sensitive. Insect feeding at this time reduces its ability to absorb nutrients from soil that helps weeds to grow and establish in the field.

Cultivars of Switchgrass

Two ecotypes, upland and lowland are distinguished on the basis of their morphology, habitat association (Monti et al. 2001), ploidy levels and molecular markers (Stroup et al. 2003). Lowland cultivars are tetraploid whereas; upland cultivars are hexaploid or octaploid (Stroup et al. 2003). Switchgrass is a cross pollinated plant but no fertilization occurs between different cultivars (Wullschleger et. al, 1996). Lowland cultivars grow in high moisture environments and have higher growth rates than upland cultivars (Lemus et al. 2002; Cassida et al. 2005).

Water and nitrogen are the major factors that affect the productivity of switchgrass cultivars (Epstein et al. 1966) with nitrogen limitation is the most important in reducing production (Redfearn et al. 1997). Upland cultivars are relatively drought tolerant while, lowland cultivars are more sensitive to drought (Stroup et al. 2003). Upland varieties produce comparatively less biomass than lowland ecotypes (Christian and Elbersen 1998). In addition, lowland cultivars require less nitrogen compared to upland cultivars (Porter 1966). The cultivars do not differ significantly in the number of tillers produced; however, upland cultivars have higher numbers of leaves. Additionally, upland and lowland cultivars of switchgrass respond differently to temperature. Lowland cultivars withstand cool temperatures better than upland cultivars while, both cultivars produce higher biomass with increasing temperature (Kandel 2005). Upland cultivars increase biomass by increasing leaves and roots while, lowland varieties increase elongation of stems and leaves with increases in temperature (Kandel 2005).

Biofuel

Biofuel is a carbon-based energy source produced from vegetative biomass. Biomass is a potential renewable energy source obtained from a number of crops. The majority of the bioenergy crops are herbaceous, woody or bunchy perennial grasses (Lemus and Lal 2005). Among various grasses, switchgrass, elephant grass (Pennissetum purpureum Schum.) and tall fescue (Fetusca arundinacea L.) have been used for biofuel whereas; short woody perennials including poplar (Populus spp.) and mesquite (Prosopis spp.) have also been tried as bioenergy crops (Lemus and Lal 2005). Currently, switchgrass, hybrid poplar and willow (Sallix spp.) are receiving the most attention for biofuel (Walsh et al. 2003). Additionally, maize has also been used for biofuel production in North America. Relative to other crops used for biofuel, switchgrass involves lesser production costs and higher biofuel production (Vogel et al. 1985). For instance, switchgrass biofuel production was estimated at 79 million gallons (MMg), when compared with production of hybrid poplar (1.2 MMg) and willow (1.3 MMg) for two years (Walsh et al. 1998). Similarly, cellulosic content and net energy is comparatively higher in switchgrass than other crops used for bioenergy in North America (McLaughlin et al. 1996). The average yield of switchgrass ranges from 5.2 to 11.1 Mg/ha, which can produce 60 Gj/ha/year of potential energy (Schmer et al. 2008). Samson et al. (2000) compared switchgrass and other non-biotic energy sources for greenhouse gas emission and observed significantly less emission of greenhouse gas produced by switchgrass biofuel production.

Switchgrass vs. Maize

Switchgrass is classified as a second generation perennial forage crop, while, maize is classified as a first generation annual crop (Sanderson and Adler 2008). Moreover, Switchgrass and maize differ in ethanol extraction because the former contains lignocellulosic compounds while, the later has starch for ethanol. Ethanol extraction in starchy crops can be carried out by two methods: i) wet milling and ii) dry milling while, the extraction from lignocellulosic crops involves fermentation with addition of enzymes (Cardona and Sanchez 2007).

To increase biofuel production, growers have started growing crops in monoculture cropping system. The consequences of monoculture in maize and switchgrass are very different in terms of management practices and productivity. Using conventional cropping methods for both crops, switchgrass (monoculture) produces 540% more energy output than production cost while, maize (rotation) produces only 25% (Schmer et al. 2008). Maize yield can be increased by 4 to 18% with more bushels/acre with sugarcane rotation (Vyn 2006). However, rotation of crops requires more cultural practices compared to monoculture cropping system and monoculture maize requires the addition of approximately 30-50 pounds nitrogen per acre. In addition, monoculture crops are more vulnerable to insect pests, when compared to alternate cropping system (Vyn 2006).

Switchgrass, as a monoculture crop, has several advantages over polyculture and mixed cropping system in terms of yield and productivity (Wang et al. 2010). It has the ability to conserve soil fertility and favors the following year???s production. Furthermore, insect herbivores cause production losses in maize while switchgrass has a tendency to maintain its productivity despite the presence of insect herbivores (Holguin 2010).

Wild Life and Switchgrass

Warm season grasses serve as habitat for wild animal species and switchgrass can provide an excellent habitat for wild life (Harper and Keyser 2008). The structure and cover of switchgrass provides shelter and food resources to many vertebrates including rabbits, bob whites, turkeys and song birds (USDA-NARCS 2011).

A single harvest of switchgrass per year is helpful to maintain wildlife because delayed harvesting provides overhead cover to wildlife during early summer with no effect on productivity (Harper and Keyser 2008).

Switchgrass and Insect Herbivory

A few insects have been recorded as pests of switchgrass including a stem boring caterpillar (B. repartella Dietz) (Prasifka et al. 2009), new species of gall midges (Chilophaga virgati Gagne??) (Boe and Gagne?? 2011), chinch bug (Blissus leucopterus leucopterus (Say) (Ahmad et al. 1984), fall armyworm (Spodoptera frugiperda J.E.Smith) (Dowd and Johnson 2009), aphids (Kindler and Dalrymple 1999) and grasshoppers (Chu and Knutson 1970). Grasshoppers can be a severe pest of switchgrass because of their behavior (Chu and Knutson 1970). In addition to feeding, they generate clippings in grasslands. Holguin (2010) observed several insects like Draeucolacephala sp., Melanoplus sp., and the family Tettigoniidae in switchgrass fields.

The C3 and C4 grasses are different in response to insect herbivory and defoliation. The stimulatory response of C3 grasses after defoliation is potentially higher compared to C4 grasses across early, intermediate and late growth stages (Anderson and Frank 2003). Insect herbivory can cause grasses to increase vegetative tiller density and maintain productivity (Jewiss 1972) and it may cause a reduction in plant size and increasing plant density (Anderson and Frank 2003). In contrast, initiation in tiller length depends on intensity of defoliation and leaf area removed (Jensen et al. 1990). Initial foliage area removal does not influence the productivity; however, follow up clippings and herbivory may cause a significant impact on plant biomass. Thereafter, herbivory may have a detrimental effect on biomass and plant health, if continued on one part of a plant for a long period (Higley 1992).

Grasshoppers cause significant damage to grasslands (Chu and Knutson 1970). Feeding by immature grasshoppers may cause problems in growth and re-establishment of grasses at early growth stages. Early clipping in switchgrass causes stem length and weight reduction and also, allows weed growth and establishment because of reduced light interception (Baker et al. 1951).

Insect pests are not likely to be a problem for switchgrass until it is grown in extensive monoculture (Parrish and Fike 2005). The monoculture cropping system has a negative effect on insect diversity (Bourn and Thomas 2002) while, herbivore densities become higher (Holguin et al. 2010). Moreover, insect outbreaks occur more often in monoculture cropping system (Andow 1991) because of the lack of natural enemies and the excess of suitable resources for the herbivore species (Root 1973; Gibson et al. 1990).

Plant response to insect herbivory varies and depends on the plant and insect species. Plants activate defense mechanism according to type of insect feeding (chewing or sucking), intensity of herbivory and growth stage of the plant (Peterson and Higley 1996). In warm season grasses, silica acts as an important defensive compound against insects and mammal herbivores. Grasshoppers and fall armyworms have reduced digestive efficiency in the presence of higher silica content of C4 grasses (Nabity et al. 2009). Several traits of switchgrass including lignin, lignocellulose, cell thickness and silica storage produce defense against herbivory (Somerville et al. 2010; Onoda et al. 2011) which have been altered through breeding techniques to increase biomass. Alteration of these traits resulted in more vulnerability of switchgrass to a variety of insect pests and herbivores (Nabity et al. 2009). Lignin concentration may have positive or negative effects on different insect herbivores (Timonen et al. 2005); however, silica always reduces the growth rate and digestion of herbivores (Keeping and Kvedaras 2008). Effect of herbivory has been considered positive under certain circumstances (Dyer et al. 1982) whereas; under most conditions, it has negative impact on plants in terms of photosynthesis, light interception and biomass productivity (Belsky 1986).

Mass Consumption by Insect Herbivores

Taxonomically insects have been divided into many groups based on certain characteristics. However, various studies supported that damage caused by insects from different taxonomic status is not unique (Peterson 2000). Therefore, insets herbivores can be placed into specific groups based on their injury mechanisms (Metcalf et al. 1962; Bardner and Fletcher 1974). According to the damage produced by insects, five injury guilds have been established by Boot (1981) including leaf consumers, sap utilizers, fruit feeders, stand reducers and turgor reducers. Whereas; several other insect categories have proposed on the basis of the injury types and physiological effects on host plants (Pedigo et al 1986; Higley et al 1993).

Several studies have been conducted on mass consumption by various insect defoliators on different crops. The purpose of these leaf-mass consumption studies was to group the insects that are producing similar physiological effects on crops after feeding (Peterson 2000). Several insect defoliators including soybean looper (Pseudoplusia includes Walker), velvetbean caterpillar (Anticarsia gemmatalis H??bner), beet armyworm (Spodoptera exigua H??bner) and bean leaf beetle (Ceratoma trifurcate (Foster)) were allowed to feed on soybean leaves to test the impact of feeding on photosynthetic response of soybean and it was determined that these insect defoliators produced similar injury effects in soybean (Hutchins et al. 1988). Similar study was conducted by Hutchins et al. (1990) with alfalfa weevil larvae and adults (Hypera postica Gyllenhal), clover leaf weevil larvae and adults (Hypera punctate Fabricius) and variegated cutworm larvae (Peridroma saucia H??bner) regarding alfalfa response to defoliation and it was reported that these insect feeders produced similar effects on plants and reduced plant growth and maturity. Mass consumption by various insects especially for leaf consumers has investigated successfully for their uniform feeding effects on soybean, alfalfa and potato crops (Hutchins et al. 1991; Peterson et al. 1995; Peterson 2000). Insect division on the basis of their impacts on host plants is greatly helpful in the development of economic injury levels of multiple species and also gives the remarkable benefits during the pest management techniques and programs (Peterson 2000).

Insect Life Stages and Food Consumption

Many generalist and specialist insect herbivores belong to the orders Coleoptera, Lepidoptera, Hemiptera and Orthoptera (Schoonhoven et al. 2005). On the basis of feeding habits, herbivores are classified into monophagous, oligophagous or polyphagous insects. Monophagous insects feed on one or few closely related plant species. Some lepidopterans, coleopterans and hemipterans are considered as monophagous insects (Chapman 1990). Oligophagous insects include herbivores that feed on a number of plants species, often belonging to same family. Colorado potato beetle (Leptinotarsa decemlineata Say) and Cabbage white butterfly (Pieris rapae L.) are examples of oligophagous insects (Klausnitzer 1983), while polyphagous insects feed on a large number of plant species belonging to diverse groups and families and include aphids (Chapman 1990) and most grasshoppers (Thompson and Gardner 1996).

Host plant selection by herbivores depends on a number of factors including host plant biology, characteristics, nutritional value and availability. Different stages of an insect may feed on different foods and the amount of food consumed varies with the life stage of insect (Delvi and Pandian 1972), condition and nutritional value of the available food (Stork et al. 2001).

Grasshoppers are among the most important pests of agricultural crops throughout the world (Gangwere et al. 1997; Weiland et al. 2002). Most species of grasshoppers are polyphagous feeders and some species cause extensive damage to almost every crop. (Gangwere et al.1997). Both nymphal and adult stages of grasshoppers are able to cause damage at the same time. Unlike many lepidopteran and coleopteran insects, both the immature and adult stages of grasshoppers are potential feeders on the same host plant. However, the damage caused by grasshoppers depends on many factors including their population density, growth stage, body size, weather conditions and, plant vigor and plant stage (McGinnis and Kasting 1967; Begna and Fielding 2003).

The maximum food consumption has been recorded in last 2 or 3 instars of many insects (Lafon 1951; Dadd 1960; Waldbauer 1964). The members of the insect order, Lepidoptera including Bombyx and Protoparce consume the most food (99%) during the last three larval instars to store energy for the non-feeding stage (pupa) (Waldbauer 1968). Insects belong to the order Orthoptera consume 70% of the total nymphal food during the last instars (Waldbauer 1968). Schistosrca gregaria Forskal (Orthoptera: Acrididae) consumes almost 63% of the total food during the fifth nymphal stage (Davey 1954; Norris 1961; Husain et al. 1946). Waldbauer (1968) reported that the feeding rate per gram of body weight by insects decreased with increase in approximate digestibility (A.D.) and A.D. of the orthopteran insects including Locusta migratoria L., Melanoplus bilituratus (Sauss.) and S. gregaria is almost 34-40% during the fifth instar indicating their high feeding rates compared to first two instars with 97% A.D. (Brenniere et al. 1949; Smith 1959; Dadd 1960) and adults with 54% or above A.D. (Waldbauer 1968). In addition, higher feeding per gram of body weight by immature insects with low A.D. values did not cause more weight gain (Delvi and Pandian 1972), however; overall food consumption is higher in adults with higher weight gain indication their higher assimilation rates (Waldbauer 1968; Delvi and Pandian 1972).

Plant response and Insect Herbivory

Photosynthesis and Insect Herbivory

Insect herbivory reduces the leaf area and disturbs the leaf physiology (Delaney and Higley 2006). Defoliation losses may be compensated to a certain limit by the plants through enhancing photosynthetic rates; however, excessive feeding damages photosynthetic apparatus and causes reduction in photosynthetic rates along with plant growth and leaf area (Welter 1989). Effects of herbivory depend on the part of plant injured and the defensive mechanism of the effected plants (Alward and Joern 1993). Hence, defensive system of plants uses the available resources within the plants to overcome and compensate for losses (Zalucki and Malcolm 1999). Physiologically, excessive herbivory by insects disturbs the source-sink relationship of the plants that reduces the photosynthetic activity of the injured leaf tissues while, defense chemicals rupture the photosynthetic mechanisms (Peterson 2000). Indirect effects of herbivory on photosynthetic rates of plants include severe vasculature, altered sink demand, defense related auto toxicity and defense induced down regulation of photosynthetic rates (Delaney and Higley 2006).

Most entomological studies deal with and concentrate on insect herbivory and its impacts on plant growth and yield but the physiological phenomenon and physical characteristics responsible for subsequent plant response have not been considered (Peterson and Higley 1993; Delaney et al. 2008). Plant response to herbivore injury varies across the plant species, although the type of injury, for example; phloem feeding, stem boring and leaf mining produce diminishing effects on photosynthetic rates (Welter 1989); however, foliar herbivory may increase, decrease or unaffected the photosynthetic rates of remaining leaf tissues on the plant canopy (Meyer 1998; Zangerl et al. 2002; Mercader and Isaacs 2003).

Numerous studies have documented the loss in production, photosynthesis and leaf areas as a result of insect herbivory (Alderfelder and Eagles 1976; Hall and Ferree 1976; Li and Proctor 1984). Additionally, Insect herbivory disturbs the physiology of not only injured leaves but also the nearby uninjured leaves (Welter 1989; Neves et al. 2006). In contrast, several studies did not find long term effects of insect herbivory on photosynthetic rates and growth of damaged plants (Higley 1992; Peterson and Higley 1996).

Despite the fact that the insect defoliation sometimes does not affect the plant photosynthesis; however, loss in plant dry matter due to reduced photosynthetic area has been observed (Boote 1981). Plants have different ways to recover losses caused by herbivory including delayed leaf senescence, changing transpiration, stomatal conductance, fasten their leaf growth and increasing number of leaves on meristem points (Peterson et al. 1992).

Other Factors Affecting Photosynthesis

Abiotic Factors

Environmental Factors

Light Intensity: Photosynthesis is affected by intensity of light. Increase in light leads to greater photosynthetic rates continuous until chloroplasts become light saturated (Kramer and Kozlowski 1979). However, high temperatures and drought conditions may affect the photosynthetic rates, despite availability of light intensity (Powles 1984).

At night, plants respire using photosynthetic products and release carbon dioxide in the air. During the day with increased intensity of sunlight, the photosynthetic rates increases until equilibrium is established between carbon dioxide and oxygen levels of plant (Kramer and Kozlowski 1979). At this point, there is no net gas exchange between the atmosphere and plant because plant is producing its own resources for respiration and photosynthesis. The light compensation point of the plant is based on the light intensity but varies with other factors like leaf age (new or old), leaf position (shaded or in exposed), carbon dioxide concentrations of the air and, temperature (Kozlowski et al. 1991; Powles 1984). The ability to compensate light is higher in younger and light exposed leaves than in older and shady leaves (Kozlowski et al. 1991). The higher temperatures increase the respiration rates with subsequent greater release of carbon dioxide; however, the potential of photosynthetic rates become lower with increase in respiration (Kramer and Kozlowski 1979). Similarly, the above canopy leaves have higher photosynthetic rates than below canopy or ground level leaves because of the amount of light received.

In the presence of higher light intensity, increase in photosynthetic rate of leaf occurs at linear points. But if light intensity keeps on increasing, leaf starts decreasing its photosynthetic rates due to light saturation in leaf. Leaf also shows fluctuation in photosynthetic rates, when after saturation point; the light intensity keeps on increasing (Kozlowski et al. 1991). The variable response of the different plant leaves towards the light intensity also depends on the genetic diversity among the plants (Kramer and Kozlowski 1979).

Air Temperature: Photosynthetic rate in plants varies at various temperatures. Plants can perform photosynthesis at temperatures above freezing to 40oC (Kramer and Kozlowski 1979). Usually the response of a plant to air temperature depends on the plant genotype, plant age, plant origin, season, light intensity and supply of CO2 to the plant leaf. An increasing trend of photosynthesis in plants is noticed with increasing temperature from 15 to 25oC (Lange et al. 1974). Whereas, the effect of air temperature changes with the changing trend in light, soil temperature, carbon dioxide availability and water supply. Low temperature usually at chilling, create problems to photosynthesis but if injury does not occur, the recovery in photosynthetic rate occurs after 2-6 days (Mooney and Shropshire 1967; Slatyer and Ferrar 1977). The decrease in temperature influences the capability of leaf to absorb carbon dioxide from the surroundings. The optimal range of temperature for plant photosynthesis depends upon their growth places and altitudes (Pallardy 2008). The plants are habitual according to their habitats and develop the optimal ranges of temperature for their best performance (Kramer and Kozlowski 1979; Pallardy 2008).

Plants have ability to recover their photosynthetic rates back to the initial points after exposure to the opposite conditions to those who bring them to lower photosynthetic rates. When plants lose their photosynthetic rates due to high temperatures, they can recover their photosynthetic rates by exposure to lower temperatures (Pallardy 2008). In the same way, if the plants are exposed to lower temperatures, they shut down their photosynthetic apparatus and go into dormancy until the environment becomes suitable for them. On the other hand, to overcome unsuitable situations, plants also change their photosynthetic apparatus including, changes in enzymatic activity, chloroplast structure, electron transport chain and stomatal closure (Zelawski and Kucharska 1969).

Soil Temperature: The effect of soil temperatures on the leaf photosynthesis is same as that of the air temperature. Usually, the decrease in soil temperature decreases the leaf photosynthesis. The inhibition of photosynthetic rates depends upon soil temperature and plant resistance to chilling and frost (Kozlowski and Pallardy 1997). Some studies showed that the shoot water potential decreases with the decrease in soil temperature causing leaves to close its stomata (Turner and Jarvis 1975). Closure of stomata lowers conductance and gas exchange. In case of higher soil temperatures, chlorophyll and carotenoids content decreases and increase the leaf soluble proteins causing negative effects on photosynthetic apparatus of leaf. Enzymes get disturbed by the increase or decrease in soil temperature and cause changes in photosynthetic apparatus that ultimately lead to the reduction in photosynthetic rates of the plants (Kozlowski and Pallardy 1997).

Carbon dioxide: Carbon dioxide concentration plays an important role in plant photosynthesis (Dungan et al. 2007). It is the major component of the photosynthetic reaction that leaf utilizes to produce photosynthate. The normal photosynthetic rates are not possible under no or low carbon dioxide concentration (Kramer and Kozlowski 1979). In plants, stomatal conductance plays important role for the in and out movement of carbon dioxide. Increasing carbon dioxide concentration enhances photosynthetic rates in plants and dry weight of leaves (Pallardy 2008).

Soil Water Contents: water is important component to maintain the photosynthetic rates of plants. Reduction in water results in stomata closure, declining carbon fixation efficiency (enzymes become less active in less water availability), and suppressing the leaf formation and finally, leaf shedding of (Pallardy 2008). Drought conditions cause a 75% drop in the normal photosynthetic rates of plants. Decrease in soil moisture contents results in the activation of hormonal system of plant that transfer signal from root to leaf that initiate stomatal closure to prevent the excessive moisture loss from plant (Parker and Pallardy 1991). It is critical for a plant to maintain enzymes and hormones to withstand lower water contents (Huffaker et al. 1970).

Leaf Water Potential: Deficiency in leaf water affects the stomatal closure that reduces the concentration of carbon dioxide available for photosynthesis. Drought conditions usually result in the loss of connection of water between roots and shoots. Like soil water contents, lowering the leaf water potential also disturbs the photosynthetic rate of the leaf (Kramer and Kozlowski 1979; Kozlowski and Pallardy 1997).

Humidity: Effect of humidity is not very clear on the photosynthesis. Leaf responds by stomatal closure when the leaf to air vapor pressure difference increases. In case of rain or mist, the photosynthetic rate of leaves reduces (Kozlowski and Pallardy 1997). Plants can partially recover the decrease in photosynthetic rates when exposed to the normal environmental conditions. Generally, humidity does not adversely affect the leaf photosynthesis compared to drought (Pallardy 2008).

Biotic Factors

Plant Factors

Stomatal characteristics: Variation in stomatal size, frequency, aperture, and occlusion influence stomatal conductance and rate of photosynthesis (Siwecki and Kozlowski 1973). The process of photosynthesis stops at the lower rate of metabolism where CO2 requirement decreases while, its amount increases in intercalary spaces (Kriedemann 1971).

Source-Sink Relationship: Photosynthesis is greatly influenced by the rate of translocation of photosynthetic products from source to sink (Kozlowski 1992). Source-sink balance in plants is very important to keep the leaf photosynthesis at required rates. The Source-sink balance in plants is as important as the Carbon-Nitrogen balance. Disturbance in balance disturbs the occlusion rate of the plants. Several cultural practices, for example; thinning, pruning and irrigation affect the source-sink relationship that may influence the photosynthetic rates (Flore and Lakso 1989).

Age of leaf: Usually, leaf photosynthetic rate increases in adult leaf stage when they are fully expanded and exposed to sunlight (Pallardy 2008). The changes in photosynthetic rates of leaves are associated with various anatomical and physiological changes that occur in leaves during their life (Dickmann 1971). The increase in photosynthetic rates at adult stage is associated with leaf expansion, fully development of internal tissues, increases in stomatal size and conductance, active photophosphorylation, active photosynthetic electron transport, protein synthesis, rubisco and other enzymes activity (Pallardy 2008).

Weeds: Weeds are the major competitors of crops in the field and compete for space and nutrients (Iqbal and Wright 1999). The nutritional deficiency in plants leads towards the less vigorous plants that have indirect effect on plant photosynthesis. Weed competition reduces photosynthesis rates due to the stomatal or non-stomatal factors. The leaf area is not fully attained due to nutrient deficiencies and decrease in stomatal density (Iqbal and Wright 1999).

Diseases: Fungi, bacteria and virus are three major categories of microorganism that cause problems in plant life and affect the photosynthesis (Buchanan et al. 1981). The diseases caused by these pathogens disturb the chloroplast structure of the plant. The diseases caused by pathogens also disturb or inhibit the phosphorylation of chloroplast (Owen 1957). These agents also disturb and inhibit the electron flow from water to Nicotinamide Adenine Dinucleotide Phosphate (NADP) that leads to the inhibition of the photosynthetic carbon dioxide assimilation (Smith and Neales 1977). Some studies have supported the effect of microorganisms on the activity of the photosynthetic enzymes like riboluse-1, 5-bisphosphate carboxylase (Buchanan et al. 1981). Non disease causing soil microorganisms help plant to degrade and recycle the plant nutrients and make them available for plants and also cause aeration in soil (Buchanan et al. 1981).

Photosynthetically Active Radiation (PAR) and Insect Herbivory

Photosynthetically active radiation (PAR) is the intensity of sunlight that can be utilized by plants for physiological functioning, growth and biomass production (Alados et al. 1996). Percent light interception is the proportion of PAR which actually interacts and absorbs by the plant canopy leaves for their active functioning. Light absorption depends on the pattern and architecture of the crop leaves (Madakadze et al. 1998). Plant canopy architecture can be modified by several abiotic and biotic factors (Haile 2000). Abiotic factors include temperature, moisture, nutrient availability and light while; biotic factors include insect herbivores, pathogens and other competitors plants (Haile 2000).

Warm season grasses are very active users of sunlight with rapid early leaf growth and high yield (Muchow et al. 1990). Lowland cultivars of the switchgrass are more robust and heighted compared to upland cultivars, so they have more capacity to absorb and utilize sunlight and produce more biomass (Brunken and Estes 1975). The capability of a canopy to absorb and utilize the active radiations is affected by the insect herbivores as they consume plant herbage and the available leaf area to interact with sunlight decreases while, sometimes herbivory helps to expose the leaves underneath canopy layer that have not been exposed to sunlight (Welter 1989; Trumble et al. 1993).

As a result of defoliation, the plant canopies recover leaf area losses by different ways without disturbing physiological phenomenon including photosynthesis (Board et al. 1997). Compensatory responses of injured plants against insect defoliation include delayed leaf senescence, produce more leaves, branching and tillering (Rubia at al. 1996; Haile et al. 1998).

Leaf Area Index (LAI) and Insect Herbivory

Leaf area index (LAI) is the ratio of leaf area to ground area. The critical LAI of any crop is the one, when crop interacts with 95% of photosynthetically active radiations (Higley 2000). Insect herbivory affects plant leaf area that ultimately reduces LAI of the plant canopy. Lower value of LAI indicates the thinner layer or lesser foliage on canopy (Trumble et al. 1993). The relation between LAI and photosynthesis is very obvious for any crop biomass production. Sometimes, defoliation causes reduction in leaf area index of the canopy but this reduction may not necessarily reduces the overall photosynthetic rates of the effected plants (Trumble et al. 1993). After insect herbivory, plants compensate for damage by increasing their leaf growth and leaf size (Kolodny-Hirsch and Harrison 1982) and delaying their leaf senescence (Gifford and Marshall 1973). Standard LAI values for many crops have been established (Davidson and Donald 1958) and below standard LAI values, the overall photosynthetic rates of the canopy and biomass production have reduced (Evans 1978).

Classen et al. (2005) conducted an experiment with a stem boring moth (Dioryctria albovittella Hulst.) and reported that no changes in LAI of the defoliated trees were recorded during the experiment. They concluded that the insect defoliated the trees in a way that it did not disturb the canopy architecture and thus, the changes in LAI were not captured by the LAI meter. Whereas, Brown (1994) supported the fact of reducing LAI following insect herbivory by conducting an experiment on leaf beetle [(Trirhabda canadensis (Kirby)] foliar injury on goldenrod (Solidago Sp.). Despite, reduction in leaf area, microclimates of canopy and soil can also be altered following defoliation that can change the quality of biomass (Classen 2004; 2005).

A linear relationship exists between LAI and light interception of the canopy of forage and bioenergy crops (Higley 2000). A crop canopy offers the leaf area to absorb sunlight and utilize it for biomass production (Redfearn et al. 1997; Haile 2000). The lower LAI represents the thin layer of foliage that ultimately provides comparatively small surface to interact with active photosynthetic radiations (Trumble et al. 1993). Insect defoliation and herbivory is one of the reasons that cause reduction in exposed leaf area to sunlight that consequently leads to the reduced light absorption by the effected canopy and results in lower net biomass production (Higley 2000). Optimum LAI values for several crops have been established at which maximum light absorbed by the crops to produce higher biomass (Ziems et al. 2006).

Actual and Simulated Insect Defoliation

Numerous studies have been conducted on the actual insect defoliation and simulated insect defoliation for several plant species to evaluate the photosynthetic response and activity of plants (Poston et al. 1976; Hammond and Pedigo 1981; Ostile and Pedigo 1984). Majority of the studies indicated no differences between insect and simulated defoliation because of similar plant response to both types of defoliations (Ingram et al. 1981). Poston et al. (1976) performed an experiment on soybean against mechanical defoliation and actual insect defoliation and reported no difference in the photosynthetic rates of injured leaves. Similarly, the experiment was conducted on several legume cultivars including Medicago sativa Cimarron, Medicago scutellata (L.) Sava, Medicago truncatula Gaertner Paraggio, Melilotus officinalis (L.) Pallas, Trifolium hybridum L., and Trifolium pretense L. against simulated and actual insect defoliation and reported that both defoliation types did not produced significant difference in response among the cultivars (Peterson et al. 2004). Peterson et al. (1992) suggested that the more precise and refined quantification of injury is obtained by simulated insect defoliation and it is more reliable compared to actual insect defoliation. Similarly, individual leaf response against defoliation can also be recorded accurately by simulated insect defoliation (Welter 1989).

Study Objectives

The review of literature regarding insect herbivory and plant response illustrated that a lot of work has been accomplished against the effects of insect defoliators and leaf mass consumers on the number of economically important crops for instance, soybean, alfalfa and maize. These studies revolved around the crop responses including photosynthetic rates, leaf area index, percent light interception and yield following actual and simulated insect feeding by foliage consumers. This aspect of insect herbivory towards switchgrass is lacking, although a number of leaf-mass consumers have been reported in switchgrass fields in past few years.

The review of literature regarding switchgrass revealed that it yields comparatively high biomass and it has been explored as an excellent source for biofuel energy. However, switchgrass is subject to insect herbivory and its yield response to defoliation has not been thoroughly investigated. Therefore, I propose a dissertation hypothesis that insect herbivory affects the quality and quantity of switchgrass biomass production. The overall goal of my dissertation is to ascertain the switchgrass biomass response to insect herbivory with specific objectives as follows:

Determine the yield losses in switchgrass cultivars in response to different levels of simulated defoliation in relation to leaf area index (LAI) and percent light interception.

Evaluate the photosynthetic rates in lowland and upland cultivars of switchgrass applying different simulated chewing patterns of insects and to predict the temporal impact on individual leaf response.

Quantify the actual feeding rates of grasshoppers as nymphal instars and adults to determine the most destructive feeding stage.

Chapter 2

Effect of Simulated Insect Defoliation on the Yield Response of Lowland and Upland Cultivars of Switchgrass (Panicum virgatum L.)

Abstract

Insect herbivory is a potential limiting factor for establishment and production of any crop. Switchgrass (Panicum virgatum L.) is an efficient C4 grass being considered for biofuel production and is known for tolerance against a number of insect herbivores. The yield of two switchgrass cultivars, Shawnee and Kanlow, was evaluated against simulated grasshopper feeding at the vegetative stage. Defoliation was generated based on leaf area index (LAI). Following defoliation, no significant reductions in yield were found with up to 80% defoliation in 2011 whereas; changes in LAI were significant at the end of the experiment. Reduction in yield was observed during the second year of the study with 100% defoliation. Drought in 2012, likely was a factor responsible for the observed differences. Moreover, stem weight may also play a role in sustained yield after defoliation. Grasshopper defoliation does not appear likely to cause significant yield losses unless there are a large number of grasshoppers during periods of abiotic stresses.

Key words: Grasshopper herbivory, switchgrass, defoliation, leaf area index, percent light interception.

Introduction

Warm season grasses have high potential for biomass production, provide soil conservation and offer a potential source of renewable energy (Madakadze et al. 1998). Grasses have also been explored to offset global warming by assimilating CO2 (Graham et al. 1992). Switchgrass (Panicum virgatum L.) can grow in a variety of environmental conditions (Porter 1966) and has been classified into upland and lowland cultivars based on habitat, genetics and morphological characteristics (Porter 1966; Vogel et al. 1985). Lowland cultivars have the ability to establish in flooded conditions while, upland cultivars require drier soils (Hefley 1937; Porter 1966). Besides water requirement, both cultivars differ in nitrogen needs for their growth (Vogel 2004). Soil pH tolerance, carbon and other soil nutrients requirements also vary to some extent between these cultivars (McLaughlin et al. 1999).

Insect herbivory is one of the major threats that limit productivity of crops (Higley 2000) but in some cases, defoliation stimulates plants to compensate for losses and produces positive impacts on crop yield (Higley 1992; Peterson et al. 1992). Although the stem boring caterpillar, Blastobasis repartella (Dietz) and the fall armyworm, Spodoptera frugiperda (J.E. Smith) have been reported as potential pests for switchgrass (Prasifka et al. 2009; Adamski et al. 2010), no detailed studies are available in relation to insect grass tissue removal and yield losses in switchgrass. The grasshoppers (Orthoptera: Acrididae) are generalist feeders and can cause economic damage to rangeland forage. Besides consumption, they also cause damage by clipping vegetation (Chu and Knutson 1970). During unfavorable conditions for crop growth, grasshoppers can cause severe damage. For instance, dry climatic conditions are not favorable for warm season grasses but support increased grasshopper populations (Edwards et al. 1992).

Light plays a key role in plant productivity and physiological functioning. When insects feed on leaves, the leaf area index (LAI) interacting with sunlight is reduced and can lead to reduced productivity of crops. However, dense canopies are helpful against defoliation as undestroyed leaves become exposed to sunlight after defoliation and play an active role in compensation (Lee and Bazzaz 1980). Light captured by plants can be measured in terms of percent light interception and is helpful in determining the relationship between leaf area, light interception and plant productivity (Ziems et al. 2006). Switchgrass has uniform tiller structure throughout the growing season (Mitchell et al. 1998) which provides potential for all leaves to utilize sunlight.

The objectives of this study were to estimate yield losses in switchgrass cultivars with changes in LAI and percent light interception as a result of simulated insect feeding damage. This study involved testing yield losses in switchgrass cultivars (Shawnee and Kanlow), by applying mechanical defoliation simulating insect feeding patterns and correlated the changes in LAI and percent light interception with the impacts on yield. The hypothesis was the leaf-mass consumption by arthropods affects the productivity and fitness of switchgrass cultivars.

Materials and Methods

Experiment 1 (2011)

The study was conducted at the Agricultural Research and Development Center (ARDC), Mead, NE, during summer, 2011. The high yielding cultivars of switchgrass, Kanlow and Shawnee, were evaluated in this study. The upland cultivar, Shawnee was planted in May, 2006 on an area of 23 hectares while, Kanlow was planted in May, 2010 on an area of 6.8 hectares. Shawnee was planted in Filbert silt loamy soil with a slope of 0 to 2% while, Kanlow was grown in Yutan silty clay loam soil with 2 to 6% slope. Natural rainfall was the only source of water for both crops. For pre-emergence weed control, a ratio of 2.22 liter atrazine and 0.5 liter quinclorac per hectare was applied for both fields. For broadleaf weed control, mowing and spraying with 4.45 liter per hectare of 2, 4-Dichlorophenoxy acetic acid was applied during the month of July. Both cultivars were at the vegetative stage (Moore et al.1991) during the experimental period.

Percent light interception and LAI were measured on odd numbered days of the experiment. For both cultivars, the initial LAI was about 5 while, initial percent light interception was about 95%. Measurements and application of treatments were carried out from July 6 to July 15 for Kanlow and July 8 to July 17 for Shawnee.

Sixteen plots of one square meter were randomly selected for each cultivar. These plots were selected carefully for their uniformity and density. Each plot was approximately a meter distance apart. A completely randomized design with four replicates of each treatment was used. The treatments were 0, 40, 60 and 80% mechanical defoliation and were gradually applied following the grasshopper feeding pattern within a period of ten days. A computer generated model, DEFOL (L. G. Higley, unpublished 1988), was used to generate the defoliation area for each day. Defoliation was applied on various parts of the plants equally. Total defoliated leaves for each plot were kept in separate paper bags and their area was measured in the laboratory using leaf area meter (LICOR-3100; Li-Cor, Lincoln, NE) daily. The measured leaf area was then projected in DEFOL for each treatment to generate the target amount of defoliation for the next day. To generate initial leaf area input for DEFOL, a plot of one square meter from the same fields of Shawnee and Kanlow was collected and measured.

At the beginning, LAI for each plot was measured taking one above and three below canopy readings using a plant canopy analyzer (LAI-2000; LI-Cor, Lincoln, NE). For Shawnee, LAI was recorded at the first, fifth, seventh and tenth day while, for Kanlow, it was recorded at the first, third, seventh and tenth day of the experiment. Percent light interception was recorded taking one above and two below canopy readings using a one meter line quantum sensor (LAI-191; LI-Cor, Lincoln, NE) connected to a data logger (LI-1000; LI-Cor, Lincoln, NE) before starting the experiment. Percent light interception was recorded at the first, fifth and tenth day for Shawnee and at the first, third, seventh and tenth day for Kanlow. The LAI was recorded between 7 AM and 10 AM while, percent light interception was recorded between 10 AM and 2 PM. Percent light interception of each canopy was calculated using above and below canopy readings of the quantum sensor. On the eleventh day of the experiment, all plots were harvested form their base and were dried by placing in a drying oven for five days at 32oC in the Stewart seed laboratory at the University of Nebraska-Lincoln. After drying, yield was quantified by weighing the dry mass.

Experiment 2 (2012)

The same fields of Shawnee and Kanlow were used during 2012. A completely randomized design with four replications of each treatment was used. The treatments; 0% (no defoliation), 10 and 20% mechanical defoliation were applied to reach 100% defoliation in 10 days and 5 days, respectively. Twelve plots of one meter square were selected randomly with uniform density in Kanlow and Shawnee. To estimate the per day defoliation, a plot of one meter square was selected and initial measurements for leaf area were calculated. Defoliation was applied at all levels on the plants uniformly. The defoliated leaves for each day were placed in separate paper bags and the leaf area was measured daily in the laboratory to calculate the target defoliation for the following day.

Percent light interception and LAI were measured almost every day of the experiment because of excessive defoliation. For both cultivars, LAI was about 5 and percent light interception was 96% at the beginning of the experiment. Measurements and defoliation were carried out from June 24 through July 3 in Kanlow and June 26 through July 5 in Shawnee. The plots were harvested at the eleventh day and dried for five days before mass was measured as in 2011.

Statistical Analysis

The two years of data for percent light interception and LAI were analyzed separately using the GLIMMIX procedure in SAS (SAS Institute 2009). A repeated measure analysis of variance (ANOVA), with the factors treatment (the error term being plot within treatment) and time (the residual error being the error term) as well as the treatment by time interaction, was used. Appropriate covariance structures were chosen based on Akaike information criteria. The yield data were also analyzed separately for both years using one-way ANOVA through the MIXED procedure in SAS (SAS institute 2009).

Results

Kanlow 2011

Yield

The ANOVA showed no significant reductions in Kanlow yield despite 40, 60 and 80% defoliation over the ten days compared to control plots during 2011. The overall reduction in yield was recorded from 7.5 to 6.5 103kg/ha between control and defoliated plots (Fig. 2).

Percent light interception

No significant changes in percent light interception of Kanlow were observed during the ten days of the experiment. The control plots continued to increase light interception while defoliated plots showed reductions in light interception (Fig. 3). The plots with 40% defoliation showed an increase in light interception from the seventh day to onwards and attained the initial level of percent light interception at the tenth day of the experiment. The plots with 60% defoliation also showed some increase in light interception after the seventh day of defoliation but were unable to reach the initial level of percent light interception at the end of the experiment. The plots with 80% defoliation showed steep decline in light interception but after the seventh day of the experiment this reduction in light interception was at lower rate (Fig. 3).

Leaf Area Index (LAI)

A decline in LAI of treated plots was recorded with significant interaction effect of treatment and time (p < 0.00001). The control plots showed increases in LAI throughout the experiment while, fluctuations in LAI of defoliated plots were observed (Fig. 4). Significant reductions in LAI of 40, 60 and 80% defoliated plots (p = 0.033, p = 0.011 and p = 0.006, respectively) were recorded at the seventh day of the experiment. These significant reductions in LAI of defoliated plots still existed (P = 0.003, 0.003 and 0.002, respectively) by the end of the experiment.

Shawnee 2011

Yield

The ANOVA showed no significant changes in Shawnee yield during 2011 in response to defoliation. The overall reduction in yield was recorded from 7.5 to 6.0 103kg/ha between control and defoliated plots by the end of the experiment (Fig. 5).

Percent Light Interception

During 2011, a significant interaction effect of time and treatment (p = 0.0203) was found for percent light interception in Shawnee. Significant reductions in percent light interception of 40, 60 and 80% defoliated plots compared to control plots were recorded on the last day of the experiment (p = 0.0222, p = 0.0310 and p = 0.0010, respectively). An increasing trend of light interception was noticed in control plots (Fig. 6). The plots with 40 and 60% defoliation showed declines in percent light interception after the fifth day of the experiment but the light interception was still higher than the initial light interception of the respective canopies. In contrast, a steep decline in percent light interception of 80% defoliated plots was observed (Fig. 6).

Leaf Area Index (LAI)

For Shawnee, ANOVA indicated a significant effect of treatment, time and treatment by time interaction (p < 0.0001, p = 0.0242 and p = 0.0060, respectively). Significant differences between control plots and 40, 60 and 80% defoliated plots were recorded by the fifth day of the experiment (p = 0.0342, 0.0439 and 0.0016, respectively) and these significant differences were continued between treated and control plots until the end of the experiment (p = 0.0001, p < 0.0001 and p < 0.0001, respectively). The plots with 40% defoliation showed an increase in LAI by the fifth day and then a slight decline was observed after the seventh day of the experiment but they maintained their initial levels of LAI by the end of the experiment. No increases in the LAI were observed for 60 and 80% defoliated plots by the end of the experiment (Fig. 7).

Kanlow 2012

Yield

During 2012, significant yield reductions were recorded in Kanlow (p = 0.0062). The yield varied from 10 to 4.0 103kg/ha for control plots and defoliation plots with maximum reduction in yield recorded from the plots with 100% defoliation within 5 days (Fig. 8).

Percent Light Interception

During 2012, treated plots of Kanlow showed the significant effects of treatment, time and treatment by time interaction on percent light interception (p = 0.0003, p < 0.0001 and p < 0.0001, respectively). The control plots showed an increase in percent light interception but 10% and 20% daily defoliation produced reduction in light interception after the second day of the experiment (Fig. 9). The defoliated plots showed an increase in percent light interception at the end of experiment but this increase was significantly lower than control plots (p < 0.0001 and p = 0.0002 for 10 and 20% defoliated plots, respectively).

Leaf Area Index

Significant effects of treatment on LAI were observed along with treatment by time interaction on treated plots of Kanlow (p < 0.0001, p < 0.0001 and p < 0.0001, respectively). The control plots showed a constant rate of LAI during the experiment but defoliated plots showed reductions in LAI throughout the experiment (Fig. 10).

Shawnee 2012

Yield

The ANOVA for Shawnee yield revealed a significant difference among treatments (p = 0.0004). The overall yield varied from 8.0 to 4.0 103kg/ha but maximum reduction in yield occurred in the plots with 10% daily defoliation (Fig. 11).

Percent Light Interception

Significant reduction effects of treatment, time and treatment by time interaction were recorded for percent light interception of defoliated plots of Shawnee (p = 0.0001, p < 0.0001 and p < 0.0001, respectively). Fairly constant interception of light was recorded in control plots throughout the experiment (Fig. 12) while, significant reductions (p = 0.0044 and p = 0.0033 respectively) in percent light interception of 10% and 20% daily defoliated plots were found by the end of the experiment.

Leaf Area Index (LAI)

Significant impacts of treatment, time and treatment by time interaction were recorded on LAI (p = 0.0010, p < 0.0001 and p < 0.0001, respectively) for Shawnee. The LAI of the plots with 10% and 20% daily defoliation became significantly different from control plots on the third day of the experiment (p = 0.0021 and p = 0.0058, respectively) and these significant reductions in LAI were continued until the end of the experiment (p = 0.0002 and p = 0.0004, respectively). The control plots maintained their LAI while, severe reductions occurred in LAI of defoliated plots (Fig. 13).

Discussion

Crop yield is affected by several biotic and abiotic factors (Haile et al. 1998). One of the most important biotic factors affecting crop yield is insect herbivory. Sometimes, plants compensate for defoliation losses by developing new leaves (Haile et al. 1998) and regrow the lost leaf area to continue biomass production. Generally, plants regrow their leaves during the vegetative stage (Boote 1981) but regrowth of defoliated leaves usually does not occur at reproductive stage of plants (Ostile 1984). The results of this study demonstrated the potential of switchgrass cultivars to regrow leaves even after 80% defoliation within ten days during the vegetative growth stage when water was available.

During these studies in 2011, no changes in the yield were recorded with up to 80% defoliation while, significant reductions in LAI and percent light interception were recorded. Despite having similar environmental conditions and growth stage during the experiment, Shawnee and Kanlow showed minor differences in percent light interception, however, similar responses for LAI were shown by both cultivars. During 2011, 30-35% [5???3.5 (Kanlow), 5.4???3.5 (Shawnee)] reduction occurred in LAI by the end of the experiment after 80% defoliation of switchgrass was targeted. A proportion of 4, 6 and 8% defoliations were applied daily to achieve the targeted defoliations (40, 60 and 80%) by the end of experiment (10 days). The substantial reductions in LAI were observed after fifth and seventh days of particular amount of defoliation applied in Shawnee and Kanlow respectively. Plants recovered leaf area losses by growth and regrowth of leaves during the earlier days of defoliation but continuity in defoliation may cause the plants less vigorous to regrow or to compensate for leaf area losses (Detling et al. 1979). However, physiological changes in plants may occur as a result of defoliation (Painter and Detling 1981). For example, it may possible that the plants