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Changes in soil quality and carbon storage under biofuel crops in central Ohio.


The atmospheric concentration of carbon dioxide (C[O.sub.2]) and other greenhouse gases (GHGs) has increased during the last century (Lai 2004; IPCC 2013; WMO 2014). The concentration of atmospheric C[O.sub.2] has increased from 280 ppmv in 1750 to 400ppmv in 2013, and is currently increasing at the rate of 2.2 ppmv [year.sup.-1] (WMO 2014). Strategies to lower net C[O.sub.2] emissions and mitigate climate change include sequestering C[O.sub.2] from point sources or from the atmosphere through engineering techniques, as well as re-carbonisation of the biosphere through improved land use and science-based agriculture (Schrag 2007; Lai et al. 2012). Efforts to increase soil organic carbon (SOC) storage through conservation management have gained momentum since 1990s, particularly to counter the effects of global warming and reduce net anthropogenic GHG emissions (Sarkhot et al. 2012).

Ethanol from maize (Zea mays L.) grain is a first-generation biofuel feedstockf--defined as fuels derived from plant sugars, starches and oils (Soetaert and Vandamme 2009). Other first-generation feedstocks include sugarcane (Saccharum officinarum L.), oil palm (Elaeis guineensis Jacq.) and soybean (Glycine max (L.) Merr.). Maize and other cereal crops have high nutrient, energy and water requirements, and may negatively affect quality of ground and surface waters through nitrogen (N) loss (Randall et al. 1997; Donner and Kucharik 2008; Khan and Hanjra 2009). Sorghum (Sorghum bicolor (L.) Moench) can be used as a dedicated bioenergy crop because it has a wide environmental adaptability, is relatively drought-tolerant, is able to grow on marginal land, and produces high biomass yields. Sorghum is especially suitable for hot, dry and saline environments, where the production of other biofuel crops may be limited (Almodares and Hadi 2009). Another significant characteristic of sorghum is that after harvesting the stalks, most varieties will regrow as ratoon, which enables multiple harvests in a year in certain environments. The major disadvantage of sorghum is that, similar to maize, it must be planted every year, increasing the cost of production and aggravating risks of soil erosion and GHG emissions (Vermerris et al. 2008).

With government regulations [Energy Independence and Security Act (EISA) of 2007, United Sates of America] and the ecological drawbacks posed by maize grain ethanol and other first-generation feedstock materials, the second-generation biofuel crops, or lignocellulosic feedstock from perennial species, may alleviate some of these problems (Bonin and Lai 2012, 2014; Lai 2014). Sequestration of atmospheric C[O.sub.2] by establishing biofuel plantations, especially perennial feedstock materials, on agriculturally marginal and degraded lands is an important co-benefit of biofuel plantations (Lai 2014). Perennial biofuel crops may have higher net energy production and lower GHG emission than maize-grain feedstock systems (Liebig et al. 2005; Adler et al. 2007). The estimated annual farm operational C[O.sub.2] emissions for maize can be 250% higher than perennial grasses in a no-till and 400% higher in a conventional-till system (Adler et al. 2007). Soils under switch grass (Panicum virgatum L.) can sequester more SOC than those under traditional grain crops, in both surface and subsurface layers to 60 cm depth (Liebig et al. 2005). Further, perennial grasses may be a C sink even during the first 3 years of establishment, whereas annual row crops are a C source (Zeri et al. 2011). Low-input, high-diversity (LIHD) grasslands can produce higher bioenergy yields than a monoculture after a decade, they may be a C-negative biofuel feedstock, and can be produced on agriculturally marginal or degraded lands. Thus, LIHD grasslands would neither displace food production nor decrease biodiversity via habitat destruction (Tilman et al. 2006).

The contribution of soil organic matter (SOM) from grasses can increase water-stable aggregates (WSA), the mean weight diameter (MWD), and soil moisture retention (Ekwue 1990). Larger root mass, root exudates, and the presence of fungal hyphae in soils under grasses improve the stability of macroaggregates (Tisdall and Oades 1982). Soils under perennial pastures or grasses are potential C sinks because perennials add OM to soils through reduced soil disturbance by elimination of tillage (Christensen 1988; Balkrishnan and Toky 1993; Paustian et al. 1997; Conant et al. 2001; Gentile et al. 2005).

The establishment of perennial grasses such as Indian grass (Sorghastrum nutans (L.) Nash), miscanthus (Miscanthus x giganteas Greef et Deu ex. Hodkinson et Renvoize; Hodkinson and Renvoize 2001) and switch grass improves soil physical properties, maintains biomass productivity, reduces risks of erosion and runoff, increases soil water retention, improves aggregate stability and sequesters SOC (Arshad and Martin 2002; Barthes and Roose 2002; Ghosh et al. 2009; Bonin and Lai 2012). Perennial grasses improve soil aggregation (Blanco-Canqui 2010), which is an important factor in maintaining soil quality and sustaining agricultural productivity (Amezketa 1999). Thus, establishing perennial grasses and forages is a good strategy for improving quality of degraded soils (Bonin and Lai 2012).

Increase in SOM concentration enhances soil structure and stability of aggregates, improves plant growth and increases use efficiency of inputs. Recently added OM binds microaggregates together into macroaggregates, and macroaggregates are cemented together by new OM (Jastrow et al. 1996). Thus, soil disturbance can reduce SOC, particularly so in macroaggregates (Six et al. 2000). Because of this, C-rich macroaggregates might form in soils under perennial species with deep roots and little soil disturbance.

The present study was conducted to compare the potential of perennial forages and annual cereals to improve soil physical properties and SOC stocks. We evaluated five species types with long-term potential as biofuel crops: (f) maize stover, a potential source of cellulosic feedstock for biofuel (ethanol) production in the USA (Kadam and McMillan 2003; Sheehan et al. 2003); (it) miscanthus, a large and productive perennial grass used as an energy crop in Europe (Lewandowski et al. 2000); (Hi) switch grass, a large perennial grass native to North America, selected by the USA Department of Energy as a model energy crop (McLaughlin and Adams Kszos 2005); (;v) sorghum (sweet sorghum), grown not for its seed but for its high stover yield (as high as 69 Mg [ha.sup.-1]), which also has high sugar concentration (Almodares et al. 2008), and (v) LIHD prairies, which can produce ~4.5Mg [ha.sup.-1] of aboveground dry biomass (Tilman et al. 2006), and native tall grass prairies, which can produce ~6.25 Mg [ha.sup.-1] of biomass (Masters et al. 1992) and thus can be grown as potential biofuel crops.

The specific objective of this study was to assess the impact of perennial and annual biofuel crops on soil properties and C storage. The hypotheses tested were that perennial grasses improve soil properties and increase SOC stocks more than annuals.

Materials and methods

Study area

The study was conducted in an ongoing field experiment at the Waterman Farm in Columbus, Ohio (40[degrees]1'1.87"N, 83[degrees]2'23.02"W). The experiment was established on a gently sloping topography (0-2% slope) with poorly drained silt loamy soil derived from the glacial till (Srinivasan et al. 2012) that had previously been planted under maize. The soil of the site has been characterised according to US soil taxonomy (Soil Survey Staff 1996) as fine, mixed, active, mesic, Aerie Epiaqualf (Jagadamma et al. 2009). The mean annual rainfall of the site is 1016 mm and mean annual air temperature is 11[degrees]C.

Layout and treatment

Five feedstock crops planted were: maize hybrid AGRA 33GT, glyphosate-tolerant, 98 days to maturity; sweet sorghum, 'Dale' variety (MAFES foundation seed stock, Mississippi State University, MS, USA); miscanthus, 'Illinois' clone (New Energy Farms, Tifton, GA, USA); switch grass, 'Shawnee' ecotype (Ernst Conservation Seeds, Meadville, PA, USA); a prairie mix, bio-diverse polyculture mix for biomass production and wildlife habitat (Ernst Conservation Seeds) (Table 1). All biofuel crops were grown under rainfed conditions. Four blocks, each 35 by 8.1 m, were separated by 4.8 m buffer along the length and 1.8 m buffer along the breadth. Five plots (8.1 by 6 m) per block were laid out, and buffer spaces of 1.2 m between plots with one replication of each feedstock per block were maintained. The experiment was laid out in a randomised block design (RBD) with four replications.

Agronomic practices

Switch grass seeds were scarified by soaking overnight in water at 5[degrees]C, then draining free water and chilling at 5[degrees]C for 6 weeks. After this, seeds were spread on a germination paper to air-dry for ~10 days. Seeds were planted within 1 week of drying.

Switch grass, prairie, and miscanthus plots were ripped and rototilled on 7 May 2012. Switch grass and prairie mix seeds were mixed with sand and then hand-broadcasted in plots at a rate of 11.2 kg live seed [ha.sup.-1]. Sorghum and maize were no-till-drilled at a row spacing of 76 cm (maize) and 60 cm (sorghum). Miscanthus plugs were hand-planted on 10 May 2012 at a spacing of 90 by 90 cm, and N:P:K(19:19:19) fertiliser at 67 kg [ha.sup.-1] was applied as establishment mixture. The no-till maize and sorghum were side-dressed with 110 kg N [ha.sup.-1] [year.sup.-1] and top-dressed with 50 kg N [ha.sup.-1].

To control weeds, maize and sorghum plots and alleys were sprayed with Roundup (active ingredient glyphosate, 3 mL [L.sup.-1]), whereas miscanthus and switch grass plots were hoed manually. Maize and sorghum were grown each year (mid-May-October) without major tillage disturbances (except by seeding and harvesting). The experiment commenced in March 2012, and data presented here were recorded in November 2013 after two growing seasons.

Soil sampling and analyses

Bulk soil samples and intact cores (0-10 and 10-20 cm depths) were collected at four random sites per block (four blocks and two depths, i.e. total 32 samples) before initiation of the experiment in March 2012 and again in November 2013. One sample per depth was collected from each plot (20 plots x 2 depths= 40 samples) after the second crop season in November 2013. Cores were 5.9 cm deep and 5.4 cm in diameter. About 2 cm of soil was removed from the surface and core samples were collected using a manually driven core sampler. Then, soil was removed to ~12cm depth to collect next core. In this way, core samples were collected from the middle of the 0-10 and 10-20 cm depths. Soil samples were obtained between rows of maize, sorghum and miscanthus, and randomly within the plots of switch grass and prairie mix. Field-moist core samples collected were trimmed and weighed to calculate the wet bulk density ([[rho].sub.b]). Soil dry [[rho].sub.b] was calculated from the wet [[rho].sub.b] and moisture content measured at 105[degrees]C (Blake and Hartge 1986). Total porosity ([f.sub.t]) was estimated from dry [[rho].sub.b] and particle density ([[rho].sub.s]) by using Eqn 1:

[f.sub.t] = 1-([[rho].sub.b]/[[rho].sub.s]) (1)

where [[rho].sub.b] is dry [[rho].sub.b] of the respective treatments, and [[rho].sub.s] = 2.65 Mg [m.sup.-3]. Bulk soil samples were air-dried, and extraneous roots were removed, gently broken apart with a rubber mallet and sieved through a nest of sieves (8, 4.75 and 2 mm). Aggregates retained on the 4.75-mm sieve and the bulk soil that passed through a 2-mm sieve were stored in airtight poly bags pending analyses.

For pH and electrical conductivity (EC) estimation, soil samples were ground and passed through 2-mm sieve and stored at room temperature. Soil pH was determined potentiometrically in 1:2.5 soil: water (Mclean 1982). The EC was determined using a conductivity probe (Helrich 1990).

Aggregate fractionation

Aggregate fractionation was performed by the wet sieving method (Nimmo and Perkins 2002). Briefly, 50 g of air-dried aggregates of size 4.75-8.0 mm were placed on top of a nest of sieves (4.75, 2, 1, 0.5 and 0.25 mm), wetted by capillarity for 30 min, and oscillated through a vertical distance of ~3 cm at 30 oscillations [min.sup.-1] in a water column for 30 min. The fractions retained in each sieve were washed into different beakers. The soil fraction <0.25 mm (microaggregates) was obtained by filtering the sediment in the collection tank after sieving. The collected fractions were oven-dried at 40[degrees]C and weighed to compute MWD, geometric mean diameter (GMD) and percentage WSA as depicted in Kemper and Rosenau (1986) (Eqns 2, 3 and 4):

MWD = [summation](Xi x Mi) (2)

where, Xi is sieve-size mean (it is constant value for all) and Mi is proportion of aggregate weights in the corresponding size fraction after deducting weight of gravels (upon dispersion and passing through the same sieve).

GMD = exp [summation](logXi x mi)/ [SIGMA] Mi (3)

% WSA = 100 x (wt retained - wt of gravel)/ (total sample wt - total wt of gravel) (4)

Subsamples from each aggregate fraction were composited and mixed together to represent two aggregate-size fractions, macroaggregates (0.25-8 mm) and microaggregates (<0.25 mm), and presented as percentage of dry aggregate after correcting the data for gravels (Tisdall and Oades 1982).

Soil organic carbon and nitrogen analyses

For SOC determination, samples including macro- and microaggregates were finely ground and passed through a 250-[micro]m sieve. Ground soil was then placed in vials with two iron rollers and rotated for 24 h to homogenise. Total C and N concentrations in bulk soil and aggregate size fractions were determined by the dry combustion (900[degrees]C) method (Nelson and Sommers 2005) by using a vario Max CN analyzer (Elementar Inc., Hanau, Germany). The SOC was assumed equal to the total C, with negligible inorganic C concentration because the soil pH was close to neutral (Jagadamma and Lai 2010). The SOC and total N stocks (Mg [ha.sup.-1]) were calculated to a depth standard using [[rho].sub.b] for the corresponding soil depth (Lee et al. 2009) (Eqns 5 and 6). The C stock was first calculated to a depth standard (DS) as:

C stock (g 100 [cm.sup.-2]) = Cconcentration (g 100 [g.sup.-1]) x [[rho].sub.b](g [cm.sup.-3]) x depth (cm) x gravel correction factor (1 - proportion gravel>0.2cm) (5)

where C stock (g 100 [cm.sup.-2]) = C stock (Mg C [ha.sup.-1]).

Carbon stock using the equivalent soil mass (ESM) was then calculated. The 2012 soil mass (initial) was used as the reference soil mass; so, 2012 stocks of C were calculated to a depth standard (as a [T.sub.0] reference soil mass), and subsequent C stocks for the same treatment were calculated based on an ESM to 2012:


Total N stock was estimated by following same procedure. The detail procedure for ESM estimation has been described by Lee et al. (2009).

Sequestration of SOC was computed by Eqn 7:

C sequestered (Mg C [ha.sup.-1]) = SOC current - SOC initial (7)

Stratification ratios for SOC and total N were computed by dividing their concentrations in 0-10 cm layer with those observed in 10-20 cm (Franzluebbers 2002).

Statistical analyses

The analysis of variance (ANOVA) method (Gomez and Gomez 1984) was used for statistical analysis of all parameters. The ANOVA for testing the effects of different treatments was computed using GLM of PASW version 18.0 (SPSS Inc., Chicago). The mean effects of treatments were separated by using the F-protected least significant difference (l.s.d.) test at the probability level (P) of 0.05. An estimate for the l.s.d. between treatments was obtained using Duncan's l.s.d.


Aboveground biomass production

The biomass production of diverse biofuel crops recorded in autumn of 2013 is presented in Fig. 1. Miscanthus produced significantly higher biomass (18.9 Mg [ha.sup.-1]) than other crops. Maize and sorghum had statistically similar biomass yields, which were significantly higher than those of switch grass and the prairie mix. Maize had an equal biomass for both grain (4.8 Mg [ha.sup.-1]) and stover (4.8 Mg [ha.sup.-1]).

Soil physical properties

Bulk density and porosity

Soil bulk density ([[rho].sub.b]) and porosity ([f.sub.t]) in the 0-10 and 10-20 cm layers were significantly influenced by species (Table 2). Average [[rho].sub.b] values in 0-10 and 10-20 cm layers were 1.54 and 1.59 Mg [m.sup.-3], respectively. Soil [[rho].sub.b] was the highest under sorghum, significantly higher than that under switch grass, miscanthus and the prairie mix in both 0-10 and 10-20 cm layers. Soil [[rho].sub.b] under switch grass and miscanthus was lower than baseline levels (initial [[rho].sub.b] in March 2012) by 6.7% and 5%, respectively, at 0-10 cm and 5.5% and 4.5%, respectively at 10-20 cm.

Mean weight diameter and geometric mean diameter

Both MWD and GMD of aggregates were significantly higher under switch grass than under sorghum and maize in the 0-10 cm layer (Table 2), the MWD of aggregates in the 0-10 cm layer under switch grass being ~35% and 16% higher than under sorghum and maize, respectively. MWD and GMD of aggregates were statistically similar under sorghum and maize. MWD and GMD of aggregates were similar under switch grass, miscanthus and prairie mix in the 0-10 cm layer.

Size distribution of water-stable aggregates

The data on size distribution of WSA revealed that, compared with maize and sorghum, perennial grasses tended to increase the proportion of large macroaggregates (>4.75 mm) in the 0-10 and 10-20 cm layers (Table 3). On the other hand, the proportion of microaggregates (<0.25 mm) tended to be higher under maize and sorghum than under perennial grasses in the 0-10 cm layer.

Total WSA values were affected by plant species (Fig. 2). The percentage WSA under miscanthus and switch grass was 11.3% and 8.9% higher in 0-10cm layer, and 5.3% and 3.1% higher in 10-20 cm layer, respectively, than under sorghum. Soils under sorghum and maize generally had a lower aggregate stability than those under perennial grasses.

Soil chemical properties

Soil pH and electrical conductivity

There was no significant effect of treatments on pH at 0-10 and 10-20 cm depths (Fig. 3). However, EC was significantly affected by diverse biofuel crops (Fig. 4). The EC of soils under miscanthus was significantly higher than under other biofuel crops in both 0-10 and 10-20 cm soil layers. Prairie mix tended to have the lowest EC; it was significantly less than miscanthus at 0-10 cm and all other biofuel crops except maize at 10-20 cm.

Soil organic carbon

Biofuel crops had a significant effect on SOC concentration but no significant effect on total N. The average SOC concentration in 0-10 and 10-20cm layers were 17 and 12.67g C [kg.sup.-1] soil, respectively (Table 4). In 0-10cm layer, SOC concentration was significantly higher under switch grass than under maize and sorghum. The SOC concentration was not significantly different between prairie mix, maize and sorghum. There was a general trend of higher SOC and total N concentrations at 0-10 cm than 10-20 cm. Relative to antecedent levels, SOC concentrations under switch grass and miscanthus were 11.7% and 9.4% higher at 0-10 cm, and 8.7 and 6.0% higher at 10-20 cm. The C: N ratio ranged from 9.1 to 11.0 at 0-10 cm and from 9.8 to 11.3 at 10-20 cm layer. There was no changes in C:N ratio relative to the baseline level (March 2012) in either layer. The C:N ratios under miscanthus and switch grass were significantly higher than under maize and sorghum, indicating the stability of C storage in soil derived from the grass biomass.

Soil organic carbon in aggregates

Averaged across all crops, macroaggregates (>0.25 mm) comprised 90.8 [+ or -]3.6% and 88.6 [+ or -]2.8% of the total weight in the 0-10 cm and 10-20 cm layers, respectively (Table 3). Soils under miscanthus and switch grass had a significantly higher proportion of macroaggregates (>0.25 mm) than soils under sorghum and maize. Biofuel crops affected SOC and N concentrations in macroaggregates (Table 5). Macroaggregates under sorghum contained 17.3% less C and 22.8% less N in 0-10 cm layer than those under switch grass, and 29.8% less C and 22% less N in 10-20 cm layer. However, macroaggregate C : N ratios showed significant differences only in the 10-20 cm layer (Table 5).

Generally, macroaggregates contained higher concentrations of C and N than microaggregates in both 0-10 and 10-20 cm soil layers. Average C concentrations in macroaggregates were 14.53 and 11.82g [kg.sup.-1] in 0-10 and 10-20cm soil layers, respectively, which were 21.7% and 6.4% higher than the respective values in microaggregates. Likewise, total N concentrations in macroaggregates were 24% and 12% higher than in microaggregates in the 0-10 cm and 10-20 cm layers.

Similar to SOC in the bulk soil, concentrations of SOC in the two aggregate classes were higher under switch grass and miscanthus than under annuals.

Stocks of SOC and total N

Estimation of SOC stock on ESM basis indicated significantly higher stock under switch grass (28.5 Mg C [ha.sup.-1]) and miscanthus (28.0 Mg C [ha.sup.-1]) than that under sorghum (24.8 Mg C [ha.sup.-1]). The SOC stocks under prairie grass (26.7 Mg C [ha.sup.-1]) and maize (26 Mg C [ha.sup.-1]) were not significantly different from those of other crops. Thus, the amounts of SOC sequestered annually in the 0-20 cm layer under switch grass and miscanthus were 1.3 and 1.05 Mg C [ha.sup.-1], respectively (Fig. 5). By comparison, the SOC stock declined under sorghum by 0.55 Mg C [ha.sup.-1] annually. Two years of biofuel crops did not significantly affect the total N stocks computed on ESM basis (Fig. 6).

Stratification ratio

There was no significant influence of biofuel crops on the stratification ratio for SOC, SOC stock (volumetric), total N, and total N stock (volumetric) (Table 6). The stratification ratio for SOC ranged from 1.33 to 1.36 and for total N from 1.33 to 1.39. Stratification ratios for SOC and total N stocks varied from 1.28 to 1.31 and from 1.24 to 1.31, respectively.


The biomass production of diverse biofuel crops varied significantly, with miscanthus having the maximum biomass and the prairies the minimum. High biomass production potential of miscanthus compared with other feedstock crops (e.g. maize, sorghum) has been reported in an earlier study (Bonin and Lai 2012). Low biomass production of the prairie mix may be due to poor establishment owing to drought in 2012 (Lal et al. 2012). Further, it is reported that prairie mix may take about a decade to reach its full production potential (Tilman et al. 2006).

In general, soil bulk density ([[beta].sub.b]) was lower under all biofuel crops, including maize and sorghum, compared with antecedent levels. As expected, a reverse trend was monitored with respect to porosity ([f.sub.t]). The f under sorghum was ~10% lower than under switch grass, miscanthus and prairie mix. Lower [[beta].sub.b] under perennial grasses is attributed to large root biomass and less soil disturbances in grasses (Ghosh et al. 2009). Adoption of no-till practices in maize and sorghum may have contributed to reduction in soil [[beta].sub.b]. Higher [[beta].sub.b] under maize than switch grass has also been reported by Bonin and Lai (2012).

Soils under switch grass had significantly higher MWD and GMD of aggregates than soil under sorghum and maize in the 0-10 cm layer. Better soil aggregation has been reported under perennial grasses (e.g. switch grass and miscanthus) due to more root biomass and exudates and subsequent improvement in physical properties (Bonin and Lai 2012) including MWD (Chantigny et al. 1997).

There was a general trend of a decreasing proportion of smaller size aggregates (from 4.75 to 0.25 mm) in both soil layers and under all crops. Generally, mucilage from plants and microbes and the wetting-drying cycles contribute to soil aggregation (Czarnes et al. 2000). The increase in macroaggregates under perennial grasses compared with maize and sorghum may be attributed to higher input of OM and detritus into the soil. This may contribute to the bonding between particles by cementing agents derived from rhizodeposition, increased microbial populations and decaying roots. The underlying processes of the impact of rhizodeposition on soil structure have been reviewed by Hinsinger et al. (2009). Among the microorganisms supported by rhizodeposition, fungi are probably of particular importance to macroaggregate formation. Chantigny et al. (1997) observed more large macroaggregates (>2 mm) under perennial grasses than under annual faba bean (Vicia faba) or wheat (Triticum aestivum), which was related to fungal glucosamine concentration. Moreover, arbuscular mycorrhizal fungi contribute to soil stability by producing exudates and by inducing shrinkage and enhancing water fluctuations in the root-zone (Hallett et al. 2009). A similar trend with regard to macro- and microaggregates was also observed by Bonin and Lai (2012).

There was a trend toward higher percentages of WSA under perennial grasses than under maize and sorghum. Soils under maize and sorghum generally had lower aggregate stability, with higher percentages of microaggregates than those under switch grass or miscanthus. These trends may be due to a reduction in belowground plant biomass under maize or the presence of fewer organic binding agents that form macroaggregates. A greater proportion of recently added OM is involved in binding microaggregates into macroaggregates, so that larger aggregates are held together by new OM originating from crops (Jastrow et al. 1996; Bonin and Lai 2014). As such, increasing cultivation activities and soil disturbance can reduce SOC concentration, and particularly so in macroaggregates (Six et al. 2000). Thus, C-rich macroaggregates can form in soils under perennials with deep roots and little soil disturbance. The improvement in pH and EC under perennial grasses can be attributed to deposition of OM from detritus and root biomass (Ghosh et al. 2009).

Biofuel crops had significant effect on SOC concentration in both layers and non-significant effects on total N. The SOC concentrations under switch grass (18.10 g [kg.sup.-1]) and miscanthus (17.73 g [kg.sup.-1]) were 11.7% and 9.4% higher in 0-10 cm and 8.7% (13.70 g [kg.sup.-1]) and 6.0% (13.35 g [kg.sup.-1]) higher at 10-20 cm layer than the antecedent levels. Ma et al. (2000) reported that the root biomass of switch grass was as much as 4.9 times greater in a clay loam than in sandy loam or silty loam soils. Increased root production in clayey soils may be due to increased fertility or improved soil structure. Concentration of total N was highest under maize, followed by sorghum, in both soil layers. Total N concentrations under perennial grasses were lower than under maize and sorghum. Such trends in both soil layers are attributed to annual application of N fertilisers to maize and sorghum. The C: N ratios under miscanthus and switch grass were significantly higher than under maize and sorghum, indicating relative stability of SOC derived from grass biomass.

Macroaggregates (all sizes, >0.25 mm) accumulated higher concentrations of SOC than microaggregates (0.05-0.25 mm). Higher C accumulation in macroaggregates under reduced landuse intensity was also reported by Grandy and Robertson (2007). Puget et al. (1995) reported greater C accumulation in macroaggregates because of lower decomposable SOM associated with these aggregates, as well as a direct contribution of SOM to the stability of macroaggregates, resulting in C-rich macroaggregates capable of withstanding slaking. All aggregate fractions had a low C: N ratio (8.75-11.15), suggesting a more humified and potentially greater degree of microbial origin associated with the fine-silt fraction, which accounts for the largest proportion of small macro- and microaggregates (Six et al. 2001; Rodionov et al. 2000). The addition of detritus and root biomass may have enhanced binding of microaggregates into macroaggregates as a result of secretion of mucilaginous substances and fungal hyphae (Tisdall and Oades 1982; Beare et al. 1994).

Numerous studies have emphasised that ESM corrections should be used when comparing soil C stocks among management practices in layers of different [[beta].sub.b] (Ellert and Bettany 1995; Gifford and Roderick 2003; Lee et al. 2009). In the present study, only switch grass and miscanthus had sequestered SOC, by 1.3 and 1.05 Mg [ha.sup.-1] [yea.sup.r-1], respectively, in 0-20 cm layer on an ESM basis. Prairie grass and maize had SOC stocks similar to the antecedent level, and the SOC stock was depleted under sorghum. Thus, the study supported the hypothesis that soils under perennial grasses are a greater C sink than those under annual cereals. However, long-term monitoring and to greater depths is needed to ascertain the impact of biofuel crops on SOC sequestration (Bonin and Lai 2014). Increase or decrease in SOC stocks, depending on land-use changes, feedstock choices and management practices are widely reported (Conant et al. 2001; Guo and Gifford 2002; Tolbert et al. 2002). Although there is a large potential to sequester a significant amount of SOC under biofuel crops, this potential is associated with a large amount of uncertainty, which may make precise calculations of C balances highly challenging (Ney and Schnoor 2002). Allocation of C to root biomass is much lower in annuals than in perennial grasses (Jackson et al. 1996). Maize and sorghum have limited SOC sequestration capacity because these annuals have a low root:shoot ratio (Lemus and Lai 2005; Anderson-Teixeira et al. 2009). It has been widely reported that roots and rhizomes are primary sources of C to the soil in biofuel crops (Garten and Wullschleger 2000; Wilhelm et al. 2004). Thus, belowground allocation of C plays a critical role in changes in SOC (Anderson-Teixeira et al. 2009). Perennials such as switch grass and miscanthus, with deep and extensive root systems, have high root: shoot ratios and have the potential to sequester greater amount of SOC (Zan et al. 2001). Reported root: shoot ratios are 0.3 for maize (Bonifas et al. 2005), 1 for miscanthus (Neukirchen et al. 1999), 1.8-6.1 for switch grass (Ma et al. 2001), and 2-8 for North American prairies (Wilson 1993; Ojima et al. 1994). Compared with cultivated croplands, soils under switch grass can store an additional 15.3 Mg SOC [ha.sup.-1] when measured to 120 cm depth (Liebig et al. 2005). In the case of perennial grasses, SOC storage can occur even when most of the aboveground biomass is removed annually (Tilman et al. 2006). Increases in SOC stock due to cultivation of temperate perennial grasses (miscanthus, switch grass, or native mixes) have been widely reported (Potter et al. 1999; Ma et al. 2000; Kahle et al. 2001; Lemus and Lai 2005). So too have the influences of plant lifeform and chemical composition on SOC dynamics (Vinton and Burke 1995; Tilman et al. 2006; Johnson et al. 2007).

The stratification ratio, as a soil quality indicator, is influenced by the SOC concentration in the surface layer (Franzluebbers 2002). Stratification ratio is the ratio of a soil property at the surface to the same property at greater depth, such as at the bottom of the tillage layer (Srinivasan et al. 2012). In the present study, the stratification ratio was not significantly influenced by the forage crops. This can be attributed to deposition of detritus on the soil surface and contribution from root exudates to build-up of soil fertility under annual and perennial biofuel crops. Longer duration of the study is expected to reveal any differential influences on the stratification ratio through variable contribution of residues, exudates, fertiliser source, etc. The stratification ratios for SOC, SOC stock, and total N and N stock were >1, indicating the build-up of soil fertility and deposition of nutrients in the surface layer. The higher concentration of total N in the surface than in subsurface layers may be attributed to the surface application of fertilisers, especially N. Build-up of SOC in surface layers can be attributed to deposition of detritus over the years, contributions from roots through exudates, and OM decomposition. These high stratification ratios of SOC and total N are indicative of the build-up of organic residues with intermediate turnover time (Cambardella and Elliott 1992), and of improvement with long-term management. Therefore, the impacts on these stocks must be critically analysed for their sustainability over time (Franzluebbers 2002).


The results presented support the following conclusions. (i) Perennial lignocellulosic crops (switch grass and miscanthus) improved soil physical properties, resulting in lower soil bulk density, higher porosity, and improved WSA, aggregate size distribution and MWD relative to maize and sorghum, and thus contributed to OM protection, (if) Soils under perennial grasses had significantly higher SOC concentrations than those under annual crops in the 0-10 and 10-20 cm soil layers after 2 years of cropping. (iii) On average, switch grass and miscanthus cultivation enhanced SOC stocks in the 0-20 cm horizon by 1.3 and 1.05 Mg [ha.sup.-1] [year.sup.-1], respectively, compared with initial C stocks on an ESM basis, (iv) The SOC stock at 0-20 cm under sorghum was depleted by 0.55 Mg C [ha.sup.-1] in 2 years compared with initial stocks on an ESM basis.

Thus, the study supported the hypotheses that establishment of the perennial biofuel grasses switch grass and miscanthus enhanced soil quality and SOC storage, whereas cultivation of annual maize and sorghum caused a slight depletion of these parameters. However, there is a need for long-term studies to a deeper soil layer to establish the SOC balance and soil-quality parameters under diverse biofuel crops.


The first author acknowledges the CMASC, Ohio State University, USA, for extending the field and laboratory facilities to undertake the study. The fund and support received from ICAR, New Delhi, and ICAR Research Complex for NEH Region, Umiam, Meghalaya, India, to visit CMASC is also duly acknowledged.


Adler PR, Del GSJ, Parton WJ (2007) Life-cycle assessment of net greenhouse gas flux for bio-energy cropping systems. Ecological Applications 17, 675-691. doi: 10.1890/05-2018

Almodares A, Hadi MR (2009) Production of bioethanol from sweet sorghum: A review. African Journal of Agricultural Research 4, 772-780.

Almodares A, Taheri R, Adeli S (2008) Stalk yield and carbohydrate composition of sweet sorghum [Sorghum bicolor (L.) Moench] cultivars and lines at different growth stages. Journal of Malaysian Applied Biology 37, 31-36.

Amezketa E (1999) Soil aggregate stability: a review. Journal of Sustainable Agriculture 14, 83-151. doi:10.1300/J064v14n02_08

Anderson-Teixeira K, Davis SC, Masters MD, Delucia EH (2009) Changes in soil organic carbon under biofuel crops. GCB Bioenergy 1, 75-96. doi: 10.1111/j. 1757-1707.2008.01001.x

Arshad MA, Martin S (2002) Identifying critical limits for soil quality indicators in agroecosystems. Agriculture, Ecosystems & Environment 88, 153-160. doi: 10.1016/S0167-8809(01)00252-3

Balkrishnan, Toky OP (1993) Significance of nitrogen fixing woody legume trees in forestry. Indian Forester 119, 126-134.

Barthes B, Roose E (2002) Aggregate stability as an indicator of soil susceptibility to runoff and erosion; validation at several levels. Catena 47, 133-149. doi: 10.1016/S0341-8162(01)00180-1

Beare MH, Hendrix PF, Coleman DC (1994) Water stable aggregates and organic matter fractions in conventional and no tillage soils. Soil Science Society of America Journal 58, 777-786. doi: 10.2136/sssaj 1994.0361 5995005800030020x

Blake GR, Hartge KH (1986) Bulk density. In 'Methods of soil analysis. Part I: Physical and mineralogical methods'. ASA Monograph No. 9. (Ed. A Klute) pp. 363-376. (ASA: Madison, WI, USA)

Blanco-Canqui H (2010) Energy crops and their implications on soil and environment. Agronomy Journal 102, 403-419. doi:10.2134/ agronj2009.0333

Bonifas KD, Walters DT, Cassman KG, Lindquist JL (2005) Nitrogen supply affects root: shoot ratio in com and velvetleaf (Abutilon theophrasti). Weed Science 53, 670-675. doi:10.1614/WS-05-002R.1

Bonin C, Lal R (2012) Physical properties of an Alfisol under biofuel crops in Ohio. Journal of Technology, Innovations Renewable Energy l, 1-13.

Bonin C, Lai R (2014) Above ground productivity and soil carbon storage of biofuel crops in Ohio. GCB Bioenergy 6, 67-75. doi: 10.1111/ gcbb. 12041

Cambardella CA, Elliott ET (1992) Particulate soil organic matter across a grassland cultivation sequence. Soil Science Society of America Journal 56, 777-783. doi: 10.2136/sssaj1992.03615995005600030017x

Chantigny MH, Angers DA, Prevost D, Vezina LP, Chalifour FP (1997) Soil aggregation and fungal and bacterial biomass under annual and perennial cropping systems. Soil Science Society of America Journal 61, 262-267. doi: 10.2136/sssaj 1997.03615995006100010037x

Christensen BT (1988) Effect of manure and mineral fertilizer on the total carbon and nitrogen contents of soil size fractions. Biology and Fertility of Soils 5, 304-307. doi:10.1007/BF00262136

Conant RT, Paustian K, Elliott ET (2001) Grassland management and conversion into grassland: effects on soil carbon. Ecological Applications 11, 343-355. doi: 10.1890/1051-0761(2001)011[0343: GMACIG]2.0.CO;2

Czarnes S, Hallett PD, Bengough AG, Young IM (2000) Root- and microbial-derived mucilages affect soil structure and water transport. European Journal of Soil Science 51, 435 443. doi: 10.1046/j.1365-2389.2000.00327.x

Donner SD, Kucharik CJ (2008) Com-based ethanol production compromises goal of reducing nitrogen export by the Mississippi River. Proceedings of the National Academy of Sciences of the United States of America 105, 4513-4518. doi:10.1073/pnas.0708300105

Ekwue EI (1990) Organic-matter effects on soil strength properties. Soil & Tillage Research 16, 289-297. doi: 10.1016/0167-1987(90)90102-J

Ellert BH, Bettany JR (1995) Calculation of organic matter and nutrients stored in soils under contrasting management regime. Canadian Journal of Soil Science 75, 529-538. doi:10.4141/cjss95-075

Franzluebbers AJ (2002) Soil organic matter stratification ratio as an indicator of soil quality. Soil & Tillage Research 66, 95-106. doi: 10.1016/SO167-1987(02)00018-1

Garten CT Jr, Wullschleger SD (2000) Soil carbon dynamics beneath switch grass as indicated by stable isotope analysis. Journal of Environmental Quality 29, 645-653. doi:10.2134/jeq2000.00472425002900020036x

Gentile RM, Martino DL, Entz MH (2005) Influence of perennial forages on subsoil organic carbon in a long-term rotation study in Uruguay. Agriculture, Ecosystems & Environment 105, 419-423. doi: 10.1016/ j.agee.2004.05.002

Ghosh PK, Saha R, Gupta JJ, Ramesh T, Das A, Lama TD, Munda GC, Bordoloi JS, Verma MR, Ngachan SV (2009) Long-term effect of pastures on soil quality in acid soil of North-East India. Australian Journal of Soil Research 47, 372-379. doi: 10.1071/SR08169

Gifford RM, Roderick ML (2003) Soil carbon stocks and bulk density: spatial or cumulative mass coordinates as a basis of expression? Global Change Biology 9, 1507 1514. doi: 10.1046/j. 1365-2486.2003.00677.x

Gomez KA, Gomez AA (1984) 'Statistical procedure for agricultural research.' 2nd edn. (International Rice Research Institute/John Wiley and Sons: Singapore/New York)

Grandy AS, Robertson GP (2007) Land-use intensity effects on soil organic carbon accumulation rates and mechanisms. Ecosystems 10, 58-73. doi: 10.1007/s 10021-006-9010-y

Guo LB, Gifford RM (2002) Soil carbon stocks and land use change: a meta-analysis. Global Change Biology 8, 345-360. doi: 10.1046/j.1354-1013.2002.00486.x

Hallett PD, Feeney DS, Bengough AG, Rillig MC, Scrimgeour CM, Young 1M (2009) Disentangling the impact of AM fungi versus roots on soil structure and water transport Plant and Soil 314, 183-196. doi: 10.1007/ sill 04-008-9717-y

Helrich K (Ed.) (1990) 'Official methods of analysis.' 15th edn. (Association of Official Analytical Chemists, Inc.: Arlington, VA, USA)

Hinsinger P, Bengough AG, Vetterlein D, Young IM (2009) Rhizosphere: biophysics, biogeochemistry and ecological relevance. Plant and Soil 321, 117-152. doi:10.!007/sl 1104-008-9885-9

Hodkinson TR, Renvoize SA (2001) Nomenclature of Miscanthus giganteus (Poaceae). Kew Bulletin 56, 759-760. doi: 10.2307/4117709

IPCC (2013) Climate change 2013, the physical science basis. Headline statements from the summary for policymakers. Intergovernmental Panel on Climate Change Working Group I, Bern, Switzerland. Available at: headlines.pdf (accessed 13 January 2014)

Jackson RB, Canadell J, Ehleringer JR, Mooney HA, Sala OE, Schulze ED (1996) A global analysis of root distributions for terrestrial biomes. Oecologia 108, 389 411. doi:10.1007/BF00333714

Jagadamma S, Lai R (2010) Distribution of organic carbon in physical fractions of soils as affected by agricultural management. Biology and Fertility of Soils 46, 543-554. doi :10.1007/s00374-010-0459-7

Jagadamma S, Lal R, Rimal BK (2009) Effects of topsoil depth and soil amendments on com yield and properties of two Alfisols in central Ohio. Journal of Soil and Water Conservation 64, 70-80. doi: 10.2489/ jswc.64.1.70

Jastrow JD, Miller RM, Boutton TW (1996) Carbon dynamics of aggregate-associated organic matter estimated by carbon-13 natural abundance. Soil Science Society of America Journal 60, 801-807. doi: 10.2136/ sssaj1996.03615995006000030017x

Johnson JM, Barbour NW, Weyers SL (2007) Chemical composition of crop biomass impacts its decomposition. Soil Science Society of America Journal 71, 155-162. doi:10.2136/sssaj2005.0419

Kadam KL, McMillan JD (2003) Availability of com stover as a sustainable feedstock for bioethanol production. Bioresource Technology 88, 17-25. doi: 10.1016/S0960-8524(02)00269-9

Kahle P, Beuch S, Boelcke B, Leinweber P, Schulten HR (2001) Cropping of Miscanthus in Central Europe: biomass production and influence on nutrients and soil organic matter. European Journal of Agronomy 15, 171-184. doi: 10.1016/S1161-0301 (01)00102-2

Kemper WD, Rosenau RC (1986) Aggregate stability and size distribution. In 'Methods of soil analysis, Part I: Physical and mineralogical methods'. 2nd edn. (Ed. A Klute) pp. 425 442. (ASA and SSSA: Madison, WI, USA)

Khan S, Hanjra MA (2009) Footprints of water and energy inputs in food production--global perspectives. Food Policy 34, 130-140. doi: 10.1016/j.foodpol.2008.09.001

Lal R (2004) Carbon emission from farm operations. Environment International 30, 981 990. doi: 10.1016/j.envint.2004.03.005

Lal R (2014) Biofules and carbon offsets. Biofuels 5, 21-27. doi: 10.4155/ bfs.13.62

Lal R, Lorenz K, Huttle R, Schneider BU, Von Braun J (Eds) (2012) 'Recarbonization of the biosphere.' (Springer: Dordrecht, The Netherlands)

Lee J, Hopmans JW, Rolston DE, Baer SG, Six J (2009) Determining soil carbon stock changes: simple bulk density corrections fail. Agriculture, Ecosystems & Environment 134, 251-256. doi:10.1016/j.agee.2009. 07.006

Lemus R, Lal R (2005) Bioenergy crops and carbon sequestration. Critical Reviews in Plant Sciences 24, 1-21. doi: 10.1080/07352680 590910393

Lewandowski I, Clifton-Brown JC, Scurlock JMO, Huisman W (2000) Miscanthus: European experience with a novel energy crop. Biomass and Bioenergy 19, 209-227. doi:10.1016/S0961-9534(00)00032-5

Liebig MA, Johnson HA, Hanson JD, Frank AB (2005) Soil carbon under switchgrass stands and cultivated cropland. Biomass and Bioenergy 28, 347-354. doi:10.1016/j.biombioe.2004.11.004

Ma Z, Wood CW, Bransby DI (2000) Carbon dynamics subsequent to establishment of switchgrass. Biomass and Bioenergy 18, 93-104. doi: 10.1016/S0961-9534(99)00077-X

Ma Z, Wood CW, Bransby Dl (2001) Impact of row spacing, nitrogen rate, and time on carbon partitioning of switchgrass. Biomass and Bioenergy 20, 413-419. doi: 10.1016/S0961-9534(01)00008-3

Masters RA, Vogel KP, Mitchell RB (1992) Response of central plains tall grass prairies to fire, fertilizer, and atrazine. Journal of Range Management 45, 291-295. doi: 10.2307/4002980

McLaughlin SB, Adams Kszos L (2005) Development of switch grass (Panicum virgatum) as a bioenergy feedstock in the United States. Biomass and Bioenergy 28, 515-535. doi:10.1016/j.biombioe.2004. 05.006

Mclean EO (1982) Soil pH and lime requirement. In 'Methods of soil analysis. Part 2: Chemical and microbiological properties'. Agronomy Monograph No. 9. 2nd edn. (Eds AL Page, RH Miller, DR Keeney) pp. 595-624. (American Society of Agronomy: Madison, WI, USA)

Nelson DW, Sommers LE (2005) Total carbon, organic carbon and organic matter. In 'Analysis of soil and plants chemical methods'. SSA Book Series 5. (Ed. DL Spark) (Soil Science of America Inc., American Society of Agronomy Inc.: Madison, WI, USA)

Neukirchen D. Himken M, Lammel J, Czypionka-Krause U, Olfs HW (1999) Spatial and temporal distribution of the root system and root nutrient content of an established Miscanthus crop. European Journal of Agronomy 11, 301 309. doi: 10.1016/S1161-0301(99)00031-3

Ney RA, Schnoor JL (2002) Incremental life cycle analysis: Using uncertainty analysis to frame greenhouse gas balances from bioenergy systems for emission trading. Biomass and Bioenergy 22. 257-269. doi: 10.1016/S0961-9534(02)00004-1

Nimmo JR, Perkins KS (2002) Aggregate stability and size distribution. In 'Methods of soil analysis. Part 4: Physical methods'. SSSA Book Series No. 5. (Eds JH Dane, GC Topp) pp. 317-328. (SSSA: Madison, WI, USA)

Ojima DS, Schimel DS, Parton WJ, Owensby CE (1994) Long- and short-term effects of fire on nitrogen cycling in tall grass prairie. Biogeochemistry 24, 67-84. doi:10.1007/BF02390180

Paustian K, Collins HP, Paul EA (1997) Management controls on soil carbon. In 'Soil organic matter in temperate agroecosystems'. (Eds EA Paul, K Paustian, ET Elliot, CV Cole) pp. 15-49. (CRC Press: Boca Raton, FL, USA)

Potter KN, Torbert HA, Johnson HB, Tischler CR (1999) Carbon storage after long-term grass establishment on degraded soils. Soil Science 164, 718-725. doi: 10.1097/00010694-199910000-00002

Puget P, Chenu C, Balesdent J (1995) Total and young organic matter distributions in aggregates of silty cultivated soils. European Journal of Soil Science 46, 449^159. doi: 10.1111/j. 1365-2389.1995.tb01341.x

Randall GW, Huggins DR, Russelle MP, Fuchs DJ, Nelson WW, Anderson JL (1997) Nitrate losses through subsurface tile drainage in Conservation Reserve Program, alfalfa, and row crop systems. Journal of Environmental Quality 26. 1240-1247. doi:10.2134/jeq1997.004724 25002600050007x

Rodionov A, Amelung W, Urusevskaja I, Zech W (2000) Carbon and nitrogen in the enriched labile fraction along a climosequence of zonal steppe soils in Russia. Soil Science Society of America Journal 64, 1467-1473. doi:10.2136/sssaj2000.6441467x

Sarkhot DV, Grunwald S, Ge Y, Morgan CLS (2012) Total and available soil carbon fractions nder the perennial grass Cynodon dactylon (L.) Pers and the bioenergy crop Arundo donax L. Biomass and Energy 41, 122-130. doi: 10.1016/j.biombioe.2012.02.015

Schrag DP (2007) Preparing to capture carbon. Science 315, 812-813. doi: 10.1126/science.1137632

Sheehan J, Aden A. Paustian K, Killian K, Brenner J, Walsh M, Nelson R (2003) Energy and environmental aspects of using com stover for fuel ethanol. Journal of Industrial Ecology 7, 117-146. doi: 10.1162/108819 803323059433

Six J, Paustian K, Elliott ET, Combrink C (2000) Soil structure and organic matter I. distribution of aggregate-size classes and aggregate-associated carbon. Soil Science Society of America Journal 64, 681-689. doi: 10.2136/sssaj2000.642681x

Six J, Guggenberger G, Paustian K, Haumaier L, Elliott ET, Zech W (2001) Sources and composition of soil organic matter fractions between and within soil aggregates. European Journal of Agronomy 52, 607-618.

Soetaert W, Vandamme EJ (Eds) (2009) 'Biofuels.' (Wiley: Hoboken, NJ, USA)

Soil Survey Staff (1996) 'Soil survey laboratory methods manual.' (USDA Soil Conservation Service: Washington, DC)

Srinivasan V, Maheswarappa HP, Lai R (2012) Long term effects of topsoil depth and amendments on particulate and non-particulate carbon fractions in a Miamian soil of Central Ohio. Soil & Tillage Research 121, 10-17. doi: 10.1016/j.still.2012.01.014

Tilman D, Hill J, Lehman C (2006) Carbon-negative biofuels from low-input high-diversity grassland biomass. Science 314, 1598-1600. doi: 10.1126/science.l 133306

Tisdall JM, Oades JM (1982) Organic matter and water-stable aggregates in soils. Journal of Soil Science 33, 141-163. doi: 10.1111/j. 1365-2389.1982.tb01755.x

Tolbert VR, Todd DE Mann LK, Jawdy CM, Mays DA, Malik R, Bandaranayake W, Houston A, Tyler D, Pettry DE (2002) Changes in soil quality and below-ground carbon storage with conversion of traditional agricultural crop lands to bioenergy crop production. Environmental Pollution 116, S97-S106. doi: 10.1016/S0269-7491 (01)00262-7

Vermerris W, Rainbolt C, Wright D, Newman Y (2008) 'Production of biofuel crops in Florida: Sweet sorghum.' Publication No. SS-AGR-293. University of Florida Cooperative Extension Service, Tallahassee, FL. pp. 4.

Vinton MA, Burke IC (1995) Interactions between individual plant species and soil nutrient status in short grass steppe. Ecology 76, 1116-1133. doi: 10.2307/1940920

Wilhelm WW, Johnson JMF, Hatfield JL, Voorhees WB, Linden DR (2004) Crop and soil productivity response to com residue removal: a literature review. Agronomy Journal 96, 1-17. doi:10.2134/agronj 2004.0001

Wilson SD (1993) belowground competition in forest and prairie. Oikos 68, 146-150. doi: 10.2307/3545320

WMO (2014) The state of greenhouse gases in the atmosphere based on global observations through 2012. WMO Greenhouse Gas Bulletin No. 9. World Meteorological Organization. Available at: www.wmo. int/pages/prog/arep/gaw/ghg/ghg9-en-online.html

Zan CS, Fyles JW, Girouard P, Samson RA (2001) Carbon sequestration in perennial bioenergy, annual com and uncultivated systems in southern Quebec. Agriculture, Ecosystems & Environment 86, 135-144. doi: 10.1016/SO167-8809(00)00273-5

Zeri M, Anderson-Teixeira K, Hickman K, Masters G, DeLucia M, Bemacchi E (2011) Carbon exchange by establishing biofuel crops in Central Illinois. Agriculture, Ecosystems & Environment 144, 319-329. doi: 10.1016/j.agee.2011.09.006

Anup Das (A,B,E), Rattan Lal (A), Upender Somireddy (A), Catherine Bonin (C), Sudhir Verma (A,D), and Basant Kumar Rimal (A)

(A) Carbon Management and Sequestration Centre, School of Environment and Natural Resources, Ohio State University, Columbus, OH 43210, USA.

(B) Indian Council of Agricultural Research (ICAR), Research Complex for North Eastern Hill (NEH) Region, Umiam, Meghalaya, India.

(C) Department of Agronomy, Iowa State University, Ames, IA 50011, USA.

(D) Dr. YS Parmar University of Horticulture and Forestry, Nauni, Solan, Himachal Pradesh, India.

(E) Corresponding author. Email:

Table 1. Composition of prairie mix and their ecotypes

Species              Scientific name

Big bluestem         Andropogon gerardii
Switch grass         Panicum virgatum

Indian grass         Sorghastrum nutans
Wild senna           Senna (Cassia) hebecarpa
Oxeye sunflower      Heliopsis helianthoides
Showy tick-trefoil   Desmodium canadense

Species              Ecotype                     % of population

Big bluestem         'Prairie View'-IN Ecotype   30
Switch grass         Cave-In-Rock                20
                     Shawnee                     20
                     Kanlow                      10
Indian grass         'Southlow'-MI Ecotype       10
Wild senna           VA and WV Ecotype           5
Oxeye sunflower      PA Ecotype                  3
Showy tick-trefoil   PA Ecotype                  2

Table 2. Soil physical properties as affected by biofuel crops
in two soil layers

[[rho].sub.b], Soil bulk density; l.s.d., least significant
difference; s.e.m., standard error of mean. Within a column, means
followed by the same letter not are significantly different at P =

                              [[rho].sub.b] (Mg [m.sup.-3])

crop                         0-10 cm              10-20 cm

Maize                         1.55ab               1.58ab
Sorghum                       1.60a                1.67a
Switch grass                  1.50b                1.55b
Miscanthus                    1.52ab               1.56b
Prairie mix                   1.50b                1.57b
s.e.m.                        0.03                 0.03
l.s.d. (P=0.05)               0.08                 0.09
Initial [+ or -] s.d.   1.60 [+ or -] 0.02   1.64 [+ or -] 0.03

                                      Porosity (%)

crop                         0-10 cm              10-20 cm

Maize                         0.41ab               0.40a
Sorghum                       0.39b                0.37b
Switch grass                  0.43a                0.41a
Miscanthus                    0.43a                0.41a
Prairie mix                   0.43a                0.41a
s.e.m.                        0.01                 0.01
l.s.d. (P=0.05)               0.04                 0.03
Initial [+ or -] s.d.   0.40 [+ or -] 0.01   0.38 [+ or -] 0.01

                              MWD (mm)           GMD (mm)

crop                    0-10cm   10-20 cm   0-10 cm   10-20 cm

Maize                   4.26bc    3.04b     1.51be     1.19b
Sorghum                 3.66c     3.45a     1.33c      1.30a
Switch grass            4.95a     3.67a     1.71a      1.38a
Miscanthus              4.78ab    4.33a     1.71a      1.55a
Prairie mix             4.70ab    3.65a     1.6lab     1.36a
s.e.m.                  0.20      0.39      0.06       0.11
l.s.d. (P=0.05)         0.62      1.19      0.19       0.34
Initial [+ or -] s.d.   4.56      3.41      1.59       1.32

Table 3. Aggregate size distribution (%) as influenced by biofuel
crops in two soil layers

l.s.d.. Least significant difference; s.e.m., standard error of
mean. Within a column, means followed by the same letter are not
significantly different at P=0.05

                               Aggregate size (mm):

Biofuel crop                4.75-8.0             2-4.75

                                  0-10 cm depth

Maize                                            11,47ab
Sorghum                      44.40c              15.92a
Switch grass                 70.40a               9.01b
Miscanthus                   66.0ab              11.59ab
Prairie mix                  65.5ab               8.71b
s.e.m.                        3.44                1.44
l.s.d. (P=0.05)               10.59               4.43
Initial [+ or -] s.d.   63.5 [+ or -] 1.3   10.1 [+ or -] 2.9

                                  10-20 cm depth

Maize                        41.08b              13.48ab
Sorghum                      39.09b              13.30ab
Switch grass                 45.1lab             14.83a
Miscanthus                   58.950a             10.93b
Prairie mix                  49.96ab             13.62ab
s.e.m.                        5.21                1.23
l.s.d. (P = 0.05)             16.05               3.80
Initial [+ or -] s.d.   39.9 [+ or -] 4.5   16.8 [+ or -] 3.2

                               Aggregate size (mm):

Biofuel crop                 1.0-2.0             0.5-1.0

                                 0-10 cm depth

Maize                         7.62a               7.08a
Sorghum                       8.76a               7.68a
Switch grass                  4.70b               4.02b
Miscanthus                    7.23a               5.27a
Prairie mix                   4.87b               6.62a
s.e.m.                         1.0                0.83
l.s.d. (P=0.05)               3.12                2.51
Initial [+ or -] s.d.   6.1 [+ or -] 0.7     6.2 [+ or -]0.7

                                   10-20 cm depth

Maize                         8.88ab             10.37a
Sorghum                      10.64a              11.70a
Switch grass                 11.78a               9.28a
Miscanthus                    6.55b               8.11a
Prairie mix                   9.75ab              9.22a
s.e.m.                        1.10                1.39
l.s.d. (P = 0.05)             3.40                4.28
Initial [+ or -] s.d.   10.8 [+ or -] 1.3   11.9 [+ or -] 1.0

                                Aggregate size (mm):

Biofuel crop                0.25-0.50             <0.25

                                  0-10 cm depth

Maize                         6.22a              10.06b
Sorghum                       8.35a              14.89a
Switch grass                  4.52a               7.32bc
Miscanthus                    4.59a               5.28c
Prairie mix                   6.34a               7.95bc
s.e.m.                        1.36                1.50
l.s.d. (P=0.05)               4.19                4.61
Initial [+ or -] s.d.   5.5 [+ or -] 1.4    8.6 [+ or -] 1.6

                                  10-20 cm depth

Maize                        12.24a              13.95a
Sorghum                      10.69a              14.57a
Switch grass                  8.38a              10.62a
Miscanthus                    7.28a               8.18a
Prairie mix                   8.03a               9.41a
s.e.m.                        1.78                2.79
l.s.d. (P = 0.05)             5.48                8.59
Initial [+ or -] s.d.   10.2 [+ or -] 1.3   10.4 [+ or -] 2.7

Table 4. Impact of biofuel crops on soil organic carbon (SOC), total
nitrogen (TN), and carbon: nitrogen (C: N) ratio of soil

l.s.d., Least significant difference; s.e.m., standard error of
mean. Within a column, means followed by the same letters are not
significantly different at P = 0.05

                                 SOC (g [kg.sup.-1])

Biofuel crop                 0-10 cm            10-20 cm

Maize                        16.67bc             12.93ab
Sorghum                      15.55c              12.23b
Switch grass                 18.10a              13.70a
Miscanthus                   17.73ab             13.35a
Prairie mix                  16.93abc            12.38b
Mean                         17.00               12.67
s.e.m.                        0.40                0.30
l.s.d. (P=0.05)               1.40                0.91
Initial [+ or -] s.d.   16.2 [+ or -] 0.6   12.6 [+ or -] 2.0

                                TN (g [kg.sup.-1])

Biofuel crop                 0-10cm             10-20 cm

Maize                         1.76a               1.32a
Sorghum                       1.71a               1.23a
Switch grass                  1.65a               1.22a
Miscanthus                    1.61a               1.18a
Prairie mix                   1.64a               1.23a
Mean                          1.67                1.24
s.e.m.                        0.05                0.05
l.s.d. (P=0.05)               0.15                0.16
Initial [+ or -] s.d.   1.60 [+ or -] 0.1   1.23 [+ or -] 0.1

                        C: N ratio

Biofuel crop                 0-10cm             10-20 cm

Maize                         9.46b               9.79b
Sorghum                       9.09b               9.92b
Switch grass                 10.95a              11.25a
Miscanthus                   11.01a              11.31a
Prairie mix                  10.34a              10.08b
Mean                          10.15               10.45
s.e.m.                        0.27                0.27
l.s.d. (P=0.05)               0.83                0.84
Initial [+ or -] s.d.   10.1 [+ or -] 0.7   10.0 [+ or -] 1.2

Table 5. Impact of biofuel crops on soil organic carbon (SOC), total
nitrogen (TN), and carbon: nitrogen (C: N) ratio of macro-and

l.s.d., Least significant difference; s.e.m., standard error of
mean. Within a column, means followed by the same letter are not
significantly different at P=0.05

                               Macroaggregates (0.25-8.0 mm)

Biofuel                  SOC                TN
crop                (g [kg.sup.-1])   (g [kg.sup.-1])   C: N ratio

0-10 cm depth

Maize                   13.58b            1.45bc          9.42a
Sorghum                 13.10b            1.32c          10.00a
Switch grass            15.82a            1.71a           9.29a
Miscanthus              14.51ab           1.66a           8.95a
Prairie mix             14.47ab           1.59ab          9.11a
Mean                    14.53             1.54            9.35
s.e.m.                   0.65             0.12            0.47
l.s.d. (P = 0.05)        2.00             0.38            1.44

10-20 cm depth

Maize                   10.66d            1.19ab          8.96b
Sorghum                  9.87e            1.00b           9.88ab
Switch grass            14.06a            1.28a          11.15a
Miscanthus              12.97b            1.32a           9.86ab
Prairie mix             11.56c            1.08b          10.74a
Mean                    11.82             1.19           10.12
s.e.m.                   0.36             0.08            0.50
l.s.d. (P = 0.05)        1.10             0.24            1.55

                               Microaggregates (<0.25 mm)

Biofuel                   SOC               TN
crop                (g [kg.sup.-1])   (g [kg.sup.-1])   C: N ratio

0-10 cm depth

Maize                   11.74ab            1.15b          10.26a
Sorghum                 10.62b             1.20ab          8.85a
Switch grass            12.60a             1.25ab         10.06a
Miscanthus              11.81a             1.36a           8.75a
Prairie mix             11.60ab            1.14b          10.26a
Mean                    11.94              1.24            9.64
s.e.m.                   0.54              0.06            0.49
l.s.d. (P = 0.05)        1.68              0.19            1.53

10-20 cm depth

Maize                    9.94c             0.97b          10.25a
Sorghum                 10.17b             1.04b           9.82a
Switch grass            12.27a             1.23a          10.08a
Miscanthus              11.84a             1.25a           9.50a
Prairie mix             11.32a             1.04b          10.95a
Mean                    11.11              1.14           10.12
s.e.m.                   0.41              0.05            0.56
l.s.d. (P = 0.05)        1.28              0.14            1.76

Table 6. Stratification ratio of soil organic carbon (SOC) and total
nitrogen (TN) under biofuel crops, with SOC and TN stocks on depth

There were no significant differences between biofuel crops for any
ratio; s.e.m., standard error of mean

Biofuel crop   SOC    SOC stock   TN     TN stock

Maize          1.36   1.31        1.34   1.25
Sorghum        1.33   1.28        1.39   1.24
Switch grass   1.32   1.28        1.36   1.31
Miscanthus     1.33   1.29        1.36   1.33
Prairie mix    1.36   1.31        1.33   1.28
Mean           1.34   1.29        1.36   1.28
s.e.m.         0.05   0.05        0.07   0.07


Please note: Some tables or figures were omitted from this article.
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Author:Das, Anup; Lal, Rattan; Somireddy, Upender; Bonin, Catherine; Verma, Sudhir; Rimal, Basant Kumar
Publication:Soil Research
Article Type:Report
Geographic Code:1U3OH
Date:Jul 1, 2016
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