Economic feasibility of producing sweet sorghum as an ethanol feedstock in the southeastern United States

b i o m a s s a n d b i o e n e r g y 3 5 ( 2 0 1 1 ) 3 0 5 0 e3 0 5 7

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Economic feasibility of producing sweet sorghum as an ethanol feedstock in the southeastern United States Joseph A. Linton 1, J. Corey Miller*, Randall D. Little, Daniel R. Petrolia, Keith H. Coble Department of Agricultural Economics, Mississippi State University, P.O. Box 5187, Mississippi State, MS 39762, USA

article info

abstract

Article history:

This study examines the feasibility of producing sweet sorghum (Sorghum bicolor (L.)

Received 17 September 2010

Moench) as an ethanol feedstock in the southeastern United States through representative

Received in revised form

counties in Mississippi. We construct enterprise budgets along with estimates of trans-

5 April 2011

portation costs to estimate sweet sorghum producers’ breakeven costs for producing and

Accepted 8 April 2011

delivering sweet sorghum biomass. This breakeven cost for the sweet sorghum producer is

Available online 29 April 2011

used to estimate breakeven costs for the ethanol producer based on wholesale ethanol price, production costs, and transportation and marketing costs. Stochastic models are

Keywords:

developed to estimate profits for sweet sorghum and competing crops in two representa-

Cost

tive counties in Mississippi, with sweet sorghum consistently yielding losses in both

Economics

counties. ª 2011 Elsevier Ltd. All rights reserved.

Ethanol Sorghum bicolor Stochastic simulation

1.

Introduction

Despite investigations into various feedstock alternatives to corn for their ethanol-producing capabilities, little present literature examines the economic feasibility of producing sweet sorghum as an ethanol feedstock. Specifically, research that identifies these costs on a large scale, particularly in the southeastern United States, is lacking. Sweet sorghum, a member of the sorghum family, is a warm-weather crop highly tolerant of drought and high temperatures primarily used for fodder and the production of sorghum syrup [1]. Sweet sorghum is touted as a viable candidate for ethanol production due to its high volume of fermentable carbohydrates and relatively low input costs [2,3]. Groups such as [4,5] claim the viability of sweet sorghum as a biofuel feedstock, but emphasize the technical aspects of

obtaining the fermentable carbohydrates from the plant itself. Absent from these discussions is the identification of the costs of ethanol production from sweet sorghum on a large scale, which involves issues such as the farm gate costs of producing sweet sorghum, fermenting the juice derived from sweet sorghum into ethanol, transportation costs for the feedstockdwhether transporting recently cut stalks or expressed juicedand the difference in the potential profits from sweet sorghum and competing crops as biofuel feedstocks. We investigate the economic feasibility of producing sweet sorghum as a biofuel feedstock in the southeastern United States. Specifically, we: (1) determine the cost of producing sweet sorghum as an ethanol feedstock in Mississippi through the use of enterprise budgeting, (2) use this feedstock cost to determine the cost of producing ethanol from sweet sorghum,

* Corresponding author. Tel.: þ1 662 325 0848; fax: þ1 662 325 8777. E-mail addresses: [email protected] (J.A. Linton), [email protected] (J.C. Miller), [email protected] (R.D. Little), [email protected] (D.R. Petrolia), [email protected] (K.H. Coble). 1 Present address: Mississippi Technology Alliance, 134 Market Ridge Drive, Ridgeland, MS 39157, USA. Tel.: þ1 601 960 3610; fax: þ1 601 960 3605. 0961-9534/$ e see front matter ª 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.biombioe.2011.04.007

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and (3) evaluate the competitiveness of sweet sorghum with other major crops in the southeastern United States by generating a distribution of potential profits through the use of stochastic models.

2.

Material and methods

2.1.

Enterprise budgets

In order to estimate costs of production of sweet sorghum, we use a standard enterprise budgeting approach. In this framework, we allocate both fixed and variable costs for sweet sorghum production on a per hectare basis. We use these data along with yield data from university test plots in order to determine the average cost of producing a tonne of sweet sorghum biomass. We construct enterprise budgets using the Mississippi State University Budget Generator, a menu-driven computer program [6]. Following [7] we divide estimates of total costs from the enterprise budgets by expected yield to determine the breakeven price for sweet sorghum biomass. Assuming a particular conversion factor of sweet sorghum biomass to ethanol, we also estimate the price of 1.0 m3 of processed ethanol that allows the ethanol-producing firm to pay the sweet sorghum producer the breakeven price for biomass. We assume the only market for the biomass is as an ethanol feedstock due to the small nature of the market for sweet sorghum as an ingredient for syrup [8]. We construct the sweet sorghum enterprise budget using yield data from on-site experiments at Mississippi State University and scientific literature concerning sweet sorghum growth and harvesting. We considered a wide range of inputs, including lime, fertilizer, and pre-planting practices, and consulted scientific literature to ascertain the best management practices for production of sweet sorghum. Due to disagreement among researchers as to the “best” production practices, cost of production estimates vary. Unlike sugar cane or corn, sweet sorghum requires little irrigation due to its nature as a drought tolerant crop [5,9]. A concern with producing sweet sorghum is selecting a suitable growing period that allows for sweet sorghum to sufficiently mature. According to [10], earlier planting dates (i.e., mid-April to late May) result in higher ethanol yields from sweet sorghum. Optimal harvest occurs somewhere between 114 and 125 d after planting, with indications that yields cease to increase 119 d after planting [11,12]. The production budget developed in this study assumes an initial planting date of 15 April and a harvest date of 15 August of the same year, a frost-free period for most of Mississippi [13]. Equipment use assumed for these budgets is similar to [2]. The fertilizers present in our enterprise budget include nitrogen, potassium, and phosphate, and we follow the recommendations of [14]. The authors use the following inputs for sweet sorghum: apply nitrogen at 100.00 kg ha1, phosphate at 40.31 kg ha1 and potassium at 20 kg ha1. Nitrogen is the only fertilizer common across the agronomic literature we review [2,15,16]. We follow recommendations from the manufacturers of pesticides and herbicides for sweet sorghum. Equipment used in planting, treating, and harvesting stems from personal observation at the sweet sorghum test plot of Memphis BioWorks Foundation in Whiteville, Tennessee, and

[2], who utilize a 5.2 m tandem disk, a 6.4 m field cultivator, an eight-row planter, an eight-row cultivator, and a 13.7 m broadcast sprayer for herbicide application. The tractors assumed in this research include a 78 kW tractor used for disking, cultivating, and planting as well as a smaller tractor (56 kW) for spraying. For harvesting [2], simulate the use of several different systems, from two-row tractor-pulled forage harvesters to four-row self-propelled mobile juice harvesters that pull a tanker. The Whiteville, Tennessee, site utilizes a two-row tractor-pulled forage harvester as well as a prototype sweet sorghum harvester manufactured by Case IH and currently not in commercial use. Table 1 presents the enterprise budget we develop in this study, which we base on a general, best management practice scenario for sweet sorghum production and results in a total production cost for sweet sorghum of 407.19 $ ha1. We compute our estimate using USD in July 2010, and all discussions that follow involving monetary values apply to this same time period, unless stated otherwise. In addition, our calculations assume the average biomass yield (wet basis) for sweet sorghum equals 52.46 t ha1, a value generated by yield data from test plots at Mississippi State University located at approximately 33.4714 latitude, 88.7742 longitude [17]. These yield data were collected from a half-

Table 1 e Estimated per hectare cost of sweet sorghum production.a Item Direct expenses Fertilizers Ammonium nitrate Phosphorus (46% P2O5) Potash (60% K2O) Herbicides Alrazine 90DF Insecticides Dipel ES Seed Sweet Sorghum Seed Operator Labor Tractors Hand Labor Implements Unallocated labor Diesel Fuel Tractors Repair & Maintenance Implements Tractors Interest on operating capital Total Direct Expenses Fixed expenses Implements Tractors Total fixed expenses Total specified expenses

Unit

Price USD

Quantity

Amount USDb

kg kg kg

0.62 1.01 0.97

100.00 40.31 20.00

61.73 40.88 19.40

kg

6.86

2.24

15.37

dm3

9.03

2.33

21.05

kg

11.02

3.62

39.91

hour

10.91

1.88

20.49

hour hour

8.19 10.91

0.07 1.51

0.61 16.45

dm3

1.00

48.45

48.45

ha ha ha

35.76 3.76 7.44

1.00 1.00 1.00

35.76 3.76 7.44 331.28

ha ha

49.79 26.12

1.00 1.00

49.79 26.12 75.91 407.19

a Cost of production estimates are based on 2008 input prices. b Some totals may not add due to rounding.

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season of production in 2009, and appear to be relatively lower than the yields reported in other recent findings [18,19,20,21]. Given this situation, we also calculate our results assuming an average yield closer to that found in other studiesdspecifically, following [20] we assume an average biomass yield (wet basis) of 75 t ha1. The calculations using 75 t ha1 do not generate materially different results from those using 52.46 t ha1, and we do not report these specific findings but discuss the differences in the appropriate sections.

2.2.

Transportation costs

Because we assume the biomass producer pays the cost of hauling the feedstock to the ethanol refinery, transportation costs of the biomass represent an important factor in determining the breakeven cost of the sweet sorghum feedstock. We draw estimates for transportation costs from other research on sweet sorghum and estimates from the Louisiana sugar cane industry, as we assume sweet sorghum transportation costs mirror those of sugar cane transportation costs [22]. We make another important related assumption regarding the distance the raw biomass is being transported, which we derive from the examination by [23] of the energy balance of sweet sorghumbased ethanol. The authors use a distance from the biomass production point to the processing facility of 64.37 km. This single-facility model corresponds more to the ethanol plants [24] describes as well as sugar cane processing in Louisiana. Examining the potential for ethanol production from sweet sorghum juice in Texas [25], finds a cost of transporting wet biomass of 0.226 $ t1 km1. Given standard assumptions about sweet sorghum biomass yield and a transportation distance of 64.37 km, this transportation cost structure yields an additional 763.26 $ ha1 for the sweet sorghum producer above production costs. By suggesting a scenario from the sugar cane industry that charges sweet sorghum producers a fee of 1.10 $ t1 of biomass loaded and then 0.103 $ t1 km1 transported [22], finds an additional cost of 404.76 $ ha1 above production costs. Finally [26], provides another possibility for sweet sorghum transportation costs, again drawn from the sugar cane industry. This scenario uses a beginning rate of 0.696 $ t1 for the first kilometer, and transportation costs increase by 0.116 $ t1 km1 transported up to 34.12 km. After 34.12 km, the maximum fee of 5.93 $ t1 is charged for transportation, yielding an additional cost of 311.09 $ ha1 above the costs of producing the biomass. Assuming the production cost of 407.19 $ ha1 and biomass yield (wet basis) of 52.46 t from section 2.1, total production and transportation costs for the three estimates [22,25,26] equal 1170.45 $, 811.95 $, and 718.28 $ ha1, respectively. These cost estimates increase approximately 20e30% when assuming a biomass yield (wet basis) of 75 t ha1.

2.3.

Conversion factors

We assume values for a number of key factors in the ethanolproducing process, including a conversion factor used for ethanol production from wet sorghum of 35.05 dm3 t1, derived from the value of 43.81 dm3 t1 [18] by applying a 200 g kg1 mass loss of fermentable sugars in transport and storage [19]. Because [19] project actual ethanol yield equals 80% of the theoretical yield in order to account for loss of fermentable

sugar in transportation and storage, we reduce this conversion factor by 20% to more accurately represent potential loss. Thus, we assume an ethanol yield of 1.839 m3 t1, which equals 96.46 m3 ha1. Using the cost of production value for sweet sorghum biomass from the enterprise budget in section 2.1 of 407.19 $, the feedstock production cost equals: ð407:19 $=haÞðð1 ha=ð52:46 tÞÞðð1tÞ=ð0:03505 m3ÞÞ ¼ 221

(1)

Adding the transportation cost estimates from section 2.2 and using our conversion factor for ethanol on a wet basis of 35.05 dm3 t1, the total feedstock production and transportation costs equal 636.59, 441.61, and 390.67 $ m3, respectively. Using an average biomass yield (wet basis) of 75 t ha1 results in a feedstock production cost of 154.90 $ m3. Total feedstock production and transportation costs per-cubic meter are approximately 10e15% lower than those for a yield of 52.46 t ha1.

2.4.

Ethanol production

Many factors play a role in the overall cost of producing ethanol, as [27] identify several factors strongly influencing the success of ethanol plants, including feedstock price, ethanol price, natural gas price, and conversion factors. Although the authors specify these factors for a corn-based ethanol plant, we assume similar importance to sweet sorghum-based ethanol production. Furthermore, we assume transportation and marketing costs of processed ethanol as well as the fixed costs of the ethanol-producing firm influence the final costs for sweet sorghum ethanol production. We assume the ethanol-producing firm faces a fixed cost of 113.59 $ m3 of ethanol produced based on work by [28] as well as data from storage tank manufacturers [29,30]. The analysis of [28] assumes an ethanol plant with a capacity of 227,125 m3 a1 and a 112.5 million $ initial construction cost, and we also assume the processing costs are 198.13 $ m3 of denatured ethanol and that the ethanol-producing firm faces transportation and marketing costs of 52.83 $ m3 of denatured ethanol [18]. Furthermore, we also assume the presence of the Volumetric Ethanol Excise Tax Credit of 118.88 $ m3 but not the 26.42 $ m3 Small Ethanol Producer Credit [31]. Based on conclusions by [32] in their examination of benefits from ethanol subsidies, we assume the entire 118.88 $ m3 credit the blender receives passes through the supply chain to the ethanol producer and, ultimately, the sweet sorghum producer as an ethanol feedstock. They assert the presence of required production quantities of biofuels and the limited production capacity of these fuels allows the ethanol industry to capture the entire ethanol subsidy. Moreover, the portion of the subsidy that passes to the sweet sorghum producer increases as the percentage of the specific feedstock produced used in ethanol production increases. Therefore, we assume because all sweet sorghum grown is used as ethanol feedstock, sweet sorghum producers receive the entire ethanol subsidy. Using the feedstock cost calculated in section 2.3 of 221 $ m3, along with the fixed cost of 113.59 $ m3, processing costs of 198.13 $ m3, and transportation and marketing costs for the ethanol-producing firm of 52.83 $ m3, we calculate a breakeven cost of sweet sorghum ethanol of 585.55 $ m3. However, this calculation assumes the sweet sorghum producer

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Table 2 e Spearman correlation coefficients for wholesale ethanol prices, corn prices, cotton prices, and soybean prices [37,38]. Spearman Correlation Coefficients, N ¼ 36 Wholesale Ethanol Price ($ m3) Wholesale Ethanol Price ($ m3) Corn Price ($ kg1) Cotton Price ($ kg1) Soybean Price ($ kg1)

Corn Price ($ kg1)

Cotton Price ($ kg1)

Soybean Price ($ kg1)

1

0.43455

0.45775

0.42284

0.43455 0.45775 0.42284

1 0.39202 0.75443

0.39202 1 0.50663

0.75443 0.50663 1

incurs zero transportation costs. Including any of the transportation costs calculated in section 2.2 results in a breakeven cost in excess of 754.75 $ m3. Based on recent prices in the ethanol market, these costs are well above the prevailing wholesale price of 523.06 $ m3 [33]. Furthermore, the latter cost estimate exceeds the highest annual average price for wholesale ethanol of 681.56 $ m3 experienced in 2006 [34]. Using an average biomass yield (wet basis) of 75 t ha1 and including any associated transportation cost estimate results in a breakeven cost of ethanol slightly above this price. Thus, under the scenarios we examinedincluding zero transportation costs for the sweet sorghum producerdthe crop does not emerge as a competitive ethanol feedstock.

3. Stochastic analysis of sweet sorghum as an ethanol feedstock One approach to ascertain the potential viability of ethanol production from sweet sorghum in Mississippi involves determining how a sweet sorghum enterprise competes with other crops for land use. Two counties, Bolivar and Monroe, embody distinct agricultural production areas in Mississippi, and we use these locations as representative production operations. Bolivar County is located in the Delta soil region; Monroe County contains a mix of Upper Coastal Plain soil and Blackbelt Prairie soil. Soybeans, corn, and cotton are among the top crops produced as measured by land area in Bolivar and Monroe Counties. According to [35,36], these three crops account for 72% of cropland use in Bolivar County and 52% of cropland use in Monroe County. The majority of the remaining cropland in Bolivar County is devoted to rice production while the remaining land in Monroe County is planted in forages and other small crops, such as tobacco and woody crops. Sweet sorghum, if grown in either of these counties, will compete for land with soybeans, corn, and cotton, as the soil types best suited toward their growth are also best for sweet sorghum. We develop a stochastic model to determine potential profits for sweet sorghum, soybeans, corn, and cotton in Bolivar and Monroe Counties, which involves the simulation of prices for these crops and wholesale ethanol prices. We gathered empirical data from [37,38] for April, 2007, to March, 2010. We calculate Spearman correlation coefficients between the wholesale price of ethanol and the prices of corn, cotton, and soybeans, which we depict in Table 2. Employing these correlation coefficients, we simulate 5000 prices using the Phoon, Quek, and Huang (PQH) procedure

[39,40] and these means and standard deviations are shown in Table 3. This procedure allows for the simulation of variables while maintaining the correlation between the variables. We use these simulated prices, along with the budget data constructed for this study, expected yields for sweet sorghum, corn, cotton, and soybeans, production costs from budgets [41,42], and transportation costs from various sources to estimate profits for sweet sorghum, corn, cotton, and soybeans. The profit calculations for both counties require several assumptions, notably our production costs of sweet sorghum biomass of 407.19 $ ha1 and production costs for the competing crops from [41,42]. The difference between the sets of simulated profits for sweet sorghum biomass in each county equals the transportation cost incurred by the sweet sorghum producer. Given these different transportation costs, we calculate potential profits for sweet sorghum, along with potential profits for corn, cotton, and soybeans in Bolivar County and Monroe County. Profit calculations in both cases for sweet sorghum assume breakeven values for the ethanol-producing firm in the production of ethanol (i.e., that the firm pays the maximum it can for sweet sorghum biomass without incurring a net loss).

4.

Results

We use a prevailing wholesale ethanol price of 523.06 $ m3 to calculate the potential price of sweet sorghum biomass. We subtract 52.83 $ m3 for transportation and marketing cost for refined ethanol; 113.59 $ m3 for fixed costs, and 198.13 $ m3 for processing costs for refined ethanol. The remainder yields a maximum feedstock cost of 158.51 $ m3 of ethanol, which is below our general, best management practice scenario for sweet sorghum production of 221 $ m3. Assuming a conversion factor (wet basis) of 35.05 dm3 t1, the ethanol-producing firm can breakeven paying up to 5.56 $ t1 of biomass. Table 4 presents sweet sorghum biomass estimated production costs,

Table 3 e Means and standard deviations of simulated prices. Variable 3

Wholesale Ethanol Price ($ m ) Corn Price ($ kg1) Cotton Price ($ kg1) Soybean Price ($ kg1)

Mean

Std. dev.

490 0.16 1.21 0.37

0.33951 0.64293 0.08178 1.66285

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Table 4 e Estimated per hectare production and transportation costs, potential revenue, and profits, USD, for sweet sorghum biomass in Bolivar County and Monroe County, Mississippi. County Revenue Production costs Transportation costs Salassi Morris Broussard Profits Salassi Morris Broussard

Bolivar

Monroe

364.28 407.19

291.44 407.19

505.95 953.89 388.87

404.76 763.26 311.09

(548.86) (996.80) (431.78)

(520.51) (879.01) (426.84)

potential revenue, estimated transportation costs (at a distance of 64.37 km) and potential profits. Estimated profits for sweet sorghum remain negative under even the lowest estimated transportation costs. Although estimated revenue is greater in Bolivar County than in Monroe County, increased transportation costs due to higher expected yields in Bolivar County (65.57 t ha1, as opposed to 52.46 t ha1 in Monroe County) lead to lower potential profits for sweet sorghum in Bolivar County in all scenarios. Similarly, when using an average biomass yield (wet basis) of 75 t ha1 for the Monroe County location and a 25% higher yield of 93.75 t ha1 for Bolivar County, potential losses increase in all scenarios for Bolivar County due to higher transportation costs. Losses are reduced but remain present for Monroe County under the transportation cost estimates of [25,26] and increase under the estimate of [22]. Table 5 encapsulates potential yield, cost, revenue, and profit data for corn, cotton, and soybeans in Bolivar County and Monroe County, drawing costs from [41,42]. We list “specified expenses”, or costs that attempt to capture both variable and fixed costs. Revenue equals expected yield multiplied by the expected price, and profit equals revenue minus specified cost. We also note that revenue and profits found in Table 5 do not include any government payments. The second portion of this estimation uses the PQH procedure to simulate 5000 random prices for ethanol, corn, cotton, and soybeans with the same correlation probability as 1095 d of empirical data gathered from [37,38]. We multiply these prices

by expected yields to calculate potential gross revenue for crop producers in Bolivar County and Monroe County. We then subtract production costs for the different crops from the gross revenue in order to estimate the distribution of potential profits for the sweet sorghum producer. As before, these calculations do not include government payments to the crop producer. We use different transportation cost scenarios to examine the potential feasibility of sweet sorghum compared to other crops in Bolivar County and Monroe County. The first scenario, found in Table 6, uses a transportation cost of sweet sorghum biomass of 0.226 $ t1 km1. In each case, stalk crushing and juice extraction occur at the ethanol-producing plant, so the transported material becomes the sweet sorghum stalks. Additionally, we assume the plant is located 64.37 km from the sweet sorghum production point. Sweet sorghum production incurs mean losses in both counties, (871.44) $ ha1 in Monroe County and (1002.83) $ ha1 in Bolivar County. Other than cotton, sweet sorghum experiences the lowest mean profits of the four crops examined in both counties. Positive potential profits for sweet sorghum take place in less than 1% of cases in Bolivar County, and do not occur in Monroe County for [25] transportation costs. The second scenario uses [22] estimates for transporting sugar cane from field to the processing mill, and because [22] indicates these transportation costs are similar to those of sweet sorghum, we use them as an estimate. This case results in higher mean potential profits for sweet sorghum in Bolivar County and Monroe County than under [25] transportation costs, but both values remain negative. For Monroe County, sweet sorghum production results in the second-highest mean profits, but the producer still incurs a net loss of about (512.94) $ ha1, as seen in Table 6. However, this value represents a smaller loss than those of the competing crops of cotton and soybeans. Similarly, in Bolivar County the producer incurs losses of (554.70) $ ha1 in this scenario; sweet sorghum earns the lowest mean estimated profits for any crop in Bolivar County. Estimated profits are positive 0.90% of the time and 0.40% of the time in Bolivar County and Monroe County, respectively, for [22]. In the last scenario, we use [26] transportation cost estimates to calculate total costs to the sweet sorghum producer, and therefore potential realized profits. We report the mean profits for Monroe County and Bolivar County in Table 6. Sweet sorghum production under these transportation cost assumptions incurs losses in Monroe County under [26]

Table 5 e Estimated production costs, yields, prices, revenues, and profits, USD, for major crops in Bolivar County and Monroe County, Mississippi [38,41,42]. Expected Yield (kg ha1)

Price ($ kg1)

Revenue

Profit

Bolivar County, Mississippi Corn 924.96 Cotton 1485.45 Soybeans 583.86

9817 951 2717

0.13 1.19 0.286

1319.42 1138.90 777.69

394.45 (346.54) 193.83

Monroe County, Mississippi Corn 893.14 Cotton 1539.84 Soybeans 604.02

5373 656 1957

0.13 1.19 0.286

721.97 784.96 560.16

(171.17) (754.91) (43.86)

Crop

Production Cost (per ha)

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Table 6 e Estimated Bolivar County and Monroe County, Mississippi, profits, USD, using multiple transportation costs [22,25,26].a Variable Bolivar Corn Profit Bolivar Cotton Profit Bolivar Soybean Profit Bolivar Sweet Sorghum Profit Salassi Morris Broussard Monroe Corn Profit Monroe Cotton Profit Monroe Soybean Profit Monroe Sweet Sorghum Profit Salassi Morris Broussard

Mean

Std. Dev.

Median

Minimum

Maximum

$616.85 ($347.28) $407.50

$102.04 $68.21 $66.88

$597.03 ($360.01) $394.31

($119.50) ($833.14) ($23.30)

$1723.54 $414.62 $1261.42

($554.70) ($1002.83) ($437.62) ($48.14) ($755.40) ($579.49)

$83.47 $83.47 $83.47 $55.84 $47.01 $1.66

($571.93) ($1020.05) ($454.82) ($58.96) ($764.17) ($579.81)

($1100.66) ($1548.78) ($983.55) ($451.04) ($1090.28) ($590.14)

$458.23 $10.11 $575.31 $557.45 ($230.30) ($558.36)

($512.94) ($871.44) ($419.26)

$66.78 $66.78 $66.78

($526.71) ($885.21) ($433.03)

($949.70) ($1308.20) ($856.02)

$297.42 ($61.08) $391.09

a Number of simulated observations ¼ 5000.

transportation costs, as the producer realizes a net loss of (419.27) $ ha1; estimated profits are positive 1.3% of the time. However, this mean estimated profit represents the secondhighest mean estimated profit for the crops examined in Monroe County. Mean estimated losses for sweet sorghum also generate mean estimated losses in Bolivar County using [26], as producers potentially lose an average of (437.62) $ ha1; profits for sweet sorghum are positive 2.56% of the time. Mean estimated profits for sweet sorghum are lower than those of any of the competing crops in Bolivar County. When assuming an average biomass yield (wet basis) of 75 t ha1 for the Monroe County location and a 25% higher yield of 93.75 t ha1 for Bolivar County, losses experienced in Bolivar County increase under all transportation cost estimates. The losses incurred by the Monroe County location under our production cost estimate and the transportation cost estimates of [25,26] decrease while the loss experienced under the transportation cost of [22] increases.

5.

Conclusions

Our study determines the economic feasibility of producing sweet sorghum as an ethanol feedstock in Mississippi with the enterprise budget we construct for a general, best management practice scenario resulting in a total production cost for sweet sorghum of 407.19 $ ha1. We assume total costs of producing and delivering sweet sorghum biomass also depend on the transportation costs, and we assume a transported distance of 64.37 km [23]. Employing three different transportation cost estimates, using breakeven costs from enterprise budgets, and recent wholesale prices of ethanol, we find no incentive to produce sweet sorghum as a feedstock. Additionally, applying all government subsidies and tax credits currently in effect for sweet sorghum-based ethanol (i.e., the 118.88 $ m3 Volumetric Ethanol Excise Tax Credit and the Small Ethanol Producer Credit of 26.42 $ m3) will not change this finding, even at the higher ranges of historic wholesale ethanol prices. We also compare the costs and benefits of producing ethanol from sweet sorghum with those of corn on a per-cubic meter

basis. Given [26] transportation cost estimates, a production cost of 407.19 $ ha1, and a yield of 52.46 t ha1, we find a cost of producing and delivering of 13.69 $ t1. Assuming a conversion factor for ethanol of 35.05 dm3 t1 of biomass, at this price the ethanol-producing firm pays 390.64 $ m3 of ethanol produced in feedstock costs, and the sweet sorghum producer can breakeven on the cost of producing biomass. Conversely, for an average corn price of 0.134 $ kg1 and a conversion factor for ethanol of 0.419 dm3 kg1 of corn, the ethanol-producing firm faces a feedstock cost of 319.99 $ m3 of ethanol produced [24]. We estimate profits for sweet sorghum and competing crops from stochastic models for both Bolivar County and Monroe County, Mississippi, which represent distinct production areas in the state. Using the PQH procedure we simulate 5000 correlated values for the average prices for wholesale ethanol, corn, cotton, and soybeans. We also utilize average estimates of yields in the two counties, along with production costs [41,42]. We find under all examined transportation cost structures both counties experience mean estimated losses for sweet sorghum. The lowest estimate of transportation cost for sweet sorghum biomass results in mean estimated profits for sweet sorghum below those of corn in Monroe County and below those of corn, cotton, and soybeans in Bolivar County. Additionally, the probability of positive profits is much lower for sweet sorghum than at least one of the competing crops in both Monroe County and Bolivar County. While sweet sorghum may be a viable source of biofuel with ethanol yields comparable to corn, at present the incentive lies with other crops for a profit-maximizing producer. Moreover, although not included in our analysis, corn, cotton, and soybeans represent crops receiving federal commodity program benefits, unlike sweet sorghum. Thus the comparative attractiveness of sweet sorghum will decrease even further when these programs are taken into account, which may also explain the continued production of these crops despite the negative returns we estimate. An obvious caveat to our findings hinges on the sensitivity of the assumptions we employ. For example, the competitiveness of sweet sorghum as an ethanol feedstock will change with

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increases in yields, decreases in transportation costs, and increases in ethanol prices.

Acknowledgements We thank Jeff Broussard and Michael Salassi for the information they provided for use in this study. This material is based upon work performed through the Sustainable Energy Research Center at Mississippi State University and is supported by the Department of Energy under Award Number DEFG3606GO86025.

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