Abstract
Previous economic analyses of energy from corn stover assumed yield reductions from residue removal (without nutrient replacement) and limited or no supply response by farmers to changes in the price of stover. We exploit agronomic and cost information from a randomized block design experiment to model and quantify farmers’ supply response to changes in relative prices of corn stover, corn grain, and soybean. We then couple this supply response with a model of a cost-minimizing processing plant. Results suggest that stover-based energy may be closer to economic viability than previously found. In addition, in areas where reductions in corn yield due to corn monoculture are small, processing plants may find optimal to pay a higher price for stover to induce farmers to adopt continuous corn because it reduces transportation cost. This suggests that such areas may experience changes in their land cover configuration if stover-based energy does become commercially viable.
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Notes
The words “stover” and “residue” are used interchangeably in this study. They both include all nongrain aboveground biomass; i.e., cob, stalk, and leaves
In particular, they have assumed that the farmer applies 7.7 kg of fertilizer/tonne of residue removed to keep nutrients and grain yields constant which constitutes a significant economic cost associated with residue harvest.
Removing corn residue from the field has been shown to reduce soil organic matter [21] and this may, though not clearly quantified in the literature, have an impact in yields in the long run. This study ignores this potential effect due to lack of sufficient information to quantify it.
The words “harvest” and “removal” are, henceforth, used interchangeably.
Simulations available from the authors.
Quantity harvested within radius R is q = πdR 2. Total transportation cost at radius r is d(2πr)rt where t is per unit transportation cost. Integrating from r = 0 to r = R, C = (2/3)tdπR 3. Substituting q for R, C(R) = (2/3)t(dπ)−1/2 q 3/2.
If stover price increases beyond that level only rises in total cost result as there are no additional density surges that the plant can benefit from.
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Acknowledgments
The authors are grateful for research assistance from Tianyun Ji, Carson Reeling, and E.M. Sajeev and would like to thank Sylvie Brouder and Jeff Volenec for crop yield data collected at the Purdue University Water Quality Field Station. This study has also received support from the North Central SunGrant Initiative.
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Appendices
Appendix 1
Proof of proposition
CRCR will dominate CRCN if and only if
Where \( y_{\mathrm{CK}}^c \) is continuous corn after residue was removed (K = R or was not removed (K = N, \( \left( {K=N} \right)c_{\mathrm{CK}}^c \) is the (per hectare) cost of producing corn after corn with residue removal or without residue removal \( \left( {K=N} \right)c_{\mathrm{CK}}^c \) is the (per hectare) cost of harvesting stover producing corn after corn with residue removal (K = R or without residue removal (K = N
Rearranging this expression yields:
If residue removal increases yield (\( y_{\mathrm{CR}}^c>y_{\mathrm{CN}}^c \)), we can re-express yield under CRCR as \( y_{\mathrm{CR}}^c=y_{\mathrm{CN}}^c+\varDelta \), where Δ is a positive number. Let us assume that the cost of harvesting stover is independent of past rotations (\( c_{\mathrm{CR}}^s=c_{\mathrm{CN}}^s \)). Therefore:
CNCN will dominate CRCN if
Rearranging this expression yields:
CRCN will be dominated by either CRCR or CNCN if \( p_s^{{\mathrm{CNCN},\ \mathrm{CRCN}}} > p_s^{{\mathrm{CRCR},\ \mathrm{CRCN}}} \), and this inequality will hold if and only if Δ is positive.
Appendix 2
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Sesmero, J.P., Gramig, B.M. Farmers’ Supply Response, Price of Corn Residue, and Its Economic Viability as an Energy Feedstock. Bioenerg. Res. 6, 797–807 (2013). https://doi.org/10.1007/s12155-013-9300-0
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DOI: https://doi.org/10.1007/s12155-013-9300-0