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Consumer Interest in Environmentally Beneficial Chicken Feeds:Comparing High Available Phosphorus Corn and Other Varieties

Published online by Cambridge University Press:  26 January 2015

John D. Pesek Jr. ,
John C. Bernard  and
Meeta Gupta
John D. Pesek Jr.
Affiliation:
Department of Food and Resource Economics, University of Delaware, Newark, Delaware
John C. Bernard
Affiliation:
Department of Food and Resource Economics, University of Delaware, Newark, Delaware
Meeta Gupta
Affiliation:
Department of Food and Resource Economics, University of Delaware, Newark, Delaware
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Abstract

One source of phosphorous pollution in areas of high chicken production isrunoff from fields using fertilizer from these operations. A potentialsolution is to feed chicken high available phosphorus (HAP) corn, reducingphosphorus in manure. This study examined consumer purchase likelihood ofchickens fed HAP, created traditionally or through genetic modification, andother genetically modified (GM) corn including Bt and Roundup-ready. Surveyresults from the Delmarva Peninsula found considerable interest in non-GMHAP corn, although GM HAP corn was not typically viewed as more acceptablethan other GM varieties. Overall, the marketplace appears open to productsgeared toward environmental benefits.

Keywords

chickenconjoint analysiscorngenetically modifiedheteroscedasticphosphorus pollutionTobitQ13D12C24
Type
Research Article
Information
Journal of Agricultural and Applied Economics , Volume 43 , Issue 4 , November 2011 , pp. 591 - 605
Copyright
Copyright © Southern Agricultural Economics Association 2011

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References

Ares, G., Giménez, A., and Gámbaro, A. “Consumer Perceived Healthiness and Willingness To Try Functional Milk Desserts. Influence of Ingredient, Ingredient Name and Heath Claim.” Food Quality and Preference 20(2009):50–56.10.1016/j.foodqual.2008.07.002Google Scholar
Atkinson, A.C., and Donev, A.N. Optimum Experimental Designs. Oxford Statistical Science Series. New York: Oxford University Press, 1992.Google Scholar
Baker, G.A., and Burnham, T.A. “Consumer Response to Genetically Modified Foods: Market Segment Analysis and Implications for Producers and Policy Makers.” Journal of Agricultural and Resource Economics 26(2001):387–403.Google Scholar
Baxter, C.A., Joem, B.C., Ragland, D., Sands, J.S., and Adeola, O. “Phytase, High-Available-Phosphorous Corn, and Storage Effects on Phosphorous Levels in Pig Excreta.” Journal of Environmental Quality 32(2003):1481–89.10.2134/jeq2003.148112931905Google Scholar
Benbrook, CM. “Genetically Engineered Crops and Pesticide Use in the United States: The First Nine Years.” BioTech InfoNet Technical Paper No. 7, 2004.Google Scholar
Bernard, J.C., Zhang, C., and Gifford, K. “An Experimental Investigation of Consumer Willingness to Pay for Non-GM Foods When an Organic Option is Present.” Agricultural and Resource Economics Review 35(2006):374–85.Google Scholar
Bernard, J.C., Pesek, J.D. Jr., and Pan, X. “Consumer Likelihood to Purchase Chickens with Novel Production Attributes.” Journal of Agricultural and Applied Economics 39(2007):581–96.S1074070800023282Google Scholar
Bonham, J., Bosch, D., and Pease, J. “Cost-Effectiveness of Nutrient Management and Buffers: Comparisons of Two Spatial Scenarios.” Journal of Agricultural and Applied Economics 38(2006):17–32.S1074070800022045Google Scholar
Boyle, K.J., Holmes, T.P., Teisl, M.F., and Roe, B. “A Comparison of Conjoint Analysis Response Formats.” American Journal of Agricultural Economics 83(2001):441–54.10.1111/0002-9092.00168Google Scholar
Center for Food Safety. 2009. “GE Food.” Internet site: http://truefoodnow.org/campaigns/genetically-engineered-foods/ (Accessed July 27, 2011).AMBIGUOUS (871133 citations)Google Scholar
M., Costa-Font, Gil, J.M., and Traill, B. “Consumer Acceptance, Valuation of and Attitudes Towards Genetically Modified Foods: Review and Implications for Food Policy.” Food Policy 33(2008):99–111.10.1016/j.foodpol.2007.07.002Google Scholar
Cox, D.N., Evans, G., and Lease, H.J. “The Influence of Information and Beliefs about Technology on the Acceptance of Novel Food Technologies: A Conjoint Study of Farmed Prawn Concepts.” Food Quality and Preference 18(2007):813–23.10.1016/j.foodqual.2007.01.011Google Scholar
Delaware Department of Agriculture. 2007. “Nutrient Management.” Internet site: http://dda.delaware.gov/nutrients/index.shtml (Accessed August 16, 2007).AMBIGUOUS (781821 citations)Google Scholar
Delmarva Poultry Industry, Inc. “Delmarva Soybeans and Corn Production and Broiler Chicken Use—2007.” Internet site: http://www.dpichicken.org/download/soybean.doc (Accessed April 24, 2008).AMBIGUOUS (830868 citations)Google Scholar
Dillman, D.A. Mail and Internet Surveys. 2nd ed. New York: John Wiley and Sons, 2000.Google Scholar
Dumouchel, W.H., and Duncan, G.J. “Using Sample Survey Weights in Multiple Regression Analyses of Stratified Samples.” Journal of the American Statistical Association 78(1983):535–43.10.1080/01621459.1983.10478006Google Scholar
Fernando-Cornejo, J.C., and McBride, W.D. The Adoption of Bionengineered Crops. Washington, DC: US Department of Agriculture, Economic Research Service, Ag Econ Rep. No. 810, 2002.Google Scholar
Fields, D., and Gillespie, J.M. “Beef Producer Preferences and Purchase Decisions for Livestock Price Insurance.” Journal of Agricultural and Applied Economics 40(2008):789–803.S1074070800002339Google Scholar
Green, P.E., and Srinivassan, V. “Conjoint Analysis in Marketing: New Developments with Implications for Research and Practice.” Journal of Marketing 54(1990):3–19.10.2307/1251756Google Scholar
Greene, W.H. LIMDEP Version 8.0 Econometric Modeling Guide. Plainview, NY: Econometric Software, 2002.Google Scholar
Haefele, M.A., and Loomis, J.B. “Improving the Connection between Theory and Empirical Analysis of Stated Preference and Conjoint Data: Improving Statistical Efficiency and Testing Robustness of Conjoint Marginal Valuations.” American Journal of Agricultural Economics 83(2001):1321–27.10.1111/0002-9092.00285Google Scholar
Halbrendt, C., Bacon, J.R., and Pesek, J. “Weighted Least Squares Analysis for Conjoint Studies: The Case of Hybrid Striped Bass.” Agribusiness 8(1992):187–98.10.1002/1520-6297(199203)8:2<187::AID-AGR2720080209>3.0.CO;2-#3.0.CO;2-#>Google Scholar
Halbrendt, C., Pesek, J.D., Parsons, A., and Lindner, R. “Consumer Preference for pST-Supplemented Pork.” Australian Journal of Agricultural Economics 38(1994):189–202.10.1111/j.1467-8489.1994.tb00539.xGoogle Scholar
Harrison, R.W., Gillespie, J., and Fields, D. “Analysis of Cardinal and Ordinal Assumptions in Conjoint Analysis.” Agricultural and Resource Economics Review 34(2005):238–52.Google Scholar
Harrison, R.W., and Mclennon, E. “Analysis of Consumer Preferences for Biotech Labeling Formats.” Journal of Agricultural and Applied Economics 36(2004):159–71.S1074070800021921Google Scholar
Harrison, R.W., and Sambidi, P.R. “A Conjoint Analysis of the U.S. Broiler Complex Location Decision.” Journal of Agricultural and Applied Economics 36(2004):639–55.S1074070800026924Google Scholar
Harrison, R.W., Stringer, T., and Priyawiwatkul, W. “An Analysis of Consumer Preferences for Value-Added Seafood Producers Derived from Crawfish.” Agricultural and Resource Economics Review 31(2002):157–70.Google Scholar
Huffman, W.E., Shogren, J.F., Rousu, M., and Tegene, A. “Consumer Willingness to Pay for Genetically Modified Food Labels in a Market with Diverse Information: Evidence from Experimental Auctions.” Journal of Agricultural and Resource Economics 28(2003):481–502.Google Scholar
Kaneko, N., and Chem, W.S. “Willingness to Pay for Genetically Modified Oil, Cornflakes, and Salmon: Evidence from a U.S. Telephone Survey.” Journal of Agricultural and Applied Economics 27(2005):701–19.Google Scholar
Koelsch, R. 2003. “Fact Sheet #2: Do I Need an NPDES Permit for My Livestock or Poultry Operation?” CAFO Fact Sheet Series. Internet site: http://www.extension.org/mediawiki/files/3/3d/02FS_Permit.pdf (Accessed July 7, 2009).AMBIGUOUS (591927 citations)Google Scholar
Kuhfeld, W.F. 2009. “Marketing Research Methods in SAS.” SAS Institute Inc., Technical Papers. Internet site: http://support.sas.com/techsup/technote/ts722.pdf (Accessed April 29, 2010).AMBIGUOUS (871133 citations)Google Scholar
Long, J.S. Regression Models for Categorical and Limited Dependent Variables. Los Angeles, CA: Sage Publications, Inc., 1997.Google Scholar
Louviere, J.J. Analyzing Decision Making: Metric Conjoint Analysis. Los Angeles, CA: Sage Publications, Inc., 1988.Google Scholar
Lusk, J.L., House, L.O., Valli, C., Jaeger, S.R., Moore, M., Morrow, J.L., and Traill, W.B. “Effect of Information about the Benefits of Biotechnology on Consumer Acceptance of Genetically Modified Food: Evidence from Experimental Auctions in the United States, England, and France.” European Review of Agriculture Economics 31(2004):179–204.10.1093/erae/31.2.179Google Scholar
Lusk, J.L., Jamal, M., Kurlander, L., Roucan, M., and Taulman, L. “A Meta-Analysis of Genetically Modified Food Valuation Studies.” Journal of Agricultural and Resource Economics 30(2005):28–44.Google Scholar
Lusk, J.L., Roosen, J., and Fox, J.A. “Demand for Beef from Cattle Administered Growth Hormones or Fed Genetically Modified Corn: A Comparison of Consumers in France, Germany, the United Kingdom, and the United States.” American Journal of Agricultural Economics 85(2003):16–29.10.1111/1467-8276.00100Google Scholar
Maryland Cooperative Extension's Nutrient Management Program. “How the MCE Nutrient Management Program Got Started.” 2006. Internet site: http://www.agnr.umd.edu/users/agron/nutrient/Bkgrnd/History_ANMP.pdf (Accessed September 20, 2006).AMBIGUOUS (743548 citations)Google Scholar
National Agricultural Statistics Service, Agricultural Statistics Board. “Poultry—Production and Value 2006 Summary.” Washington, DC: U.S. Department of Agriculture, 2007. Internet site: htm://usda.mannlib.comell.edu/usda/current/PoulProdVa/PoulProdVa-04-27-2007_revision.pdf (Accessed April 24, 2008).AMBIGUOUS (781821 citations)Google Scholar
National Agricultural Statistics Service. 2007a. 2007 Census of Agriculture-State Data. “Delaware Table 27. Poultry—Inventory and Number Sold: 2007 and 2002.” Washington, DC: U.S. Department of Agriculture. Internet site: http://www.agcensus.usda.gov/Publications/2007/Full_Report/Volume_ 1,_Chapter_1_State_Level/Delaware/st10_1_027_028.pdf (Accessed July 20, 2009).AMBIGUOUS (781821 citations)Google Scholar
National Agricultural Statistics Service. 2007b. 2007 Census of Agriculture-State Data. “Maryland Table 27. Poultry—Inventory and Number Sold: 2007 and 2002.” Washington, DC: U.S. Department of Agriculture. Internet site: http://www.agcensus.usda.gov/Publications/2007/Full_Report/Volume_1,_Chapter_1_State_Level/Maryland/st24_l_027_028.pdf (Accessed July 20, 2009).AMBIGUOUS (781821 citations)Google Scholar
Natural Resources Conservation Service. 2005. “Delaware 2005 State Environmental Quality Incentive Program (EQIP) Sign-Up and Application Information. General Program Description.” Washington, DC: U.S. Department of Agriculture, 2005. Internet site: http://www. de.nrcs.usda.gov/programs/eqip/2005/index.html (Accessed July 23, 2009).AMBIGUOUS (697180 citations)Google Scholar
Natural Resources Conservation Service, Environmental Quality Incentives Program. “Program Description.” Washington, DC: U.S. Department of Agriculture, 2009. Internet site: http://www.nrcs.usda.gov/programs/eqip/index.html#prog (Accessed July 23, 2009).AMBIGUOUS (871133 citations)Google Scholar
Norwood, F., and Chvosta, J. “Phosphorus-Based Applications of Livestock Manure and the Law of Unintended Consequences.” Journal of Agricultural and Applied Economics 37(2005):79–90.S1074070800007112Google Scholar
Onyango, B., Nayga, R.M. Jr., and Schilling, B. “Role of Product Benefits and Potential Risks in Consumer Acceptance of Genetically Modified Foods.” AgBioForum 7(2004):202–11.Google Scholar
Pew Initiative on Food and Biotechnology. “Public Sentiment about Genetically Modified Food.” 2001. Internet site: http://www.pewtrusts.com. (Accessed June 12, 2006).AMBIGUOUS (544358 citations)Google Scholar
Pew Initiative on Food and Biotechnology. “Public Sentiment about Genetically Modified Food.” 2003. Internet site: http://www.pewtrusts.com (Accessed June 12, 2006).AMBIGUOUS (591927 citations)Google Scholar
Raboy, V., and Gerbasi, P. “Genetics of myoinositol phosphate synthesis and accumulation.” Subcellular Biochemistry: Myo-inositol Phosphates, Phosphoinositides, and Signal Transduction L. Biswas, B.B. and Biswas, S., eds. New York: Plenum Press, 1996.Google Scholar
Raboy, V., Young, K.A., Dorsch, J.A., and Cook, A. “Genetics and breeding of seed phosphorus and phytic acid.” Journal of Plant Physiology 158(2001):489–97.10.1078/0176-1617-00361Google Scholar
Ribaudo, M., Gollehon, N., Aillery, M., Kaplan, J., Johansson, R., Agapoff, J., Christensen, L., Breneman, V., and Peters, M. Manure Management for Water Quality: Costs to Animal Feeding Operations of Applying Manure Nutrients to Land. Washington, DC: U.S. Department of Agriculture/Economics Research Service, Agricultural Economic Report No. 824, 2003. Internet site: http://www.ers.usda.gov/PUBLICATIONS/AER824/ (Accessed February 6, 2006).Google Scholar
Rosett, R.N., and Nelson, F.D. “Estimation of the Two-Limit Probit Regression Model.” Econometrica 43(1975):141–46.10.2307/1913419Google Scholar
SAS Institute Inc. SAS OnlineDoc® 9.1. Cary, NC: SAS Institute Inc., 2003.Google Scholar
Saylor, W.W. Personal Communication. Mono-gastric Nutritionist, University of Delaware, College of Agriculture and Natural Resources, Department of Animal and Food Sciences. May 2007.AMBIGUOUS (781821 citations)Google Scholar
Saylor, W.W., Sims, J.T., Malone, G.W., and Lavahun, M.F. “Use of Phytase and High-Available Phosphorus Corn in Broiler Diets: Impact on Litter Phosphorus Levels and Solubility.” 2001 Maryland Nutrition Conference Proceedings, April, 2001.Google Scholar
Saylor, W.W., Sims, J.T., Malone, G.W., and Lavahun, M.F. “Phytase, HAP Corn Combination May Reduce Phosphorus Excretion.” Feedstuff's 74(2002):16–19, 33.Google Scholar
Smith, D.S., Moore, P.A. Jr., Miles, D.M., Haggard, B.E., and Daniel, T.C. “Decreasing Phosphorus Runoff Losses from Land Applied Poultry Litter with Dietary Modifications and Alum Addition.” Journal of Environmental Quality 33(2004):2210–16.10.2134/jeq2004.221015537944Google Scholar
Teisl, M.F., Garner, L., Roe, B., and Vayda, M.E. “Labeling Genetically Modified Foods: How Do U.S. Consumers Want to See It Done?” AgBioForum 6(2003):48–54.Google Scholar
U.S. Census. 2000. Internet site: http://www.census.gov/mairi/www/cen20(X).html (Accessed February 6, 2011).Google Scholar