The economic implications of new technologies that may be commercialized are of paramount concern for industry stakeholders. Agricultural economists are keenly aware that producers face such choices and offer a range of practices to measure the potential benefits and costs of new technologies. Work has been done that focuses on specific technologies in specific industries; for example, Lemieux and Wohlgenant (1989) and Lesser et al. (1999) present frameworks to examine the ex ante economic impacts of specific biotechnologies in animal agriculture that had not yet been deregulated and commercialized. Much of this earlier work examined industries with relatively little product differentiation, and in the modeling effort the technology was assumed to affect all products in the same way. Horticultural crops, however, often are highly differentiated across, and even within, cultivars. For many fruit crops there are different grades, and then within each grade there are various size classifications. If new technologies introduced into horticultural markets affect products differentially, then the economic framework for evaluation needs to accommodate these idiosyncrasies.
An accurate ex ante evaluation of novel innovations is difficult when the benefits of the new technology to individual producers are not very well understood. This is further complicated in food and agricultural markets as new technologies are often controversial and the benefits are not shared equally to all constituents (including all products and all producers) in the supply chain. New technologies are typically described as either revenue enhancing or cost reducing. Revenue-enhancing technologies have the capacity to increase yields, increase quality, and influence prices if the final products are transformed or are able to enter new markets. Cost-reducing technologies often introduce innovations that reduce overall input use or allow producers to switch to less expensive inputs. In some cases, we observe innovations that are both revenue-enhancing and cost-reducing.
The empirical example that motivates our work is the use of biomarkers to manage postharvest physiological disorders in long-term controlled atmosphere (CA) apple storage. Such disorders are nontrivial for some of the major apple cultivars produced in the United States, and they can lead to significant economic losses for apple producers (Rudell and Watkins, 2011). Some of the most critical physiological disorders that occur in apple storage include superficial scald for ‘Granny Smith’, soft scald for ‘Honeycrisp’, external CO2 injury for ‘Empire’, and firm-flesh browning for ‘Empire’ (see illustrations in Supplemental Fig. 1). Biomarker technologies have the capacity to be a revenue-enhancing technology if they provide reliable information that would allow the storage operator to reduce the share of downgraded fruit and/or to market a greater share of the stored fruit in higher quality grades. The biomarker technology could also lead to reduced costs if fewer materials are needed in storage.
Here, we focus specifically on firm flesh browning of the ‘Empire’ apple (Malus sylvestris var. domestica Borkh.), which is a major cause of revenue loss for growers and storage operators in New York State. ‘Empire’, is a cross between ‘McIntosh’ and ‘Delicious’ and was released in 1966 (Derkacz et al., 1993). It is a major cultivar in the northeastern United States, particularly in New York State as well as in Canada. ‘Empire’, at almost 1860 ha, was the second most planted cultivar after ‘McIntosh’ in the northeast in 2006 (USDA-NASS, 2012), and is the fifth most important cultivar in the United States with a total production of 170,000 tons in 2011 (Lehnert, 2012). Symptoms of flesh browning in ‘Empire’ typically become visible after several months in storage (in the May or June following harvest in the northern hemisphere), but can occur earlier in some years. Flesh browning is not externally visible and mostly starts at the stem end of the fruit in the shoulder region (Lee et al., 2012).
‘Empire’ apples are air stored to meet market demand until about December with fruit for marketing beyond this time usually being CA stored. Both air-stored and CA-stored fruit are often treated with the inhibitor of ethylene perception, 1-methylcycopropene (Watkins, 2008). A storage period of at least 10 months is desired by the whole fruit and fresh cut industries, but the cultivar is susceptible to several physiological disorders that limit its storage potential (Watkins et al., 1997; Watkins and Liu, 2010). Flesh browning has been especially problematic for the fresh cut industry as only apples with no internal browning—even slight browning in the stem end region (shoulder)—are acceptable.
Akhtar, S.I. & Jones, V.C. 2013 Proposed Transatlantic Trade and Investment Partnership (TTIP): In brief. Congressional Research Service Report for Congress Report No. R43158. 11 Feb. 2016. <https://www.fas.org/sgp/crs/row/R43158.pdf>
DeMarree, A., Robinson, T.L., Hoying, S. & Breth, D. 2010 Fresh Apple NPV Analysis - Excel workbook. 10 Feb. 2016. <http://lof.cce.cornell.edu/submission.php?id=268&crumb=business%7Cbusiness>
Doerflinger, F.C., Rickard, B.J., Nock, J.F. & Watkins, C.B. 2015 An economic analysis of harvest timing to manage the physiological storage disorder firm flesh browning in ‘Empire’ apples Postharvest Biol. Technol. 107 1 8
Fontagné, L., Gourdon, J. & Jean, S. 2013 Transatlantic Trade: Whither Partnership, Which Economic Consequences?” Centre d’Etudes Prospectives et d’Informations Internationales (CEPII), CEPII Policy Brief No. 2013-1. 11 Feb. 2016. <http://www.cepii.fr/PDF_PUB/pb/2013/pb2013-01.pdf>
Gallardo, K. & Galinato, S.P. 2012 Cost estimates of establishing, producing, and packing Red Delicious apples in Washington. 10 Feb. 2016. <http://cru.cahe.wsu.edu/CEPublications/FS099E/FS099E.pdf>
Lee, J., Cheng, L., Rudell, D.R. & Watkins, C.B. 2012 Antioxidant metabolism of 1-methylcyclopropene (1-MCP) treated ‘Empire’ apples during controlled atmosphere storage Postharvest Biol. Technol. 65 79 91
Lemieux, C. & Wohlgenant, M.K. 1989 Ex ante evaluation of the economic impact of agricultural biotechnology: The case of porcine somatotropin Amer. J. Agr. Econ. 71 4 903 914
Lesser, W., Bernard, J. & Billah, K. 1999 Methodologies for ex ante projections of adoption rates for agbiotech products: Lessons learned from rBST Agribusinss 15 2 149 162
USDA 2002 United States Standard for Grades of Apples. <http://www.ers.usda.gov/data-products/chart-gallery/detail.aspx?chartId=30486#.VEl4V_nF9FM>
USDA-NASS 2012 New York Apple Tree Survey. U.S. Dept. Agr., Natl. Agr. Stat. Serv., Washington, D.C
Watkins, C.B. & Liu, F.W. 2010 Temperature and carbon dioxide interactions on quality of controlled atmosphere-stored ‘Empire’ apples HortScience 45 1708 1712
Watkins, C.B., Silsby, K.J. & Goffinet, M.C. 1997 Controlled atmosphere and antioxidant effects on external CO2 injury of ‘Empire’ apples HortScience 32 1242 1246