The sweetpotato industry contributes significantly to the U.S. agricultural economy. In 2018, it harvested 144,400 acres nationally, which produced 27.4 million cwt valued at $654.1 million [U.S. Department of Agriculture (USDA), 2018]. Although commercial production is concentrated in North Carolina, California, Mississippi, Louisiana, and Texas, skinning injury remains one of the greatest concerns to sweetpotato producers nationally (M.W. Shankle, unpublished data). Sweetpotato skin is relatively thin and easily sloughed off of storage roots during harvest, transport, packing, and stocking. At harvest, skinning injury can create entry points for postharvest plant pathogens and allow for increased water loss, often causing roots to shrivel (Arancibia and LaBonte, 2013; Edmunds et al., 2008). Current recommendations to minimize skinning injury include devining (flail mowing sweetpotato foliage) 4 to 10 d before harvest and irrigating fields before harvest to “soften” the soil (Arancibia and LaBonte, 2013). In Mississippi, a limited number of sweetpotato growers have the ability to irrigate fields, and most rely solely on devining. Despite any preharvest treatment, most sweetpotatoes still experience at least one or two skinning wounds during the harvest operation (Wang et al., 2013). Wang et al. (2013) investigated changes in skinning severity in response to preharvest foliar applications in three different years and found that in sweetpotato plants devined 5 to 7 d before harvest, 80% to 100% of harvested sweetpotato storage roots were skinned.
Although skinning injury is very common, the percentage of sweetpotato storage root surface area affected by skinning injury can vary widely (Schultheis et al., 2000). Several researchers have attempted to quantify skinning injury severity with limited success and/or efficiency (Bouwkamp et al., 1972; Wright and LaBonte, 1994). Recently, Ward and McKee (2014) developed a consistent method of quantifying skinning injury. The method uses image analysis to estimate the skinning severity (percent skinned surface area) of a root. Images are collected using an off-the-shelf digital color camera and the system uses color differences between root skin and flesh to segment the imagery into skinned and unskinned regions. Four images of each root are analyzed and a ratio of the total number of pixels classified as skinned to the total number of pixels in each root is calculated. The system is validated against simulated targets with known ratios and verified to have less than 2% error in estimated skinning incidence.
Skinning injury can contribute to postharvest losses, but can also result in losses of marketable products due only to unattractive marketable appearance (Wang et al., 2013). Skinning injury is considered to be aesthetically displeasing to consumers and can result in otherwise consumable fresh market sweetpotatoes being sold in processing markets at 20% or less of the fresh market price, assuming the producer has a processing contract. However, what is considered an allowable percentage of skinning is often determined by the produce retailer and may differ widely from what sweetpotato producers and packers may feel is acceptable. Ultimately, the marketability of fresh sweetpotatoes with varying degrees of skinning injury will be determined by consumers who often choose to purchase produce based on visual examination. A greater understanding of how skinning injury severity relates to consumer preferences is needed to establish a research-based threshold for fresh market marketability.
The objectives of this project were to estimate consumers’ mean WTP for sweetpotatoes with varying amounts of skinning injury and to identify whether there are differences in valuations when the extent of skinning injury is made salient by labeling it. WTP was assessed by conducting a nonhypothetical, incentive-compatible laboratory experimental auction. Experimental auctions are regularly used by applied economists, psychologists, and marketers to valuate new products, technologies, and treatments (Alfnes and Rickersten, 2003, 2008; Lusk and Shogren, 2007). In horticulture research, they have been used to elicit consumer preferences for products and attributes, including cosmetic damage in organic apples [Malus ×domestica (Yue et al., 2009)], biodegradable plant containers (Yue at al., 2010), labeled native and invasive plants (Yue et al., 2012), pomegranates [Punica ×granatum (McAdams et al., 2013)], energy and water efficiency in plant production (Yue et al., 2015), and quality attributes in ‘Honeycrisp’ apples (Gallardo et al., 2015). Although experimental auctions can be hypothetical, hypothetical auctions can sometimes suffer from hypothetical bias (List and Gallet, 2001). In this project, we follow the image analysis methods of Ward and McKee (2014) to measure and classify sweetpotatoes by skinning injury levels and subsequently conduct a nonhypothetical (real) Vickrey experimental auction.
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