41 Sugar beet

41 Sugar beet

Koen Dillen and Matty Demont

INTRODUCTION Sugar beet (Beta vulgaris L.) is a specialized agricultural crop aimed solely at the refined sugar industry. Its root contains a high percentage of sucrose, the basic input for sugar processing. As such, sugar beet directly competes on a global scale with sugar cane, a crop with similar sucrose content. Sugar cane, a.C-4 plant, outperforms sugar beet in the warm and dry climates, leading to spatial separation of cultivation. Sugar beet is mainly cultivated in the more temperate and colder climates around the world such as Europe and parts of North America where it is an important agricultural crop. Table 41.1 demonstrates the importance and spatial distribution of sucrose-containing crops worldwide. The specific properties of sugar beet and its importance in industrialized countries with strong institutions and commercially oriented farmers makes it an interesting crop to be targeted by the biotechnology sector. As early as 1998, approval was granted for both food and feed use and environmental release in the US for genetically modified herbicide tolerant (GMHT) sugar beet (CERA, 2010). In this chapter we will first highlight the particular characteristics of sugar beet which make it suitable for genetic modification and try to explain why the first commercial application of GM sugar beet only took place in 2007, a decade after it was first officially granted permission. Next, we expand on the farmer experiences with cultivation. In the following section different methodologies that were used to assess the socio-economic impact of GM sugar beet are discussed and their respective strengths and weaknesses highlighted. The metrics section continues with Table 41.1 Global production of sucrose crops in 2009 Sugar cane 6

Area planted worldwide (10 ha) Europe (103 ha) North America (103 ha) Rest of Americas (103 ha) Africa (103 ha) Asia (103 ha) Oceania (103 ha) Yield (ton/ha) Production (106 ton) Sugar extraction

Sugar beet

23.8 – 354 11 721 1537 9 680 449

4.3 2 911 476 15 172 699 –

70 1 661 12%

53 227 15%

Source: F.O.Licht (2005); FAO (2011); USDA (2011).

661

SMYTH 9780857938343 PRINT (M3309) (G).indd 661

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662 Handbook on agriculture, biotechnology and development a presentation of the results of the available socio-economic studies. The final section concludes and raises some topics and consideration for further research. Sugar, the final product of the sugar beet production chain, consists of 99.7 per cent sucrose. This makes it physically impossible to distinguish GM sugar from conventional sugar as no protein or DNA is present (Klein et al., 1998). As sugar from both sources is chemically identical, human health is not an issue in the case of GM sugar beet. Moreover, from a consumer acceptance point of view, this equivalence made GM sugar beet potentially very interesting. At the time of the development of GMHT sugar beet, the impossibility to detect DNA or protein from GM sugar beet in the final product (sugar) allowed marketing in the EU without the need for labeling. Indeed, Article 8 of Regulation (EC) 258/97 on novel foods and novel foods’ ingredients stated that ingredients should be labeled only ‘if scientific assessment [. . .] can demonstrate that the characteristics assessed are different in comparison with a conventional food or food ingredient’. However, by the time the EU regulatory framework for GM labeling was revised in 2004 and GM sugar beet could have been deregulated, this regulation had been replaced. The new Regulation (EC) 1830/2003 states that all products produced from GM ingredients should be labeled regardless of the presence of proteins or DNA in the final product. This change in labeling regime affected mainly sugar (and edible oils such as canola) derived from GM crops and further hampered the marketability and hence interest in GM sugar beet in the EU. As a result, technology providers shifted their focus to the remaining sugar beet markets, albeit with a technology initially developed for the EU market. One of these markets is North America, where labeling regimes are voluntary and consumers are accustomed to GM crops (Gruère, 2007). Nevertheless, an analysis of the US sugar sector’s decision of whether or not to allow GM sugar beet demonstrated that public opinion against GM crops was an important consideration for introduction, independent of human health issues (DeVuyst and Wachenheim, 2005). Moreover, the same study showed that the marketability of the by-products was a major constraint to sugar processors accepting GM sugar beet. Pulp and molasses are sold to a variety of outlets, including both food and feed use. These by-products contain DNA and proteins of the GM crops which makes them subject to labeling in a variety of US trade partners. Following the food and feed approval in Australia, New Zeland, Japan and the EU in 2007, the sugar industry has finally opened its door to commercial introduction of GM sugar beet (Dillen et al., 2009b). Both the end-product and the crop itself possesses specific characteristics that make it interesting for biotechnology. Sugar beet is a biennial plant, flowering and producing seed only every second year. However, sugar beet is harvested after the first growing season, which minimizes the chances of outcrossing between GM and non-GM sugar beet fields and hence facilitating coexistence at farm level. Gene flow with a potential detrimental effect on agricultural productivity can only occur via two pathways (Desplanque et al., 2002). During seed production introgression of the GM trait to conventional seed production may occur. However, this is not a new problem for the seed industry. When breeding different varieties of a conventional variety, breeders also have to assure that the variety is kept as pure as possible. The industry solved this problem through spatial isolation of different seed-producing varieties. According to the OECD, certified sugar beet seed production should be located at least 1000 m from the nearest sugar beet field


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Sugar beet 663 (OECD, 2011). In the case of GM sugar beet seed production, the industry is bounded to more stringent regulatory distances and even increased the spatial separation to avoid liability claims. In the US, for example, the legal spatial isolation distance was decided at 4828 m while the industry is requiring a 6437 m isolation distance (McGinnis et al., 2010). Until now this requirement has not created problems in the supply of GM sugar beet seeds, affirming the feasibility of these regulations. An important concern in sugar beet gene flow is the appearance of ‘weed beets’. Occurring since the 1970s, this infestation causes yield losses and mechanical problems during harvest (Longden, 1989). Weed beets are ‘hybrids’ originated from the introgression of wild beet (Beta maritima, Beta macrocarpa) genes into fields of cultivated sugar beet seed production. Weed beets are genetic bolters, emerging soon after the sowing of sugar beet, bolting in spring and producing large amounts of seeds before sugar beet is harvested (Sester et al., 2003). As sugar beet may bolter under specific vernalization conditions such as unusually cold springs or due to genetic impurities, cross-pollination with weed beet might occur. If the GM trait transfers to the weed beet, farmers may have severe problems in controlling weed beet population in their fields in the future. Farmers are used to controlling bolters in their fields, as bolters compete with the crop for sucrose allocation and interfere with harvest. Moreover, farmers growing GM sugar beet in the US contractually agree to remove any flowering plants in their field (McGinnis et al., 2010). Hence, compared to some other crops described in this book, the agri- environmental risk from GM sugar beet is rather small. This chapter mainly focuses on genetically modified herbicide tolerant (GMHT) sugar beet for which out-crossing of the GMHT trait to wild relatives is not a major issue as it does not offer a competitive advantage outside of agricultural fields. If in the future GM traits were to be commercialized with competitive advantage outside of the field, the present analysis may have to be updated. The impossibility to differentiate GM from conventional beet sugar and the manageable environmental and coexistence constraints makes sugar beet an interesting crop for technology providers. Investigating the data on deliberate releases of GM crops in the environment we observe that the biotechnology industry has mainly focused on two specific phenotypes. Since 2004, most field tests were focused on broad spectrum herbicide tolerance. In recent years technology providers have also experimented with a variety resistant to rhizomania, a disease caused by beet necrotic yellow vein virus, which leads to smaller roots and lower sucrose content (European Commission, 2011; Information Systems for Biotechnology, 2011). Herbicide tolerance is a very interesting trait for sugar beet farmers as economic sugar production is not possible without efficient weed control. Competition from uncontrolled weeds can result in large yield reductions (Märländer, 2005). Therefore, in order to achieve a successful crop, an efficient weed management strategy is required. However, there is no universal solution and the weed management strategies carried out to achieve optimal sugar beet production are expensive, labor intensive and generally complicated. Conventional weed control programs include both pre-and post-emergence herbicide treatments. The most important products in terms of volume are those used pre-emergence. In post-emergence, tank mixes are used in most countries, usually in several split applications at lower dose rates than in pre-emergence. In Europe most farmers use a balanced but very low rate of different active ingredients in the tank mixes


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664 Handbook on agriculture, biotechnology and development in post-emergence. However, these schemes are far from perfect as current herbicides used in Europe are estimated to cause between 5 per cent and 15 per cent yield reduction, mainly as a result of phytotoxicity following application when the sugar beet crop is under stress (Coyette et al., 2002). Typically chemical control is combined with mechanical weeding to fight the bolters and weed beets in the field. A GM beet tolerant to a broad spectrum herbicide (GMHT sugar beet) gives producers the capability of weed control using only one post-emergence herbicide, applied two or three times during the growing season, of course without neglecting the rules of good agricultural practice. This increases the efficacy of weed control while at the same time reducing complexity and offering higher flexibility, as the timing of applying broad-spectrum herbicide is less stringent. Overall, HT technology reduces the cost of production through lower expenditures for herbicides, labor, machinery and fuel (Qaim, 2009). How this change in production system affects the economic value of the technology is discussed in the sections below. Moreover, Bennett et al. (2006) compare both production systems, GMHT and conventional, in terms of environmental effects through means of a lifecycle assessment. Their findings show that for the case of sugar beet, the GM production system is less of a burden to the environment than the conventional production system. Against this background, the commercial introduction of GMHT sugar beet took place in 2007 in the US and Canada. The cultivated event is called H7-1, commercialized by Monsanto in cooperation with KWS Saat (CERA, 2010). This specific GMHT crop is tolerant against glyphosate, a commonly used broad spectrum herbicide, often marketed as Roundup™. Note that commercial introduction was preceded by a peak in field trials in the years preceding the decision, as can be seen in Figure 41.1. Stachler et al. (2010) report on the experiences from US growers in Minnesota and North Dakota. The survey results show that US farmers embraced the GMHT sugar beet (Dobbs, 2011) for its superior weed control, reflected by the swift ramp up in adoption to 49 per cent in 2008, the second year of cultivation, to 88 per cent in 2009 and to 93 per cent in 2010. According to the Animal and Plant Health Inspection Service (APHIS) adoption at the national level was even more rapid, reaching 95 per cent of US acreage Number of environmental releases

20 18 16 14 12

US EU

10 8 6 4 2 0 2004

2005

2006

2008

2009

2010

2011

Source: European Commission (2011); Information systems for biotechnology (2011).

Figure 41.1 The number of field trials with GMHT glyphosate-tolerant sugar beet


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Sugar beet 665 in GMHT sugar beet by 2009 (McGinnis et al., 2010). This rate of adoption makes it the most successful GM introduction so far, as predicted by Demont and Dillen (2008). This real life example offers an ideal case study to compare the theoretical agronomic effects with the experience in the field. The regional survey in Minnesota and North Dakota shows that since the introduction of GMHT sugar beet, the average number of herbicide applications decreased from 3.9 to 2.6 during the period 2007–10. Moreover, 71 per cent of the surveyed farmers using GMHT sugar beet reported excellent weed control while among conventional growers only 21 per cent of the farmers made such a statement. The higher efficiency under the broad spectrum herbicide is further confirmed by the significant reduction in the use of the rotary hoe (from 41 per cent to 2.8 per cent during 2007–10) and the area hand-weeded (from 28 per cent to 1 per cent during 2007–10). Despite the commercial success of GMHT sugar beet in the US, its future is unclear. The initial deregulation of GMHT sugar beet was overturned in 2009 following a lawsuit by some NGOs. As a result, a Californian district court banned the planning in 2010. The court judged that the APHIS failed to take into account that transgenic pollen flow from GMHT sugar beet may hamper the production of conventional and organic sugar beet. However, as a shortage in the sugar market was predicted due to the under-supply of conventional seed (Neuman and Pollack, 2010), APHIS issued a ‘partial deregulation’ decision as an interim measure pending the completion of the court-ordered environmental impact statement. This statement, due mid-2012, is expected to propose full deregulation; a version open for public consultation is already available on the website (APHIS, 2011). The effect of the court ruling can be clearly observed in Figure 41.1 as field trials in the US restarted in 2009 in order to support the data collection for the new environmental impact statement. In the EU, the largest sugar beet producer, the future is even more uncertain. As indicated before, H7-1 sugar beet was granted permission for import and feed use in the EU in 2008. Despite the remarkable success in the US and the importance of the crop for EU agriculture, H7-1 is not yet authorized for cultivation in the EU. The application for cultivation started in 2008. This is visible in Figure 41.1 through the increase of field trials which aim at gathering data for the scientific risk assessment conducted by the European Food Safety Authority. At the end of 2011, the assessment had not been finalized as it has to be made compatible with the new EFSA opinion on post-market environmental monitoring (EFSA, 2011).

MODELS Despite the fact that GMHT sugar beet has been grown in the US for several years, knowledge about the socio-economic impacts of the innovation is limited. Kniss (2010) presents findings from a limited number of fields in Wyoming in the first year of adoption. The limited geographical scope and number of observations makes extrapolations from these results problematic. Dillen et al. (2013), on the other hand, present a simulation model assessing the aggregated effect but have to rely on field trial data as no other data is available. However, several studies have tried to estimate the potential socio-economic impact ex ante, that is, before the crop was introduced. In this section we describe the different approaches followed, their particular strengths and weaknesses and the lessons learned.


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666 Handbook on agriculture, biotechnology and development Table 41.2 Technology fee predictions in the literature on the ex ante impact of GMHT sugar beet Source May (2003) Märländer (2005) Gianessi et al. (2003) Demont and Tollens (2004); Demont et al. (2004) Dillen et al. (2009a) Demont and Dillen (2008) Dillen et al. (2009b) Burgener (2001) Rice et al. (2001) Kniss et al. (2004a; 2004b)

Technology fee

Area under research

Methodology Expert opinion Expert opinion Expert opinion

Modeling Modeling Modeling Field trials Field trials Field trials

20–30 30–45 38

£/ha €/ha €/ha

40

€/ha

UK UK Denmark, France, Germany, Italy, Netherlands, Spain, UK and Belgium EU15

88–98 88 95 123 141 245

€/ha €/ha €/ha $/ha $/ha $/ha

EU27 Czech Republic, Hungary EU27 US US US

Expert opinion

The results will be summarized in the metrics section. If we start with the US where GMHT sugar beet was adopted first, one ex ante impact assessment is available (Kniss et al., 2004a, 2004b). As GMHT sugar beet was not yet commercialized at the time of the study, the authors relied on experimental field trials with near-equivalent cultivars simulating different chemical weed control practices both in conventional and GMHT sugar beet. From the resulting differences in yields and production costs, they calculated potential profits for adopters of the technology. This highly controlled procedure of gathering data leads to very detailed results. The results show that the pay-off from the technology depends on different factors and is not uniformly positive. A first determinant is the price of GMHT sugar beet seed. As the technology is protected by intellectual property rights (IPRs), the technology provider will charge a licensing fee for the use of the technology, which decreases the profit for the adopter. Its direct impact on profits makes the technology fee a crucial parameter in ex ante impact assessment of IPR-protected technologies (Table 41.2). Kniss et al. (2004b) predict the technology fee by calculating a break-even price and then assuming the lower bound of the 90 per cent confidence interval to be a realistic estimator for the technology fee. A second set of determinants consists of the yield and cost effects which are primarily determined by the nature of the ‘counterfactual’ production practices to which GMHT sugar beet is compared. The study by Kniss et al. (2004b) therefore lists a magnitude of different potential outcomes based on different counterfactuals. However, the set-up of the study does not allow for aggregation of the different scenarios as no information is given on the actual use of conventional treatment programs in the US. Moreover, although a controlled experiment delivers very detailed results on the potential impact of the technology, it does not reflect the situation within farms. The adoption of GMHT sugar beet does not happen in a vacuum. Its introduction on-farm involves a simultaneous decision over a bundle of complementary inputs (for example GMHT seed complemented with a broad-spectrum herbicide, reduced tillage and different crop rotation). Therefore the value of each technology should be calculated as the value of the new


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Sugar beet 667 production system as a whole taking into account conventional farmer practices (Dillen et al., 2009a). One possible solution to this problem is to start from aggregated data, an approach followed by several authors (Burgener, 2001; Gianessi et al., 2003; May, 2003). Using average cost and yield data, these studies rely on partial budgeting techniques to estimate the potential value from adopting GMHT sugar beet. This approach has different strengths, including transparency, ease and the low cost of its implementation as it usually relies on existing secondary data. However, following this approach the assessor implicitly assumes the existence of an average farmer representing the whole population. Previous research has showed that the value of a technology is not uniformly distributed among farmers; some realize a profit from the technology and adopt it, while others rationally choose not to adopt. In particular, GM seed technologies will pay off differentially depending on field conditions, pest and weed pressure, crop rotation and environmental conditions. Moreover, the valuation of the technology by any particular farm will depend on managerial expertise and local market conditions that condition the profitability of GM seed technologies relative to alternative technologies (Weaver, 2004). Indeed Demont et al. (2008) demonstrate that not considering this heterogeneity leads to a bias in the ex ante impact estimates. Therefore they propose a stochastic simulation model using probability density functions representing the heterogeneity among farmers. Demont and Dillen (2008) and Dillen et al. (2009a) apply this framework to the case of GMHT sugar beet in the EU. Moreover, they build on the framework by explicitly modeling the pricing decision of the technology provider. The value of the technology fee determines to a great extent the adoption by farmers as they weigh it against their valuation for the technology. If farmers consider the value of the innovation to be higher than the technology fee, they will adopt it; otherwise they will reject the technology. Endogenizing this pricing decision adds more realism and consistency to ex ante impact assessment and allows one to predict consistent potential adoption ceilings for the GMHT technology, an improvement on previous expert predictions (Coyette et al., 2002). The former methodologies mainly looked at the isolated impact at the farm level. To gain insight into the welfare creation induced by the adoption, technology effects should be aggregated and market effects incorporated (Frisvold et al., 2003). A first approach, followed by Gianessi et al. (2003) and Park et al. (2011), applies a change in revenue methodology with homothetic extrapolation, approximating the producers’ gain in welfare by multiplying the gross margin per hectare with an assumed adoption rate. However, this method implicitly assumes a small, open economy with inelastic supply such that no price effects are generated by the cost-reducing effects of the technology. Demont et al. (2008) assess the impact of GMHT sugar beet through a shift of an inelastic supply curve in two new EU member states. Similarly, the small, open-economy assumption causes prices to be unaffected by the technology. However, large-scale adoption of GMHT sugar beet would affect world prices. The EUWABSIM model, a partial equilibrium model developed by Demont and Tollens (2004), extends this line of reasoning by assuming a large open economy. EUWABSIM assesses the distributional effects of introducing GMHT sugar beet in three regional aggregates, that is, the EU, the Rest of the World (ROW) sugar beet region and the ROW sugar cane region. EU supply is further disaggregated to allow for differences among member states in competitiveness and production practices. Since its conception, the model has evolved to incorporate (i) the change in European


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668 Handbook on agriculture, biotechnology and development sugar policy; (ii) the accession of new member states to the EU; and (iii) the farm-level model by Dillen et al. (2009a) discussed earlier. The model has been used in a variety of studies to address different questions (Dillen et al., 2008, 2009b, 2009c). Besides market effects, the introduction of a novel technology might also have irreversible and time effects which are not included in the presented studies. As GMHT sugar beet does not show up in the consumed end-product, these would mainly include environmental issues. Many consumers are concerned about potential future irreversible costs of GM crops reducing the overall welfare from introduction. The Bayesian decision analysis of real options, suggested by Morel et al. (2003) and Wesseler (2003) in the context of GM crops, offers a tool to account for these irreversible effects by estimating the maximum incremental social tolerable irreversible costs (MISTICs) for society that would justify the introduction of the technology. Two studies applied this approach using the output from the EUWABSIM model to explain the decision-making process in the EU (Demont et al., 2004; Dillen, 2010).

METRICS Before turning to a review of the results of different ex ante impact assessments, we focus on the technology fees used in the different studies as they largely determine the distribution of welfare. The larger the share of the technology fee in the value creation, the less profit accrues to farmers. The literature overview in Table 41.2 shows the wide range of technology fee predictions that have been used to assess the ex ante impact of GMHT sugar beet. The wide range of estimates can be explained methodologically. The lower end of the spectrum is based on expert opinions while the highest predictions are based on controlled field experiments. The middle ground comes closest to the fee of $131/ha applied in the US (Kniss, 2010) and is a result of modeling attempts to endogenize the pricing decision in the impact assessment. Generally speaking the technology fees are very high compared to other GM food crops (Demont et al., 2007); Bt cotton is the only crop known to reach fees of similar magnitude (for example Qaim and de Janvry, 2003). The mere size of the fee either suggests that the technology is of high value to farmers such that they have a high willingness to pay for it, or that the technology provider is able to extract a large share of the created value, or a combination of both. Dillen et al. (2009a) argue that farmers’ heterogeneous valuation of the technology constrains the technology provider’s pricing strategy and ability to extract technology rents even under the assumptions of monopolistic market power and price discrimination. The results from different impact assessments in the literature seem to confirm this as farmers are predicted to capture considerable profits from the technology (Table 41.3). According to this literature, average net profits for farmers from the adoption of GMHT sugar beet are in the range of 50–250 €/ha depending on the geographical scope and the underlying assumptions. Dillen et al. (2013) in their ex post analysis estimate an average benefit for the US of $257/ha which falls within this range. Kniss (2010), however, indicates an average benefit of $576/ha, indicating the particularity of the case study. All of the results clearly demonstrate the high economic potential of GMHT sugar beet for farmers. This does not come as a surprise since the adoption by US farmers was


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Sugar beet 669 Table 41.3 Net returns generated by the introduction of GMHT sugar beet and yield assumptions Area under research

Net profit/ha

Type of data

Method

Assumed yield increase

Source

Partial budgeting Partial budgeting Partial budgeting

Case by case 2%

Kniss et al. (2004b) May (2003)

n.a.

Gianessi et al. (2003)

n.a.

Gianessi et al. (2003)

n.a.

Park et al. (2011)

5%

Demont et al. (2008)

5%

Demont and Dillen (2008) Dillen et al. (2009a)

US

141

$/ha

Field trial

UK

154

£/ha

Denmark, France, Germany, Italy, Netherlands, Spain, UK and Belgium US

111

€/ha

Aggregated data Aggregated data

149

€/ha

EU27

50–150

€/ha

Czech Republic, Hungary Czech Republic, Hungary EU27

172–247 €/ha

EU15

164–174 €/ha 116

€/ha

217

€/ha

Aggregated data Secondary data Aggregated data Aggregated data Aggregated data Aggregated data

Partial budgeting Review Partial budgeting Partial budgeting Partial budgeting Partial equilibrium

5% 5%

Demont and Tollens (2004); Demont et al. (2004)

so successful. However, as discussed before, behind these averages are farmers who obtain a heterogeneous pay-off from adopting the technology. Looking at the potential adoption ceilings provides a deeper insight in the farmer segment which is projected to gain from the technology and take part in benefit sharing. The available figures are presented in Table 41.4. The estimated adoption ceilings are high, averaging around 80 per cent for the EU. This indicates that the benefits are not only captured by an exclusive group of farmers with high weed problems but that almost all farmers could potentially gain from the introduction. Different studies have tried to expand the assessment to the wider economy for which the results are presented in Table 41.5. Depending on the chosen methodology and the geographical coverage, the results vary. The most complete assessment stems from the last update of the EUWABSIM model covering the period from 1996 until 2015 and assessing the benefits forgone from not adopting GMHT sugar beet in the EU when the technology became available (Dillen et al., 2009b). The net present value of these forgone benefits amounts to €15.5 billion worldwide in 2015; 29 per cent of this value would have accrued to the EU producers adopting the technology while 31 per cent of the benefits would have been captured outside the EU. This is a net effect of the gains by consumers from lower sugar prices and the loss of sugar cane growers from the same price decrease.


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670 Handbook on agriculture, biotechnology and development Table 41.4 Predicted adoption ceilings (EU) and observed adoption rate (US) of GMHT sugar beet Source

Average adoption

Coyette et al. (2002)

84%

Demont et al. (2008) Demont and Dillen (2008) Dillen et al. (2009a) Demont and Tollens (2004); Demont et al. (2004) Dillen et al. (2009b) McGinnis et al. (2010)

Area under research

68–88% 60–80% 51–99% 75%

Germany, France, UK, Belgium, Netherlands and Spain Czech Republic, Hungary Czech Republic, Hungary EU27 EU15

47–100% 95%

EU27 US

Table 41.5 Annual global value generation of GMHT sugar beet its and distribution over the supply chain Source

Country

Demont et al. (2008) Czech Republic Hungary Gianessi et al. (2003) Denmark, France, Germany, Italy, Netherlands, Spain, UK and Belgium Park et al. (2011) EU27 Dillen et al. (2009b) EU27 Note:

a

Annual global value (106 €)

Global benefit sharing Technology Domestic Domestic Net provider farmers consumers ROW

13 11 390

34% 26% n.a.

66% 74% n.a.

0%a 0%a n.a.

0%a 0%a n.a.

73–219 772

n.a. 39%

n.a. 29%

n.a. 0%

n.a. 31%

as discussed before this is a direct effect of the assumption of an open small economy.

The remaining 39 per cent would have been extracted by the technology provider. This simulation shows that even under the situation of strong intellectual property rights and the assumption of a monopolistic technology provider, welfare would have been distributed throughout the supply chain. EU consumers would not have gained from the introduction of GMHT sugar beet as domestic sugar prices are made inelastic by the EU common market organization (CMO). Dillen et al. (2008) in turn demonstrate that the 2006 reform of the CMO for sugar would have significantly altered the demand for the technology in favor of low-cost farmers. On the other hand, the total area planted with sugar beet decreased as a result of the reform, which has eroded the potential market for the technology provider. Finally, Demont et al. (2004) show that at the aggregated EU level the maximum incremental social tolerable irreversible costs (MISTICs) are high, around €100 million per year. Purely from a rational point of view, this means that if the regulator expects the


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Sugar beet 671 true irreversible costs of GMHT sugar beet introduction to be lower than this threshold value, the crop should be deregulated. However, until now this has not happened. If we assume that regulators take decisions based on voting incentives and consider the problem from the standpoint of an individual EU household, we can calculate the household-level MISTIC value, which is around €1 per year. Hence it is rational for individual households not to support the introduction of GMHT sugar beet as soon as they expect the irreversible costs to be more than €1 per year. This is easy to understand as EU consumers are hardly capturing any direct benefits from the technology in the context of the actual CMO for sugar. Therefore Dillen (2010) investigates which countries would be most inclined to deregulate GMHT sugar beet if the European Commission decides to delegate the decision on cultivation to the individual member states. His results show that Denmark and Belgium might be most inclined to deregulate while Italy and Portugal will not embrace the technology based on the MISTIC criterion.

CRITICAL ASSESSMENT During the last 15 years GMHT sugar beet has been the center of attention of different stakeholders in the agricultural complex. Biotechnology providers were interested because of the low risk of gene flow and the potential to generate significant commercial returns on the innovation. Farmers were interested because of problematic weed control in conventional sugar beet and the potential to improve operating margins. The food industry was interested because of the initial absence of labeling and possible consumer acceptance of the equivalent ‘GM’ sugar, which would come at a lower price. Agricultural economists picked up this interest and applied some of the state-of-the-art methodologies (stochastic modeling, partial equilibrium and real options) to predict the outcome of a commercial introduction on society and assess the distribution of welfare along the supply chain in an ex ante setting. The limited studies available studying the commercial introduction in 2007 in North America, seem to confirm the findings of the ex ante assessments which should not come as a surprise given the rapid adoption by US farmers and the size of the technology fee. However, as the area planted with sugar beet in North America only represents 10 per cent of the global sugar beet area, the welfare gains in that region do not compensate in any way the benefits forgone in the EU estimated by the EUWABSIM model. A thorough assessment of the benefits in the supply chain and its spillover effects on the world sugar market is essential. Moreover, the use of a general equilibrium model might be appropriate as the demand for sugar has changed drastically in the last couple of years. Sucrose containing crops are an important input for the biofuel sector. This new outlet for the crop altered the demand and supply of the crops, hence increasing the total value of GMHT sugar beet for society. As discussed in an earlier section, coexistence is not a major issue in the case of GMHT sugar beet. However, including coexistence measures in socio-economic assessments could fine-tune the results as some EU member states have national coexistence regulations for GM sugar beet in place; for example, Latvia and the Netherlands have established isolation distances (European Commission, 2009). These measures may hamper adoption of the technology and lower welfare creation (Areal et al., 2011; Beckmann


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672 Handbook on agriculture, biotechnology and development et al., 2006; Ceddia et al., 2011; Demont et al., 2009). Finally the existing literature fails to include technological advancements in sugar cane that may reshape the world sugar market. A look at the pipeline for plant biotechnology reveals that the biotechnology sector is developing GM sugar cane with increased yield potential which directly affects the comparative advantage of sugar beet production (CropLife International, 2013). Furthermore, ex post impact assessments would allow for the validation of the different ex-ante methodologies that were developed. This would increase the future capacity for evidence-based decision-making by policymakers in ex ante settings. Returning to the plant biotechnology pipeline and the results from the field trial analysis, we see that the novel traits from sugar beet will most likely include virus resistance and increases in genetic yield potential. Both of these technologies will have a different socio-economic impact and hence should be studied in due time using the right approaches.

DISCLAIMER The views expressed are purely those of the authors and may not in any circumstances be regarded as stating an official position of the European Commission.

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