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{{Paper
|id=Vol-1498/HAICTA_2015_paper49
|storemode=property
|title=Attitude of Evros’ s Farmers for the Genetically Modified Trees
|pdfUrl=https://ceur-ws.org/Vol-1498/HAICTA_2015_paper49.pdf
|volume=Vol-1498
|dblpUrl=https://dblp.org/rec/conf/haicta/ValsamidisPTT15
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==Attitude of Evros’ s Farmers for the Genetically Modified Trees==
https://ceur-ws.org/Vol-1498/HAICTA_2015_paper49.pdf
Attitude of Evros’ s Farmers for the Genetically Modified
Trees
Stavros Valsamidis1, Ioannis Petasakis2, Elpida Tenidou3, Lambros Tsourgiannis4
1
Department of Accounting and Finance, EMaTTech Institute of Technology, Kavala, Agios
Loukas, 65 404, Kavala, Greece, e-mail: svalsam@teikav.edu.gr
2
Department of Accounting and Finance, EMaTTech Institute of Technology, Kavala, Agios
Loukas, 65 404, Kavala, Greece, e-mail: jpetasakis@hotmail.com
3
Department of Accounting and Finance, EMaTTech Institute of Technology, Kavala, Agios
Loukas, 65 404, Kavala, Greece, e-mail: elpida.tenidou@gmail.com
4
Department of Accounting and Finance, EMaTTech Institute of Technology, Kavala, Agios
Loukas, 65 404, Kavala, Greece, e-mail: ltsourgiannis@gmail.com
Abstract. Genetically modified trees are now one more expression of human
intervention in nature. As for other people is a suicidal mood at the cost of profit
maximization, for others is an inevitable trend for the survival of continuing
growing world population that gathers several advantages, a survey of those
directly involved in the primary sector, farmers, and deemed necessary. The
implementation of this research includes the completion of 100 questionnaires from
farmers in the region of Evros. Then, using the widely used Excel and SPSS
software packages are processed research results with the discovery of useful
correlations. The results show that in the region of Evros opinions of farmers who
have negative attitude to the cultivation of genetically modified forest trees is much
more (70) versus those with positive (30). Both trends express their concern on
different characteristics, the systematic mapping of which is attempted in this work.
The intension to cultivate genetically modified trees in relation to the demographic
characteristics of the farmers, the farm size, the farm size and the type of cultivation
are also investigated.
Keywords: Genetically Modified Forest Trees, Evros, Farmers, Analysis of
attitudes.
1 Introduction
Biotechnology is characterized as the technology of biological processes using organisms,
or parts of their processes for the manufacture or production of useful or commercially
exploitable substances and to provide services for the benefit of man (Thieman and
Palladino, 2008). According to the Convention on Biological Diversity, biotechnology is
defined as any technological application uses biological systems, living organisms or
401
their derivatives to create or modify products for specific use (Convention on Biological
Diversity, 1992). This definition includes medical and industrial applications as well as
the tools and techniques used in agriculture and food production (FAO, 2004). The term
denotes a wide range of processes, from the use of earthworms for protein production by
the production of human genes, such as growth hormone. In biotech products include
pharmaceutical proteins, foods, detergents, etc., while a variety of applications including
the services of waste water and waste as a medical diagnosis, or achievements of gene
therapy (EuropaBio, 2012). Biotechnology today, builds on the achievements of modern
molecular biology and uses a number of techniques, including genetic engineering
(recombinant DNA), Methods and tissue engineered cell cultures on a large scale, the
polymerase chain reaction, etc. It has numerous applications in health sciences,
environmental protection (eg use in waste management), agriculture, livestock and
industry. Together with biomedical technology, which the development of technologies
with applications in medicine, biotechnology sometimes called biological engineering
(Walter and Menzies, 2010). In fact the term biotechnology includes a broad set of tools
and application of these tools. Genetic engineering only started in 1982 when (Palmiter et
al., 1982) created the first genetically modified or otherwise transgenic mice. Genetic
engineering may be new but the creation of new agencies with modified genetic material,
can be done relatively quickly.
Agricultural biotechnology concerns mainly Genetically Modified Trees (GMT) and is
particularly interesting since the first seeds of GM in America planted. The commercial
sale of genetically modified food began in 1994, when Calgene brought first marketed
the slow ripening tomato (Clive, 1996). According to the World Health Organization
(WHO), Genetically Modified Trees are trees whose genetic material (DNA) has been
altered in a way not found in nature. This technology is often called modern
biotechnology or gene technology and sometimes recombinant DNA technology or
genetic engineering (WHO, 2002). According to Sedjo (2004) a plant comprising
introducing a gene using an approach beyond sex (nonsexual) considered bioengineered
plant and designated as a transgenic. Among the various techniques used to generate
transgenic plants, Agrobacterium transformation is the most widely used tool,
representing 80% of the transgenic plants produced (Broothaerts et al., 2005). The term
GM crops refer to crop plants created with the latest technologies used molecular biology
and which plants intended for consumption by humans or animals. The modification is
done in laboratory conditions and its goal usually is to support them in a desirable
feature, for example resistance to herbicides or improved nutritional content (Varzakas et
al., 2007a).
Over the last two decades there have been significant developments in
biotechnological applications. The overall coverage in a survey (Sedjo, 2004) and the
working paper (Preliminary review of biotechnology in forestry, 2004) present that the
cultivation of GM foods and crops include dynamic technology, potential risks to public
health and safety of ecosystems, powerful economic lobbies, impact on small surface
areas and small farmers, nutritional promises and scandals, political strategies, European
402
directives and easy identification of citizens with actual or potential problems and
injustices arising from their use. Furthermore, the use of GM forest trees in commercial
plantations would contribute to increased forest productivity, improved pulp for paper,
biofuel production, climate change mitigation, preservation of biodiversity and reduction
of energy, pesticides and fertilizers utilization (Sedjo 2006, Chapotin and Wolt 2007,
FAO 2008, 2010, Hinchee et al. 2009, Flachowsky et al. 2009, Harfouche et al. 2011).
While these practices may perhaps increase profits for wood and paper products firms,
the high economic, ecological and social costs associated with industrial tree plantations
are paid by those living in and around large scale plantations and by society at large
(Carman et al 2006).
The working group led by Professor Athanasios Tsaftaris (2004), the former Minister
for Rural Development and Food, among other findings, discovers a reluctance of Central
Macedonia farmers in dealing with the agro-biotechnologies. The Greeks generally have
negative attitudes towards the cultivation and consumption of GM trees and products, and
there seems to be consensus among politicians and citizens in their opposition to
genetically modified (Kousis, 2009). Greece has, so far, chosen the cultivation of GM
trees mainly because of the small agricultural clergy, the geomorphological features,
different microclimates and soil conditions favor the biological and integrated crop
(Varzakas et al., 2007b).
Furthermore, the application of GM technologies to trees has raised a number of
potential public concerns. Many of these concerns, although not all, are the same raised
for GM annual crop plants, including the potential for spread of antibiotic or herbicide
resistance genes to other non-target species from GM trees; the potential for long –
distance pollen spread over many years from long – lived trees, the potential for adverse
effects on biodiversity from forests of GM trees; and any unexpected effects (Gartland et
al 2003).e
Public acceptance in particular is influenced by environmental, public health and
socio-cultural concerns, which have been raised mainly by opinion influencing groups.
Concerns often focus on potential genetic flow between GM and wild trees and
consequent implications for the natural environment, increased use of broad spectrum
herbicides, more pesticide resistant forest trees, negative effects on forest tree fitness,
potential higher vulnerability of forest trees to viral and other diseases, increased soil
decomposition, adverse effects on biotrophic processes in host ecosystems, flowering
suppression and cultural adaptation to altered biodiversity conditions due to transgene
escape (El- Lakany 2004,Van Frankenhuyzen and Beardmore 2004, Williams 2006,
Sedjo 2006, Farnum et al. 2007, FAO 2008, 2010). In the Eurobarometer survey,
(European Community, 2010) becomes apparent the opposition of the Greeks towards
GM crops. While a small, relatively, a majority of Europeans (54%) believes that
genetically modified foods are not good for them and their families, in Greece the
percentage of those who oppose reaches 78%. The Greeks, in 89%, believe that it is
fundamentally unnatural. Furthermore, 85% expressed huge concerns on security issues.
As the former Minister of Rural Development and Food as Professor of Genetics and
403
Biotechnology at AUTH, expressed concern for possible adoption of personal views in
formulating national agricultural policy (Journal Ling, 2012). On the other hand,
according to Tsourgiannis et. al. (2013), (2014), (2015a), (2015b) it appears that there
might be potential buyers of products derived from GM trees and more particular for
wood products, woody biomass energy products and paper products originating from
transgenic plantations in Greece. Indeed, most of these potential consumers willing to
purchase transgenic wood products base their buying decisions on economic issues
(Tsourgiannis et. al. 2013, 2014, 2015a, 2015b). Taking into consideration that most of
these products are not directly linked with human health impacts, there is a potential for
development of a market for such products, particularly in current times of economic
depression.
The Peter Coventry (2001) argued that the Forest Council in the US should allow the
certification of GM tree plantations as "well managed" by the effects of GM trees with
reduced lignin in soils in relation to the physical produced. The Zolotov (2003) mentions
the success of GM maize crops in the United States and expresses concern about the low
rates of crops in Europe. Despite initial skepticism about whether biotechnology in
forestry can also be related to environmental issues, including the effects on organisms
associated with tree living and ecosystems, are presented and benefits from genetic
modification of lignin (Axelsson et al., 2010). The reasons for not widespread
commercial use of biotechnology research presented in 90 specific US (Strauss et al.,
2009).
The transgenic biotechnology can help the forest improvement programs, but can also
simultaneously be of concern for the safety of the environment. Today there is an urgent
need to establish a European platform to build on this knowledge of GMT (Gallardo et
al., 2011). Due to the negative public opinion about the GMT, the Strif and Broshe
(2001) proposed to focus the efforts of the whole enterprise in producing trees which are
not intended for consumption by humans or animals. For example, crops for the
manufacture of fibers such as cotton or flax.
Developments in the field of GMT in plant industry have led to increased crop
production and yield in turn have increased the use of genetically modified (GM) foods
in the human food chain. The use of genetically modified foods for human consumption
has raised a number of fundamental issues such as the ability of genetically modified
foods cause potentially harmful immunological side effects like allergic hypersensitivity
(Prescott and Hogan, 2006). Kuiper and Kleter (2003) do compare the safety of
conventional food with respect to genetically modified food.
Interesting aspects about genetically modified trees in forests, are the ethical
considerations (Gamborg and Sandoe, 2010), the relevant environmental concerns in
forests (Fladung et al., 2010), social, legal and regulatory issues related to genetically
modified plants (Sedjo, 2010).
The paper is organized as follows. Section 2 describes the approach. Section 3
describes the results for both descriptive statistics and advanced analysis. Section 4
presents discussion about the results together with directions in the future.
404
2 Approach
This study proposes an approach for analyzing the attitudes of farmers in the region of
Evros regarding the Genetically Modified Trees. The research method used was simple
random sampling. Information was recorded following an interview with each farmer
individually.
The questionnaire consists of three parts. The first part comprises three farmers'
attitude questions regarding Genetically Modified Forest Trees with analytical control of
many individual factors. The second part includes the recording demographics of
farmers. Finally the third part includes the recording of operating data for each of 100
farmers.
The questionnaire includes mainly qualitative data that is data stored in non-numeric
form in contrast to quantitative data that are in numerical form. The quality is the data
that describe the characteristics or properties held by an object (Strauss and Corbin,
1998). The properties are categorized into classes that can then be assigned a numerical
value. There is no significance to these data values, simply object characteristics. In some
areas of social research, the distinction between qualitative-quantitative data has led to
prolonged disputes where each group supports the superiority of its own data type
(Trochim and Donnelly, 2006). The 'quantitative' claim that their data is strictly reliable
and scientifically while 'quality' that their are respectively sensitive, detailed and
contextual.
Therefore, we suggest the following assumptions:
H1: The cultivation intention is related to the gender of the farmer.
H2: The cultivation intention is related to the age of the farmer.
H3: The cultivation intention is related to the level of education.
H4: The cultivation intention is related to the farm size.
H5: The cultivation intention is related to the type of cultivation.
The analysis performed includes both descriptive statistics and advanced analysis
using X2 test.
3 Results
Here are the results after data processing in Excel software packages 2007 and SPSS
18.0.
405
3.1 Descriptive Analysis
The sample is 100 farmers in the region of Evros, in the North East Greece. 55 of them
are male and 45 are women. 65 are married and for 65 of them farming is their main
occupation.
Table 1. Distribution of the sample based on the knowledge of the term GMT.
Knowledge of the term Number Percentage
Know 100 100,0
Table 2. Distribution of the sample by the intention of cultivation.
Cultivation intention Number Percentage
No 70 70,0
Yes 30 30,0
Total 100 100,0
Table 3. Distribution of the sample by age.
Age Number Percentage
20-29 35 35,0
30-44 25 25,0
45-64 35 35,0
65+ 5 5,0
Total 100 100,0
60% of the farmers in the sample are younger than 44 years old.
Table 4. Distribution of the sample based on educational level
Education Number Percentage
Primary school 25 25,0
Secondary school 15 15,0
High School 40 40,0
University 20 20,0
Master / Doctorate 0 0,0
Total 100 100,0
The distribution of the sample based on educational level is presented at table 4. 80%
has graduated in High school or lower and only 20% are graduates of university.
406
Table 5. Distribution of the sample based on the number of children
Number of children Number Percentage
None 30 30,0
1-2 kids 60 60,0
3+ Children 10 10,0
Total 100 100,0
Table 6. Distribution of the sample by age of child
Age of children Number Percentage
No children 35 35,0
Small children (0-12 years) 15 15,0
In adolescents (13-18 years) 15 15,0
Large (18+ years) 35 35,0
Total 100 100,0
Table 7. Distribution of the sample by farm size
Farm size Number Percentage
<10 acres 25 25,0
11-50 acres 15 15,0
51-100 acres 10 10,0
101-200 acres 50 50,0
Total 100 100,0
Table 8. Distribution of sample by type of cultivation
Type of crop Number Percentage
Arable 15 15,0
Vegetables 35 35,0
Orchards 10 10,0
Groves 10 10,0
Forest plantations 30 30,0
Other 0 0,0
Total 100 100,0
3.2 Advanced Analysis
The results of the Chi-Square test regarding the hypotheses of section 2, are presented
in this subsection.
407
Table 9. Cultivation intention in relation to gender
Cultivation of GMT Female Male Total
No 30 40 70
Yes 15 15 30
Total 45 55 100
There is no dependence to gender (value of Pearson Chi-Square= is 0.433, df=1, p-
value=0.511).
Table 10. Cultivation intention in relation to age
Age
Cultivation of GMT Total
20-29 30-44 45-64 65+
No 20 10 35 5 70
Yes 15 15 0 0 30
Total 35 25 35 5 100
There is dependence to age (value of Pearson Chi-Square= is 30.612, df=3, p-
value<0.001). Younger farmers are less negative to the cultivation of GM forest trees.
Table 11. Cultivation of GMTs in relation to level of education
Level of education
Total
Would you cultivate GMTs? Primary Secondary High University
school school School
No 25 10 20 15 70
Yes 0 5 20 5 30
Total 25 15 40 20 100
There is dependence to level of education (value of Pearson Chi-Square= is 18.651,
df=3, p-value<0.001). It is worth to notice that farmers with basic education and
university graduates are the most negative to the cultivation of GMT.
408
Table 12. Cultivation of GMTs in relation to farm size
Farm size
Would you cultivate GMTs? Total
<=10 acres 11-50 acres 51-100 acres 101-200 acres
No 5 10 10 45 70
Yes 20 5 0 5 30
Total 25 15 10 50 100
There is dependence to the farm size (value of Pearson Chi-Square= is 43.651, df=3,
p-value<0.001). Farmers who own less or equal to 10 acres, responded that would
cultivate GMT in 80%.
Table 13. Cultivation of GMTs in relation to the type of cultivation
Type of cultivation (crop) Total
Would you cultivate GMTs? Forest
Arable Vegetables Orchards Groves
plantations
No 5 20 10 5 30 70
Yes 10 15 0 5 0 30
Total 15 35 10 10 30 100
There is dependence to the type of cultivation (value of Pearson Chi-Square= is
31.406, df=4, p-value<0.001). Farmers. Farmers who cultivate arable and vegetables are
these who mostly would accept the cultivation of GMTs.
Table 14. Distribution of cultivation factors in median and percentile points (quartiles)
Cronbach’s
Factor 25% Median 75%
Alpha
Q2a 2,50 3,50 4,00
Q2b 1,00 3,50 4,00
Q2c 1,00 3,50 5,00
Q2d 1,75 3,00 3,00
Q2e 1,00 2,50 3,00 0.854
Q2f 1,00 2,00 3,25
Q2g 1,00 1,00 2,00
Q2h 1,00 1,00 1,25
Q2i 1,00 1,00 1,00
The Cronbach’s Alpha value is 0.854.
409
We create a new variable which is the average value of all factors of table 15. Its mean
value is 2.17 (standard deviation 0.69).
Table 15. Relation of cultivation with gender
gender N Mean
Female 15 2,5926
cultivation
Male 15 1,7407
Males seem to be more positive about cultivation compared to Females (t=4.271,
df=14, p-value=0.001).
Table 16. Relation of cultivation with type of cultivation
95% Confidence Interval
for Mean
N Mean
Lower Upper
Std. Deviation Bound Bound
Arable 5 1,8889 ,00000 1,8889 1,8889
Vegetables 20 2,3056 ,25964 2,1840 2,4271
Orchards 10 3,1667 ,99553 2,4545 3,8788
Forest plantations 30 2,6667 ,00000 2,6667 2,6667
Other 70 2,4444 ,89224 2,1113 2,7776
Total 70 2,4841 ,76678 2,3013 2,6670
The willingness of farmers not to cultivate genetically modified products depends on
the type of crop (F4,65 = 3.555, p = 0.011). Those with orchards are on average from
0.13 to 2.4 higher willingness not to cultivate genetically modified compared with those
with arable (p-value = 0.018). Similarly those who have Orchards have, on average,
from 0.1 to 1.7 higher willingness to cultivate non-GM compared to those with
Vegetables (p-value = 0.0028).
Table 17. Relation of cultivation with farm size
95% Confidence
Interval for Mean
N Mean
Lower Upper
Std. Deviation Bound Bound
<10 acres 5 2,5556 ,00000 2,5556 2,5556
11-50 acres 10 3,3333 ,81985 2,7468 3,9198
51-100 acres 10 2,4444 ,35136 2,1931 2,6958
101-200 acres 45 2,2963 ,74724 2,0718 2,5208
Total 70 2,4841 ,76678 2,3013 2,6670
410
The willingness of farmers not to cultivate genetically modified products depends on
the farm size (F3,66 = 6.130, p = 0.001). Those who have croplands from 11 to 50 acres
have, on average from 0.04 to 1.7 units, higher willingness not to cultivate genetically
modified comparatively with those who have from 51 to 100 acres (p-value = 0.033).
Similarly those who have croplands from 11 to 50 acres have, on average from 0.4 to 1.7,
higher willingness not to cultivate genetically modified comparatively with those who
have from 101 to 200 acres (p-value = 0.001).
Table 18. Distribution of non cultivation factors in median and percentile points (quartiles)
Factor 25% Median 75% Cronbach’s Alpha
Q2p 2,50 4,00 5,00
Q2q 1,00 1,00 2,00
Q2r 1,75 2,50 3,25
Q2s 1,00 2,00 3,25
Q2t 2,00 3,00 4,00 0.820
Q2u 1,00 3,00 3,25
Q2v 1,75 3,00 4,00
Q2w 1,00 3,00 3,25
Q2x 1,00 1,00 1,00
The Cronbach’s Alpha value is 0.820. We create a new variable which is the average
value of all factors of table 18. Its mean value is 2.48 (standard deviation 0.77).
Table 19. Relation of type gender with the possitiveness about non cultivation
q4a N Mean Std. Deviation
Female 30 2,6852 ,70399
q2second
Male 40 2,3333 ,78567
Males and females does not differ according to possitiveness about non cultivation
compared to Females. (t=1.937, df=68, p-value=0.057)
Table 20. Relation of type of cultivation with the willingness of farmers to cultivate GMT
95% Confidence Interval for Mean
N Mean
Lower Bound Upper Bound
Arable 10 2,6667 2,5829 2,7505
Vegetables 15 2,1481 1,7648 2,5315
Forest Plantations 5 1,2222 1,2222 1,2222
Total 30 2,1667 1,9091 2,4242
411
The willingness of farmers to cultivate genetically modified products depends on the
type of crop (F2.27 = 13.764, p = 0.001). Those who cultivate arable are on average from
0.7 to 2.1 higher willingness to cultivate genetically modified compared with those who
cultivate forest plantations (p-value = 0.001). Similarly those who cultivate vegetables
are on average from 0.3 to 1.5 higher willingness to cultivate genetically modified
compared with those who have forest plantations (p-value = 0.001).
Table 21. Distribution of attitude factors vs the use of biotechnology (quartiles)
Factor 25% Median 75% Cronbach’s Alpha
Q3a 2,00 2,50 4,00
Q3b 1,00 3,00 4,00
Q3c 2,00 3,00 3,75
Q3d 1,00 3,00 3,00
Q3e 2,25 3,50 4,00
Q3f 3,25 4,00 5,00 0.915
Q3g 1,00 5,00 5,00
Q3h 4,00 5,00 5,00
Q3i 3,25 5,00 5,00
Q3j 1,00 3,00 3,00
Q3k 1,00 3,00 3,75
4 Discussion and Conclusions
The aim of this study was to investigate the attitudes of farmers regarding the GMT.
From the beginning there was the limitation of the number of responses. All the
responders come from the same area (Evros). So possible generalized conclusions would
be unreliable.
Nevertheless the value of the study in precious as it is the first study in Greece which
examines the farmers attitudes towards the use of biotechnology in forest tree sector. In
this research confirmed the continued negative attitude of the majority of farmers in
relation to the cultivation of GMT, which has been recorded by the relevant survey
reports Eurobarometer (European Commission - EC, 2010). In general, elder people with
low education, mainly female, with large scale farms seems not to be in favour of
cultivating transgenic trees whilst most of the younger, high educated, mainly male, small
scale farmers are more positive towards the cultivation of GM trees.
In a constantly changing world, the persistence of the established notions of the past
creates rigidities and barriers to future challenges. On the other hand the respect of values
and tradition is essential for any organization. Somewhere there must be "balance" one
for cultivation or not GMT.
412
According to Mc Donell et al (2010), the current decade will be important for
researchers of trees. Conducting such research could contribute to better information on a
subject that for others considered "taboo" and other necessary development. Furthermore
the potential developers of such forest tree plantations and paper, wood and woody
biomass energy products should structure their marketing and promotion according to the
farmers profile that this study developed. Additionally a campaign that will aim to inform
public about the use of biotechnology in forest tree sector and its advantages and
disadvantages should take place.
References
1. Broothaerts W.; Mitchell H.J.; Weir B.; Kaines S.; Smith L.M.; Yang W.; Mayer J.E.;
Roa-Rodriguez C. and Jefferson R.A., (2005) Gene transfer to plants by diverse
species of bacteria. Nature, Vol.433, No.7026, (February, 2005), pp. 629-633, ISSN
0028-0836.
2. Clive J., (1996) Global Review of the Field Testing and Commercialization of
Transgenic Plants: 1986 to 1995". The International Service for the Acquisition of
Agri-biotech Applications. Available at:
http://www.isaaa.org/kc/Publications/pdfs/isaaabriefs/Briefs%201.pdf. [Accessed 13
April 2015].
3. Coventry P., (2001) Forest Certification and Genetically Engineered Trees: Will the
two ever be compatible?, Oxford Forestry Institute Occasional Papers, No. 53.
4. EuropaBio, (2012) Available at: http://www.europabio.org/what-biotechnology.
[Accessed 10 March 2015].
5. European Commission - EC, (2010) Eurobarometer 341 / Wave 73.1, TNS Opinion &
Social. Available at: http://ec.europa.eu/public_opinion/archives/ebs/ebs_341_en.pdf.
[Accessed 11 April 2015].
6. F.A.O., (2004) The state of food and agriculture 2003-2004. Food and Agricultural
Organization of the United Nations, Publishing Management Service, Rome.
7. Fladung M., Pasonen H.-L. and Walter C., (2010) Genetically modified trees and
associated environmental concerns in Forests and Genetically Modified Trees, Food
and Agriculture Organization of the United Nations Rome, 2010, p.p. 177-202.
8. Gallardo F., Ionita L., Ruohonen-Lehto M., Harfouche A., Biricolti S., Boerjan
W., Glandorf B., Jouanin L., Fladung M., Vettori C., (2011) Environmental impact
assessment and monitoring of genetically modified trees. BMC Proceedings 2011 5
(Suppl 7): O59.
9. Gamborg C. and Sandοe P., (2010) Ethical considerations regarding genetically
modified trees in Forests and Genetically Modified Trees, Food and Agriculture
Organization of the United Nations Rome, 2010, p.p. 163-176.
413
10. Kousis M., (2009) New challenges for 21st century environmental movements:
agricultural biotechnology and nanotechnology. In The International Handbook of
Environmental Sociology (2nd edition). Redclift Μ.Ρ. and Woodgate W. (eds.).
Cheltenham: Edward Elgar.
11. Kuiper HA and Kleter GA, (2003) The scientific basis for risk assessment and
regulation of genetically modified foods. Trends Food Sci Technol 14: 277–293.
12. McDonnell L.M., Coleman H.D., French D.G., Meilan R. and Mansfield S.D., (2010)
Engineering trees with target traits in Forests and Genetically Modified Trees, Food
and Agriculture Organization of the United Nations Rome, 2010, p.p. 77-122.
13. Palmiter R.D., Brinster R.L., Hammer R.E., Trumbauer M.E., Rosenfeld M.G.,
Birnberg N.C. and Evans R,M., (1982) Dramatic growth of mice that develop from
eggs microinjected with metallothionein-growth hormone fusion genes. Nature.
300(5893): 611-615.
14. Preliminary review of biotechnology in forestry, (2004) Forestry Department Food
and Agriculture Organization of the United Nations, Working Paper FGR/59E, FAO,
Rome, Italy.
15. Prescott VE and Hogan SP, (2006) Genetically modified plants and food
hypersensitivity diseases: usage and implications of experimental models for risk
assessment. Pharmacol Ther 111: 374–383.
16. Sedjo R.A., (2004) Genetically Engineered Trees: Promise and Concerns,
Washington DC: Resources for the Future.
17. Sedjo R.A., (2010) Social, legal and regulatory issues related to transgenic trees in
Forests and Genetically Modified Trees, Food and Agriculture Organization of the
United Nations Rome, 2010, p.p. 203-216.
18. Strauss A.L. and Corbin J.M., (1998) Basics of Qualitative Research: Techniques and
Procedures for Developing Grounded Theory (2nd edition). Thousand Oaks,
California: Sage Publications Inc.
19. Strauss SH, Schmitt M. and Sedjo R., (2009) Forest scientists views on regulatory
obstacles to research and development of transgenic forest biotechnology. J For
107:350–357.
20. Strid Å. and Brosché M., (2001) Opportunities to genetically modify plants to cope
with environmental stress. Brit. Food J. 103: 796-800.
21. The Convention on Biological Diversity (Article 2. Use of Terms). United Nations,
(1992) Available at: http://www.cbd.int/convention/text/. [Accessed 22 April 2015].
22. Thieman W.J.; Palladino M.A., (2008) Introduction to Biotechnology.
Pearson/Benjamin Cummings. ISBN 0-321-49145-9.
23. Trochim W. and Donnelly J.P., (2006) The Research Methods Knowledge. Base (3rd
edition). Mason, Ohio: Cengage Learning-Atomic Dog.
414
24. Tsourgiannis L., Kazana V., Karasavvoglou A., Nikolaidis M. Florou G. and
Polychronidou P. (2013). Exploring Consumers’ Attitudes towards wood products
that could be derived from transgenic plantations in Greece Elsevier Procedia
Technology (8), 554-560.
25. Tsourgiannis L. , Kazana V., Karasavvoglou A., Vettori C., Fladung M., Sijacic-
Nikolic M., Ionita L.(2014), Would consumers be willing to buy woody biomass
energy products of transgenic origin? in the Book “EU Crisis and the Role of the
Periphery” Springer Verlag Berlin Heidelberg.
26. Tsourgiannis L., Kazana V., Iakovoglou V. (2015a) Exploring the potential behavior
of consumers towards transgenic forest products: the Greek experience. iForest (early
view): 1-e7 [online 2015-01-13] URL:
http://www.sisef.it/iforest/contents/?id=ifor1339-007 (Impact Factor 5ετίας 1.092).
27. Tsourgiannis L., Kazana V., Karasavvoglou A., Tsourgiannis C.A., Florou G. and
Polychronidou P., (2015b). Exploring consumers’ attitudes towards paper products
that could be derived from transgenic plantation in Greece, Int. Journal Data Analysis
Techniques and Strategies 7 (2), 156-171
28. Varzakas T.H., Arvanitoyannis I.S. and Baltas H., (2007a) The politics and science
behind GMO acceptance. Critical Review in Food Science and Nutrition. 47: 335-
361.
29. Varzakas T.H., Chryssochoidis G. and Argyropoulos, D., (2007b) Approaches in the
risk assessment of genetically modified foods by the Hellenic Food Safety Authority.
Food and Chemical Toxicology. 45: 530-542.
30. W.H.O., (2002) 20 questions on genetically modified (GM) foods. Available at:
http://www.who.int/foodsafety/publications/biotech/en/20questions_en.pdf.
[Accessed 22 April 2015].
31. Walter C. and Menzies M., (2010), Genetic modification as a component of forest
biotechnology in Forests and Genetically Modified Trees, Food and Agriculture
Organization of the United Nations Rome, 2010, p.p. 3-18.
32. Working group headed by Athanasios Tsaftaris, (2004). The development of agro-
biotechnologies until 2015, Technological Foresight in Central Macedonia (In Greek).
33. Zolotov Yu A., (2003) Revealing Genetically Modified Plants and Foodstuff Made on
Their Basis, Journal of Analytical Chemistry; Jan2003, Vol. 58 Issue 1, p1.
415