Implication analysis for biotechnology regulation and management in Africa: baseline studies for assessment of potential effects of genetically modified maize (Zea mays L.) cultivation in Ghanaian agriculture
Gespeichert in:
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| Format: | Abschlussarbeit Buch |
| Sprache: | English |
| Veröffentlicht: |
Frankfurt am Main ; Berlin [u.a.]
Lang
2009
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| Schriftenreihe: | Theorie in der Ökologie
15 |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | 240 S. Ill., graph. Darst., Kt. |
| ISBN: | 9783631594506 |
Internformat
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| 245 | 1 | 0 | |a Implication analysis for biotechnology regulation and management in Africa |b baseline studies for assessment of potential effects of genetically modified maize (Zea mays L.) cultivation in Ghanaian agriculture |c Denis Worlanyo Aheto |
| 264 | 1 | |a Frankfurt am Main ; Berlin [u.a.] |b Lang |c 2009 | |
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Datensatz im Suchindex
| _version_ | 1804145371424751616 |
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| adam_text | Titel: Implication analysis for biotechnology regulation and management in Africa
Autor: Aheto, Denis Worlanyo
Jahr: 2009
Contents
Figures 17
Tables 21
Acronyms 23
Parti: Introduction 25
Chapter 1: The General context 27
1.1 Overview 27
1.2 The development of transgenic crops 29
1.3 Transgenic crop cultivation worldwide 30
1.4 The aims of the Ghana case study 31
1.4.1 Study objectives 32
1.4.2 Study hypotheses 33
Chapter 2: Risk assessment of transgenic crops 37
2.1 Risk implication analyses in the context of transgenic crop cultivation 37
2.2 Regulatory requirements of biosafety at the international level and
sub-regional contexts 38
Part II: Method development in the international context 41
Chapter 3: Methodological approaches adapted from the international
contexts 43
3.1 Estimations of outcrossing probability between oilseed rape fields (and feral/
volunteer hybridization partners) using distribution frequency and neighbour¬
hood distance analysis 43
3.1.1 Introduction- The 6th EU Framework Research Project SIGMEA 43
3.1.2 Methodology 46
3.1.3 Results and discussion 48
3.1.4 Conclusions 57
3.2 Analysis of the spatial density and neighbourhood distances of cultivated
oilseed rape (Brassica napus) fields in Northern Germany 58
3.2.1 Introduction 58
3.2.2 Methodology 58
3.2.3 Results 58
3.2.4 Discussion 62
3.2.5 Conclusions 62
Part III: The Ghana case study on small-scale maize farming 63
Chapter 4: Background 65
4.1 The context of small-scale agriculture in Ghana and relevance for a biosafety
monitoring concept in maize crop production 65
4.2 Specific terms of reference to transgenic maize contamination events in the
past decade 67
4.3 The maize plant (Zea mays L.) 70
4.3.1 Origin 70
4.3.2 Production 70
4.3.3 Usage 70
4.3.4 Reproductive biology 71
4.4 Studies on pollen mediated gene flow/ outcrossing 73
4.5 Factors influencing gene flow 74
4.5.1 Pollen viability and competitive ability 74
4.5.2 Pollination vectors 75
4.5.3 Environmental factors 75
4.5.4 Buffer crops 76
4.5.5 Size of pollen source and sink 76
4.5.6 Temporal congruence of pollen and receptor plants 76
4.5.7 Volunteers 76
4.6 Hybridization and gene introgression 77
4.7 Urban agriculture in the developing world 77
Chapters: Methodology 79
5.1 The study area of Accra 79
5.2 Spatial analysis with the help of Geographic Information System (GIS) 80
5.2.1 Concept of the Global Positioning System (GPS) 80
5.2.2 Ground surface data gathering 81
5.3 Crop fields, volunteers, feral/ wild relative demography 84
5.3.1 Cultivation density 84
5.3.2 Classification of varieties grown 84
5.3.3 Phenological classification 85
5.3.4 Vitality of maize stands 85
5.3.5 Farm type 87
5.3.6 Characterization of feral stands 87
5.3.7 Photo documentation 88
5.4 Modeling methods 88
5.4.1 The Maize Model (MaMo) 88
5.4.2 Model parametisation 89
5.4.3 Map specification and investigated scenarios 92
5.4.4 Estimating duration of pollen availability 93
5.5 Socio-economic survey with smallholder farmers 93
5.6 Molecular genetic methods 95
5.6.1 Plant materials 95
5.6.2 Preservation and storage 96
5.6.3 Experimental steps 96
5.7 Statistical evaluation and softwares used 98
Chapter 6: Results 101
6.1 Geographic Aspects 101
6.1.1 Nearest neighbour distance analyses 101
6.1.2 Spatial characterization of maize stands with the help of GIS 105
6.1.3 Spatial distribution of farms and ferals across larger distances 105
6.1.4 Number of farm neighbours across larger distances 110
6.1.5 Number of feral neighbours across larger distances 111
6.1.6 GIS-based registration of maize field polygons 112
6.1.7 Field size distribution analysis 119
6.1.8 Site characterization of finding places 119
6.2 Crop Demographic Aspects 124
6.2.1 Stand frequencies and site characterization 124
6.2.2 Farm neighbourhood frequencies under specified buffer conditions 125
6.2.3 Crop phenological status and feral development data 127
6.2.4 Summary of results of geographical and crop demographic data 133
6.3 Ecological Modeling of Cross-Pollination Probabilities 134
6.3.1 Simulation of regional cross-pollination between GM and conventional
small-scale maize cropping systems 134
6.3.2 Summary of results from modeling approaches 148
6.4 Socio-economic Aspects 149
6.4.1 Demographic profile of respondents 149
6.4.2 Classification of farmer resource capacity at the household level 151
6.4.3 Gender effects and farmers socioeconomic circumstances 154
6.4.4 Farmers seed selection criteria 155
6.4.5 Analysis of seed acquisition and farmers selection criteria 159
6.4.6 If seeds are bought, are hybrids eventually re-planted? 159
6.4.7 Cultivation period and seasonally: 161
6.4.8 Demographic factors associated with farm type orientation 162
6.4.9 Intra-household factors influencing seed type utility 164
6.4.10 Farmers land rights 166
6.4.11 Implication of land tenure and land rights on cropping intensity 166
6.4.12 Crop rotational measures 167
6.4.13 Analysis of socioeconomic background of farmers in relation to farm
land holdings 168
6.4.14 Summary results of socio-economic data 170
6.5 Molecular Genomic Aspects 172
6.5.1 DNA concentration and absorbance measurements 172
6.5.2 SSR analysis 174
Chapter 7: Discussion 179
7.1 Relevance of the study for the African biosafety context 179
7.2 Genetically modified organisms in agriculture and issues of risk assessment 180
7.3 The spatial pattern of maize cultivation practices and implications for gene
flow 182
7.3.1 The methodological approach 182
7.3.2 Assessment of maize field neighbourhood distances 183
7.3.3 Assessment of feral distances from flowering field neighbours 183
7.3.4 Analysis of field acreage and spatial distribution 184
7.3.5 Number of farms within certain distances and implications for moni¬
toring over larger areas 186
7.4 Crop population demography and implications for gene flow 186
7.4.1 Crop growing areas 186
7.4.2 Flowering synchrony of farms 187
7.5 Quantifying the spatial spread of transgenes (modeling cross-pollination) 188
7.5.1 Quantitative models 188
7.5.2 Simulation of regional cross-pollination through ecological modeling
(The case of the Maize Model, MaMo) 189
7.6 Assessing the socioeconomic background of farmers and implications of gene
flow 189
7.6.1 Demographic characterization of the local farmer population 191
7.6.2 Seed acquisition criteria and technology access 191
7.6.3 Features of the subsistence and commercial farming contexts 193
7.6.4 Analysis of land ownership rights and gender factors 193
7.6.5 Socio-economic implications of gene flow 194
7.7 Analytical procedure for maize seed variety differentiation at the molecular
genomic level 197
7.7.1 Experimental genomic steps and limitations 197
7.7.2 Relevance of molecular DNA markers in gene flow estimation 198
7.8 Potential agronomic and environmental impacts of gene flow 198
Chapter 8: Conclusion 201
8.1 Ecological and biosafety management implications 201
8.2 Limitations and recommendations for further research 204
References 207
Appendices 223
Appendix 1: Study background 225
Appendix 2: Study methods and protocols 228
Appendix 2.1: Geographical aspects and crop demography 228
Appendix 3: Documentation of reagents, materials and instruments used 235
Acknowledgements 239
Figures
Figure 1.1: Biotech Crop Countries 31
Figure 1.2: Global transgenic crop plantings by main trait and crop 32
Figure 1.3: Outline of overall project approach 35
Figure 1.4: Outline of overall project approach 35
Figure 3.1: Oilseed rape field near Bremen (Northern Germany), 2005 44
Figure 3.2: Locations of the five demographic study areas for feral oilseed rape,
examined in SIGMEA made up of Tayside (UK), Mid-Jutland (Denmark),
Selommes (France), Bremen and Braunschweig (Germany) 45
Figure 3.3: Mapping of OSR (shown in circle) at a rural agricultural site in 2005
using a hand-held Garmin Etrex GPS 47
Figure 3.4: Distribution of oilseed rape fields and potential hybridization partners
within an area of 40km2 rural agricultural site of Bremen, 2005 49
Figure 3.5: Distance of feral populations to nearest OSR field location within the
40 km2 area 50
Figure 3.6: Examples of wild relatives of OSR found 51
Figure 3.7: Nearest distances between OSR field locations within the investigated
40 km2 area 51
Figure 3.8: Feral plants along grain fields nearby an OSR field, and occuring
between wheat field and pasture 52
Figure 3.9: Distance of feral populations to nearest feral location within the 40 km2
area 52
Figure 3.10: Demographic and site characteristics of oilseed rape and potential
hybridization partners found in rural areas of Bremen 54
Figure 3.11: Feral Oilseed rape 55
Figure 3.12: Nearest distance analysis between crops and ferals among the
cooperation states 55
Figure 3.13: Automated detection of Oilseed rape cultivation areas in Northern
Germany through a LANDSAT 7 ETM+ remote sensing image application
in 2001 (data adapted from Laue, 2004) 59
Figure 3.14 A-D: For the identified oilseed rape fields in the stated regions, it is
shown how many fields were counted having how many neighbours at a
particular distance 61
Figure 4.1: Maize production in Ghana (1965- 2005) 66
Figure 4.2: The vegetative and reproductive parts of the maize plant (Zea mays L.) 72
Figure 5.1: Map of study area (marked square), covering area of 25 km2 79
Figure 5.2: GARMIN ETREX H Handheld GPS Receiver used in the surveys and
screenshots of pass points 80
Figure 5.3: Transects of mapping routes followed by investigators within 1 x 1 km
grids in Accra West (2006) based on a Gauss-Kriiger coordinates 82
Figure 5.4: Mapping of some cultivated locations in peri-urban suburbs of Accra 83
Figure 5.5: Commercially-oriented fields within available open spaces and
Subsistence-oriented farms in spatially restricted areas within living areas 86
Figure 5.6: Feral maize stands growing on the side of highways, roads and other
crop fields 87
Figure 5.9: Literature studies on distance out-crossing rates in maize hybrids 90
Figure 5.10: Diagram of sampling scheme used to estimate temporal heterogeneity
of maize flowering and pollen exposure 91
Figure 5.11: Estimating the duration of pollen exposure through tagging
procedure at the center of a field 91
Figure 6.1.1: Distance to the next field neighbours for all locations of maize
cultivation on a scale of 5 m distances 101
Figure 6.1.2: Distance to next feral neighbour for all locations of feral occurences
on a scale of 5 m distances 103
Figure 6.1.3: Nearest distance from farm to feral neighbours on a scale of 5 m
distances 104
Figure 6.1.4: Nearest distance from feral to farm neighbours on a scale of 5 m
distances 105
Figure 6.1.5: Distribution of maize cropping fields (white dots) and feral
locations (black dots) on a 1 km2 grid in Accra West on Google image 106
Figure 6.1.6: Grid-based land use model to study land use due to maize field
and feral stand occurrences within each 1 km2 blocks for a 144 km2
settlement region, obtained by replication of the central area 107
Figure 6.1.7: Number of farm neighbours within intermediate distance ranges
in an area of 144 km2 110
Figure 6.1.8: Number of feral neighbours within intermediate distance ranges
in an area of 144 km2 111
Figure 6.1.9: Map of total maize acreage in Accra West for 2006 covering an
area of 25 km2 in twelve demarcated zones on a 2 x 2 km2 grid (WGS84,
UTMZone30) 112
Figure 6.1.10: Spatial structure of maize fields in Zones 1 and 2. The relative
positions of the frames are shown as inserts in the right top corner maps 113
Figure 6.1.11: Spatial structure of maize fields in Zones 3 and 4. The relative
positions of the frames are shown as inserts in the right top corner maps 114
Figure 6.1.12: Spatial structure of maize fields in Zones 5 and 6 115
Figure 6.1.13: Spatial structure of maize fields in Zones 7 and 8. The relative
positions of the frames are shown as inserts in the right top corner maps 116
Figure 6.1.14: Spatial structure of maize fields in Zones 9 and 10 117
Figure 6.1.15: Spatial structure of maize fields in Zones 11 and 12. The relative
positions of the frames are shown as inserts in the right top corner maps 118
Figure 6.1.16: Acreage of maize fields in Accra West displayed as a histogram
on a logarithmic scale indicating the nature of the agricultural structure
basing on 1,390 maize fields in 25 km2 areas 119
Figure 6.1.17: A pie chart showing the distribution range of farming acreage
based on the 1,390 fields found 121
Figure 6.1.18: Percentage number of field locations within respective sites 121
Figure 6.1.19: Examples of cultivated plots 122
Figure 6.1.20: Percentage number of feral locations within respective sites 123
Figure 6.1.21: Examples of feral locations 123
Figure 6.2.1: Crop demography in relation to site characteristics of cultivated plots... 124
Figure 6.2.2: Feral demography in relation to their site characteristics 125
Figure 6.2.3: Mean distribution of farm crops at the various sites 126
Figure 6.2.4: Number of farm neighbours within certain distance ranges
(assumed here to be buffer) 126
Figure 6.2.5: A 3D classification of farm neighbours to assess efficiency of
isolation distance management based on the spatial structure 127
Figure 6.2.6: Number of farm neighbours of cases in 0.1, 0.2, 0.3, 0.4 and
0.5 km distances 128
Figure 6.2.7: Flowering duration of 4 farmer cultivars using temporal difference
from onset to shed of pollen 131
Figure 6.2.8: Estimation of cross-pollination potential between cultivated crops
and feral locations 132
Figure 6.2.9: Feral stand in groundnut field few meters from farm crops 132
Figure 6.3.1: Spatial configuration of 42 GM fields among 1,348 conventional
fields 135
Figure 6.3.2: Simulation of pollen hybridization rates (%) between small-scale
GM and conventional fields presented on a logarithmic scale 136
Figure 6.3.3: Quantitative estimation in percentiles of the mean GM pollination
rates of conventional fields based on the farmer seed exchange criteria for the
10 repeated model runs 137
Figure 6.3.4: Model result of GM presence in conventional fields under seed
exchange among farmers involving modern hybrids (MHs) or open-pollinated
varieties (OPVs) 138
Figure 6.3.5: GM cross-pollination rates in 1,348 conventional fields in relation
to acreage displayed on a logarithmic scale 138
Figure 6.3.6: Initial model assumption stipulating the criteria that fields planted
with GM utilised seeds obtained from the food market 139
Figure 6.3.7: Simulation of pollen hybridization rates (%) between small-scale
GM and conventional fields presented on a logarithmic scale 139
Figure 6.3.8: Quantitative estimation in percentiles of the mean GM pollination
rates of conventional fields with the assumption that the GM sources were
from food grain (market) 141
Figure 6.3.9: Model result of GM presence in conventional fields due to intro¬
ductions from food market, assumed to be modern hybrids (MHs) or open-
pollinated varieties (OPVs) 141
Figure 6.3.10: Initial model assumption stipulating the criteria that fields planted
with GM utilised seeds obtained from the seed market and extension services 142
Figure 6.3.11: Simulation of pollen hybridization rates (%) between small-scale
GM and conventional fields presented on a logarithmic scale 142
Figure 6.3.12: Quantitative estimation in percentiles of the mean GM pollination
rates of conventional fields with the assumption that the GM sources were
from the seed market and extension 144
Figure 6.3.13: Model result of GM presence in conventional fields due to intro¬
duction from seed market and extension services assumed to be modern
hybrids (MHs) or open-pollinated varieties (OPVs) 144
Figure 6.3.14: GM cross-pollination rates in 1,283 conventional fields in relation
to acreage displayed on a logarithmic scale 145
Figure 6.3.15: Model result stipulating the criteria of a single centre GM field
among conventional fields numbering 1,389 146
Figure 6.3.16: Percentage cross-pollination rates in 1,389 conventional fields
from a single central GM source field 147
Figure 6.3.17: Validation of model (a) and GIS (b) approaches 148
Figure 6.4.1: Age distribution of survey respondents 150
Figure 6.4.2: Demography of respondents interviewed 150
Figure 6.4.3: Farm household structure 153
Figure 6.4.4: Farmers access to technology 154
Figure 6.4.5: Perceived criteria for seed selection among sample population 158
Figure 6.4.6: Modern and landrace seed procurement by (a) male and (b) female
respondents in the study area 160
Figure 6.4.7: Respondents maize planting and harvesting cycle (2006) 162
Figure 6.4.8: Tree diagram to estimate the relation between land tenure and
specific land rights of farmers 166
Figure 6.4.9: Land holding rights and cropping intensity 167
Figure 6.5.1 a b: Simple Sequence Repeat (SSR) profiles obtained on agarose
gel for 49 maize landraces obtained from farmers in Accra 175
Figure 6.5.1 c: Simple Sequence Repeat (SSR) profiles obtained on agarose gel
for 11 maize landraces obtained from fanners in Accra 176
Figure 6.5.2 a b: Simple Sequence Repeat (SSRs) profiles obtained on agarose
gel for 66 populations of Z. Mays (OPVs from local farmers (LVs) and
commercial varieties (CVs) from Ghana 177
Figure 7.1: An example of the spatial configuration of a large maize field in
close proximity to a larger number of smaller fields 185
Figure 7.2: An example of the spatial configuration of maize fields depicting a
dense cultivation practice 185
Figure 7.3: Simulation of gene flow into GM or conventional fields based on
external pollen received from each field in the region aggregated for each
recipient field. Note that the introgression levels are presented on the loga¬
rithmic scale with the data indicating various average contamination levels
from 0-10 188
Figure 7.4: Hofmann (2007) Pollen movement and deposition in relation to
nearest distance to maize field determined with a pollen sampler PMF from
2001-2006 at different locations in Germany 190
Figure 7.5: Farm orientation and levels of seed selection criteria in Accra West
in 2006 195
Tables
Table 3.1: Characteristics of the rural study site in Bremen, Germany 46
Table 3.2: Field protocol and parametization 47
Table 3.3: Species looked for, species found in 2005 48
Table 3.4: Characteristics of the feral/ volunteer populations in specific habitat
types in the 40 km2 agricultural area 53
Table 3.5: Assessing implications for gene flow between crop and feral plants in
Bremen 56
Table 3.6: Number of field cases, average nearest centroid distance from neigh¬
bours, and field acreage within the respective Federal States of Northern
Germany 59
Table 5.1: Ground surface data based on GPS measurements 81
Table 5.2: Mapping of farm locations and corners (outlines) of cultivated areas 84
Table 5.3: Descriptors for plant locations 84
Table 5.4: Parameter description for frequency, degree of covered surface size
estimations 85
Table 5.5: Phenological descriptors of maize stands 85
Table 5.6: Parameter descriptors for the vitality states of plants 86
Table 5.7: Parameter descriptors for the farm types found 88
Table 5.8: Photo documentation of plant stands location 88
Table 5.9: Local variables used in the model scenarios 89
Table 5.10: Agricultural practices and smallholder economy 94
Table 5.11: Crop management conditions (farm site-specific) 95
Table 5.12: Procurement locations of commercial varieties 96
Table 5.13: Commercial maize hybrids analysed 96
Table 5.14: SSR Primer sets used. Primers were all obtained from MWG Biotech
Company 98
Table 6.1: Characteristics of the study area 102
Table 6.2: Number of farm neighbours within certain distance ranges ( 200 m)
for the area of 25 km2 of Accra West. The minimum number of farm neigh¬
bours for all respective distance ranges is zero 103
Table 6.3: Number of feral neighbours within certain distance ranges ( 200 m)
for the area of 25km2 of Accra West. The minimum number of feral neigh¬
bours for all cases was found to be zero 104
Table 6.4: Maize field acreage within Accra West in 2006 120
Table 6.5: Phenological characters of crop plants determined on weekly basis 129
Table 6.6: Phenological characters of feral plants determined on weekly basis 130
Table 6.7: Gene flow conditions basing on geographical and crop demography 133
Table 6.8: Gene flow conditions based on model approach 149
Table 6.9: Analysis of population demographic characteristics using Pearson s
correlation coefficient 152
Table 6.10: Analysis of intra-household factors using Pearson s correlation
coefficient 156
Table 6.11: Analyses of gender and farmers socioeconomic circumstances 157
Table 6.12: Farmers ascribed criteria for seed selection 157
Table 6.13: Multivariate analyses of seed acquisition in relation to farmers
selection criteria in urban areas 160
Table 6.14: Reasons for replanting hybrid seeds from previous harvests 161
Table 6.15: Analyses of demographic factors associated with subsistence and
commercial farming approaches 163
Table 6.16: Factors associated with farmers adoption of local and modern
varieties 165
Table 6.17: Estimations of crop rotational measures 168
Table 6.18: Maize acreage at the household level 169
Table 6.19: Farm size holdings by men and women 169
Table 6.20: Farm size holdings estimated according to marital status 169
Table 6.21: Analysis of period of stay in community on land holding 170
Table 6.22: Gene flow conditions based on smallholder socioeconomic and seed
exchange factors 171
Table 6.23: Photometric measurements of DNA extracts obtained from the maize
samples 173
|
| any_adam_object | 1 |
| author | Aheto, Denis Worlanyo 1972- |
| author_GND | (DE-588)138618410 |
| author_facet | Aheto, Denis Worlanyo 1972- |
| author_role | aut |
| author_sort | Aheto, Denis Worlanyo 1972- |
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| ctrlnum | (OCoLC)636066409 (DE-599)DNB99509473X |
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| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 633 - Field and plantation crops |
| dewey-raw | 633.1523309667 |
| dewey-search | 633.1523309667 |
| dewey-sort | 3633.1523309667 |
| dewey-tens | 630 - Agriculture and related technologies |
| discipline | Agrar-/Forst-/Ernährungs-/Haushaltswissenschaft / Gartenbau Geographie |
| format | Thesis Book |
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| genre | (DE-588)4113937-9 Hochschulschrift gnd-content |
| genre_facet | Hochschulschrift |
| geographic | Ghana (DE-588)4020949-0 gnd |
| geographic_facet | Ghana |
| id | DE-604.BV026754123 |
| illustrated | Illustrated |
| indexdate | 2024-07-09T23:18:23Z |
| institution | BVB |
| isbn | 9783631594506 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-022291275 |
| oclc_num | 636066409 |
| open_access_boolean | |
| owner | DE-188 DE-703 |
| owner_facet | DE-188 DE-703 |
| physical | 240 S. Ill., graph. Darst., Kt. |
| publishDate | 2009 |
| publishDateSearch | 2009 |
| publishDateSort | 2009 |
| publisher | Lang |
| record_format | marc |
| series | Theorie in der Ökologie |
| series2 | Theorie in der Ökologie |
| spelling | Aheto, Denis Worlanyo 1972- Verfasser (DE-588)138618410 aut Implication analysis for biotechnology regulation and management in Africa baseline studies for assessment of potential effects of genetically modified maize (Zea mays L.) cultivation in Ghanaian agriculture Denis Worlanyo Aheto Frankfurt am Main ; Berlin [u.a.] Lang 2009 240 S. Ill., graph. Darst., Kt. txt rdacontent n rdamedia nc rdacarrier Theorie in der Ökologie 15 Zugl.: Bremen, Univ., Diss., 2008 Mais (DE-588)4037135-9 gnd rswk-swf Gentechnisch veränderter Organismus (DE-588)4353579-3 gnd rswk-swf Auswirkung (DE-588)4112646-4 gnd rswk-swf Ghana (DE-588)4020949-0 gnd rswk-swf (DE-588)4113937-9 Hochschulschrift gnd-content Ghana (DE-588)4020949-0 g Mais (DE-588)4037135-9 s Gentechnisch veränderter Organismus (DE-588)4353579-3 s Auswirkung (DE-588)4112646-4 s DE-604 Theorie in der Ökologie 15 (DE-604)BV013427125 15 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=022291275&sequence=000004&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Aheto, Denis Worlanyo 1972- Implication analysis for biotechnology regulation and management in Africa baseline studies for assessment of potential effects of genetically modified maize (Zea mays L.) cultivation in Ghanaian agriculture Theorie in der Ökologie Mais (DE-588)4037135-9 gnd Gentechnisch veränderter Organismus (DE-588)4353579-3 gnd Auswirkung (DE-588)4112646-4 gnd |
| subject_GND | (DE-588)4037135-9 (DE-588)4353579-3 (DE-588)4112646-4 (DE-588)4020949-0 (DE-588)4113937-9 |
| title | Implication analysis for biotechnology regulation and management in Africa baseline studies for assessment of potential effects of genetically modified maize (Zea mays L.) cultivation in Ghanaian agriculture |
| title_auth | Implication analysis for biotechnology regulation and management in Africa baseline studies for assessment of potential effects of genetically modified maize (Zea mays L.) cultivation in Ghanaian agriculture |
| title_exact_search | Implication analysis for biotechnology regulation and management in Africa baseline studies for assessment of potential effects of genetically modified maize (Zea mays L.) cultivation in Ghanaian agriculture |
| title_full | Implication analysis for biotechnology regulation and management in Africa baseline studies for assessment of potential effects of genetically modified maize (Zea mays L.) cultivation in Ghanaian agriculture Denis Worlanyo Aheto |
| title_fullStr | Implication analysis for biotechnology regulation and management in Africa baseline studies for assessment of potential effects of genetically modified maize (Zea mays L.) cultivation in Ghanaian agriculture Denis Worlanyo Aheto |
| title_full_unstemmed | Implication analysis for biotechnology regulation and management in Africa baseline studies for assessment of potential effects of genetically modified maize (Zea mays L.) cultivation in Ghanaian agriculture Denis Worlanyo Aheto |
| title_short | Implication analysis for biotechnology regulation and management in Africa |
| title_sort | implication analysis for biotechnology regulation and management in africa baseline studies for assessment of potential effects of genetically modified maize zea mays l cultivation in ghanaian agriculture |
| title_sub | baseline studies for assessment of potential effects of genetically modified maize (Zea mays L.) cultivation in Ghanaian agriculture |
| topic | Mais (DE-588)4037135-9 gnd Gentechnisch veränderter Organismus (DE-588)4353579-3 gnd Auswirkung (DE-588)4112646-4 gnd |
| topic_facet | Mais Gentechnisch veränderter Organismus Auswirkung Ghana Hochschulschrift |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=022291275&sequence=000004&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV013427125 |
| work_keys_str_mv | AT ahetodenisworlanyo implicationanalysisforbiotechnologyregulationandmanagementinafricabaselinestudiesforassessmentofpotentialeffectsofgeneticallymodifiedmaizezeamayslcultivationinghanaianagriculture |