GCRI · Biotechnology and Biosecurity
Agricultural biotechnology
Agricultural biotechnology applies biological tools to crops, livestock, soils and food processing: improved varieties, disease diagnostics, biological pest control and microbial products for soils. It can help agriculture adapt to climate change and reduce chemical inputs, while raising questions about environmental effects, equity and governance. This topic, studied at Biotechnology and Biosecurity, a platform of The Global Centre for Risk and Innovation (GCRI), examines those applications and their effects across food systems.
What experts ask.
- How do gene-edited and conventionally bred crops differ in their risks and regulation?
- What are the environmental effects of biotechnology in agriculture, positive and negative?
- How do plant and animal diseases spread through food systems, and how can biotechnology help detect them?
- Who benefits from agricultural biotechnology, and how do intellectual property and access shape this?
- How are new agricultural products assessed before use?
Growing conditions in West Africa.
Crop greenness, root-zone soil moisture and plant growth over West Africa, from NASA GIBS. Each layer carries its own date.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 3
Growing conditions, for this page
About this layer
- Evidence
- Observed (clouds leave gaps)
- Source
- MODIS Terra NDVI (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite index; clouds leave gaps
- Newest at build
- 2026-10-13
- Resolution
- about 250 m grid
- Uncertainty
- Satellite greenness index over the 8 days to the date shown; an indicator of crop and pasture condition, not a yield estimate or a food security warning.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Modelled
- Source
- SMAP Level 4 (NASA NSIDC DAAC)
- Provider
- NASA NSIDC DAAC
- Licence
- NASA open data
- Vintage
- daily; Model with satellite data assimilated
- Newest at build
- 2026-10-11
- Resolution
- about 2 km grid
- Uncertainty
- Model with satellite data assimilated. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Modelled (latest 8-day period GIBS publishes)
- Source
- MODIS Aqua GPP (MYD17) (NASA LP DAAC)
- Provider
- NASA LP DAAC
- Licence
- NASA open data
- Vintage
- 8-day; Satellite-driven model; latest 8-day period GIBS publishes
- Newest at build
- 2026-09-30
- Resolution
- about 500 m grid
- Uncertainty
- Model estimate of carbon taken up by plants over the 8-day period shown; an indicator of growth, not harvest or production.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed
- Source
- VIIRS NOAA-20 corrected reflectance (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite image
- Newest at build
- 2026-10-14
- Resolution
- about 250 m grid
- Uncertainty
- Satellite image. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Modelled (latest year GIBS publishes)
- Source
- MODIS Terra and Aqua land cover (MCD12Q1) (NASA LP DAAC)
- Provider
- NASA LP DAAC
- Licence
- NASA open data
- Vintage
- yearly; Satellite classification; latest year GIBS publishes
- Newest at build
- 2024-01-01
- Resolution
- about 500 m grid
- Uncertainty
- Satellite land cover classes for the year shown, including croplands; a classification with known errors, not a farm register.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed (persistent cloud still leaves gaps)
- Source
- VIIRS NOAA-20 Level 3, 8-day (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- 8-day; Satellite 8-day composite; persistent cloud still leaves gaps
- Newest at build
- 2026-09-14
- Resolution
- about 1 km grid
- Uncertainty
- Satellite skin temperature of the ground over the 8 days ending on the date shown, a heat exposure indicator; not air temperature, heat index or a heat warning.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
Keyboard, with the map focused
Hold Ctrl or ⌘ and scroll to zoom
Latest available
NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth
Loading the latest NASA imagery.
Drag to move. Ctrl or ⌘ and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.
Growing conditions, framed on West Africa.Satellite and model products as NASA publishes them, each with its own date. They are indicators, not assessments of any place.
Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA EONET · NASA JPL OPERA DIST-ALERTSources and licences
- We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- SMAP Level 4 soil moisture and snow mass, NASA Global Modeling and Assimilation Office; distributed by the NASA National Snow and Ice Data Center DAAC; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). Cite as: NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. NASA open data
- Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
- © OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). ODbL
- Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, © OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.
- Live events: NASA Earth Observatory Natural Event Tracker (EONET); events are indicative and keep their original source links.
- Live: NASA EONET Events are indicative, not authority warnings.
- Observed (EO): NASA JPL OPERA DIST-ALERT (contains modified Copernicus Sentinel data 2026). We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
- NASA GIBS: We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
- River discharge forecast, 30 days with range (GloFAS via Open-Meteo): Contains modified Copernicus Emergency Management Service information 2026; not a flood warning.
- Past year, daily temperature (ERA5 via Open-Meteo): Contains modified Copernicus Climate Change Service information 2026.
- Past year, daily temperature and sunshine (NASA POWER): These data were obtained from the NASA Langley Research Center (LaRC) POWER Project funded through the NASA Earth Science/Applied Science Program..
- Weather data by Open-Meteo.com (https://open-meteo.com/), licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).
- Optional layers (13 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.
Layers and dates
- Vegetation greenness (NDVI), rolling 8 days: MODIS Terra NDVI, NASA LANCE · 13 Oct 2026
- Root-zone soil moisture, 0 to 100 cm: SMAP Level 4, NASA NSIDC DAAC · 11 Oct 2026
- Gross primary production, 8-day total: MODIS Aqua GPP (MYD17), NASA LP DAAC · 30 Sep 2026
- True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
- Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
- Land surface temperature, day, 8-day composite: VIIRS NOAA-20 Level 3, 8-day, NASA LANCE · 14 Sep 2026
Agricultural biotechnology couples food, nature and health.
Findings are designed for the Exponential Technology series. The Cartagena Protocol and the Codex principles of 2003 frame biosafety and food safety assessment; national authorities decide.
- Field outcome studies.
- Biosafety decision records.
Oversight and capacity register.
The screen a team would use to follow this subject: its measures, states and decisions. Names are examples and values are illustrative.
Oversight and capacity register
Agricultural biotechnology · National committee · Review year 2
- Institutions with a committee, %65Watch
- Staff trained, %71Normal
- Reviews completed65this year
- Incident reports filed9Info
Institutional oversight
| Institution A | Active | Q1 | 88 | Current |
| Research campus | Active | Q2 | 87 | Audit due |
| Biomanufacturing site | Forming | none | 59 | Support |
| Diagnostic network | Active | Q3 | 86 | Current |
Scope note
- Covers
- governance, training, review capacity
- Excludes
- technical methods and agents
- Authority
- national oversight body
- Label
- SURVEY
Drivers and dynamics.
Plant and animal breeding have long relied on genetic variation; biotechnology adds tools to create and select it more precisely. Applications include drought and disease tolerance, improved nutrition and reduced post-harvest losses. Biological pest control and soil microbial products offer alternatives to some chemical inputs. Diagnostics help detect crop and livestock diseases early, limiting spread.
Environmental effects depend on the trait, the farming system and the landscape: effects on non-target species, gene flow to wild relatives, and changes in pesticide use have all been studied. Social effects depend on access, ownership and the structure of seed and input markets. Regulatory approaches differ widely between jurisdictions, which affects trade in seeds, grain and food products and the speed at which new varieties reach farmers. Food systems are studied at Food Nexus and ecosystems at Biodiversity Nexus.
A shock through an input-output economy.
A loss of output in one sector propagates through the technical coefficients to its suppliers and customers, and recovers at the rate you set; the coefficients are teaching values, not national accounts. Teaching model with stated illustrative values, not a prediction. The map on this page shows West Africa; the model itself is not tied to a place.
Controls
- Sector hit first (position in the list)
- 0
- Size of the shock
- 30% of its output
- Duration of the shock
- 30 days
- Recovery rate
- 0.08 per day
- Days simulated
- 180 days
Readouts
- Output lost over the run
- 0.74% of a year’s output
- Total over direct (multiplier)
- 1.83 times
- Most affected other sector
- Wholesale and retail
- Its peak inoperability
- 3.3%
Numbers, methods and sources
| Sector | Peak inoperability (%) | Output weight (%) |
|---|---|---|
| Farming | 33.31 | 16.1 |
| Fertiliser and inputs | 2.66 | 20.4 |
| Food processing | 0.59 | 16.2 |
| Transport | 1.74 | 18.4 |
| Wholesale and retail | 3.34 | 15.7 |
| Energy | 0.21 | 13.2 |
Methods
- Input-output analysis Leontief (1936); Miller and Blair (2009), Input-Output Analysis, Cambridge University Press
- Inoperability input-output model Haimes and Jiang (2001), Journal of Infrastructure Systems 7
- Dynamic inoperability and recovery Lian and Haimes (2006), Systems Engineering 9
- Uncertainty fan (parameter Monte Carlo) Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
- One-at-a-time sensitivity (tornado) Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley
Data
The model runs on the teaching values set by the controls. To calibrate it for a place, read it against these admitted layers and series, which this page’s map can draw:
- Seaports Natural Earth
- Maritime chokepoints Nexus (named straits and canals at their published coordinates)
- Railways Natural Earth
- Major roads Natural Earth
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Biotechnology and Biosecurity in Foundry
- Tested at Biotechnology and Biosecurity in Universe
- Codified in Health and Biosecurity in Standards
- Published in Biotechnology and Biosecurity in Reports
- Taught in Faculty of Health and Society in Academy
How it is studied.
- 01
Field and environmental studies
Controlled trials and monitoring, drawing on agricultural, soil and food science, measure agronomic and ecological effects.
- 02
Risk assessment
Comparative frameworks assess new products against conventional counterparts.
- 03
Socio-economic analysis
Studies examine adoption, incomes, access and market structure.
- 04
Limits
Long-term and landscape-scale effects are hard to observe, results vary by context, and studies differ in independence and design.
Model agricultural biotechnology as a system. Run the cascade.
Assembled from the Nexus Standards area profile Biological hazard standards: the hazards it names, the systems and sectors that carry the loss, the controls that dampen it and the data that observe it. Choose the components, pick an initiating hazard and step through the cascade. The Map view places the run on an example geography with open data. Every coupling weight is a stated assumption you can change. A teaching model, not a forecast, an assessment or a certification. To model a place of your own choosing, open the full System Builder.
Hazards
Systems and couplings
- Biological hazard standards
- Health risk standards Cascade
- Food and agriculture risk standards Cascade
- Biodiversity and nature risk standards Common driver
- Health security and One Health Mechanism
Controls
NS-0Constitution and principlesNS-3Risk record UNIs (grammar, legacy crosswalk, allocation authority)NS-11Verification and monitoring (evidence, attestations, zero-trust conformance observation)NRS-H41Hazard family: Animal-to-human spillover (NHS-1 health.zoonotic)NRS-H44Hazard family: Plant disease and pests (NHS-1 health.plant-health)NRS-H43Hazard family: Livestock and aquaculture epizootics (NHS-1 health.animal-health)NRS-H35Hazard family: Airborne and respiratory infection (NHS-1 health.respiratory)NRS-H40Hazard family: Blood-borne and sexually transmitted infection (NHS-1 health.bloodborne)NRS-H60Hazard family: Supply-chain and flow disruption (NHS-1 sys.supply-chain)
Observation
- WHO Disease Outbreak News (listed for reference)
- WAHIS animal health events (listed for reference)
- GBIF occurrence API and downloads (listed for reference)
- International Health Regulations capacity and health emergency preparedness
- Proportion of countries adopting relevant national legislation and adequately resourcing the prevention or control of invasive alien species
Example geography
- West Africa: 59 hexagonal cells
- Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
What it informs and who decides.
This evidence informs regulatory decisions on new varieties and products, agricultural research priorities and plant and animal health surveillance. National regulators, agricultural ministries, farmers and research institutions decide. Governance of food systems and nature is convened by Climate and Nature Governance at The Global Risks Forum (GRF). Related topics are One Health impacts, synthetic biology and biomanufacturing; methods sit on agricultural, soil and food science and biotechnology platforms.
Published analysis on this topic is designed to carry a named subject reviewer, its references and the views of independent specialists, including biosafety professionals and those who disagree.
The sector signature of agricultural biotechnology.
The sectors agricultural biotechnology touches and how strongly they depend on each other: what a study has to observe and model together.
Signature
Food and its partners
Food gives nutrition to health (0.7), land conversion to biodiversity (0.6) and withdrawals and runoff to water (0.3).
W · E · I · F · H · B
- Sectors
- 4 of 6
- Relations
- 6 of 15
- Coupling
- 0.46 share of total
Strongest relations in play
- Food → Biodiversity · land conversion0.6
- Water → Food · irrigation0.8
- Water → Biodiversity · environmental flows0.6
- Food → Health · nutrition0.7
Where this page’s references lead.
The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.
How agricultural biotechnology is modelled, measured and tested.
The model, its assumptions, its data and its uncertainty, in the form a scientist or engineer would check. Structures follow published methods. The values drawn are illustrative, not findings.
Uncertainty bands
How far the outlook for agricultural biotechnology could spread, shown as ranges rather than a single line.
- Central estimate
- median of the ensemble
- Ranges
- likely and very likely, in IPCC calibrated language
- Ensemble
- members, scenarios and initial conditions stated
- Read with
- the sensitivity of the result to each input
Questions and answers.
Is gene editing regulated the same way as genetic modification?
Does the platform take a position for or against biotechnology in farming?
How does biotechnology help with plant and animal disease?
Who reviews coverage of this topic?
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