GCRI · Food Nexus
Storage and cold chain
Between harvest and plate, food is dried, stored, cooled, processed, packed and moved. Each step can lose food to spoilage, pests and damage, and each can introduce hazards that make food unsafe. Perishable foods such as fruit, vegetables, dairy, meat and fish depend on an unbroken cold chain, which in turn depends on electricity and refrigerants. This page sets out where losses and safety failures arise, how they are measured, and who acts on the evidence.
How the work runs.
Storage and cold chain
Storage and cold chain · Supply corridor 2 · Week 31
- Sites reporting21of 24Normal
- Excursions this week7Watch
- Estimated post-harvest loss7pct of throughputWatch
- Days of stock in reserve38daysNormal
Store temperature
Stores
| CS-01 | 67 | 4 | In band |
| CS-04 | 62 | 8 | Excursion |
| WH-02 | 79 | 19 | Ambient |
| CS-07 | 23 | 7 | In band |
Fig.Storage and cold chain: example names and illustrative values, not a record or a live system.
Storage and cold chain: how the risk develops.
Refrigeration, logistics and food safety. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Losses differ by stage and setting
Where drying, storage and transport are weak, losses concentrate on the farm and in storage, from moulds, pests and damage. Where they are strong, waste concentrates in retail and households. Each stage needs different measures.
Cold chains depend on power
Refrigeration needs continuous electricity or fuel. Outages, heatwaves beyond equipment design and gaps at transfer points let temperatures rise, and quality and safety degrade within hours.
Contamination travels with the product
Mycotoxins from poorly dried grain, pathogens from broken temperature control and chemical residues move with food through trade. One contaminated lot can reach many countries before it is traced.
Storage capacity sets the buffer
Public and private stocks smooth supply between harvests and through shocks. Stocks that are too small, poorly managed or in the wrong place leave a country exposed when imports or harvests fail.
Growing conditions in the Black Sea region.
Crop greenness, root-zone soil moisture and daytime surface heat over the Black Sea region, 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
- 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
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
- 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
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 the Black Sea region.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
- Land surface temperature, day, 8-day composite: VIIRS NOAA-20 Level 3, 8-day, NASA LANCE · 14 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
- Gross primary production, 8-day total: MODIS Aqua GPP (MYD17), NASA LP DAAC · 30 Sep 2026
Storage and cold chains depend on power, heat and safe water.
| Domain | How it couples here | What to watch |
|---|---|---|
| Energy | Refrigeration stops when the grid fails, and heat raises cooling load. See heat and cooling. | Hours of cold storage autonomy without grid power |
| Health | Temperature abuse causes food-borne illness; vaccines share the same cold chains in many places. See health supply chains. | Food-borne outbreak reports; temperature excursions |
| Water | Washing, processing and ice production need safe water. | Water quality at processing sites |
| Biodiversity | Losses upstream mean more land and water used for the same food reaching people. | Food loss by stage |
SDG target 12.3 separates food loss (from harvest up to retail, measured by FAO’s Food Loss Index) from food waste (at retail and consumption, measured by UNEP’s Food Waste Index, latest report 2024). The UNEP and FAO report on sustainable food cold chains (2022) sets out the energy and refrigerant trade-offs.
Model storage and cold chain as a system. Run the cascade.
Assembled from the Nexus Standards area profile Food security and nutrition risk: 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
- Famine
- Mass displacement (set off downstream)
- Health-system overload (set off downstream)
- Chronic malnutrition (set off downstream)
- Acute malnutrition surge (set off downstream)
Systems and couplings
Controls
NS-0Constitution and principlesNS-3Risk record UNIs (grammar, legacy crosswalk, allocation authority)NS-9Contextual UNIs (deployments, instances, programme instances)NS-10Policies and clauses (machine-readable obligations: definition, binding, evaluation and enforcement)NS-11Verification and monitoring (evidence, attestations, zero-trust conformance observation)NRS-H57Hazard family: Humanitarian crises (NHS-1 soc.humanitarian)NRS-H61Hazard family: Cascading failure (NHS-1 sys.cascade)NRS-H81Hazard family: Malnutrition and micronutrient deficiency (NHS-1 health.nutrition)NRS-H59Hazard family: Economic shocks and governance failure (NHS-1 soc.economic)NRS-N3Food and agriculture risk and resilienceNRS-N7Water-energy-food-health-biodiversity-infrastructure nexus coupling
Observation
- IPC acute food insecurity analyses (listed for reference)
- FEWS NET outlooks and data (listed for reference)
- FAO GIEWS Food Price Monitoring and Analysis tool (listed for reference)
- CHIRPS quasi-global gridded precipitation (listed for reference)
- Prevalence of undernourishment
- Prevalence of moderate or severe food insecurity
- Prevalence of stunting among children under 5 years of age
- Prevalence of malnutrition among children under 5 years of age
Example geography
- The Ganges and Brahmaputra Basin: 178 hexagonal cells
- Surface soil moisture (SMAP), NASA GIBS
- Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
- Surface water through cloud, 30 m (OPERA DSWx-S1 radar), NASA GIBS
- Rain rate, last half hour (IMERG), NASA GIBS
Cold chain evidence and how operators can add to it.
Cold chain resilience studies are designed for the Global Sector Risk and Resilience series. Food safety rules are set by national authorities under Codex principles; the Global Centre for Risk and Innovation (GCRI) sets none. Useful contributions: outage and temperature logs from cold stores, loss measurements by stage, and lessons from off-grid cooling.
How storage and cold chain 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.
System model
The couplings between the systems in storage and cold chain: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.
What is measured, and how well.
Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| Food loss index (SDG 12.3.1a) | index of loss percentage against a base period | annual | National loss surveys and models | ESTIMATED |
| Food waste per capita (SDG 12.3.1b) | kilograms per person per year | annual | Household, retail and food service measurement | ESTIMATED |
| Post-harvest loss by crop and stage | percent of harvested quantity | seasonal | Loss assessment surveys | ESTIMATED |
| Refrigerated storage capacity | cubic metres | annual | Industry and government inventories | REPORTED |
| Temperature excursions in storage and transport | hours outside the specified range | continuous | Data loggers | OBSERVED |
| Food safety notifications | count by hazard and product | weekly | Rapid alert systems | Published statistics |
| Aflatoxin exceedance in sampled grain | percent of samples above the applicable limit | per survey | Laboratory testing | OBSERVED |
| Public grain stock level | months of consumption | monthly | Reserve agency records | Published statistics |
Where the evidence comes from.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| Source | What it gives | Licence class |
|---|---|---|
| FAO Food Loss and Waste Database | Loss and waste estimates by commodity, stage and country | Free and open, attribution |
| UNEP Food Waste Index reports | Household, retail and food service waste estimates and the measurement method | Free, attribution |
| African Postharvest Losses Information System (APHLIS) | Cereal post-harvest loss estimates by country and province | Free, attribution |
| EU Rapid Alert System for Food and Feed (RASFF) | Notifications of food and feed hazards found in trade | Public records, terms per European Commission |
| WHO estimates of the global burden of foodborne diseases | Illness and death from foodborne hazards by region | Free, attribution |
| World Bank Logistics Performance Index | Comparative performance of trade logistics by country | Free and open, attribution |
| National food safety authorities and reserve agencies | Inspection results, recalls and stock records | Public records, terms per agency |
Who decides, and what the evidence serves.
Food Nexus prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Who decides | The question | Evidence this page serves |
|---|---|---|
| Food safety authorities | Which hazards and products need sampling, border checks or recall readiness | Notification trends, laboratory exceedances and the trade routes of affected products |
| Agriculture and trade ministries, and reserve agencies | How large strategic stocks should be, where to hold them and when to release them | Stock levels against consumption, import lead times and shock scenarios |
| Cold-chain operators and logistics firms | Where backup power, insulation or redundancy is needed to keep product within specification | Temperature excursion records against outage and heat exposure |
| Development finance institutions | Which storage and cold-chain investments reduce loss where it is largest | Loss estimates by stage and commodity, with their method and uncertainty |
Outputs this topic produces
- Loss and waste hotspot maps by commodity and stage
- Cold-chain dependency maps linking storage and transport to power supply
- Food safety hazard traces along trade routes
- Storage and reserve siting scenarios
What experts ask.
A harvest is only food security once it reaches people safely. Losses after harvest can be large for perishable produce and in places with limited storage, and a broken cold chain can turn a supply of food into a public health hazard. The resilience of this middle part of the chain is often less studied than production or consumption, which makes it a frequent hidden weakness.
- Where along the chain is food lost or wasted, and why?
- How dependent are cold chains on grid power, fuel and refrigerant supply, and how long can they hold temperature in an outage?
- Which storage options suit smallholders, and what limits their use?
- How do temperature failures translate into microbial growth and food safety incidents?
Drivers and processes.
Losses come from biology, infrastructure and organisation together.
Spoilage and pests
Moisture, heat and time drive mould, rot and insect damage. Some moulds produce toxins that make grain unsafe even when it looks sound.
Power and logistics
Refrigeration needs continuous power; transport needs roads, ports and fuel. A grid failure can spoil perishable stocks within hours to days.
Handling and coordination
Delays at markets and borders, poor packaging and weak handling practices add loss at every step.
How the evidence is built, and its limits.
- 01
Loss studies
Measure losses at stages of the chain. Methods differ, so estimates are hard to compare across studies.
- 02
Temperature monitoring
Sensors record cold chain performance; data are often held privately by operators.
- 03
Food safety surveillance
Outbreak and contamination data show consequences, but under-reporting is common.
- 04
Network models
Logistics and facility location models built with optimisation and operations research assess capacity and redundancy, within the limits of their input data.
How it is studied, and what the methods cannot say.
- 01Water and environmental engineeringIrrigation and drainage design · Safe wastewater reuse in agricultureApplied here
- 02Optimisation and operations researchHumanitarian supply and prepositioning · Strategic reserve designApplied here
- 03Agricultural, soil and food scienceCrop simulation for seasonal yield risk · Yield gap and nutrient limitation analysisApplied here
- 04Biotechnology platformsBreeding for stress tolerance · Rapid diagnostics for pests and diseaseApplied here
- 05Forecasting and time-series analysisSeasonal production outlooks · Staple price forecasting · Anticipatory action triggersApplied here
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.
- The State of Food and Agriculture 2019, Moving forward on food loss and waste reduction (FAO, 2019)
- Food Waste Index Report 2024 (UNEP, 2024)
- Sustainable Food Cold Chains: opportunities, challenges and the way forward (UNEP and FAO, 2022)
- Codex General Principles of Food Hygiene, CXC 1-1969, revised 2020 (FAO and WHO Codex Alimentarius Commission)
Where this page leads across the Consortium.
Questions and answers.
What is the difference between food loss and food waste?
Why does refrigeration raise climate concerns?
How are aflatoxins controlled?
Does Food Nexus inspect food safety?
Why does the platform link cold chains to the power grid?
Are medicines included?
Which investments reduce post-harvest loss most?
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