Cold Chain Export Monitoring Metrics
This dataset provides granular monitoring metrics for agricultural export shipments in cold chains, including temperature, humidity, handling events, and ESG compliance indicators. It enables climate tech startups and agri-businesses to optimize supply chain resilience, reduce spoilage risk, and improve international logistics reporting. The comprehensive structure supports traceability, risk analysis, and sustainability benchmarking across global supply chains.
Sample rows
preview · 8 of 54 rows · all 23 columns| shipment_idstring | avg_humidity_percentfloat | esg_compliance_flagboolean | origin_countrystring | container_idstring | product_typestring | destination_countrystring | departure_datetimedatetime | arrival_datetimedatetime | transit_duration_hoursfloat | avg_temperature_celsiusfloat | min_temperature_celsiusfloat | max_temperature_celsiusfloat | min_humidity_percentfloat | max_humidity_percentfloat | handling_event_countinteger | handling_event_typesstring | temperature_excursion_countinteger | humidity_excursion_countinteger | spoilage_risk_scorefloat | carrier_namestring | exporter_namestring | importer_namestring |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| SHPMNT-1A2B3C4D | 73.2 | true | India | CONT-1001 | mango | Germany | 2024-03-02T10:15:00Z | 2024-03-06T13:45:00Z | 99.5 | 7.2 | 5.6 | 8.9 | 68.1 | 78.4 | 4 | loading,inspection,transfer,unloading | 1 | 0 | 0.21 | Maersk Logistics | AgriFresh India Pvt Ltd | Berlin Fruit GmbH |
| SHPMNT-4E5F6G7H | 84.9 | true | Mexico | CONT-1002 | avocado | France | 2024-03-10T08:30:00Z | 2024-03-13T12:40:00Z | 76.2 | 4.6 | 2.9 | 6.1 | 80.2 | 89.7 | 3 | loading,inspection,unloading | 0 | 2 | 0.28 | Hapag-Lloyd | Green Valley Exporters | Paris Produce S.A. |
| SHPMNT-8J9K0L1M | 91.3 | true | USA | CONT-1003 | berries | Japan | 2024-03-18T14:10:00Z | 2024-03-23T20:55:00Z | 130.75 | 2.8 | 1.2 | 4.5 | 87.2 | 95 | 4 | loading,inspection,transfer,unloading | 0 | 1 | 0.19 | NYK Line | Pacific Berry Farms | Tokyo Foods Co Ltd |
| SHPMNT-2N3P4Q5R | 86.4 | false | South Africa | CONT-1004 | grapes | Netherlands | 2024-02-25T07:50:00Z | 2024-03-01T16:20:00Z | 104.5 | 3.1 | 2 | 5 | 82.5 | 89.9 | 5 | loading,inspection,transfer,transfer,unloading | 1 | 1 | 0.33 | MSC | Cape Vines Export | Rotterdam Agro Import |
| SHPMNT-6S7T8U9V | 77.1 | true | Costa Rica | CONT-1005 | pineapple | UK | 2024-02-13T13:30:00Z | 2024-02-16T16:00:00Z | 74.5 | 8.2 | 6.8 | 9.6 | 73 | 81.9 | 2 | loading,unloading | 0 | 0 | 0.12 | Kuehne+Nagel | Tropical Fresh Exporters | London Fruit Import Ltd |
| SHPMNT-0W1X2Y3Z | 82.6 | true | Peru | CONT-1011 | avocado | Canada | 2024-03-05T09:00:00Z | 2024-03-08T17:15:00Z | 80.25 | 5 | 3.2 | 7.1 | 79 | 86.2 | 3 | loading,inspection,unloading | 0 | 0 | 0.15 | DB Schenker | Andes Agro Peru | Toronto Produce Inc |
| SHPMNT-4A5B6C7D | 71.2 | false | Brazil | CONT-1012 | mango | Spain | 2024-03-08T05:40:00Z | 2024-03-11T18:30:00Z | 80.83 | 7.9 | 6.5 | 9.3 | 68.5 | 74.8 | 4 | loading,inspection,transfer,unloading | 2 | 0 | 0.34 | Hamburg Süd | Rio Harvest Ltd | Madrid Fruit SL |
| SHPMNT-8E9F0G1H | 93.5 | true | New Zealand | CONT-1013 | kiwi | Singapore | 2024-02-19T15:20:00Z | 2024-02-22T21:30:00Z | 78.17 | 1.7 | 0.8 | 3 | 89.2 | 97 | 3 | loading,inspection,unloading | 0 | 1 | 0.13 | CMA CGM | Kiwi Farms NZ | Asia Fruit Pte Ltd |
| SHPMNT-2I3J4K5L | 75.2 | true | Philippines | CONT-1014 | pineapple | China | 2024-03-12T12:10:00Z | 2024-03-15T20:00:00Z | 79.83 | 9.5 | 8.1 | 10.7 | 72 | 78.9 | 2 | loading,unloading | 0 | 0 | 0.15 | OOCL | Tropical Isles Export | Shanghai Markets Ltd |
| SHPMNT-6M7N8O9P | 88.6 | false | Italy | CONT-1015 | grapes | Sweden | 2024-02-28T11:50:00Z | 2024-03-03T17:40:00Z | 101.83 | 3.8 | 2.5 | 5.2 | 84 | 92.1 | 5 | loading,inspection,transfer,transfer,unloading | 1 | 2 | 0.39 | Evergreen Line | Vino Italia Srl | Stockholm Fruit AB |
| SHPMNT-0Q1R2S3T | 74.8 | true | Pakistan | CONT-1016 | mango | UAE | 2024-02-15T09:45:00Z | 2024-02-17T22:05:00Z | 60.33 | 8.7 | 7.1 | 10.2 | 70.6 | 79.3 | 3 | loading,inspection,unloading | 1 | 0 | 0.17 | DP World | Sindh Mango Exporters | Dubai Fruit Wholesale |
| SHPMNT-4U5V6W7X | 90.4 | true | Italy | CONT-1017 | kiwi | Russia | 2024-03-15T07:20:00Z | 2024-03-18T16:45:00Z | 81.42 | 2.1 | 1.1 | 3.7 | 86.3 | 94.1 | 4 | loading,inspection,transfer,unloading | 0 | 1 | 0.2 | COSCO | Frutta Italia | Mosfruit OOO |
| SHPMNT-8Y9Z0A1B | 81.5 | true | Chile | CONT-1018 | avocado | USA | 2024-02-18T20:30:00Z | 2024-02-21T23:55:00Z | 75.42 | 4.8 | 3.1 | 6.9 | 77.4 | 85.2 | 2 | loading,unloading | 0 | 0 | 0.09 | ZIM Integrated | Andes Avocado Export | California Produce Corp |
| SHPMNT-2C3D4E5F | 92 | false | Morocco | CONT-1019 | berries | UK | 2024-03-06T05:15:00Z | 2024-03-09T11:30:00Z | 78.25 | 3.2 | 2 | 4.4 | 87.8 | 96.3 | 3 | loading,inspection,unloading | 1 | 1 | 0.32 | Maersk Logistics | Atlas Berry Morocco | London Fruit Import Ltd |
| SHPMNT-6G7H8I9J | 72.5 | false | Thailand | CONT-1020 | mango | Australia | 2024-03-13T06:00:00Z | 2024-03-15T22:10:00Z | 64.17 | 9 | 7.8 | 10.4 | 67.9 | 77.2 | 3 | loading,transfer,unloading | 2 | 0 | 0.27 | Pacific International Lines | Bangkok Agro Export | Sydney Produce Co |
| SHPMNT-0K1L2M3N | 74.6 | true | Vietnam | CONT-1021 | pineapple | Kuwait | 2024-03-20T09:40:00Z | 2024-03-22T19:30:00Z | 57.83 | 11.1 | 9.7 | 12.3 | 71.9 | 77.5 | 2 | loading,unloading | 1 | 0 | 0.19 | MSC | Indochina Fruits Ltd | Kuwait Agro Co |
| SHPMNT-4O5P6Q7R | 85.1 | true | USA | CONT-1022 | grapes | Germany | 2024-03-09T11:10:00Z | 2024-03-12T15:35:00Z | 76.42 | 4.4 | 2.5 | 6.3 | 80.9 | 89.2 | 4 | loading,inspection,transfer,unloading | 0 | 1 | 0.25 | Hapag-Lloyd | California Grape Export | Berlin Fruit GmbH |
| SHPMNT-8S9T0U1V | 91.2 | true | Greece | CONT-1023 | kiwi | Qatar | 2024-02-21T10:05:00Z | 2024-02-24T14:50:00Z | 76.75 | 2 | 1 | 3.4 | 86.7 | 95.4 | 3 | loading,inspection,unloading | 0 | 1 | 0.18 | Maersk Logistics | Hellenic Kiwi Export | Doha Fruit Co |
| SHPMNT-2W3X4Y5Z | 93.7 | false | Chile | CONT-1024 | berries | South Korea | 2024-03-11T16:25:00Z | 2024-03-15T08:55:00Z | 88.5 | 3 | 1.4 | 4.7 | 90 | 98.1 | 4 | loading,inspection,transfer,unloading | 1 | 2 | 0.36 | NYK Line | Andes Berry Exporters | Seoul Fruit Co |
| SHPMNT-6A7B8C9D | 80.3 | true | Kenya | CONT-1025 | avocado | UAE | 2024-03-04T08:40:00Z | 2024-03-07T13:00:00Z | 76.33 | 4.3 | 2.7 | 5.8 | 75.9 | 84.2 | 3 | loading,inspection,unloading | 0 | 0 | 0.11 | CMA CGM | Kenya Fresh Exporters | Dubai Fruit Wholesale |
What the 54 rows show
from the 54-row sample- 67%esg_
compliance_ flag = true - 85.2median avg_
humidity_ percent - 127.0median transit_
duration_ hours - 4.9median avg_
temperature_ celsius - 3.5median min_
temperature_ celsius - 7.0median max_
temperature_ celsius
Median 85.2, from 70.4 to 93.7.
- string 9
- integer 3
- float 8
- datetime 2
- boolean 1
Columns
23 columns in four groups| column | type | description | example |
|---|---|---|---|
| Text 9 columns | |||
shipment_id | string | Unique identifier for each export shipmentunique | SHPMNT-1A2B3C4D |
container_id | string | Unique identifier for the shipping container or unit | CONT-1001 |
product_type | string | Type of agricultural product being shipped (e.g., mango, avocado, berries) | mango |
origin_country | string | Country where the shipment originated | India |
destination_country | string | Country where the shipment is destined | Germany |
handling_event_types | string | Comma-separated list of handling event types encountered (e.g., loading, unloading, inspection, transfer)optional | loading,unloading |
carrier_name | string | Name of the logistics carrier responsible for the shipmentoptional | Maersk Logistics |
exporter_name | string | Name of the exporting agri-business or organizationoptional | AgriFresh India Pvt Ltd |
importer_name | string | Name of the importing business or organizationoptional | Berlin Fruit GmbH |
| Numbers 11 columns | |||
transit_duration_hours | float | Total transit time in hours from departure to arrival0 or more · optional | 99.5 |
avg_temperature_celsius | float | Average temperature recorded during transit (°C)-30 to 40 | 7.2 |
min_temperature_celsius | float | Minimum temperature recorded during transit (°C)-30 to 40 · optional | 5.6 |
max_temperature_celsius | float | Maximum temperature recorded during transit (°C)-30 to 40 · optional | 8.9 |
avg_humidity_percent | float | Average humidity percentage during transit0 to 100 | 73.2 |
min_humidity_percent | float | Minimum humidity percentage during transit0 to 100 · optional | 68.1 |
max_humidity_percent | float | Maximum humidity percentage during transit0 to 100 · optional | 78.4 |
handling_event_count | integer | Number of handling events (e.g., loading, unloading, inspections) during transit0 or more | 4 |
temperature_excursion_count | integer | Number of times temperature exceeded safe thresholds during transit0 or more · optional | 1 |
humidity_excursion_count | integer | Number of times humidity exceeded safe thresholds during transit0 or more · optional | 0 |
spoilage_risk_score | float | Calculated risk score for spoilage based on environmental metrics and handling events (0-1 scale)0 to 1 · optional | 0.21 |
| Dates and times 2 columns | |||
departure_datetime | datetime | Date and time when the shipment departed from origin | 2024-03-02T10:15:00Z |
arrival_datetime | datetime | Date and time when the shipment arrived at destinationoptional | 2024-03-06T13:45:00Z |
| True or false 1 column | |||
esg_compliance_flag | boolean | Indicates if shipment met ESG (Environmental, Social, Governance) compliance standardsoptional | true |
Use it for
A logistics dashboard
The esg_
compliance_ flag rate, avg_ humidity_ percent and a breakdown of origin_ country. Excel, Power BI or Tableau. Why do 36 of 54 rows have esg_
compliance_ flag = true? A class exercise
Hand out the rows and one question. Everyone works from the same 54 rows.
- Shipments54SHPMNT-1A2B3C4D73.2trueSHPMNT-4E5F6G7H84.9trueSHPMNT-2N3P4Q5R86.4false
A software demo
Believable shipments with container_
id, product_ type and origin_ country to fill a screen in front of a buyer.
This dataset54 rows23 columns
Yours1,000 rows23 columnsorigin_country: UK only
blueprint · cold-chain-export-monitoring-metrics
Behind this dataset
Same schema. As many rows as you need.
These 54 rows came out of a blueprint — 23 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.
Rules it was built with
- Temperature readings are recorded at each transport stage
- Humidity thresholds must remain within crop-specific safe limits
- Handling events (loading, unloading, transfer) are timestamped and location-tagged
- Alert events trigger if temperature deviates >2°C from set point
- Shipment IDs are unique per export batch
- Spoilage risk score calculated for each shipment
Open the blueprint in Data Factory
1 credit per row. Preview 20 rows free. Buy rows for the full run.
- Exports
- CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
- Licence
- yours to use, including commercially
- API slug
- cold-chain-export-monitoring-metrics