🔔 USDA FDC Calorie Conversion Factors

Delivers the published USDA FoodData Central calorie conversion factors — one calorie_factor_record per row of the food_calorie_conversion_factor.csv member of the official FoodData Central full-CSV release. Each record carries the source-native food_nutrient_conversion_factor_id and the three Atwater-style factors (protein_value, fat_value, carbohydrate_value) in kcal per gram, verbatim — plus the source food's fdc_id, attached from the small food_nutrient_conversion_factor.csv dimension so each factor stays tied to the specific food it was published for.

Output is one calorie_factor_record row per result; billing is pay-per-event, the value event being one calorie conversion factor record (a $0.02 start fee per run, then $0.02 per calorie conversion factor record). Source: fdc.nal.usda.gov.

No login, no API key and no CAPTCHA solving are involved: the source is read logged-out with an identified contact User-Agent.

📊 Sample Output

Real rows from run ittKzs7eOPjlzOktE on build 0.1.5 (2026-09-19), the same input as the Quick start below — every value is as the source published it (emails masked, long text shortened):

food_nutrient_conversion_factor_id	protein_value	fat_value	carbohydrate_value	release_date	release_checksum
22721	4.27	9.02	3.87	2026-04-30	6a860e3e-1cb35fb7

The run finished with the status message: NORMAL: 1 unique rows (0 duplicates collapsed) from 2026-04-30. billable=1

✅ What you get

Each row is flat JSON with these fields (from the dataset schema and the sample run; a field the source does not publish for a given row is null):

• record_type (string/null) — e.g. calorie_factor_record
• food_nutrient_conversion_factor_id (string/null) — e.g. 22721
• protein_value (string/null) — e.g. 4.27
• fat_value (string/null) — e.g. 9.02
• carbohydrate_value (string/null) — e.g. 3.87
• fdc_id (string/null) — e.g. 746952
• context_note (string/null) — e.g. published USDA Atwater-style calorie conversion factors (kcal per gram) that app
• source_url (string/null) — e.g. https://fdc.nal.usda.gov/food-details/746952/nutrients
• source (string/null) — e.g. fdc-calorie-conversion-factors
• release_date (string/null) — e.g. 2026-04-30
• observed_at (string/null) — e.g. 2026-09-19T02:19:35Z
• release_checksum (string/null) — e.g. 6a860e3e-1cb35fb7
• license (string/null) — e.g. USDA FoodData Central — CC0 1.0 (public domain dedication). Cite: U.S. Departmen
• attribution (string/null) — e.g. USDA Agricultural Research Service — FoodData Central (https://fdc.nal.usda.gov)
• terminal (string/null) — null in every sample row
• scope (string/null) — null in every sample row
• note (string/null) — null in every sample row
• reported_total (string/integer/null) — null in every sample row
• raw_seen (string/integer/null) — null in every sample row
• duplicates (string/integer/null) — null in every sample row
• unique_found (string/integer/null) — null in every sample row
• delivered (string/integer/null) — null in every sample row

✅ What you get

• record_type (string/null) — e.g. calorie_factor_record
• food_nutrient_conversion_factor_id (string/null) — e.g. 22721
• protein_value (string/null) — e.g. 4.27
• fat_value (string/null) — e.g. 9.02
• carbohydrate_value (string/null) — e.g. 3.87
• fdc_id (string/null) — e.g. 746952
• context_note (string/null) — e.g. published USDA Atwater-style calorie conversion factors (kcal per gram) that app
• source_url (string/null) — e.g. https://fdc.nal.usda.gov/food-details/746952/nutrients
• source (string/null) — e.g. fdc-calorie-conversion-factors
• release_date (string/null) — e.g. 2026-04-30
• observed_at (string/null) — e.g. 2026-09-19T01:40:54Z
• release_checksum (string/null) — e.g. 6a860d85-1cb35fb7
• license (string/null) — e.g. USDA FoodData Central — CC0 1.0 (public domain dedication). Cite: U.S. Departmen
• attribution (string/null) — e.g. USDA Agricultural Research Service — FoodData Central (https://fdc.nal.usda.gov)
• terminal (string/null) — null in every sample row
• scope (string/null) — null in every sample row
• note (string/null) — null in every sample row
• reported_total (string/integer/null) — null in every sample row
• raw_seen (string/integer/null) — null in every sample row
• duplicates (string/integer/null) — null in every sample row
• unique_found (string/integer/null) — null in every sample row
• delivered (string/integer/null) — null in every sample row

Output

One record per unique food_nutrient_conversion_factor_id: food_nutrient_conversion_factor_id, protein_value, fat_value, carbohydrate_value (all verbatim), fdc_id (source food), context_note, source_url. Values are carried as strings exactly as published; a schema canary refuses to bill if the source header drifts.

⚙️ Sample inputs

1. Quick start — the Store example (this is what the sample above came from)

{
  "factorIds": [
    "22721"
  ],
  "maxRecords": 10,
  "maxScanRows": 20000
}

The sample run charged exactly: 1 × $0.02 apify-actor-start + 1 × $0.02 calorie_factor_record = $0.04 on the Free tier — every delivered row was billed.

2. A smaller, narrowed run

{
  "factorIds": [
    "22721"
  ],
  "maxRecords": 5,
  "maxScanRows": 20000
}

Caps the run at 5 rows — about $0.12 on the Free tier ($0.02 start + 5 × $0.02).

3. A full-size run

{
  "factorIds": [
    "22721"
  ],
  "maxRecords": 2500,
  "maxScanRows": 20000
}

Up to 2500 rows (the schema default for maxRecords) — about $50.02 on the Free tier ($0.02 start + 2500 × $0.02) if the source has that many.

🧾 JSON sample record

One real record from run ittKzs7eOPjlzOktE, exactly as it lands in the dataset (emails masked, long text shortened):

{
  "record_type": "calorie_factor_record",
  "food_nutrient_conversion_factor_id": "22721",
  "protein_value": "4.27",
  "fat_value": "9.02",
  "carbohydrate_value": "3.87",
  "fdc_id": "746952",
  "context_note": "published USDA Atwater-style calorie conversion factors (kcal per gram) that apply ONLY within their source food's context; no calorie calculation is performed by this actor",
  "source_url": "https://fdc.nal.usda.gov/food-details/746952/nutrients",
  "source": "fdc-calorie-conversion-factors",
  "release_date": "2026-04-30",
  "observed_at": "2026-09-19T02:19:35Z",
  "release_checksum": "6a860e3e-1cb35fb7",
  "license": "USDA FoodData Central — CC0 1.0 (public domain dedication). Cite: U.S. Department of Agriculture, Agricultural Research Service, FoodData Central.",
  "attribution": "USDA Agricultural Research Service — FoodData Central (https://fdc.nal.usda.gov)"
}

🔧 How it works

Source. The actor reads fdc.nal.usda.gov — endpoints: https://fdc.nal.usda.gov, https://fdc.nal.usda.gov/fdc-datasets/FoodData_Central_csv_. Public pages and feeds only; nothing behind a login.

Transport. Plain HTTPS from the Apify platform, no proxy. robots.txt is read first and a disallowed path is never fetched. Every request carries an identified contact User-Agent. Pacing: CRAWL_DELAY=0.0.

Terminal states. A run ends NORMAL, CAPPED (your cap was reached), PARTIAL (something was withheld and the message says what), GENUINE_EMPTY (the source was read and truly had nothing in scope) or BLOCKED (the source refused or changed shape — the run FAILS loud and bills nothing). A zero-row run is never reported as a silent success.

Charging. Each calorie conversion factor record is charged at the moment it is pushed (calorie_factor_record); a row that fails to charge is not delivered, so the dataset count always equals the charged count.

🔧 How it works

What this actor is — and is NOT

It is a faithful mirror of factors USDA already published. The values are copied exactly as they appear in the release; nothing is computed, rounded, or re-derived.

It is NOT a calorie calculator. This actor performs no calorie calculation, produces no diet product, and makes no claim that a food's factors apply outside their source context. Atwater-style factors are food-specific: the factors published for one food are valid only for that food. A context_note on every record states this in plain language. No health claim of any kind is made.

The door

The only source is the official FoodData Central full-CSV dump — https://fdc.nal.usda.gov/fdc-datasets/FoodData_Central_csv_<date>.zip. The 481 MB archive is never materialized: the actor reads the ZIP central directory over HTTP Range requests and streams only the two members it needs (food_calorie_conversion_factor.csv and the small food_nutrient_conversion_factor.csv dimension). The keyed FoodData Central API is never called — there is no api_key, apiKey, or DEMO_KEY anywhere in this actor.

Licence & attribution

USDA FoodData Central is released into the public domain under CC0 1.0. Cite: U.S. Department of Agriculture, Agricultural Research Service. FoodData Central. https://fdc.nal.usda.gov.

What is not done. No login, no cookie or CAPTCHA bypass, no private or personal-account data, no browser automation.

💰 Pricing example

Event	Free	Bronze	Silver	Gold
Actor Start (apify-actor-start)	$0.02	$0.02	$0.02	$0.02
Calorie conversion factor record (calorie_factor_record)	$0.02	$0.018	$0.016	$0.0134

Worked at the live Free-tier price:

• 1 calorie conversion factor records: $0.02 start + 1 × $0.02 = $0.04
• 25 calorie conversion factor records: $0.02 start + 25 × $0.02 = $0.52
• 2500 calorie conversion factor records: $0.02 start + 2500 × $0.02 = $50.02

A run that delivers zero rows charges the $0.02 start fee only. A BLOCKED run (source refused) fails loud and charges no value event. The start fee is charged once per GB of run memory; the default run memory is 4096 MB.

Yield on the sample run: NORMAL: 1 unique rows (0 duplicates collapsed) from 2026-04-30. billable=1. maxRecords is a hard ceiling on what is delivered and billed, never a target.

⚖️ Legal & ToS

This actor reads public, logged-out pages and feeds published by fdc.nal.usda.gov. It collects only what the source publishes to any visitor, keeps to the source's robots rules (checked on every run), identifies itself with a contact User-Agent, and does not access accounts, private data or anything behind authentication. Use the output in line with the source's terms and your local law; the intended use is B2B research and monitoring.

❓ FAQ

Q: Do I need an API key or a login?
A: No. The source (fdc.nal.usda.gov) is read logged-out; the input schema has no key field and the actor carries no secrets.

Q: Why did my run return 0 rows?
A: Read the run's status message. GENUINE_EMPTY means the source was read and had nothing in scope for your input; BLOCKED means the source refused and the run failed without billing a value event — retry later or narrow the input. A zero-row run bills the start fee only.

Q: How many rows can one run return?
A: Up to maxRecords (default 2500). Raise the cap for a bigger run; you pay per delivered row.

Q: How fresh is the data?
A: Every run reads the source live at run time; nothing is cached between runs. Put it on a schedule for a continuous feed.

Q: What formats can I export?
A: The dataset downloads as JSON, CSV, Excel, XML or RSS from the run's Dataset tab or the Apify API, and any run can push to a webhook or integration.

Q: How is this different from the other NexGen Watch actors actors?
A: Same output shape and billing model; this one covers fdc.nal.usda.gov. The siblings under Related Actors cover the other sources or slices — run several on one schedule for a combined feed.

Q: Are there rate limits?
A: The actor paces itself against the source (CRAWL_DELAY=0.0) and honours its robots rules; there is no per-buyer limit beyond your Apify plan's concurrency.

🆘 Troubleshooting

• Run FAILED with BLOCKED → the source refused the request or changed its page shape → nothing was billed beyond the start fee; retry after a while, and if it persists open an Issue with the run id.
• Status says CAPPED → your cap (maxRecords) was reached → raise it for a bigger run.
• Input validation error on start → a field is outside the schema's allowed values → start from the Quick start block and change one field at a time.
• Run TIMED-OUT → a very wide request on a slow day → raise the run timeout in Run options or narrow the input; what was delivered before the timeout is still in the dataset.

🔗 Related Actors

• EU Transparency Register Organisations — One structured organisation_record per interest representative in the EU Transparency Register — from the official current full XML export, keyless a…
• Euronext Oslo Regulated News — One record per regulated Euronext Oslo announcement — issuer, title, category, topic, timestamp, official archive link. Disclosure facts only; the an…
• USDA FDC Analytical Sub-Sample Results — Structured laboratory sub-sample measurement records from USDA FoodData Central, read directly from the official FDC full-CSV data dump (sub_sample_r…
• USDA FDC Sample Provenance Graph — The provenance / traceability graph behind USDA FoodData Central foods — how a sample food links to its sub-samples and to the market acquisition it…
• USDA FNDDS Recipe Ingredient Composition — Structured recipe composition records from USDA FoodData Central — which input foods compose each survey (FNDDS) or recipe (SR-legacy) food — read di…
• USDA FNDDS Survey Food Master — Structured FNDDS (What We Eat In America) survey food master records from USDA FoodData Central, read directly from the official FDC full-CSV dump (s…
• 🏢 About NexGenData — NexGen Watch is NexGenData's fleet of more than 300 public data actors built on official sources, pay-per-result. Browse the catalog at apify.com/nexgenwatch.

⭐ Found this useful?

If this actor saved you a manual check, a quick review on the Apify Store helps other teams find it. Feature request or a source that changed? Open it from the Issues tab — every one is read.