Jerusalem artichoke is a knobbly tuber unrelated to globe artichoke, rich in the prebiotic fibre inulin, potassium, iron, and thiamin. The inulin can cause wind in people not used to eating it.
Boil briefly with the skin on to retain potassium and iron; introduce gradually to allow gut tolerance.
Where Artichoke, Jerusalem, boiled in unsalted water, flesh only Stands Out
Macronutrients per 100g
Vitamins & Minerals
| Nutrient | Per 100g | % Daily Value* | Level |
|---|---|---|---|
| Potassium | 420 mg | 21% | |
| Chloride | 58.0 mg | 7% | |
| Phosphorus | 33.0 mg | 5% | |
| Calcium | 30.0 mg | 4% | |
| Magnesium | 11.0 mg | 3% | |
| Vitamin A (RE) | 3.00 µg | 0% | |
| Vitamin C | 2.00 mg | 3% | |
| Niacin equivalents (NE) | 1.30 mg | 8% | |
| Niacin (B3) | 0.900 mg | 6% | |
| Iron | 0.400 mg | 3% | |
| Vitamin E (alpha-TE) | 0.200 mg | 2% | |
| Copper | 0.120 mg | 12% | |
| Zinc | 0.100 mg | 1% | |
| Thiamin (B1) | 0.100 mg | 9% | |
| Vitamin B12 | 0.000 µg | 0% | |
| Riboflavin (B2) | 0.000 mg | 0% | |
| Vitamin D | 0.000 µg | 0% | |
| Sucrose | 1.30 g | — | |
| Fructose | 0.200 g | — | |
| Glucose (dextrose) | 0.100 g | — | |
| Maltose | 0.000 g | — | |
| Cholesterol | 0.000 mg | — | |
| Beta-carotene | 20.0 µg | — | |
| Retinol (vitamin A) | 0.000 µg | 0% |
* % Daily Value is the proportion of an adult
EU Nutrient Reference Value (NRV) supplied by 100g of this food.
NRVs are the labelling standard — the same basis as the “%RI” figures printed on
food packaging — so these percentages are directly comparable with a shop label.
They are a single adult figure and do not vary by age or sex, which is why they
sometimes differ from UK dietary reference values: the NRV for vitamin C is 80mg
where the UK RNI is 40mg. When Nutriofia assesses your own intake in the
reports and trackers, it uses the age- and sex-specific UK values instead.
Fibre is shown without a percentage. Our fibre values use the UK
Englyst NSP method, while the published 30g daily goal is an AOAC figure — the two
are measured differently and a single percentage would mislead.
How we source and normalise our data →