TAURINE · DATA & METHODOLOGY

タウリンの算出根拠Basis of Taurine Estimates

食材ごとの推定値を、40万件以上の食品へ。From ingredient-level estimates to more than 400,000 foods.

IMD食品栄養データベースは、すべての商品・食品について、八訂の食材と分量からなる食材構成情報（レシピ）を持っています。この食材にタウリンの推定値を追加することで、商品・食品ごとのタウリン量を計算し、提供できます。The IMD Food Nutrition Database holds a recipe (ingredient composition) for every product and food, expressed as ingredients of the Standard Tables of Food Composition in Japan (8th revised edition) and their amounts. By adding an estimated taurine content to each ingredient, we can calculate and provide the taurine content of every product and food.

タウリン（2-アミノエタンスルホン酸）は日本食品標準成分表（八訂）の収載成分ではありません。本ページの値は、論文・公的資料の分析値をもとにIMDが推定した参考値です。掲載データの基準日：2026年9月3日（9月23日改訂）／ページ作成：2026年9月6日／改訂：2026年9月23日Taurine (2-aminoethanesulfonic acid) is not a component listed in the Standard Tables of Food Composition in Japan (8th revised edition). The values on this page are reference estimates made by IMD from analytical values reported in papers and public documents. Data as of Sep 3, 2026 (revised Sep 23, 2026) / Page created Sep 6, 2026; revised Sep 23, 2026

データの公開についてOpen data本ページのタウリン統合データ（全2,490項目の食材別推定値と算出根拠）は公開しており、どなたでも閲覧・CSVで保存できます。タウリンのデータのみを有料で販売・提供することはありません。The integrated taurine data on this page (estimates and their basis for all 2,490 ingredients) are published openly; anyone can view them and save them as CSV. We do not sell or provide the taurine data on its own for a fee.

食品別の推定値を見るView estimates by food 算出のしくみを知るHow it is calculated

40万件以上400,000+レシピを持つ商品・食品products and foods with recipes

2,490項目itemsタウリン値を付与した食材ingredients with a taurine value

940項目items採用値が0より大きい食材ingredients with a value above 0

13件sources根拠とした論文・公的資料papers and public documents cited

食材の値と分量から、積み上げるSumming ingredient values and amounts

食品ごとのレシピを共通の食材マスターに結び付け、各食材が持つタウリン量を合計します。食材ごとの値を整備すれば、同じ食材を使う多くの商品・料理へ一貫した計算を適用できます。Each food's recipe is linked to a common ingredient master, and the taurine contributed by each ingredient is summed. Once ingredient values are in place, the same calculation can be applied consistently to every product and dish that uses those ingredients.

既存のレシピと共通の食材マスターを利用する計算のしくみ。掲載2,490項目はIMDの食材マスターの収録範囲（食品番号をもつ2,478項目と、食品番号のない12項目）で、八訂の全収載食品数を示すものではありません。Calculation using existing recipes and a common ingredient master. The 2,490 items are the scope of IMD's ingredient master (2,478 items with a food number and 12 without) and do not represent the total number of foods in the 8th edition tables.

「含有量 × 食べる量」が基本Content × amount eaten

1商品・1食のタウリン推定量（mg）Estimated taurine per product or serving (mg)

Σ ［食材値（mg/100g）× 食材の可食部分量（g）÷ 100］Σ [ingredient value (mg/100 g) × edible amount of the ingredient (g) ÷ 100]

100g当たりで提供する場合は、この合計を出来上がり重量（g）で割り、100を掛けます。For values per 100 g, the sum is divided by the finished weight (g) and multiplied by 100.

食材値と分量の状態を揃えます。「ゆで」項目にはゆで後の分量、「乾燥」項目には乾燥状態の分量を使います。原料重量から調理後を求める場合は、歩留まり・流出・煮汁の扱いを別途考慮し、調理済み食材への二重補正を避けます。The state of the ingredient value and the amount must match: use the boiled weight for a “boiled” item and the dry weight for a “dried” item. When deriving cooked amounts from raw weights, yield, losses and cooking liquid are handled separately so that an already-cooked ingredient is not corrected twice. [07 調理の研究][07 Cooking study]

分量を変えて計算してみるTry changing the amounts

例：まあじ（皮つき、生）129.5 mg/100g と、水稲めし（精白米・うるち米）0 mg/100g。掲載一覧の採用値を使った、加熱工程を含まない2食材の計算例です。Example: Japanese jack mackerel (maaji, skin-on, raw) 129.5 mg/100 g and cooked white rice 0 mg/100 g. A two-ingredient example using adopted values from the list, without a cooking step.

まあじの可食部（g）Jack mackerel, edible (g)

ごはん（g）Cooked rice (g)

2食材の合計Total of the two ingredients
103.6 mg合計230 g ／ 100g当たり 45.043 mg129.5 × 80 ÷ 100 ＋ 0 × 150 ÷ 100

小数第3位までの表示は計算上の桁数で、分析精度を表すものではありません。Values shown to three decimal places reflect calculation, not analytical precision.

食材別の値は、何を根拠にするかWhat the ingredient values are based on

タウリンは八訂に収載されていないため、食材ごとの値は論文・公的資料の分析値を起点に推定しています。推定は性格の異なる2つの方法で独立に行い、両者を統合して採用値としています（統合の規則は03）。Because taurine is not listed in the 8th edition tables, each ingredient value is estimated starting from analytical values in papers and public documents. Two estimation methods of different character are applied independently, and the two are combined into the adopted value (the integration rule is given in 03).

推定法 1METHOD 1

食品別推定Food-level estimate

食品ごとに、魚種・畜種・部位・状態に対応する文献の分析値や代表値を当てはめ、必要に応じて部位・乾燥・缶詰などの補正を加えた値です。食品ごとに推定方法・根拠・想定状態・信頼度を記録しています。For each food, a literature analytical or representative value matching the species, animal, cut and state is applied, with corrections for cut, drying, canning and so on where needed. The method, basis, assumed state and confidence are recorded for each food.

推定法 2METHOD 2

分類別代表値Class-level value

食品名と食品群から23の区分に分類し、区分ごとに1つの代表値を当てはめた値です。個々の部位や状態までは反映しませんが、食品別推定とは独立した基準で値の水準を与えます。Foods are assigned to 23 classes by name and food group, and each class has a single representative value. It does not reflect individual cuts or states, but it sets the level of the value on a basis independent of the food-level estimate.

食品別推定：根拠の優先順位Food-level estimate: order of evidence

同一食品・同一状態の文献分析値Literature values for the same food and state
魚種、畜種、部位、可食部の状態が対応する分析値を優先します。Analytical values matching the species, animal, cut and state of the edible portion take priority.
近縁種・同じ食品群・同じ部位からの類推Inference from related species, the same food group or the same cut
直接の分析値がない項目は、近縁の食品や同じ食品群の代表値から類推します。Items without a direct analytical value are inferred from related foods or from representative values of the same food group.
部位・乾燥・缶詰などの状態を補正Corrections for cut, drying, canning and other states
部位差、乾燥による濃縮、缶詰の液汁への溶出を理論的に補正します。Differences between cuts, concentration by drying and leaching into canning liquid are corrected theoretically.
複合食品は原材料の配合から推定Composite foods estimated from their formulation
肉・魚介・乳・卵など、タウリン源となる原材料の割合から推定します。Estimated from the proportion of taurine-containing ingredients such as meat, seafood, milk and eggs.
主要な含有食品群以外は0相当Zero outside the main taurine-containing groups
穀類・野菜・果実などの植物性食品は、分析報告で不検出〜極微量であることから0相当とします。0は推定モデル上の値で、不検出や絶対ゼロを保証するものではありません。海藻は例外として種類ごとに推定します。Plant foods such as cereals, vegetables and fruits are treated as zero because analyses report taurine as not detected or present only in trace amounts. Zero is a model value and does not guarantee non-detection or absolute absence. Seaweeds are an exception and are estimated by type.

同じ考え方を用いた先行研究A precedent using the same approach

Domotoら（2024）は、日本食品標準成分表2010年版のうち5食品群（藻類・魚介類・肉類・卵類・乳類）の751食品を対象に、文献・既存データ・新規分析と、類似食品からの補完を組み合わせた暫定タウリン表を作成しています。加熱した魚・肉については、定量的な影響が不明なため加熱による変化を考慮していません。Domoto et al. (2024) built a provisional taurine table for 751 foods in five food groups (algae, fish and shellfish, meats, eggs, and milk and milk products) of the Standard Tables of Food Composition in Japan 2010, combining literature, existing data and new analyses with imputation from similar foods. For cooked fish and meat, changes due to cooking were not considered because their quantitative effect is unclear. [01]

197文献・既存データ・新規分析literature, existing data, new analyses

＋+

469類似食品から補完imputed from similar foods

＝=

666食品の暫定値foods with provisional values

この研究は「食品別含有量を整備し、食品の分量から摂取量を推計する」という手法の先例です。本ページの推定値を直接検証した研究ではありません。This study is a precedent for compiling food-level contents and estimating intake from the amounts of foods eaten. It did not directly validate the estimates on this page.

食品名だけでは決まらない変動Variation not captured by the food name

魚の普通肉と血合肉、肉の部位、魚種や季節、乾燥や水さらしで含量は変わります。海藻にも種類による違いがあり、植物性として一律に0とはできません。食品別推定では、食品名に部位（内臓・脂身・皮など）が示される場合、普通肉・赤肉の値をそのまま当てはめず部位補正を加えています。Content differs between ordinary and dark muscle of fish, between cuts of meat, by species and season, and with drying or washing. Seaweeds also differ by type and cannot be set to zero as plant foods. In the food-level estimate, when the food name indicates a part (viscera, fat, skin and so on), the value for ordinary or lean muscle is not applied as is; a correction for that part is added. [04 魚介・組織][04 Seafood tissues] [08 肉・部位][08 Meat cuts] [03 食品分析][03 Food analysis] [13 海藻][13 Seaweed]

状態・加工の扱い（食品別推定）Handling of states and processing (food-level estimate)

対象Target	扱いTreatment	項目数Items
焼き・ゆでなど単純な加熱（状態別の分析値がない場合）Simple cooking such as grilling or boiling (no state-specific analytical value)	定量的な影響が不明なため、原則として補正しないNot corrected in principle, as the quantitative effect is unclear [01]	628
部位の違い（脂身・内臓・皮など）Different parts (fat, viscera, skin and so on)	部位差を理論的に補正Theoretical correction for the part [08]	143
加工品・複合食品Processed and composite foods	原材料の配合・加工状態から理論的に推定Theoretical estimate from formulation and processing [12]	93
乾燥品Dried products	水分の減少による濃縮を1.5倍で近似Concentration by moisture loss approximated as ×1.5	42
缶詰Canned products	液汁への溶出を考慮して0.75倍×0.75 allowing for leaching into the canning liquid [07]	30

項目数は、食品別推定の値が0より大きい936項目の内訳です。倍率は状態ごとの近似で、個々の製品の水分量や工程を測定したものではありません。The counts break down the 936 items whose food-level estimate is above 0. The factors are approximations by state, not measurements of the moisture or processing of individual products.

近縁の食品群・代表値から類推した値など310項目には、推定値全体の水準を推定の設計段階で示された集計値と整合させるための一律の調整係数 0.927 を乗じています。統計上の水準調整であり、調理による保持率など生理的・化学的な意味をもつ係数ではありません。該当項目は一覧とCSVに明記しています。For 310 items, including values inferred from related food groups or representative values, a uniform adjustment factor of 0.927 is applied so that the overall level of the estimates is consistent with the summary values set at the design stage. This is a statistical level adjustment with no physiological or chemical meaning, such as retention during cooking. The affected items are marked in the list and in the CSV.

分類別代表値：23区分Class-level values: 23 classes

食品名と食品群にもとづく区分と、区分ごとの代表値（mg/100g）です。区分は名称にもとづく簡易分類のため、実態を十分に表さない区分が当たる項目があります（例：藻類・菓子類→植物性食品）。そのような項目では2つの推定の差が大きくなることがあり、一覧に注記しています。Classes based on food names and food groups, with the representative value of each class (mg/100 g). Because the classification is a simple name-based one, some items fall into a class that does not fully represent them (e.g., algae and confectionery fall into “plant foods”). Such items can show a large difference between the two estimates and are annotated in the list.

植物性食品Plant foods0mg/100g含まれない、または極微量として0相当Treated as zero: not present or only in trace amounts1,631項目1,631 items
卵類・乳類Eggs and dairy1mg/100g動物性食品として極微量を含むAnimal foods containing trace amounts82項目82 items
動物性油脂Animal fats1mg/100g極微量を含む可能性May contain trace amounts5項目5 items
鶏肉（むね・ささみ）Chicken (breast, tenderloin)20mg/100g鶏肉の中では含量が比較的少ない部位Cuts with relatively low content among chicken7項目7 items
食肉加工品Processed meats25mg/100g原料肉に由来。添加物や水分調整によりやや低いFrom the raw meat; slightly lower due to additives and moisture adjustment26項目26 items
食肉一般Meat (general)30mg/100g畜種を特定しない一般的な食肉General meat without a specified species40項目40 items
牛肉Beef40mg/100g牛肉の代表値Representative value for beef138項目138 items
鶏肉（もも等）Chicken (thigh etc.)40mg/100g鶏のもも肉などの代表値Representative value for thigh and similar cuts28項目28 items
豚肉Pork50mg/100g食肉の中では比較的多いRelatively high among meats65項目65 items
水産練り製品Fish paste products50mg/100g魚肉に由来。水さらし等の工程で減少From fish meat; reduced by washing and other steps11項目11 items
魚介類一般Fish and shellfish (general)80mg/100g一般的な魚介類の平均的な値Average value for fish and shellfish in general263項目263 items
内臓肉Organ meats80mg/100gレバーなど。他の部位より多いLiver and others; higher than other parts6項目6 items
青魚Oily blue-backed fish120mg/100gあじ・いわし・さばなどの青魚Horse mackerel, sardines, mackerel and similar fish59項目59 items
回遊魚の赤身Red meat of migratory fish150mg/100gかつお・まぐろなどの赤身肉。比較的多いSkipjack, tuna and similar; relatively high28項目28 items
えび類Shrimps and prawns200mg/100g甲殻類（えび）Crustaceans (shrimp)12項目12 items
かに類Crabs300mg/100g甲殻類（かに）Crustaceans (crab)1項目1 items
魚介系調味料Seafood-based seasonings300mg/100g原料の魚介類から抽出されたタウリンを含むContain taurine extracted from the seafood ingredients5項目5 items
貝類（あさり・しじみ）Clams (asari, shijimi)600mg/100g日常的に食べる貝類Commonly eaten clams6項目6 items
いか類Squids750mg/100g含量が多い代表的な食材A typical food with high content21項目21 items
貝類（ほたて・はまぐり等）Shellfish (scallop, hamaguri, etc.)1,000mg/100g含量が多い貝類Shellfish with high content10項目10 items
かきOysters1,100mg/100g貝類の中でも含量が多いHigh content even among shellfish4項目4 items
さざえTurban shell (sazae)1,500mg/100g貝類の中でも特に多いParticularly high among shellfish2項目2 items
魚介の干物・乾物Dried seafood2,000mg/100g水分が抜けているため、100g当たりの含量が高いHigh content per 100 g due to moisture loss40項目40 items

食品別推定の推定方法・信頼度の内訳Food-level estimate: breakdown by method and confidence

推定方法（項目数）Method (items)

理論0推定Theoretical zero1,554
同一・近縁食品実測値Measured value, same or related food265
部位補正Part correction143
畜種別代表実測値Representative measured value by animal species136
魚類カテゴリ代表値Fish category representative value78
加工品推定Processed-product estimate70
乾燥補正Drying correction42
褐藻類類推Inferred from brown algae33
缶詰補正Canning correction30
配合推定Formulation estimate23
複合食品配合推定Composite-food formulation estimate22
同一食品群実測値Measured value, same food group20
その他（24種類）Other (24 methods)74

信頼度（項目数）Confidence (items)

高High124
中Medium2,023
低Low343

信頼度は食品別推定の根拠の強さを3段階で示した評価です。高：同一食品・同一部位の分析値など根拠が直接的なもの。中：近縁種・同じ食品群の代表値からの補完や、主要な含有食品群以外の0相当など。低：加工品・複合食品の配合推定など、追加の仮定を要するもの。Confidence is a three-level rating of the strength of the basis of the food-level estimate. High: a direct basis, such as analytical values for the same food or part. Medium: imputation from related species or representative values of the same food group, or zero outside the main taurine-containing groups. Low: requires further assumptions, such as formulation estimates for processed or composite foods.

2つの推定を、同じ規則で統合Combining the two estimates with one rule

食品別推定と分類別代表値は、同じ食材マスターの2,490項目それぞれに対して独立に作成しました。採用値は、全項目に同じ規則を適用して決めています。The food-level estimate and the class-level value were produced independently for each of the 2,490 items of the same ingredient master. The adopted value is determined by applying the same rule to every item.

2つの推定が一致する1,551項目1,551 items where the two estimates agree

同じ値をそのまま採用します。うち1,550項目は、両方の推定が0の食材です。0.0 と 0 のような表記だけの違いは、数値の一致として扱います。The common value is adopted as is. Of these, 1,550 are ingredients for which both estimates are 0. Differences in notation only, such as 0.0 and 0, are treated as equal values.

一致値を採用Agreed value

2つの推定が異なる939項目939 items where the two estimates differ

両者に同じ重みを与えた算術平均を採用します。The equal-weight arithmetic mean of the two is adopted.

採用値＝（食品別推定＋分類別代表値）÷ 2Adopted value = (food-level estimate + class-level value) ÷ 2

内訳：両方が正の値で異なる854項目、食品別推定のみ正の値81項目、分類別代表値のみ正の値4項目。平均は10進数で計算しています。Breakdown: 854 items with two different positive values, 81 where only the food-level estimate is positive, and 4 where only the class-level value is positive. Means are computed in decimal arithmetic.

平均値を採用Mean adopted

等重みの平均を用いる理由Why an equal-weight mean

食品別推定は食品ごとの文献値や補正を反映できる一方、代表値の当てはめや補正の倍率に仮定を含みます。分類別代表値は区分単位の粗い値ですが、食品別推定とは独立した基準です。両者が異なるとき、追加の分析なしにどちらが正しいかを項目ごとに判定する客観的な根拠はありません。そこで、項目ごとの恣意的な選択を避け、全項目に同じ規則を適用できる等重みの算術平均を採用しています。The food-level estimate reflects food-specific literature values and corrections, but it involves assumptions in how representative values and correction factors are applied. The class-level value is coarse, set per class, but it rests on a basis independent of the food-level estimate. When the two differ, there is no objective basis for deciding item by item which is correct without further analysis. To avoid arbitrary item-by-item choices, we adopt the equal-weight arithmetic mean, which applies the same rule to every item.

採用値は必ず2つの推定値の間に入ります。両者の差（推定幅）は、その食材の値の不確かさの目安になります。The adopted value always lies between the two estimates, and the difference between them (the estimate range) serves as an indicator of the uncertainty of that ingredient's value.

平均は統合の規則による値で、測定値の平均や信頼区間ではなく、精度の向上を保証するものでもありません。食品別推定が同一食品の分析値にもとづき、分類別代表値が粗い区分の値である項目（例：はちみつ 0.34 と 0 → 0.17 mg/100g）では、採用値が分析値から離れます。2つの推定値と根拠を一覧・CSVに併記しているため、用途に応じて確認できます。The mean is a value produced by the integration rule. It is neither an average of measurements nor a confidence interval, and it does not guarantee improved accuracy. Where the food-level estimate is based on an analytical value for the same food and the class-level value is a coarse class value (e.g., honey: 0.34 and 0 → 0.17 mg/100 g), the adopted value departs from the analytical value. Both estimates and their basis are listed in the table and in the CSV so they can be checked as needed.

平均値の例：かき／養殖、生Example of a mean: oyster, cultured, raw

食品別推定はかき（養殖、生）の文献実測値・代表値、分類別代表値は「かき」区分の値です。平均値は本ページの統合規則による値で、実測値・信頼区間・精度向上の保証を意味しません。0と正の値の組合せも同じ規則で処理し、片方の値だけを優先することはありません。The food-level estimate is the literature (measured or representative) value for cultured raw oyster; the class-level value is that of the “oysters” class. The mean is a value produced by this page's integration rule and does not imply a measurement, a confidence interval or a guarantee of improved accuracy. Combinations of 0 and a positive value are handled by the same rule, with neither value given priority.

採用値の分布Distribution of adopted values

全2,490項目を採用値で集計。各食品を1項目として数えた分布で、食事中の摂取割合を示すものではありません。All 2,490 items counted by adopted value. Each food counts as one item; the distribution does not indicate shares of dietary intake.

推定の差が大きい項目Items with a large difference between the estimates

2つの推定値の比が5倍以上かつ差が10 mg/100g以上の項目（一方が0の場合は、他方が10 mg/100g以上の項目）を「推定の差が大きい項目」として一覧に注記しています。該当は162項目で、内訳は魚介類79、肉類55、調理加工食品類12、藻類11、調味料及び香辛料類5項目です。Items where the two estimates differ by a factor of 5 or more and by at least 10 mg/100 g (or, when one of them is 0, where the other is at least 10 mg/100 g) are annotated in the list as items with a large difference. There are 162 such items: 79 fish and shellfish, 55 meats, 12 prepared foods, 11 algae, and 5 seasonings and spices.

差が生じる主な理由には、分類別代表値の区分が食品の実態と合わない場合（藻類・菓子類などへの「植物性食品」、名称の一致による区分など）と、食品別推定の代表値が部位や状態の違いを十分に反映しない場合（畜種の代表値を部位の異なる肉に当てはめた場合など）の両方があります。どちらの推定が妥当かは項目ごとに異なるため、採用値は同じ規則で平均しています。Differences arise both when the class does not fit the food (e.g., “plant foods” assigned to algae or confectionery, or classes matched by name) and when the representative value used in the food-level estimate does not sufficiently reflect differences in part or state (e.g., a species-level value applied to a different cut of meat). Which estimate is more appropriate differs by item, so the adopted value is averaged by the same rule.

一覧の信頼度（高・中・低）は食品別推定の根拠に対する評価で、平均値を採用した項目の採用値について改めて評価したものではありません。計算で生じた小数の桁を残しても、測定精度が高くなるわけではありません。The confidence shown in the list (high, medium, low) rates the basis of the food-level estimate; it has not been re-evaluated for adopted means. Retaining decimal places from the calculation does not make the values more precise.

食品別の推定値と根拠Estimates and basis by food

単位はすべて可食部100g当たりのタウリン量（mg）です。生・ゆで・乾燥などの状態は各食品名に対応します。採用値と、その元になった2つの推定値・推定根拠を、一覧とCSVで確認できます。All values are taurine in mg per 100 g of edible portion. States such as raw, boiled or dried correspond to each food name. The adopted value, the two underlying estimates and their basis can be checked in the list and in the CSV.

Food names and categories are shown in Japanese as recorded in the IMD ingredient master. Each item can be identified by its five-digit food number in the Standard Tables of Food Composition in Japan (8th revised edition).

公開データOpen dataこの一覧は公開データで、全2,490項目をCSVで保存できます。タウリンのデータのみを有料で販売・提供することはありません。This list is open data; all 2,490 items can be saved as CSV. We do not sell or provide the taurine data on its own for a fee.

検索・一覧の表示・CSVでの保存・計算例の操作にはJavaScriptを有効にしてください。全2,490項目のデータはこのHTML内に保存されています。Enable JavaScript to search, display the list, save CSV files and use the calculation example. The data for all 2,490 items are stored in this HTML file.

全2,490項目

表は左右・上下にスクロールできます。「推定の詳細」を開くと、想定状態・状態の扱い・信頼度などを確認できます。The table scrolls horizontally and vertically. Open “Estimate details” to see the assumed state, handling of state, confidence and more.

タウリン推定量一覧（mg/100g）Taurine estimates (mg/100 g)
食品名・識別情報Food and identifiers	採用値Adopted value一覧・CSVで共通same in list and CSV	食品別推定Food-level estimate文献値にもとづくfrom literature	分類別代表値Class-level value23区分の代表値value of 23 classes	推定根拠Basis食品別推定の根拠と分類区分food-level basis and class

全件CSVは標準の順序で、絞り込みCSVは現在の検索・食品群・採用区分・並び順を反映した全該当項目を出力します。ページの表示件数には制限されません。食品番号は5桁で出力します（例：01001）。CSVの見出しと語句は表示中の言語で出力します。The full CSV is in the standard order; the filtered CSV contains all matching items, reflecting the current search, food group, status and sort order, regardless of rows per page. Food numbers are output as five digits (e.g., 01001). CSV headings and terms follow the language currently displayed; food names and categories remain in Japanese.

推定の根拠とした論文・公的資料Papers and public documents used as evidence

食品別推定の根拠とした論文・公的資料です。出版社・学会・公的機関の原典にリンクしています。これらは推定方法と食品群ごとの値の水準を支える資料であり、個々の採用値をすべて実測・検証したものではありません。文献の探索・整理にはAIによる調査支援を併用しており、書誌情報は出版社・学会・公的機関の公開情報にもとづいて記載しています。These papers and public documents are the evidence for the food-level estimates, linked to the original sources of publishers, academic societies and public bodies. They support the estimation methods and the levels of values by food group; they do not measure or validate every adopted value. AI-assisted research support was used to search and organize the literature, and bibliographic information follows the information published by the publishers, societies and public bodies.

01 · 暫定タウリン表の構築方法01 · Building a provisional taurine table

Association of taurine intake with changes in physical fitness among community-dwelling middle-aged and older Japanese adults: an 8-year longitudinal study ↗

Domoto T. ほか（大正製薬・国立長寿医療研究センターほか）Domoto T, et al. (Taisho Pharmaceutical; National Center for Geriatrics and Gerontology; and others)

2024 · Frontiers in Nutrition 11:1337738 ／発行：Frontiers2024 · Frontiers in Nutrition 11:1337738 / Publisher: Frontiers

DOI: 10.3389/fnut.2024.1337738

食品別の暫定タウリン表を作成し、食品の摂取量からタウリン摂取量を推計した先行研究。類似食品からの補完や、加熱した魚・肉に加熱による変化を考慮しない扱いは本推定と共通。表の構築方法は本文2.2、食品別データはSupplementary Table S1に記載。A preceding study that built a food-level provisional taurine table and estimated taurine intake from food consumption. Imputation from similar foods and not adjusting cooked fish and meat for cooking are shared with this estimation. The table construction is described in Section 2.2 and the food-level data in Supplementary Table S1.

02 · 食品を同定する公的基準02 · Official reference for identifying foods

日本食品標準成分表（八訂）増補2023年Standard Tables of Food Composition in Japan 2020 (Eighth Revised Edition), Supplement 2023 (in Japanese) ↗

文部科学省Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan

2023 · 公表：文部科学省2023 · Published by MEXT

食品番号、食品名、可食部、加工・調理状態の基準。タウリンは収載成分ではないため値の出典ではなく、本ページでは別途推定値を付与。Reference for food numbers, food names, edible portions and processing and cooking states. Taurine is not a listed component, so the tables are not a source of values; this page assigns separate estimates.

03 · 日本の食品中タウリン分析03 · Taurine analysis of Japanese foods

吸着・分配カラムを用いた高速液体クロマトグラフィーによる食品中タウリンの定量法Determination of Taurine in Foods Using an Adsorption-Distribution HPLC (in Japanese) ↗

大山秀夫・久保眞清・榎本俊樹（上越教育大学）Hideo Ohyama, Makiyo Kubo, Toshiki Enomoto (Joetsu University of Education)

1991 · 日本栄養・食糧学会誌 44(4):305–308 ／発行：日本栄養・食糧学会1991 · Nippon Eiyo Shokuryo Gakkaishi 44(4):305–308 / Publisher: Japanese Society of Nutrition and Food Science

DOI: 10.4327/jsnfs.44.305

HPLCによる食品中タウリンの定量法と各種食品の分析。食品種による差や、海藻を一律に0としない判断を支える主要な一次資料。An HPLC method for taurine in foods and analyses of various foods. A key primary source for differences between food types and for not setting seaweed uniformly to zero.

04 · 魚種・組織による違い04 · Differences by species and tissue

魚介類のタウリン含量Taurine content in fish and shells (in Japanese) ↗

小沢昭夫・青木滋・鈴木香都子・杉本昌明・藤田孝夫・辻啓介（日本水産中央研究所・国立栄養研究所）Akio Ozawa, Shigeru Aoki, Katsuko Suzuki, Masaaki Sugimoto, Takao Fujita, Keisuke Tsuji (Nippon Suisan Central Research Laboratory; National Institute of Nutrition)

1984 · 日本栄養・食糧学会誌 37(6):561–567 ／発行：日本栄養・食糧学会1984 · Nippon Eiyo Shokuryo Gakkaishi 37(6):561–567 / Publisher: Japanese Society of Nutrition and Food Science

DOI: 10.4327/jsnfs.37.561

魚種や、普通肉・血合肉・臓器などの組織によるタウリン含量の違いを示す研究。魚介類の代表値と、部位を区別して扱う根拠。Domotoらの参考文献17にも収録。Shows differences in taurine content by fish species and by tissue, such as ordinary muscle, dark muscle and organs. A basis for representative seafood values and for treating parts separately. Also reference 17 in Domoto et al.

05 · 食肉・魚介の既存分析資料05 · Existing analytical data for meat and seafood

飼料添加物評価書タウリン及び飼料添加物として使用されるタウリンの食品健康影響評価について[Risk assessment report on feed additives: taurine, and food health impact assessment of taurine used as a feed additive] (in Japanese) ↗

食品安全委員会Food Safety Commission of Japan

2008年6月 · 公表：内閣府食品安全委員会June 2008 · Published by the Food Safety Commission of Japan, Cabinet Office

本文「8. その他の知見」の表7〜10に食肉・魚介の分析値を収録。食肉・魚介の代表値の参照資料。湿重量当たりのmg/gは100倍してmg/100gに換算。Analytical values for meat and seafood are compiled in Tables 7–10 of section 8 (“Other findings”). A reference for representative values of meat and seafood; values in mg/g wet weight are multiplied by 100 to give mg/100 g.

06 · 肉・乳・植物性食品の分析06 · Analyses of meat, dairy and plant foods

The taurine content of common foodstuffs ↗

Laidlaw S. A. ほか（Harbor-UCLA Medical Center）Laidlaw SA, et al. (Harbor-UCLA Medical Center)

1990 · JPEN 14(2):183–188 ／掲載誌発行元：ASPEN1990 · JPEN 14(2):183–188 / Journal publisher: ASPEN

DOI: 10.1177/0148607190014002183

肉・乳製品などでのタウリン検出と、調査した植物性食品での非検出を報告。植物性食品を0相当とする根拠の一つ。すべての植物・加工品について絶対ゼロを証明するものではない。Reports taurine in meat, dairy products and other foods and none detected in the plant foods examined. One basis for treating plant foods as zero; not proof of absolute absence in all plants and processed foods.

07 · 調理と流出の影響07 · Effects of cooking and leaching

Taurine concentrations in animal feed ingredients; cooking influences taurine content ↗

Spitze A. R. ほか（University of California, Davis）Spitze AR, et al. (University of California, Davis)

2003 · Journal of Animal Physiology and Animal Nutrition 87(7–8):251–262 ／出版：Wiley2003 · Journal of Animal Physiology and Animal Nutrition 87(7–8):251–262 / Publisher: Wiley

DOI: 10.1046/j.1439-0396.2003.00434.x

水に接する調理などによるタウリンの損失を検討（PMID:12864905）。缶詰の液汁への溶出や、原料の値から調理後を考える際の参考。特定の保持率を全食品に一律適用する根拠ではない。Examines taurine losses in cooking methods involving water (PMID: 12864905). A reference for leaching into canning liquid and for deriving cooked values from raw values; not a basis for applying a single retention factor to all foods.

08 · 肉の部位差・加熱変化08 · Differences between cuts and changes on heating

Concentrations in beef and lamb of taurine, carnosine, coenzyme Q(10), and creatine ↗

Purchas R. W. ほか（Massey University）Purchas RW, et al. (Massey University)

2004 · Meat Science 66(3):629–637 ／出版：Elsevier2004 · Meat Science 66(3):629–637 / Publisher: Elsevier

DOI: 10.1016/S0309-1740(03)00181-5

牛・羊の筋肉部位間の違いと加熱時の変化を分析。畜種だけでなく部位を区別して補正する理由となる。Analyses differences between muscles of beef and lamb and changes on cooking. A reason to correct for the cut as well as the species.

09 · 肉の加熱条件09 · Cooking conditions for meat

Cooking temperature effects on the forms of iron and levels of several other compounds in beef semitendinosus muscle ↗

Purchas R. W. ほか（Massey University）Purchas RW, et al. (Massey University)

2004 · Meat Science 68(2):201–207 ／出版：Elsevier2004 · Meat Science 68(2):201–207 / Publisher: Elsevier

DOI: 10.1016/j.meatsci.2004.02.018

加熱温度と牛肉中タウリン等の変化を調査。原料の値から調理後を考える際の参考資料。Examines cooking temperature and changes in taurine and other compounds in beef. A reference when deriving cooked values from raw values.

10 · 食品群別の含量分析10 · Content by food group

Taurine content in Chinese food and daily intake of Chinese men ↗

Zhao X. ほか（Chinese Academy of Preventive Medicine）Zhao X, et al. (Chinese Academy of Preventive Medicine)

1998 · Advances in Experimental Medicine and Biology 442:501–505 ／出版：Springer（Plenum Press）1998 · Advances in Experimental Medicine and Biology 442:501–505 / Publisher: Springer (Plenum Press)

DOI: 10.1007/978-1-4899-0117-0_60

中国の食品中タウリン量を調査し、魚介・食肉の含量範囲と、植物性食品・鶏卵での非検出を報告。日本の各食品項目の直接測定値ではない。Surveys taurine in Chinese foods, reporting ranges for seafood and meat and no detection in plant foods and hen's eggs. Not direct measurements of the Japanese food items.

11 · 魚の季節変動11 · Seasonal variation in fish

浜田産カレイの体成分の季節変動The characteristics and seasonal changes of the body constituents of flounder landed at Hamada fishing port (in Japanese) ↗

秋廣高志・古田賢次郎・小酒由佳・大島朗伸・岡本満・井岡久（島根大学・島根県水産技術センター）Takashi Akihiro, Kenjiro Furuta, Yuka Kosake, Akinobu Ohshima, Mitsuru Okamoto, Hisashi Ioka (Shimane University; Shimane Prefectural Fisheries Technology Center)

2018 · 日本水産学会誌 84(5):809–817 ／発行：日本水産学会2018 · Nippon Suisan Gakkaishi 84(5):809–817 / Publisher: Japanese Society of Fisheries Science

DOI: 10.2331/suisan.17-00079

3種のカレイのタウリン含量などの季節変動を分析。同じ魚種でも季節により値が変わることを示す資料。Analyses seasonal changes in taurine and other constituents in three flounder species, showing that values vary by season even within a species.

12 · 水産物の加工による変化12 · Changes with seafood processing

Impact of processing on the taurine content in processed seafood and their corresponding unprocessed raw materials ↗

Dragnes B. T. ほかDragnes BT, et al.

2009 · International Journal of Food Sciences and Nutrition 60(2):143–152 ／出版：Taylor & Francis2009 · International Journal of Food Sciences and Nutrition 60(2):143–152 / Publisher: Taylor & Francis

DOI: 10.1080/09637480701621654

加工水産物とその原料のタウリン含量を比較し、加工による変化を検討。練り製品・缶詰など加工水産物の扱いの参考。書誌情報は出版社の登録情報で確認。Domotoらの参考文献19にも収録。Compares taurine in processed seafood with the corresponding raw materials and examines changes with processing. A reference for processed seafood such as fish paste and canned products. Bibliographic data checked against the publisher's record. Also reference 19 in Domoto et al.

13 · 海藻の種類と加工による違い13 · Differences by seaweed type and processing

海藻および海藻加工製品のタウリン含量の分析[Analysis of the taurine content of seaweeds and processed seaweed products] (in Japanese) ↗

川﨑安都紗ほか（福井県立大学・大脇萬蔵商店）Kawasaki, et al. (Fukui Prefectural University; Owaki Manzo Shoten)

2017 · タウリンリサーチ 3(1):24–26 ／発行：国際タウリン研究会2017 · Taurine Research 3(1):24–26 (in Japanese)

DOI: 10.32172/taurine.3.1_24

海藻37種と加工製品を分析し、種類や加工による差を報告。海藻を一律に0としない判断を支える資料。Domotoらの参考文献21。Analyses 37 seaweed species and processed products, reporting differences by type and processing. Supports not setting seaweed uniformly to zero. Reference 21 in Domoto et al.

食品成分表に関する補足資料と、原典を特定していない値Supplementary references on the food composition tables, and values without an identified original source

食品成分表の基準や食品番号の体系については、次の資料も参照しています。The following were also consulted for the conventions of the food composition tables and the food numbering system (all in Japanese).

文部科学省・食品成分データベース「アマランサス／玄穀」MEXT Food Composition Database: “Amaranth, whole grain”：可食部100gと食品番号の表示例。: an example showing the edible portion (100 g) and the food number.
農林水産省・令和5年度食育白書「日本食品標準成分表」の充実、活用促進MAFF, FY2023 White Paper on Shokuiku: enhancing and promoting the use of the Standard Tables of Food Composition in Japan：成分表全体についての公的な説明。: an official explanation of the tables as a whole.
富士産業 Nutrans「日本食品標準成分表」の縦と横Fuji Sangyo Nutrans: a column on the structure of the Standard Tables of Food Composition in Japan：食品番号の体系についての一般向け解説（企業コラム）。タウリンの一次分析資料ではありません。: a general explanation of the food numbering system (corporate column); not a primary source on taurine.

卵・乳・蜂蜜などの一部の代表値（例：鶏卵黄1.26、普通牛乳0.58、ヨーグルト0.51、チーズ0.12、蜂蜜0.34 mg/100g）は、既報の分析値として食品別推定に用いていますが、原著論文の表との対応を特定できていません。一覧の根拠欄にある「実測値」は、推定に用いた値の区分を示すもので、本ページで原著の表まで照合したことを意味しません。Some representative values for eggs, dairy and honey (e.g., hen's egg yolk 1.26, ordinary cow's milk 0.58, yogurt 0.51, cheese 0.12 and honey 0.34 mg/100 g) are used in the food-level estimate as previously reported analytical values, but their correspondence to tables in the original papers has not been identified. “Measured value” in the basis column indicates the type of value used; it does not mean that this page has checked it against the original tables.

データの解釈と限界Interpretation and limitations

位置づけ：タウリンは八訂の収載成分ではなく、本データは文献の分析値と推定規則にもとづく推定参考値です。公定値ではなく、個別製品の実測値や分析証明を表すものでもありません。商品表示・規格保証・臨床判断など分析値が必要な用途では、個別の実測値を用いてください。Status: Taurine is not a listed component of the 8th edition tables; these data are reference estimates based on literature analytical values and estimation rules. They are not official values and do not represent measurements or analytical certificates for individual products. For uses that require analytical values, such as labelling, specification guarantees or clinical decisions, use measurements of the individual product.
0の意味：0は推定モデル上の0相当で、不検出や絶対ゼロを保証するものではありません。Meaning of 0: 0 is a model value (treated as zero) and does not guarantee non-detection or absolute absence.
変動：魚種・部位・季節・産地・養殖条件、調理・加工条件により、実際の含量は変動します。レシピの食材構成や分量の推定誤差も、商品・食品ごとの値に影響します。Variation: Actual content varies with species, part, season, origin, farming conditions, and cooking and processing. Estimation errors in recipe composition and amounts also affect the values for each product and food.
文献と各項目の対応：全2,490項目と論文の表・分析条件を1対1で対応付けた出典表はありません。一覧の根拠欄は推定方法と用いた代表値の種類を示すもので、各項目の直接の出典（論文の表番号など）は特定していないため、食品別の出典番号は付与していません。Links between literature and items: There is no source table linking all 2,490 items one-to-one to tables and analytical conditions in papers. The basis column shows the estimation method and the type of representative value used; the direct source of each item (such as a table number in a paper) is not identified, so no item-level reference numbers are assigned.
対応付け：食品別推定・分類別代表値とも、食品名と食品群にもとづいて代表値を対応付けているため、名称の類似による不適切な対応付けが残っている可能性があります。お気づきの点はお問い合わせください。Matching: Both the food-level estimate and the class-level value assign representative values based on food names and food groups, so inappropriate matches caused by similar names may remain. Please contact us if you notice any.
統合の規則：平均値は2つの推定を統合する規則による値で、測定値の平均や信頼区間ではありません。Integration rule: A mean is a value produced by the rule that combines the two estimates; it is neither an average of measurements nor a confidence interval.
数値の桁：小数点以下の桁は計算上の桁数で、分析精度を表すものではありません。Decimal places: Decimal places reflect calculation, not analytical precision.
食品番号：食品番号のない12項目は、名称・カテゴリ・状態から対応する食品を判断して推定しています。新たな食品番号は付与していません。Food numbers: The 12 items without a food number were estimated by identifying the corresponding food from the name, category and state. No new food numbers have been assigned.
見直し：新たな分析値や文献が得られた場合は食材値を見直し、レシピを通じて商品・食品の値に反映します。Revision: When new analytical values or literature become available, ingredient values are reviewed and reflected in product and food values through the recipes.
利用上の注意：弊社食品データは、その性格上、医療・治療など人命に直接関わる用途には利用できません。Use: Owing to their nature, IMD food data cannot be used for purposes directly related to human life, such as medical care or treatment.
保存：食品データ・図・計算式・推定根拠・書誌情報はすべてこのHTMLに収録しており、外部のデータを読み込む処理はありません。外部リンクは原典を閲覧するためのものです。Storage: All food data, figures, formulas, basis information and bibliographic information are contained in this HTML file, and no external data are loaded. External links are for viewing the original sources.
公開：本ページのタウリン統合データは公開データです。タウリンのデータのみを有料で販売・提供することはありません。Openness: The integrated taurine data on this page are open data. We do not sell or provide the taurine data on its own for a fee.