Use of canonical variate analysis biplot in examination of choline content data of some foods

Adequate intake (AI) of choline as part of the daily diet can help prevent major diseases. Low choline intake is a major risk factor for liver and several neurological disorders. Extreme choline consumption may cause diseases such as hypotension, sweating, diarrhea, and fishy body odor. The AI of choline is 425 mg/day for adult women; higher for pregnant and lactating women. The AI for adult men is 550 mg/day. The total choline content of foods is calculated as the sum of free choline, glycerophosphocholine, phosphocholine, phosphatidylcholine and sphingomyelin. These are called the choline variables. Observed values of choline variables may be different in amounts of nutrients. So different food groups in terms of choline variables are useful to compare. The present paper shows the advantages of using canonical variate analysis biplot to optimally separate groups and explore the differentiality of choline variables amounts in foods.