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    Examination of relation between nutrient components and fruits: Biplot approach
    (Taylor & Francis Ltd, 2009) Atakan, Cemal; Alkan, Baris; Sahin, Afsin
    Adequate intake of fruits and vegetables as part of the daily diet may help prevent major diseases. Low fruit intake is a major risk factor for cancer, coronary heart disease and stroke. The World Health Organization recommends eating at least five portions of a variety of fruit, which is nearly 400 g/day. Essential nutrients, water, carbohydrates, oils and vitamins are needed in appropriate quantities in order to have a well-functioning body. In this study we try to carry out a food composition study to identify and determine the chemical nature of the organic and inorganic macro-nutrient and micro-nutrient properties of the main fruit types that affect human nature, by a biplot graphical approach. The biplot can be considered as multivariate equivalents of scatter plots that have been used for graphically analyzing bivariate data. Biplot approaches show a simultaneous display of fruits and nutrient components in low dimensions. In the present study, the theory of biplot and different types of biplot will be given and than an application of the biplot approach will be applied to the real data.
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    Öğe
    Use of canonical variate analysis biplot in examination of choline content data of some foods
    (Taylor & Francis Ltd, 2011) Alkan, Baris; Atakan, Cemal
    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.