Investigators: Wen-Harn Pan^a, Ray-Yu Yang^b, Meng-Tsan Chiang^c, Sue-Joan Chang^d, Ching-Jang Huang^e, Bi-Fong Lin^e

Research staff: Naihua Yeh^a, Wei-Hsuan Lin^a

^aInstitute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
^b Nutrition, AVRDC – The World Vegetable Center, Tainan, Taiwan
^c Department of Food Science, National Taiwan Ocean University, Taipei, Taiwan
^dDepartment of Life Sciences, National Cheng Kung University, Tainan, Taiwan
^eDepartment of Biotechnology, National Taiwan University, Taipei, Taiwan

Study period: 2014-2015

Funding: A grant from the Nutrilite Health Institute for phytonutrient analysis

Contacting us: pan@ibms.sinica.edu.tw; Naihua@ibms.sinica.edu.tw

Introduction

A phytonutrient content table was created for 933 plant-based food items commonly consumed by Taiwanese participants of the Nutrition and Health Survey in Taiwan (NAHSIT) 2005-2008 (1). We combined phytonutrient data from databases of the Food Industry Research Development Institutes (FIRDI), Taiwan (2); USDA (3-5); and Korea (6); as well as those provided in the relevant literature (7-22). In addition, we sent 172 Taiwanese commonly consumed plant foods to AVRDC – The World Vegetable Center, Taiwan to examine their phytonutrient contents. This integrated Taiwanese phytonutrient database contains information on 10 phytonutrients (see below). Twenty four hour recall was used to obtain consumption data from 2908 adult participants. This database has been used to estimate Taiwanese phytonutrient status and comparison has been made with Americans and Koreans (23).

1.α-carotene
2.β-carotene
3.β-cryptoxanthin
4.Lycopene
5.Lutein/zeaxanthin
6.Anthrocyanidins
7.Quercetin
8.Hesperetin
9.EGCG
10.Isoflavones

III Methods

1. Obtaining existing databases
         ◎FIRDI food composition table (2)：data on α-carotene & β-carotene
         ◎USDA phytonutrient database (3-5): USA_caro.xls、USA_flav.mdb、USA_isoflav.mdb
         ◎Korean phytonutrient database (6)

2. Compiling food items consumed in NAHSIT 2005-2008 (7)
          Data on 24-hour recall was used. We calculated frequency, average, maximum, and minimum weight for each food item.

3. Creating food-phytonutrient excel table
         i. Priority of selecting phytonutrient data: FIRDI > AVRDC > Korean > USDA
         ii. For EGCG: USDA + measurements from AVRDC
         iii. We used the original data for foods with only physical changes due to such as grounding or freezing.

4. Literature search for phytonutrient content
    Keyword search order
         A. By genus name, species name, and phytonutrient name
         B. By genus name and phytonutrient name
         C. By phytonutrient name and vegetables
         D. By phytonutrient name and fruits
         E. By phytonutrient name only

5. Food classification with cluster analysis
    Clustering foods with existing nutrient and phytonutrient data. The missing value may be filled with values from foods classified in the same group.
         A. Preliminary Classification: Mushroom, onions, green leafy vegetable, red leafy vegetable, etc.
         B. Clustering analysis was carried out within preliminary classification

6. Food analysis in AVRDC
    AVRDC analyzed phytonutrient content for 172 foods with insufficient phytonutrient data. Detail methods have been described in previous reports (8-26).
         A. Food list containing 172 food names and photos
         B. AVRDC carried out chemical analysis in 2014 and 2015
         C. Compiling data for Lutein+Zeaxanthin, integrating data from 6 anthocyanidins and 3 isoflavones

4. Phytonutrient data integration
    Plant foods were organized in six food group: vegetables, fruits,
    grains/cereals/root/tubers, soy/products, tea, and seeds/nuts.

IV Results

Taiwan phytonutrient database.

V Reference
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