DEVELOPMENT AND EVALUATION OF AN HPLC METHOD FOR THE ANALYSIS OF CAROTENOIDS IN FOODS, AND THE MEASUREMENT OF THE CAROTENOID CONTENT OF VEGETABLES AND FRUITS COMMONLY CONSUMED IN THE UK
Dj. Hart et Kj. Scott, DEVELOPMENT AND EVALUATION OF AN HPLC METHOD FOR THE ANALYSIS OF CAROTENOIDS IN FOODS, AND THE MEASUREMENT OF THE CAROTENOID CONTENT OF VEGETABLES AND FRUITS COMMONLY CONSUMED IN THE UK, Food chemistry, 54(1), 1995, pp. 101-111
This study further examines the factors which affect the chromatograph
ic response of carotenoids and contribute to analytical variation and
inaccuracies in their quantitative determination. A method for the ana
lysis of carotenoids in vegetables and fruits is described and data ar
e presented for the carotenoid content of vegetables and fruits common
ly consumed in the UK. The addition of a solvent modifier (triethylami
ne) to the mobile phase was shown to improve the recovery of carotenoi
ds from the column from around 60% to over 90%. The linearity and repr
oducibility of the chromatographic response was investigated and the r
obustness and reproducibility of the method nias measured using a refe
rence vegetable material developed in the laboratory. Short and longer
term reproducibility showed an average CV of around 8% for all carote
noids. Analysis showed that good sources (>1000 mu g/100 g) of lutein
were: broccoli, butterhead lettuce, parsley, peas, peppers, spinach an
d watercress; of lycopene: tomatoes and tomato products; and of beta-c
arotene: broccoli, carron, greens, butterhead lettuce, mixed vegetable
s, parsley, spinach and watercress. There was little or no loss of car
otenoids on cooking, green vegetables showed an average increase in lu
tein levels of 24% and in beta-carotene levels of 38%. This study and
previous studies in our laboratory have demonstrated that a number of
factors affect the validity of the 'peak response' and are likely to c
ontribute to within and between laboratory variation. It is suggested
that the development and use of standard reference materials would sig
nificantly improve the quality of data.