微波消解FAAS测定新疆出口番茄酱中的微量元素

采用微波消解试样,FAAS法对新疆4个厂家出口番茄酱中的微量元素进行测定.经过回收率和精密度试验,结果表明:6种微量元素的相对标准偏差在0.23%-2.10%;回收率在94.8%-104.5%;并以番茄叶的标准样品(ESP-1)进行比较测定,标准样品的测定值与参考值基本一致,该方法获得了满意的精密度和准确度.     

ICP-AES法测定番茄酱中Ca、Cu、Fe、Zn、Mn、K、Al、Sr、P等9个元素

本文采用ＩＣＰ－ＡＥＳ法对新疆地区出口番茄酱中Ｃａ,Ｃｕ,Ｆｅ,Ｚｎ,Ｍｎ,Ｋ,Ａｌ,Ｓｒ,Ｐ等九个元素进行了同时测定,根据仪器的特点,最大限度地避开了干扰及合理地扣除了光谱背景,改变了以往原子吸收法测定时的繁琐,费时情况,本法的准确度,精密度,回收率（９２．５％￣１０４．１％）均达到满意结果。     

The ability of spectrum autocorrelation models to predict the lycopene concentration in foods through visible spectroscopic data

We developed a novel computerized approach based on lag-k autocorrelation coefficients (LCCs) and linear models (LMs) to estimate the concentration of lycopene in foods by the spectroscopy. The LCCs were calculated using the data obtained using whole visible scans from 400 to 600 nm (vide supra) of lycopene standards and food samples (ketchup, tomato juice and tomato sauce). The chaotic parameter (CP) was then transferred into a LM to estimate the concentration of lycopene compound. The integrated LCC/visible spectroscopy method developed can be considered as a satisfactory analytical technique able to estimate lycopene concentration in food samples in a fast accurate way, with a mean prediction error lower than 5.7% and a mean correlation coefficient higher than 0.957.