论文部分内容阅读
采用主成分分析法,对青海省海东地区6种主要农产品中10种矿物元素含量与产品品质之间的关系进行综合评价。通过该法对微量元素的含量数据进行降维处理,并利用SPSS 19.0软件进行计算,提取特征值大于1.2的成分为主成分,其结果显示前3个主成分的累计方差贡献率达到86.15%,即保留了全部原始数据86.15%的信息,基本能反映总体情况。主成分综合得分反映出微量元素在6种农产品中的总体含量水平,其顺序由高到低依次为:春小麦>蚕豆>玉米>青稞>豌豆>油菜籽,进而体现了微量元素在几种农产品中的分布特征。分析结果表明主成分分析和因子得分可以用于农产品质量的综合评价,为农产品生产、品质评价及相关研究提供数据支撑和科学依据。
Principal component analysis was used to evaluate the relationship between the content of 10 mineral elements and the product quality of 6 main agricultural products in Haidong, Qinghai Province. By this method, the content of trace elements was reduced dimensionally, and SPSS 19.0 software was used to calculate and extract the components whose eigenvalues were more than 1.2 as the main components. The results showed that the cumulative variance of the first three principal components reached 86.15% That is, it retains 86.15% of the total raw data and basically reflects the overall situation. The main component comprehensive score reflects the total content of trace elements in six kinds of agricultural products, the order from high to low are: spring wheat> broad bean> corn> barley> pea> rapeseed, and then reflects the trace elements in several agricultural products Distribution characteristics. The analysis results show that the principal component analysis and factor score can be used for the comprehensive evaluation of agricultural product quality and provide data support and scientific basis for agricultural product production, quality evaluation and related research.