Characteristics of corn variety using principal components analysis and Q-type cluster analysis

• Published in: Shenyang nong ye da xue xue bao Vol. 40; no. 1
• Main Authors: Zeng Jie, Henan Institute of Science and Technology, Xinxiang(China), College of Food Science, Sun Junliang, Henan Institute of Science and Technology, Xinxiang(China), College of Food Science, Li Guanglei, Henan Institute of Science and Technology, Xinxiang(China), College of Food Science
• Format: Journal Article
• Language: Chinese
• Published: 01.02.2009
• Subjects: http://www.fao.org/aos/agrovoc#c_12332; http://www.fao.org/aos/agrovoc#c_7377; http://www.fao.org/aos/agrovoc#c_8157; MAIS; MAIZ; MAIZE; METHODE STATISTIQUE; METODOS ESTADISTICOS; STATISTICAL METHODS; VARIEDADES; VARIETE; VARIETIES
• ISSN: 1000-1700

探讨主成分分析和聚类分析在研究不同玉米品种特性中的应用，筛选玉米加工特性的有效指标。选取辽宁地区26个主栽玉米品种，采用湿磨工艺制备玉米粉，测定了玉米粉的主要成分和理化性质，并对各指标进行基本参数估计、主成分分析和聚类分析。结果表明：不同品种玉米湿磨粉的成分和理化性质具有明显差异；主成分分析表明玉米粉品质由6个主成分构成，其中淀粉品质对玉米湿磨粉品质的贡献率最大，占44．69％；Q型聚类分析按照淀粉品质将供试品种分为4类。主成分分析和Q型聚类分析在结果上的一致性说明多因素分析技术在不同玉米品种特性中的研究是可行的。[著者文摘] The contents of chemical components and physicochemical properties of 26 corn flours processed by wet milling were determined and the basic parameter estimation, principal component analysis and cluster analysis were applied in data analysis. The results showed that the chemical components and physicochemical properties were significantly different among 26 corn vari- eties. The corn flour quality included six principal components from principal component analysis and the contribution rate of starch quality was important, accounted for 44.69%. 26 corn varieties were classified into four groups according to starch quality by Q-type cluster analysis. Consistency between principal components analysis and Q-type cluster analysis indicated that multiva