Assessment of agricultural modernization level in Zhejiang using SPSS software

Agricultural modernization plays an important role in agricultural socioeconomic development. Three multivariate statistical methods, hierarchical cluster analysis (HCA), factor analysis (FA) and discriminant analysis (DA) were applied to a subgroup of the dataset to evaluate their usefulness to classify agricultural modernization in Zhejiang, and to identify agricultural modernization hidden patterns. The FA yielded three factors explaining more than 91% of the total variance. The HCA and DA showed that the studied agricultural modernization regions can be grouped into three clusters i.e., relatively less agriculture modernization level, medium agriculture modernization level and highly agriculture modernization level regions in Zhejiang. The recognition capacities of the two discriminant functions were 97.8% and 2.2%, respectively. Agricultural modernization level of eastern and northern region in Zhejiang was higher, whereas that of western and southern region was lower. This study demonstrated that SPSS software and multivariate statistical techniques are effective for agricultural modernization classification, and for rapid assessment of agricultural modernization.