ObjectivesIn soil testing and formulated fertilization, soil testing is the key to realize rational fertilization through practical guidance. However, collection of representative soil samples is often difficult because of highly decentralized farmland management, and soil sample analysis is cost and time-consuming. Therefore, statistical pattern recognition techniques were studied in this paper to explore category attribution of nitrogen (N), phosphorus (P) and potassium (K) fertilization without soil testing for early rice.

MethodsData from eighty field experiments in southeast of Fujian Province, China, were used in this study. Based on the response of early rice to N, P and K fertilizers, the paddy fields were divided into regional fertilization categories, using clustering analysis method of Euclideana distance-sum of squares of deviations. Then the NPK fertilization category for a field was calculated based on the statistical pattern recognition principle, the application rates of N, P and K fertilizers and the outputs.

ResultsOn condition of ensuring that the average yield of the blank area and that of balanced fertilization had statistical significant differences between any two fertilization categories, the 80 paddy fields were divided clearly into six fertilization categories. Multivariate statistics showed that the differences of covariance matrix of six categories were not all equal, and the Bayesian discrimination function of each category was established based on that. The standardization of the original data greatly improved the discrimination accuracy, with the back substitution misjudgment rate and cross misjudgment rate of training samples of only 1.2% and 1.3% respectively, and the category discrimination accuracy of the 84 treatments in the 6 reserved experimental sites reached 81.0%.

ConclusionsStatistical pattern recognition principle and its Bayesian discriminate analysis method may provide an effective technical approach for the attribution decisions of N, P and K fertilization category of early rice without soil testing, and its results could meet the accuracy requirements of fertilizer recommendation.