MULTIVARIATE STATISTICAL ANALYSIS OF YIELD-DETERMINING FACTORS
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概要
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This study is aimed at developing a multivariate statistical method to identify yield-determining factors and to evaluate their relative magnitude. Principal component analysis was used to summarize the rice growing environment in a"hydromorphic"field into a number of factors which may affect the yield performance. Four major factors were recognized; i) Soil moisture factor, ii) Soil texture factor, iii) Fertilizer factor, and iv) Insect damage factor. Using the scores of the indicated factors as independent variables, stepwise regression analysis was performed to derive a yield prediction function. The coefficient of determination (R^2) reached 0.924 and the magnitude of the factor effect on yield followed the order of Soil moisture ≫ Insect damage > Fertilizer. Soil texture was not significant as a yield-determining factor. Although the current report is only a case study, the method developed should be useful for predicting yield potentials of plant varieties adapting to different soil environments.
- 社団法人日本土壌肥料学会の論文
著者
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Kosaki Takashi
Department Of Tourism Science Tokyo Metropolitan University
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Kosaki Takashi
Department Of Agro-environmental Science Obihiro University Of Agriculture And Veterinary Medicine
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Juo Anthony
International Institute Of Tropical Agriculture
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WASANO Kikuo
Faculty of Agriculture, Saga University
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Wasano K
Faculty Of Agriculture Saga University
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Wasano Kikuo
Faculty Of Agriculture Saga University
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