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Full-Text Articles in Physical Sciences and Mathematics
Response Of Soybean Yield And Yield Components To Phosphorus Fertilization In South Dakota, Adams Kusi Appiah, Rebecca Helget, Yi Xu, Jixiang Wu
Response Of Soybean Yield And Yield Components To Phosphorus Fertilization In South Dakota, Adams Kusi Appiah, Rebecca Helget, Yi Xu, Jixiang Wu
Conference on Applied Statistics in Agriculture
Increased demand for soybean [Glycine max (L.) Merrill] production for industrial, human, and animal consumption has provided many incentives for farmers and producers to increase their production. In many soils used for soybean production, phosphorus (P) becomes a major limiting factor to soybean growth and grain production. A field experiment was conducted in five locations across Eastern South Dakota in 2013 to study the response of soybean yield and yield components to phosphorus fertilizer applications. The experiment was laid out in a randomized complete block (RCB) design with four replications. The treatments consisted of five P levels 0, 20, 40, …
Statistical Analysis Software For Multiplicative Interaction Models, Eun-Joo Lee, Dallas E. Johnson
Statistical Analysis Software For Multiplicative Interaction Models, Eun-Joo Lee, Dallas E. Johnson
Conference on Applied Statistics in Agriculture
In a two-way cross-classified experiment, one is almost always interested in whether the two factors interact or not. When there are no independent replications, there are no traditional tests for interaction. This research considers the problem of analyzing a two-way cross-classified experiment using multiplicative interaction models when there are no independent replications and interaction between the two factors may exist. The purpose of this research is to develop SAS® macros to provide user-friendly statistical software for the analysis of interaction in two-way experiments. The macros also provide many useful graphical displays including displays to help one determine the pattern of …
Using Interaction In Two-Way Data Tables, Hugh G. Gauch Jr., Richard W. Zobel
Using Interaction In Two-Way Data Tables, Hugh G. Gauch Jr., Richard W. Zobel
Conference on Applied Statistics in Agriculture
Agronomists and breeders frequently collect yield data for a number of genotypes in a number of environments (site-years), resulting in a two-way data table. The Additive Main effects and Multiplicative Interaction (AMMI) model combines regular analysis of variance (ANOVA) for additive main effects with principal components analysis (PCA) for multiplicative structure within the interaction (that is, within the residual from ANOVA). AMMI is effective for (1) understanding genotype-environment interaction, (2) improving the accuracy of yield estimates, (3) increasing the probability of successfully selecting genotypes with the highest yields, (4) imputing missing data, and (5) increasing the flexibility and efficiency of …