William M. Clapham

Risk analysis, analysis of variance: getting more from our data.

Analysis of variance (ANOVA) and regression are common statistical techniques used to analyze agronomic experimental data and determine significant differences among yields due to treatments or other experimental factors. Risk analysis provides an alternate and complimentary examination of the same data by determining yield probabilities for each treatment or factor. We generated and analyzed a synthetic data set to illustrate that data with similar means, as determined by ANOVA, can have markedly different probability distributions due to differences in standard deviations. We then applied the techniques to data from a five-year yield trial of twelve Bermudagrass cultivars. ANOVA detected significant year-by-cultivar interactions while risk analysis illustrated differences among the cultivars in yield stability and in the probabilities of achieving specific yield goals. Together, ANOVA and risk analysis provide a more complete view of the data that facilitates technical transfer of experimental results to producers and other end-users.

Development and maturation of white lupine seed

(...) The objectives of this study were to develop a descriptive index of maturation for white lupine pods and seeds, and to relate physiological maturity to the relationship between seed and pod moisture contents. Field data from a series of studies on the effects of planting date and plant density on white lupine growth and yield were used to generate the developmental index (...)