Plant growth analysis: an evaluation of experimental design and computational methods

摘要: Various aspects of the experimental design and computational methods used in plant growth analysis were investigated. This was done either analytically, or by repeatedly simulating harvests from theoretical populations upon which imposed underlying curves as well variability material. In first part consequences neglecting an In-transformation primary weight data considered. T-tests are affected such a way that significant differences between treatments show up less readily than transformed data. A more fundamental point is most hypotheses on concern proportional effects rather absolute ones. these cases, prior to statistical test required anyway. Secondly, accuracy average RGR estimates evaluated. Variability estimation increases linearly with It also strongly dependent time interval number replicates per harvest. Even conservative values for variability, chances arriving at aberrant high. Therefore, it suggested population decreased deliberately, unless within itself biological interest. Thirdly, three fit dry progressions describe trends related parameters Although complicated calculate, Richards function superior polynomials fitted through ('polynomial' approach), classically derived ('combined' approach).