Quantifying abortion rates of reproductive organs and effects of contributing factors using time-to-event analysisA. M. Wubs A B D , E. Heuvelink A , L. F. M. Marcelis A C and L. Hemerik B
A Horticultural Supply Chains Group, Wageningen University, PO Box 630, 6700 AP, Wageningen, The Netherlands.
B Biometris, PO Box 100, 6700 AC, Wageningen, The Netherlands.
C Wageningen University and Research Centre, Greenhouse Horticulture, PO Box 644, 6700 AP, Wageningen, The Netherlands.
D Corresponding author. Email: email@example.com
Functional Plant Biology 38(5) 431-440 https://doi.org/10.1071/FP10249
Submitted: 22 December 2010 Accepted: 13 March 2011 Published: 2 May 2011
Time-to-event analysis, or survival analysis, is a method to analyse the timing of events and to quantify the effects of contributing factors. We apply this method to data on the timing of abortion of reproductive organs. This abortion often depends on source and sink strength. We hypothesise that the effect of source and sink strength on abortion rate can be quantified with a statistical model, obtained via survival analysis. Flower and fruit abortion in Capsicum annuum L., observed in temperature and planting density experiments, were analysed. Increasing the source strength as well as decreasing the sink strength decreased the abortion rate. The effect was non-linear, e.g. source strengths above 6 g CH2O per plant per d did not decrease abortion rates further. The maximum abortion rate occurred around 100 degree-days after anthesis. Analyses in which sink strength was replaced with the number of fruits in a specified age category had an equal or better fit to the data. We discuss the advantages and disadvantages of using survival analyses for this kind of data. The technique can also be used for other crops showing reproductive organ abortion (e.g. soybean (Glycine max L.), cucumber (Cucumis sativus L.)), but also on other event types like bud break or germination.
Additional keywords: flower abortion, fruit abortion, sink strength, source strength, survival analysis, sweet pepper.
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