Modeling Cut Rose Yield Over an 18‐Month Period After Compost Amendment Using Repeated Sigmoidal Gompertz Curve Fitting - E. A. deNijs; A. Tietema; R. Bol; E. E. vanLoon (Plant-Environment Interactions, 2025)
ABSTRACT Understanding the growth, development, and production patterns of perennial crops is crucial for optimizing agricultural practices and enhancing crop productivity. Growth models are valuable tools in this regard, offering insights into how crops respond to different experimental treatments. This study evaluates the suitability of repeated Gompertz growth curves for assessing the impact of compost amendment on the yield of cut roses over an 18‐month period. Yield data was collected from an experiment testing the effects of four different compost treatments on cut roses, with daily records of the number of stems harvested per replicate plot. Comparison of Generalized Additive Mixed Models with repeated Gompertz growth curves showed that the Gompertz model effectively captured yield dynamics in individual flushes with minimal compromise in model accuracy. As the crop matured, asymptote parameter estimates increased, while growth rate parameter estimates decreased, reflecting a stabilization of growth patterns. Compost amendment significantly enhanced early‐stage yield, with treatments receiving full fertigation consistently outperforming the control during the first year. As the crop matured, differences in yields among treatments diminished, indicating that the benefits of compost amendment are most pronounced during the initial growth phase within the 18‐month timeframe. The substantial increase in yield after compost amendment highlights its potential for sustainable management practices, guiding the sector in optimizing compost usage to enhance yield while supporting environmental sustainability. To understand the dynamic effects of different management practices (in this case different compost treatments) on rose yield across flowering flushes, the repeated growth curve provides an adequate framework.