Calibration of the LINGRA-N model to simulate herbage yield of grass monocultures and permanent grassland in Slovenia



In this study, we calibrated the LINGRA-N model using the minimization of RMSE, and proceeded to evaluate its performance. We simulated herbage dry matter yield of cock's foot (Dactylis glomerata L.) and perennial ryegrass (Lolium perenne L.) in Jablje in the period 1998–2013, and multiplespecies grassland in Ljubljana (S72) in 1974–1993. The overall performance of LINGRA-N is fair for perennial ryegrass (RMSE% < 25%) and good for cock’s foot and S72 (RMSE% < 15%). The index of agreement (d) suggests that LINGRA-N is not calibrated well enough to simulate the interannual herbage yield variability for S72, so the model cannot yet be used for the simulation of multi-species grassland herbage yield. In contrast, the herbage yields of cock’s foot and perennial ryegrass in Jablje are simulated correctly (with d values 0.84 and 0.78, respectively). One of our further goals is to use the calibrated model on a specific location for the simulation of the herbage yield of grass monocultures under various weather conditions as well as for the simulation of climate change effect on it.


grasses; gramineae; dry matter content; crop yield; statistical data; statistical methods; models; simulation; weather data

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