"[2DA437608AFA]" . "A simple statistical model for predicting herbage production from permanent grassland"@en . "1365-2494" . "Schaumberger, Andreas" . "Trnka, Miroslav" . "Buchgraber, Karl" . . "19"^^ . "Jednoduch\u00FD statistick\u00FD model pro progn\u00F3zu v\u00FDnosu na trval\u00FDch travn\u00EDch porostech"@cs . "Austria; climate change; grassland"@en . . . . "P(GA205/05/2265)" . . "61" . . "CZ - \u010Cesk\u00E1 republika" . "463829" . "A simple statistical model for predicting herbage production from permanent grassland" . "RIV/62156489:43210/06:00102904!RIV07-GA0-43210___" . . "253;271" . . "1"^^ . "3" . "Jednoduch\u00FD statistick\u00FD model pro progn\u00F3zu v\u00FDnosu na trval\u00FDch travn\u00EDch porostech"@cs . . "Eitzinger, Josef" . . "A simple statistical model for predicting herbage production from permanent grassland" . "A simple statistical model for predicting herbage production from permanent grassland"@en . "The considerable year-to-year and seasonal variation in grassland production is of major importance to dairy farmers in Europe, as production systems must allow for the risk of unfavourable weather conditions. A large portion of the variability is caused by weather and its interaction with soil conditions and grassland management. The present study takes advantage of the interactions between weather, soil conditions and grassland management to derive a reliable grassland statistical model (GRAM) for grasslands under various management regimes using polynomial regressions (GRAM-R) and neural networks (GRAM-N). The model performance was tested with a focus on predicting its capability during unusually dry or wet years using long-term experimental data from Austrian sites. The GRAM model was then coupled with the Met&Roll stochastic weather generator to provide estimates of harvestable herbage dry matter (DM) production early in the season. It was found that, with the GRAM-N or GRAM-R" . . "43210" . "RIV/62156489:43210/06:00102904" . "Grass and Forage Science." . . . "Podrobn\u00FD popis viz. anglick\u00FD abstrakt."@cs . . "Resch, K." . "6"^^ . . "Gruszczynski, Gregorz" . "The considerable year-to-year and seasonal variation in grassland production is of major importance to dairy farmers in Europe, as production systems must allow for the risk of unfavourable weather conditions. A large portion of the variability is caused by weather and its interaction with soil conditions and grassland management. The present study takes advantage of the interactions between weather, soil conditions and grassland management to derive a reliable grassland statistical model (GRAM) for grasslands under various management regimes using polynomial regressions (GRAM-R) and neural networks (GRAM-N). The model performance was tested with a focus on predicting its capability during unusually dry or wet years using long-term experimental data from Austrian sites. The GRAM model was then coupled with the Met&Roll stochastic weather generator to provide estimates of harvestable herbage dry matter (DM) production early in the season. It was found that, with the GRAM-N or GRAM-R"@en .