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Description
  • 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
  • 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)
  • Podrobný popis viz. anglický abstrakt. (cs)
Title
  • A simple statistical model for predicting herbage production from permanent grassland
  • Jednoduchý statistický model pro prognózu výnosu na trvalých travních porostech (cs)
  • A simple statistical model for predicting herbage production from permanent grassland (en)
skos:prefLabel
  • A simple statistical model for predicting herbage production from permanent grassland
  • Jednoduchý statistický model pro prognózu výnosu na trvalých travních porostech (cs)
  • A simple statistical model for predicting herbage production from permanent grassland (en)
skos:notation
  • RIV/62156489:43210/06:00102904!RIV07-GA0-43210___
http://linked.open.../vavai/riv/strany
  • 253;271
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GA205/05/2265)
http://linked.open...iv/cisloPeriodika
  • 3
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 463829
http://linked.open...ai/riv/idVysledku
  • RIV/62156489:43210/06:00102904
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Austria; climate change; grassland (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • CZ - Česká republika
http://linked.open...ontrolniKodProRIV
  • [2DA437608AFA]
http://linked.open...i/riv/nazevZdroje
  • Grass and Forage Science.
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...v/svazekPeriodika
  • 61
http://linked.open...iv/tvurceVysledku
  • Eitzinger, Josef
  • Schaumberger, Andreas
  • Trnka, Miroslav
  • Buchgraber, Karl
  • Gruszczynski, Gregorz
  • Resch, K.
issn
  • 1365-2494
number of pages
http://localhost/t...ganizacniJednotka
  • 43210
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