| 000 | 02930nam a22003857a 4500 | ||
|---|---|---|---|
| 001 | G74623 | ||
| 003 | MX-TxCIM | ||
| 005 | 20211006081059.0 | ||
| 008 | 121211s ||||f| 0 p|p||0|| | | ||
| 020 | _a9974-7586-0-2 | ||
| 040 | _aMX-TxCIM | ||
| 072 | 0 | _aF01 | |
| 072 | 0 | _aH50 | |
| 082 | 0 | 4 |
_a633.1158 _bKOH |
| 100 | 1 |
_aMagrin, G.O. _uExplorando Altos Rendimientos de Trigo; La Estanzuela (Uruguay); 20-23 Oct 1997 |
|
| 110 | 2 | _aCentro Internacional de Mejoramiento de Maiz y Trigo (CIMMYT), Mexico DF (Mexico) | |
| 245 | 0 | 0 | _aIntroducción al modelo de simulación CERES-Wheat y ejemplos de aplicación en Argentina |
| 260 |
_aLa Estanzuela (Uruguay) _bINIA|CIMMYT : _c1998 |
||
| 340 | _aPrinted | ||
| 520 | _aThe CERES-Wheat model estimates the growth, development and yield of the wheat crop depending on the availability of water and nitrogen. It has been calibrated and validated for a wide range of environmental conditions and utilized for different purposes. In Argentina, CERES-Wheat estimates the yield of a wheat crop within the average margin of error of 8% and is utilized for the following purposes:||1. To anticipate production estimates in the Pampas region by calculating the yield with CERES-Wheat and seeded area through satellite images of high resolution. The first estimate is made a month before the harvest and is updated periodically.||2. To estimate the yield potential and its spatial and temporal variability. The potential yield is considered as one obtained under optimum crop management conditions and without water and nutrient limitations. Its spatial/ temporal variability corresponds with the variations of temperature and radiation and depends on the genotype utilized.||3. To quantify the relative importance of factors that limit yield (availability of water and/or nutrients) by analyzing the factors causing gaps or differences between the actual and the potential yields.||4. To estimate the vulnerability of the Pampas region in the face of predicted climatic changes. To work with the future scenarios generated with the atmospheric models, analyze the sensitivity of the distinct climatic parameters and the projections on the basis of historic tendencies.||5. To evaluate the utility of anticipated climatic predictions. The utility of the anticipated predictions of the ENSO phenomena is being evaluated to determine the optimum management of the wheat crop in each phase of the event ( Niño, Niña and Neutro) | ||
| 546 | _aSpanish | ||
| 591 | _a0105|AL-Wheat Program|AGRIS 0102 | ||
| 593 | _aJose Juan Caballero | ||
| 595 | _aCPC | ||
| 650 | 1 | 7 |
_aCrop management _gAGROVOC _2 _91061 |
| 650 | 1 | 0 |
_aResearch projects _91237 |
| 650 | 1 | 0 |
_aSimulation models _92569 |
| 650 | 1 | 0 |
_aVariety trials _92474 |
| 653 | 0 | _aCIMMYT | |
| 653 | 0 | _aINIA | |
| 650 | 1 | 7 |
_aWheat _gAGROVOC _2 _91310 |
| 650 | 1 | 0 |
_91313 _aYields _gAGROVOC |
| 700 | 1 |
_aKholi, M.M.|Martino, D. _eeds. |
|
| 942 | _cBK | ||
| 999 |
_c5205 _d5205 |
||