| 000 | 03207nab|a22004817a|4500 | ||
|---|---|---|---|
| 001 | 65068 | ||
| 003 | MX-TxCIM | ||
| 005 | 20220920160412.0 | ||
| 008 | 20211s2021||||mx |||p|op||||00||0|eng|d | ||
| 022 | _a21510032 | ||
| 024 | 8 | _ahttps://doi.org/10.13031/trans.14586 | |
| 040 | _aMX-TxCIM | ||
| 041 | _aeng | ||
| 100 | 1 |
_aBerton Ferreira, T. _8001712776 _gFormerly Integrated Development Program _gFormerly Sustainable Agrifood Systems _919053 |
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| 245 | 1 |
_aCoupling a Pest and Disease Damage Module with CSM-NWheat: _bA Wheat Crop Simulation Model |
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| 260 |
_bAmerican Society of Agricultural and Biological Engineers, _c2021. _aUSA : |
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| 500 | _aPeer review | ||
| 500 | _aOpen Access | ||
| 520 | _aWheat is one of the most important global staple crops and is affected by numerous pests and diseases. Depending on their intensity, pests and diseases can cause significant economic losses and even crop failures. Pest models can assist decision-making, thus helping reduce crop losses. Most wheat simulation models account for abiotic stresses such as drought and nutrients, but they do not account for biotic stresses caused by pests and diseases. Therefore, the objective of this study was to couple a dynamic pest and disease damage module to the DSSAT model CSM-NWheat. Coupling points were integrated into the CSM-NWheat model for applying daily damage to all plant components, including leaves, stems, roots, and grains, the entire plant, and to the assimilate supply. The coupled model was tested by simulating a wheat crop with virtual damage levels applied at each coupling point. Measured foliar damage caused by tan spot (Pyrenophora tritici-repentis) was also simulated. The modified model accurately estimated the reduction in leaf area growth and the yield loss when compared with observed data. With the incorporation of the pest module, CSM-NWheat can now predict the potential impact of pests and diseases on wheat growth and development, and ultimately economic yield. | ||
| 546 | _aText in English | ||
| 650 | 7 |
_aCrops _2AGROVOC _91069 |
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| 650 | 7 |
_aDecision making _2AGROVOC _98770 |
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| 650 | 7 |
_aLosses _2AGROVOC _913540 |
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| 650 | 7 |
_aPlants _2AGROVOC _94199 |
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| 650 | 7 |
_aBiotic stress _2AGROVOC _97593 |
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| 650 | 7 |
_aDecision support _2AGROVOC _916361 |
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| 650 | 7 |
_aDiseases _2AGROVOC _95952 |
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| 650 | 7 |
_aEconomic losses _2AGROVOC _917225 |
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| 650 | 7 |
_aYield losses _2AGROVOC _96242 |
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| 650 | 7 |
_aDecision support systems _2AGROVOC _93096 |
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| 700 | 1 |
_aPavan, W.O. _98187 |
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| 700 | 1 |
_aCunha Fernandes, J.M. _8001713392 _gSustainable Agrifood Systems _914316 |
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| 700 | 1 |
_aAsseng, S. _91568 |
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| 700 | 1 |
_aAntunes de Oliveira, F. _926690 |
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| 700 | 1 |
_aHölbig, C.A. _926691 |
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| 700 | 1 |
_8001710201 _aPequeno, D.N.L. _gSocioeconomics Program _gSustainable Agrifood Systems _96381 |
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| 700 | 1 |
_aDalmago, G.A. _926692 |
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| 700 | 1 |
_aLazaretti Zanatta, A. _926693 |
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| 700 | 1 |
_aHoogenboom, G. _94150 |
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| 773 | 0 |
_tTransactions of the ASABE _gv. 64, no. 6, p. 2061-2071 _dUSA : American Society of Agricultural and Biological Engineers, 2021. _x21510032 |
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| 856 |
_yOpen Access through DSpace _uhttps://hdl.handle.net/10883/22007 |
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| 942 |
_cJA _n0 _2ddc |
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| 999 |
_c65068 _d65060 |
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