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Advances in modeling machine-soil-plant interactions
Year:
1988
Source of publication :
Soil and Tillage Research
Authors :
Hadas, Aviva
;
.
Volume :
11
Co-Authors:
Hadas, A., Agricultural Research Organization, Institute of Soils and Water, Department of Soil Physics, Bet Dagan 50-250, Israel
Larson, W.E., Department of Soil Science, University of Minnesota, Agricultural Research Service, St. Paul, MN 55108, United States
Allmaras, R.R., Department of Soil Science, University of Minnesota, Agricultural Research Service, St. Paul, MN 55108, United States
Facilitators :
From page:
349
To page:
372
(
Total pages:
24
)
Abstract:
Modern agriculture involves mechanized operations which affect crop growth and yields through changes in the soil environment. Field research to study the phenomena involved in the soil-machine-crop system is usually site-specific with respect to edaphic, climatic and management factors. Field experiments are often expensive to conduct, and generalization to other sites or practices is usually tenuous at best. Computer-based techniques to simulate machine-soil-plant (or crop) systems can test many combinations of site characteristics and management practices, and screen the most promising combinations. Once these promising combinations are validated, the simulation techniques, together with stochastically-supported data bases can be used to predict tillage management systems suitable for specific sites and crops. Current efforts to model plant response to soil conditions created by tillage and machines have serious shortcomings, because the link between tool action, subsequent soil structure, and the parameters that describe fluxes of water, heat and gas need further development for deterministic modeling. Machine-soil models focus on efficiency of the tillage operation, while soil-plant models focus on soil structure and related parameters influencing plant growth. While current models for simulating the machine-soil-crop system have limitations, an approach to bridge between the two model applications offers great promise and should be a high research priority. When used with improved measurements of tool action and of soil structural properties before and after tillage and traffic, including position or placement of the crop residues, current models can be doubly effective for improving tillage management. © 1988.
Note:
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More details
DOI :
10.1016/0167-1987(88)90006-2
Article number:
Affiliations:
Database:
Scopus
Publication Type:
article
;
.
Language:
English
Editors' remarks:
ID:
19957
Last updated date:
02/03/2022 17:27
Creation date:
16/04/2018 23:32
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Scientific Publication
Advances in modeling machine-soil-plant interactions
11
Hadas, A., Agricultural Research Organization, Institute of Soils and Water, Department of Soil Physics, Bet Dagan 50-250, Israel
Larson, W.E., Department of Soil Science, University of Minnesota, Agricultural Research Service, St. Paul, MN 55108, United States
Allmaras, R.R., Department of Soil Science, University of Minnesota, Agricultural Research Service, St. Paul, MN 55108, United States
Advances in modeling machine-soil-plant interactions
Modern agriculture involves mechanized operations which affect crop growth and yields through changes in the soil environment. Field research to study the phenomena involved in the soil-machine-crop system is usually site-specific with respect to edaphic, climatic and management factors. Field experiments are often expensive to conduct, and generalization to other sites or practices is usually tenuous at best. Computer-based techniques to simulate machine-soil-plant (or crop) systems can test many combinations of site characteristics and management practices, and screen the most promising combinations. Once these promising combinations are validated, the simulation techniques, together with stochastically-supported data bases can be used to predict tillage management systems suitable for specific sites and crops. Current efforts to model plant response to soil conditions created by tillage and machines have serious shortcomings, because the link between tool action, subsequent soil structure, and the parameters that describe fluxes of water, heat and gas need further development for deterministic modeling. Machine-soil models focus on efficiency of the tillage operation, while soil-plant models focus on soil structure and related parameters influencing plant growth. While current models for simulating the machine-soil-crop system have limitations, an approach to bridge between the two model applications offers great promise and should be a high research priority. When used with improved measurements of tool action and of soil structural properties before and after tillage and traffic, including position or placement of the crop residues, current models can be doubly effective for improving tillage management. © 1988.
Scientific Publication
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