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Taschenbuch. Zustand: Neu. CMS-CERES-Maize model (DSSAT v 4.0) | Calibration, Validation and Simulation of maize growth and yield | Tej Narayan Bhusal | Taschenbuch | 132 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783844302721 | Verantwortliche Person für die EU: OmniScriptum GmbH & Co. KG, Bahnhofstr. 28, 66111 Saarbrücken, info[at]akademikerverlag[dot]de | Anbieter: preigu.
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Sprache: Englisch
Verlag: LAP LAMBERT Academic Publishing Apr 2011, 2011
ISBN 10: 3844302727 ISBN 13: 9783844302721
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In recent years, the use of crop model has been increasing exponentially for agro-climatic and site specific resource management to increase the grain yield. Among them, the CMS-CERES-Maize model is one, but, very little academic literature exists on how to best utilize the resource using simulation model to optimize the yield in reference to developing countries like Nepal. Best fit (calibration and validation)of model using the available datasets is prerequisites for its application. Site specific management of resources like nitrogen (dose, time and method), water (amount and time), etc. have increased the yield of maize minimizing their losses in field.Likewise, climate of the year, sowing dates, initial moisture content of the field,etc. also significantly affect on the yield performance. From the findings of this study, we concluded that the change in magnitude of climatic parameters creates stress on the limited resource management to increase the grain yield. Further, The analysis should help shed some light on this new and exciting field and should be especially useful to professionals and anyone else involve in agriculture. 132 pp. Englisch.
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In den WarenkorbZustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Bhusal Tej NarayanMr. Tej Narayan Bhusal is an assistant professor at IAAS/TU, Nepal (http:/iaas.edu.np). He has been studied MSc Agriculture (Agronomy) and BSc Agriculture in 2006 and 2008, respectively at IAAS/TU, Nepal. His res.
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In den WarenkorbZustand: New. Print on Demand pp. 132 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam.
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In recent years, the use of crop model has been increasing exponentially for agro-climatic and site specific resource management to increase the grain yield. Among them, the CMS-CERES-Maize model is one, but, very little academic literature exists on how to best utilize the resource using simulation model to optimize the yield in reference to developing countries like Nepal. Best fit (calibration and validation)of model using the available datasets is prerequisites for its application. Site specific management of resources like nitrogen (dose, time and method), water (amount and time), etc. have increased the yield of maize minimizing their losses in field.Likewise, climate of the year, sowing dates, initial moisture content of the field,etc. also significantly affect on the yield performance. From the findings of this study, we concluded that the change in magnitude of climatic parameters creates stress on the limited resource management to increase the grain yield. Further, The analysis should help shed some light on this new and exciting field and should be especially useful to professionals and anyone else involve in agriculture.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 132 pp. Englisch.
Sprache: Englisch
Verlag: LAP LAMBERT Academic Publishing, 2011
ISBN 10: 3844302727 ISBN 13: 9783844302721
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In recent years, the use of crop model has been increasing exponentially for agro-climatic and site specific resource management to increase the grain yield. Among them, the CMS-CERES-Maize model is one, but, very little academic literature exists on how to best utilize the resource using simulation model to optimize the yield in reference to developing countries like Nepal. Best fit (calibration and validation)of model using the available datasets is prerequisites for its application. Site specific management of resources like nitrogen (dose, time and method), water (amount and time), etc. have increased the yield of maize minimizing their losses in field.Likewise, climate of the year, sowing dates, initial moisture content of the field,etc. also significantly affect on the yield performance. From the findings of this study, we concluded that the change in magnitude of climatic parameters creates stress on the limited resource management to increase the grain yield. Further, The analysis should help shed some light on this new and exciting field and should be especially useful to professionals and anyone else involve in agriculture.