Loading menu…

Modeling Maize Production towards Site Specific Fertilizer Recommendation in Ghana

§ CSIR-Savanna Agricultural Research Institute

Send Message

To: Author

Modeling Maize Production towards Site Specific Fertilizer Recommendation in Ghana

Article Fingerprint

ReserarchID

A8327

Modeling Maize Production towards Site Specific Fertilizer Recommendation in Ghana Banner

Key Research Insights

Synthesized scholarly intelligence & interactive research assistant
  • English
  • Afrikaans
  • Albanian
  • Amharic
  • Arabic
  • Armenian
  • Azerbaijani
  • Basque
  • Belarusian
  • Bengali
  • Bosnian
  • Bulgarian
  • Catalan
  • Cebuano
  • Chichewa
  • Chinese (Simplified)
  • Chinese (Traditional)
  • Corsican
  • Croatian
  • Czech
  • Danish
  • Dutch
  • Esperanto
  • Estonian
  • Filipino
  • Finnish
  • French
  • Frisian
  • Galician
  • Georgian
  • German
  • Greek
  • Gujarati
  • Haitian Creole
  • Hausa
  • Hawaiian
  • Hebrew
  • Hindi
  • Hmong
  • Hungarian
  • Icelandic
  • Igbo
  • Indonesian
  • Irish
  • Italian
  • Japanese
  • Javanese
  • Kannada
  • Kazakh
  • Khmer
  • Korean
  • Kurdish (Kurmanji)
  • Kyrgyz
  • Lao
  • Latin
  • Latvian
  • Lithuanian
  • Luxembourgish
  • Macedonian
  • Malagasy
  • Malay
  • Malayalam
  • Maltese
  • Maori
  • Marathi
  • Mongolian
  • Myanmar (Burmese)
  • Nepali
  • Norwegian
  • Pashto
  • Persian
  • Polish
  • Portuguese
  • Punjabi
  • Romanian
  • Russian
  • Samoan
  • Scots Gaelic
  • Serbian
  • Sesotho
  • Shona
  • Sindhi
  • Sinhala
  • Slovak
  • Slovenian
  • Somali
  • Spanish
  • Sundanese
  • Swahili
  • Swedish
  • Tajik
  • Tamil
  • Telugu
  • Thai
  • Turkish
  • Ukrainian
  • Urdu
  • Uzbek
  • Vietnamese
  • Welsh
  • Xhosa
  • Yiddish
  • Yoruba
  • Zulu
Reading Preferences
Font Size
Line Spacing
Background
This converted HTML version may contain rendering inconsistencies. Please refer to the PDF for the authoritative version, or click here to provide feedback.

Abstract

The use of crop growth simulation models such as those incorporated into Decision Support System for Agro technology Transfer (DSSAT) are useful tools for assessing the impacts of crop productivity under various management systems. The maize growth model of DSSAT is CERES-Maize. To use it to predict fertilizer recommendation for maize (Zea mays L.) under Guinea savanna agro ecological conditions, data on maize growth, yield and development as well as data on soil and weather were collected from field experiment conducted during the 2010 growing season at Kpalesawgu in Ghana. The model was calibrated using various crop growth and development data observed at the field experiment at Kpalesawgu. Maize variety obatanpa was used in the experiment. The cultivar coefficient was calibrated with data collected from the field experiment. All measured data on phenology, grain yield and biomass from the field experiment were used for model validation and simulations.

References

36 Cites in Article
  1. 1. T. Addiscott (1985). Concepts of solute leaching in soils: a review of modelling approaches. Journal of Soil Science, 36(3), 411-424.
  2. 2. T. Addiscott,A. Whitmore (1987). Computer simulation of changes in soil mineral nitrogen and crop nitrogen during autumn, winter and spring. Camb, 109, 141-157.
  3. 3. S. Adu (1995). Soils of the Nasia basin.
  4. 4. B. Badu-Apraku,M. Fakorede,S. Ajala,L. Fontem (2004). Strategies of WECAMAN to promote the adoption of sustainable maize production technologies in West and Central Africa J Food Agric. J. Food. Agric. Environ, 2(3&4), 106-113.
  5. 5. G. Benneh,G. Agyepong,J. Allotey (1990). Land degradation in Ghana.
  6. 6. C. Black (1965). Methods of Soil Analysis. Methods of soil analysis. Part I. Physical and mineralogical properties, including statistics of measurements and sampling. Part II. Chemical and mineralogical properties
  7. 7. L. Bundy,T. Andraski,J. Powell (2001). Management Practice Effects on Phosphorus Losses in Runoff in Corn Production Systems. Journal of Environmental Quality, 30(5), 1822-1828.
  8. 8. Craig Chase,Michael Duffy,John Webb,Regis Voss (1991). An economic assessment of maintaining high phosphorus and potassium soil test levels. American Journal of Alternative Agriculture, 6(2), 83-86.
  9. 9. A. Chaudhry (1983). Maize in Pakistan.
  10. 10. F. Cox,I. Lins (1984). A phosphorus soil test interpretation for corn grown on acid soils varying in crystalline clay content. Communications in Soil Science and Plant Analysis, 15(12), 1481-1491.
  11. 11. A. Dankyi,P. Sallah,A. Adu-Appiah,A. Gyamera (2005). Determinants of the adoption of Quality Protein Maize, Obatanpa, in southern Ghana-Logistic regression analysis. Paper presented at the Fifth West and Central Africa Regional Maize Workshop, 2-7.
  12. 12. FAO Statistical Databases (2008). FAO Statistical Databases.
  13. 13. G. Hoogenboom,J. Jones,C. Porter,P. Wilkens,K. Boote,W. Batchelor,L. Hunt,G. Tsuji (2003). DSSAT v4.
  14. 14. G. Hoogenboom,J. Jones,C. Porter,P. Wilkens,K. Boote,W. Batchelor,L. Hunt,G. Tsuji (2003). DSSAT v4.
  15. 15. L. Hunt,S. Pararajasingham (1994). A and Pararajasingham, S. Genotype Coefficient Calculator, 2, 201-233.
  16. 16. W. Hussan,A. Haqqani,S. Shafeeq (2003). Knocking the doors of Balochistan for fodder crops production Agridigest - An in house J. ZTBL (Pakistan, 23, 24-30.
  17. 17. IBSNAT (1994). Decision Support System for Agrotechnology Transfer (DSSAT). User guide. Version 3.
  18. 18. John Jemison,Jalal Jabro,Richard Fox (1994). Evaluation of LEACHM: I Simulation of drainage, bromide leaching, and corn bromide uptake Agron. Agronomy Journal, 86(5), 843-851.
  19. 19. J. Jones (1983). Decision support systems for agricultural development. Systems approaches for agricultural development, 459-471.
  20. 20. J. Kiniry (1997). Evaluation of two maize models for nine U.S locations Agron. Agronomy Journal, 89(3), 421-426.
  21. 21. Neil Lecler (1998). Integrated Methods and Models for Deficit Irrigation Planning. Agricultural Systems modeting and Simulation, 283-299.
  22. 22. Laura Lengnick,Richard Fox (1994). Simulation by NCSWAP of seasonal nitrogen dynamics in corn I.: Soil nitrate Agron. Agronomy Journal, 86(1), 167-175.
  23. 23. Keith Loague,Richard Green (1991). Statistical and graphical methods for evaluating solute transport models: overview and application Contam J. Journal of Contaminant Hydrology, 7(1-2), 51-73.
  24. 24. Q. Ma,R. Wauchope,J. Hook,C. Johnson,C. Truman,G. Dowler,J. Gascho,H. Davis,R. Summer,L. Chandler (1998). GLEAMS, Opus, and PRZM-2 model predicted versus measured runoff from coastal plain loamy sand. Transactions of the ASAE, 44(1), 77-88.
  25. 25. MoFA (2000). Food and Agriculture Sector Development Policy (FASDEP I). Food Policy, 55.
  26. 26. M. Morris,R. Tripp,A. Dankyi (1999). L., Tripp, R. and Dankyi, A.A. 1999. Adoption and Impacts of Improved Maize Production Technology. A Case Study of the Ghana Grains Development Project, Economics Program Paper 99-01. Mexico, D.F., CIMMYT. Available online. Economics Program Paper, 99-01.
  27. 27. Of commercial fertilizer nutrients to food production. Agron. J, 97, 1-6.
  28. 28. F. Penning de Vries,H. Van Laar (1982). Simulation of plant growth and crop production.
  29. 29. (1989). Simulation of ecophysiological processes of growth in several crops.
  30. 30. A. Retta,L. Vanderlip,R. Haggins (1996). Application of SORKAM to Simulate Shattercane Growth Using Forage Sorghum. Agronomy Journal, 88(4), 596-601.
  31. 31. SARI (1996).
  32. 32. Mofa SRID (2007). National Crop production estimates. National Crop production estimates
  33. 33. W. Stewart,D. Dibb,A. Johnston,T. Smyth (2005).
  34. 34. C. Stockel (1997). Comparison of Crop Syst performance for water management in southwestern France using submodels of different levels of complexity. European Journal of Agronomy, 7(1-3), 89-98.
  35. 35. D. Wallach,B. Goffinet (1989). Mean squared error of prediction as a criterion for evaluating and comparing system models. Ecological Modelling, 44(3-4), 299-306.
  36. 36. Cort Willmott (1982). Some comments on the evaluation of model performance Am Meteorol Soc. Bulletin of the American Meteorological Society, 63(11), 1309-1313.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Williams Kwame Atakora., Mathias Fosu.. 2014. "Modeling Maize Production towards Site Specific Fertilizer Recommendation in Ghana". Global Journal of Science Frontier Research - D: Agriculture & Veterinary GJSFR-D Volume 14 (GJSFR Volume 14 Issue 26 (D6)).

More Citation Formats

Download Citation

Journal Specifications

Crossref Journal DOI 10.17406/GJSFR

Print ISSN 0975-5896

e-ISSN 2249-4626

Keywords
Classification
GJSFR-D Classification FOR Code: 820401
079999
Version of record
v1.2

Issue date
July 7, 2014

Language
English
Order Article Reprint
Experience in AR

Explore published articles in an immersive Augmented Reality environment. Our platform converts research papers into interactive 3D books, allowing readers to view and interact with content using AR and VR compatible devices.

Read in 3D

Your published article is automatically converted into a realistic 3D book. Flip through pages and read research papers in a more engaging and interactive format.

Article Matrices
Total Views: 1.1K
Total Downloads: 93
All Trends

Request Access

Please fill out the form below to request access to this research paper. Your request will be reviewed by the editorial or author team.
X

This is the heading

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.

High-quality academic research articles on global topics and journals.

Modeling Maize Production towards Site Specific Fertilizer Recommendation in Ghana

Williams Atakora.
Williams Atakora. CSIR-Savanna Agricultural Research Institute
Mathias Fosu.
Mathias Fosu. <p>CSIR-Savanna Agricultural Research Institute</p>