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AQS: An Analytical Query System for Multi-Location Rice Evaluation Data

  • Nazareno, Franco (Chungbuk National University, Dept. of Bio-Information Technology) ;
  • Jung, Seung-Hyun (Chungbuk National University, Dept. of Information Industrial Engineering) ;
  • Kang, Yu-Jin (Chungbuk National University, Dept. of MIS / u-Biz BK21 Team) ;
  • Lee, Kyung-Hee (Chungbuk National University, Dept. of MIS / u-Biz BK21 Team) ;
  • Cho, Wan-Sup (Chungbuk National University, Dept. of MIS / u-Biz BK21 Team)
  • Received : 2010.06.08
  • Accepted : 2010.06.20
  • Published : 2010.06.30

Abstract

Rice varietal information exchange is vital for agricultural experiments and trials. With the growing size of rice data gathered around the world, and numerous research and development achievements, the effective collection and convenient ways of data dissemination is an important aspect to be dealt with. The collection of this data is continuously worked out through various international cooperation and network programs. The problem in acquiring this information anytime anywhere is the new challenge faced by rice breeders, scientist and crop information specialists, in order to perform rapid analysis and obtain significant results in rice research, thus alleviating rice production. To address these constraints, we propose an Online Analytical Query System, a web query application to provide breeders and rice scientist around the world a fast web search engine for rice varieties, giving the users the freedom to choose from which trial it has been used, trait observation parameters as well as geographical or weather conditions, and location specifications. The application uses data warehouse techniques and OLAP for summarization of agricultural trials conducted, and statistical analysis in deriving outstanding varieties used in these trials, consolidated in an Model-View-Controller Web framework.

Keywords

References

  1. J. P. Bradley, K. H. Knittle, A. F. Troyer, "Statistical methods in seed corn product selection," Journal of Production Agriculture, vol. 1, pp.34-38, 1988. https://doi.org/10.2134/jpa1988.0034
  2. R. Bruskiewich, et. al., "Generation Challenge Program (GCP): Standards for Crop Data," OMICS Journal of Integrative Biology, vol. 10, no. 2, pp.215-219, 2006. https://doi.org/10.1089/omi.2006.10.215
  3. R. Elmasri and S. Navathe. Fundamentals of Database Systems. Boston, MA: Addison Wesley, 2006.
  4. W. Federer, M. Reynolds, J. Crossa, "Combining results from augmented designs over sites," Agronomy Journal, vol. 93, pp.389-395, 2001. https://doi.org/10.2134/agronj2001.932389x
  5. K. Gomez and A. Gomez. Statistical procedures for agricultural research. New York, NY: Wiley-Interscience, 1984.
  6. J. J. Johnson, J. R. Alldredge, S. E. Ullrich, "Replacement of replications with additional locations for grain sorghum cultival evaluation," Crop Science, vol. 32, pp.43-46, 1992. https://doi.org/10.2135/cropsci1992.0011183X003200010010x
  7. R. Kimball and M. Ross. The Data Warehouse Toolkit: The complete guide to dimensional modeling. New York, NY: Wiley Computer Publishing, 2002.
  8. S. Ladd, K. Donald, D. Davison, S. Devijver, C. Yates. Expert Spring MVC and Web Flows. Berkeley, CA, 2006.
  9. J. Machacek, A. Vukotic, A. Chakraborty, J. Ditt. Pro Spring 2.5. Berkeley, CA: Apress, 2008.
  10. C. G. McLaren, R. Bruskiewich, A. Portugal, A. Cosico, "The International Rice Information System - A Platform for Meta-Analysis of Rice Crop Data," Plant Physiology, vol. 139, pp. 637-642, 2005. https://doi.org/10.1104/pp.105.063438
  11. The Spring Framework - Reference Documentation. Retrieved on February, 2010 from http://www.springsource.org/.