1 / 51

Efficiency of data presentation & utilization in state soybean variety trials

This report explores the efficiency of data presentation and utilization in state soybean variety trials. It discusses the methods used for data collection, analysis, and presentation, as well as the utilization of this data in variety selection and research. The report also highlights the benefits of utilizing a database for soybean variety trials.

sbreeden
Télécharger la présentation

Efficiency of data presentation & utilization in state soybean variety trials

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Efficiency of data presentation & utilization in state soybean variety trials Lingxiao (Ling) Zhang Delta Research and Extension Center Mississippi State University Tampa, FL. 01-28-2010

  2. State Soybean Variety Test Procedures Recommendations OVT Group Producers Seed company Uni. researcher Extension agent Find locations & cooperators Result Report Variety collection Data analysis Experimental design Data collection Harvest Preparation Planting

  3. Hard copy Report Methods for OVT • Field Day • Internet • htm • pdf • - xls • - database

  4. Soybeans Variety Test Results in Illinois

  5. SOYVA 2009 - Soybean Variety Selection Program (SOYVA) is a computerized soybean variety selection program (U-AR). 

  6. Database Modeling Information system Internet Data Utilization from OVT Deltasoy An Internet-base soybean variety trial database for research, extension and production

  7. Diagram of a three-tier of architecture of a Web-based database

  8. Entity relationship diagram of parameters in Deltasoy database.

  9. Dependency diagram of parameters in Deltasoy database.

  10. Variety selection interface of Deltasoy

  11. An example of Deltasoy result table

  12. Multi-year => result

  13. Multi-year => single variety)

  14. Deltasoy – Home page

  15. Variety comparison of Deltasoy Database

  16. “Disease info” of Deltasoy Database

  17. Soypheno

  18. “SoyPheno” of Deltasoy Database

  19. SoyPheno - search results & recommendation

  20. A database for national soybean OVT? Soyrus Soy-r-us

  21. Who gets benefit from Soyrus? • Crop grower • Seed company • Private consultant • County agent • University researcher

  22. How can a database help? • Multi-year • Multi-location • Comparing different Variety or systems • Add more function for analysis (weighted) • Vt = (a) P1 + (b) P2 + (c) P3 + … • Long-term data accumulation • Initial other research topics

  23. Modify Soybean MG Adaptation Zones (Scott and Aldrich, 1970)

  24. Test site distribution of OVT MI IL SD MS

  25. Materials and Methods • Data sources - State soybean variety trials - All soybean producing states Data criteria - Most of irrigated test - Yield over 45 bu/A (3030 kg/h) - 30 varieties or more in a test - Planting date within certain range

  26. Map construction (Locations selected for creating adaptive zones of soybean MG in the USA)

  27. Zones of optimum soybean maturity groups for maximum yield in the US (Figure was created by the Kriging interpolation method using variety trial data from 1998 to 2003 )

  28. Modified zone of optimum soybean maturity groups for maximum yield in the US

  29. Application of OVT data • Growth stage and maturity prediction at all location? • Data source – latitude, PD & MD • Method – modeling (regression, ANN, etc.)

  30. Information links to soybean producing states in the USA

  31. Diagram of 3-layers of back propagation ANN

  32. A sigmoid function and calculation process for one node.

  33. Potential researchable topics using an OVT database • * Yield trend? • - historical data may tell real genetic gain? • * Environmental effects on yield? • G x E • Soil type, • Irrigation, disease, insect • * Protein & oil content? • Type of variety • Year trend under diff. envion. conditions

  34. Major Problems • Funding - USB ? - Other agents? • Need action • Form a committee • Different focuses for each state • - Focus on the similarity

  35. Parameters in database Common Variety name MG (RM) Yield Plant height Maturity Date Location Irri. vs. N-iir. Conv. vs. RR (Planting Date) ….. May be Varied Shattering score Lodging score Protein content Oil content ….. Genetic controlled Flower& Pod Pubescence Disease …..

  36. Other Problems • Update information? • - Variety turn over past • - Disease resistance • Website/Server maintenance • Web submission • Other

  37. A Diagram of Soyrus for Soyean Production

  38. Thank You ! Question?

  39. Field Day – what makes up the lunch?

  40. Comparison summary • The adaptive zone for one MG is about 3-4 degrees latitude, wider than it was suggested, especially for mid-late MGs (>III) in the south. • VI is the latest MG adapted in the US for the optimum yield, and MG VII-VIII are not optimum MGs for the US (if not count FL) 00- • Late maturity (VI) soybeans adapted to East coast rather than the Midsouth due to available late precipitation.

  41. Recent Soybean Variety Turn-over Ratio Data source: popular conventional and roundup ready soybean varieties collected by NCST (n=245)

  42. Zones and planting date divided for soybean producing states involved in MG map construction

  43. Materials and Methods (cont.) • Determination of the values of optimum maturity groups - regression method: yield vs. MG - maximum yield weighted average

  44. Determination of MG values using regression

More Related