1 / 13

Sensing Resolution in Corn

Sensing Resolution in Corn. Kyle Freeman Soil 4213 4-29-02. Objectives of the Precision Sensing Team at Oklahoma State University. Determine suitable resolution for corn to efficiently and economically sense and fertilize on the go using Greenseeker ™ lighted sensors. Hypotheses.

deepak
Download Presentation

Sensing Resolution in Corn

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. Sensing Resolution in Corn Kyle Freeman Soil 4213 4-29-02

  2. Objectives of the Precision Sensing Team at Oklahoma State University • Determine suitable resolution for corn to efficiently and economically sense and fertilize on the go using Greenseeker™ lighted sensors.

  3. Hypotheses • It is possible to accurately predict final yield on a by-plant basis. • Corn should be treated similar to winter wheat, sensing and treating each square meter. • The sensing resolution of corn should be large including by row for a set distance, or even larger than that like x-rows by y-distance.

  4. Spatial Variability in Soils • Raun et al. (1998) found significant differences in mobile an immobile nutrients on a sub-meter scale. • Solie et al. (1999) stated that in order to describe the variability encountered in the field, measurements should made at the submeter level.

  5. Resolution in Winter Wheat • Raun et al. (2001) showed the ability to predict yield on 2m x 2m areas by taken the sum of two NDVI reading and dividing it by the GDDs between the two readings. • Lukina et al. (2001) showed a stronger correlation between yield and one NDVI reading divided by the total number days from planting where GDD>0.

  6. Wheat Resolution cont. • Raun et al. (2002) demonstrated that sensing and treating 1m2 areas could increase yields decrease N inputs and increase NUE.

  7. Methods to Determine Field Resolution in Corn. • Environments • Dryland • Irrigated • Varieties • Hybrids and open pollinated varieties • Maturities • GMO’s and conventional • Nutrient status • Nitrogen • Micronutrients

  8. Methods cont. • Plant architecture • Large plants and rooting zones • During sensing period do not have 100% ground cover. • Engineering issues • By plant sensing and treating is a possibility • Where to apply fertilizer (foliar or to the soil) • What types of fertilizer can we apply (liquids, solids, and AA)

  9. Methods cont. • Agronomy issues • Determining algorithms that work across hybrids and environments • Determining the most efficient and practical means to apply nitrogen fertilizer to maize to increase yield and NUE. • To continually destroy all new sensing equipment developed by the engineers.

  10. What about other Research • University of Nebraska • Using aerial imaging at a 0.5 m2 resolution • Ground rig sense and treat applicator operates at approximately 9 m2 • Everybody else • Who knows • Currently not much work on fertilizing small scale resolution in corn.

  11. Expected Results • Who Knows! That is why I have a job. • A reliable algorithm and N management strategy will be developed at OSU by the Precision Ag Sensing team. • Small scale resolution will be essential to making precision ag technology work in corn.

  12. Importance to Precision Ag • Precision Ag Technologies will be advancing in Maize and Greenseeker and OSU wants to be a part of it. • Corn precision ag systems will drive the industry to adapt new technologies. • Due to higher input costs • More intensively managed.

  13. Questions?

More Related