Managing Global Resources for a Secure Future

2017 Annual Meeting | Oct. 22-25 | Tampa, FL

33-7 Utilizing Mobile Applications and RGB Imagery for Estimating Grain Yield in Winter Wheat.

See more from this Division: ASA Section: Agronomic Production Systems
See more from this Session: Development of Tools for Precision Agriculture I (includes student competition)

Monday, October 23, 2017: 9:50 AM
Marriott Tampa Waterside, Room 3

Ashley Lorence, Kansas State University, Manhattan, KS and Antonio Ray Asebedo, Department of Agronomy, Kansas State University, Manhattan, KS
Abstract:
In Today’s world technology is advancing daily especially, in the agriculture communities. Hand held active optical sensors (AOS) have the potential to assess the N status of winter wheat in these cropping systems by optimize N recommendations and increasing yield. However, considering most producers own smart phones, it may be possible to utilize these devices instead of AOS for estimating yield and N status. Therefore, making the purchase of AOS unnecessary. This study was conducted to determine if RGB images from mobile devices could be used to predict yield in winter wheat. Field trials across Kansas were conducted during the 2015-2016 & 2016-2017 crop season in cooperation with County Ag Agents and producers. Images and AOS readings were taken at Zadoks growth stage 30, 32, 37, and 39 across sites for each plot. Results indicate RGB images from mobile devices prove to be a viable tool for predicting yield in winter wheat.

See more from this Division: ASA Section: Agronomic Production Systems
See more from this Session: Development of Tools for Precision Agriculture I (includes student competition)