2014_08_22_PrecitionAg

The Development of Crop Monitoring Tech: Part 1

posted: August 22, 2014 | author: Aaron Lawrence

Woolpert is currently working on a research study, one of the first of its kind in terms of data collection methodologies and layered sensing analysis.

In collaboration with Air Force Research Labs (AFRL), the Ohio State University (OSU) and the Design Knowledge Company (TDKC), we are excited to work on a project that will hopefully lead to a crop monitoring plan that helps farmers visualize trends in the field, provides a better understanding of the growth cycle, and allows for earlier identification of crop health issues. This research’s potential ultimately includes better crop yields, a benefit to both farmers and the general public alike.

To complete this goal, we have developed three main focuses of research including corn emergence, hyperspectral reflectance of corn and crop vigor. As we continue, we will unveil our lessons learned and updates from our research. Follow us as we develop this technology for the masses.

Corn Emergence

Our goal is to define what spatial resolution of photography is needed to see crops at different stages throughout the growing season. The primary mission is to determine the earliest stage in the growth cycle that vegetation can be detected. If possible, we also are aiming to identify and count seedlings as they sprout from the ground.

Hyperspectral Reflectance

Our team will be collecting field spectra of 16 different corn hybrids with a handheld spectrometer throughout the growing season with the intention of trying to identify and separate the hybrids using spectral analysis. Essentially, we are trying to build a spectral library containing information about each hybrid and how it changes throughout its life cycle.

Crop Vigor

We want to quantify what effects soil compaction has on overall plant health and yield. To do so, this study is targeted at assessing the crop vigor of both corn and soybeans after severe compaction events were experienced during the spring planting.

Data inputs for these studies include:

  • High-resolution multispectral photography
  • Precision planting technology
  • Tractor telemetry
  • Field spectra using handheld spectrometer

This research study will be ongoing, and we have full intentions of not only taking lessons learned from our data collection and analysis techniques this year and sharing them with you, but also applying them to future research.