Improving soybean using remote sensing, automated irrigation, and promiscuous nodulation

Schmitz, Nathan Evan

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https://hdl.handle.net/2142/99297 Copy

Description

Title

Improving soybean using remote sensing, automated irrigation, and promiscuous nodulation

Author(s)

Schmitz, Nathan Evan

Issue Date

2017-11-02

Director of Research (if dissertation) or Advisor (if thesis)

Diers, Brian

Department of Study

Crop Sciences

Discipline

Crop Sciences

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

M.S.

Degree Level

Thesis

Keyword(s)

• Soybean
• Remote sensing
• Soybean cyst nematode
• Nodulation

Abstract

Remote Sensing of Soybean Maturity Dates via Drones
High-throughput phenotyping (HTP) using remote sensing is a fast developing technology, which has the capacity to reduce the time it takes to measure phenotypic traits in the field. HTP shows particular promise as a method for predicting plant maturity. Maturity is the date where 95% of the pods reached mature color (R8 growth stage) and is commonly recorded on all yield plots in breeding programs by periodically walking through experiments and visually estimating maturity dates. Precise maturity dating is a time critical task; therefore, satellites and other previously developed methods of remote sensing would not be applicable to this research. To combat the limitations of other methods of remote sensing, we constructed a two-camera mounted Unmanned Aerial Vehicle (UAV) platform with the capacity to capture visible and near-infrared (NIR) images. This study was done in three broad steps: the acquisition of multi-spectral images using UAVs, constructing composite images of the visible and (NIR) images, and extracting digital values to build a model to predict maturity dates from images. Using these procedures, we were able to develop a binary prediction model from the multi-spectral image data and achieved over 91% accuracy in classifying soybean maturity. The maturity model was validated in an independent breeding trial with a different plot type. These results show that remote sensing can be effectively used to estimate the maturity of plots, but the analysis of images needs to be more efficient before it can be used routinely.
Automated Greenhouse SCN Screening System
Heterodera glycine (Ichinohe 1952) or soybean cyst nematode (SCN) is a pest of economic importance to soybean (Glycine max (L.) Merr.) in the USA and around the world. From 2003-2009, SCN was estimated to reduce soybean yields more than any other disease or pest in the U.S.A. Methods of control include crop rotation and nematicides, but the most effective form of control is the use of resistant soybean cultivars. The current, established greenhouse screening method uses soil-filled crocks suspended in thermoregulated water baths to control the soil temperature. No current screening method controls the soil moisture to maintain optimal levels for SCN survival and propagation. With the use of soil moisture probes that automatically controlled an irrigation system, we were able to maintain the moisture levels at a constant level. Reproduction of the SCN was improved, with a significant increase in the number of cysts counted on the soybean roots. Overall, these results demonstrate that maintaining soil moisture increases the effectiveness of greenhouse screening methods for SCN.
Promiscuous Nodulation
Soybean (Glycine max.) is an important source of oil and protein for the U.S.A. and has the potential to be a staple crop in Africa because of its high protein seed and the benefits of nitrogen fixation from the symbiotic relationship with rhizobium bacteria. Soybean has a natural relationship with Bradyrhizobium japonicum, which is not indigenous to the tropical soils in Africa. For soybean to fix nitrogen with B. japonicum, inoculants of this bacteria would be needed, which are generally not available to small-holder African farmers. The cowpea strain of rhizobium bacteria is indigenous to the soils throughout Africa, although it does not nodulate most US soybean cultivars. Some soybean accessions from the USDA Soybean Germplasm Collection can nodulate with the cowpea strain and these are called promiscuous nodulators. The objective of this study was to identify additional accessions from the germplasm collection that are promiscuous nodulators. By screening plants in inoculated pots in a greenhouse, 415 accessions were evaluated for their ability to nodulate and if the nodules were effective. Of the lines tested, 200 were able to form effective, nodules and 42 lines showed no foliar signs of chlorosis due to nitrogen deficiency. Accessions that stood out were PI 429330 (Nigeria) for the highest number of nodules produced, and PI 281883C (Indonesia) for the one of the highest average nodule weights.

Graduation Semester

2017-12

Type of Resource

text

Permalink

http://hdl.handle.net/2142/99297

Copyright and License Information

Copyright 2017 Nathan Schmitz

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