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oai:www.ideals.illinois.edu:2142/44494 2023-07-11 col_2142_14847 col_2142_5131 com_2142_683 com_2142_397 com_2142_5130

Grift, Tony E. Roy, William 2013-05-24T22:18:12Z 2013-05-24T22:18:12Z 2015-05-24T10:01:48Z 2013-05 2013-05-24T22:18:12Z 2013-05 Over the past few decades, both researchers and commercial farmers have attempted to find means to accurately predict crop yields during the growing season. Modern science has been successful in mapping the genes of crops to help aid in drought protection, germination timing, and frost protection. These biological traits have assured crop seed strength and protection, enabling higher yields. However, many other physical traits such as plant height, leaflet count, color, germination rate, and biomass are indicators of the plants’ overall health and future yields. This research provided a means in which an operator can measure an individual trait of a corn plant, and predict yield. The first study used an imaging system comprising a CCD camera and a slanted laser sheet, to measure the diameter of the corn stalk. After processing the data, the diameters of the corn stalks were shown to be positively correlated with the grain weight of the corn ear. Therefore, the system allows the farmer to predict the per-plant-yield (PPY) based on measuring the diameters of the corn stalks. In addition, the measurement system is easy to use, and is not affected by environmental conditions such as ambient light. The accuracy of the optical system was determined by comparing the measurements against those taken with a pair of digital calipers. 26.7 and 33.5 mm PVC tubes were used to assess the measurement accuracy. The optical system measured the diameter of the PVC tubes with an accuracy of 98% while varying the location of the PVC tubes within the measurement zone. The same optical system was used in the greenhouse to measure diameters of corn stalks, where the accuracy decreased to 84% due to measurement location variability created by the corn stalks. The theme of phenotyping was extended in the second part of the research. While the corn stalk data could be used to predict the PPY, the below ground root system is indicative of iii the plants’ stability, and of its ability to reach nutrients and water. A “Rhizotron” was constructed, which consists of a soil volume, visible behind a vertical glass pane. By growing a single corn plant in the Rhizotron, its roots are being pushed against the glass pane which allows for studying root development over time. A key parameter is the root angle, which has been shown highly influential in explaining the historic yield increases in the Midwest over the past decades (Hammer, et al., 2002). Since the roots grow behind a glass pane, the challenge was to obtain high resolution images of the root systems without reflections created on the glass. A camera was mounted on a linear actuator that allowed for taking images that can be overlapped to produce a complete mosaic of the root system. Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2013-04-25T19:40:00Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 2 Roy_William.docx: 11968230 bytes, checksum: 5f287bfdf296ccb2f41ebbc8ee384822 (MD5) Roy_William.pdf: 3747781 bytes, checksum: f82db4a00d1db0e64ede99c0711e37bd (MD5) Made available in DSpace on 2013-05-24T22:18:12Z (GMT). No. of bitstreams: 3 William_Roy.pdf: 3747535 bytes, checksum: 6d962d603436e5a8deaccf88f9e5cdf3 (MD5) Roy_William.docx: 11968230 bytes, checksum: 5f287bfdf296ccb2f41ebbc8ee384822 (MD5) license.txt: 4058 bytes, checksum: 5a0a0e6b1a28a976e77637b05199ef4a (MD5) Item marked as restricted to the 'UIUC Users [automated]' Group (id=2) by Seth Robbins (srobbins@illinois.edu) on 2013-05-24T22:19:27Z Item is restricted until 2015-05-24T22:18:31Z Restriction data tranferred 2014-07-01T11:36:21-05:00 Original Data Group with Access UIUC Users [automated] Release Date: 2015-05-24 17:18:31 UTC Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system U of I Only Restriction Lifted for Item 44467 on 2015-05-24T10:01:48Z. http://hdl.handle.net/2142/44494 en Copyright 2013 William Roy high throughput phenotyping rhizotron Above and below ground phenotyping methods for corn text Agricultural & Biological Engr 1741 Technical Systems Management 0025 University of Illinois at Urbana-Champaign Thesis M.S. MS: Tech Sys Mgmt - UIUC 10KS0025MS