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dc.contributor.advisorChairperson, Graduate Committee: Richard Engel; Daniel Long (co-chair)en
dc.contributor.authorMeier, Corey Granten
dc.date.accessioned2013-06-25T18:39:45Z
dc.date.available2013-06-25T18:39:45Z
dc.date.issued2004en
dc.identifier.urihttps://scholarworks.montana.edu/xmlui/handle/1/1855en
dc.description.abstractThe feasibility of using a combine harvester mounted, Case New Holland ProSpectra TM Grain Analyzer to determine protein content of hard red spring wheat (Triticum aestivum L.) was tested at a level of accuracy of 0.5% protein. Should the sensor meet the target accuracy, it would be useful for on-farm segregation of wheat by protein content and for field mapping protein. Geo-referencing protein values in the field, at harvest, enables creation of protein maps to be used as surrogates for maps of soil nitrogen for directing variable rate nitrogen applications. Models were developed in the lab using partial least squares regression to relate spectra in near infrared wavelengths to grain protein, then tested on a combine harvester. The sensor did not meet the target level of accuracy in the lab and performance degraded in the field. Poor field performance was due to the presence of contaminants present in grain samples at harvest and to sensor hardware problems that yielded inconsistent results. These results suggest that the sensor is not accurate for the purpose of segregating grain, but may be accurate enough to characterize broad patterns of variability in a field to direct soil sampling efforts, if hardware problems can be fixed to replicate the best lab results in the field. An approach to characterize topographic relief in fields using LandmapR TM software in a geographic information system was utilized to relate hillslope position to grain protein and yield variability. A direct relationship would allow partitioning fields into management zones for directing soil sampling efforts and variable rate applications of soil nitrogen based on hillslope. A five class categorical hillslope model and wetness index explained the most variability of the models tested, explaining less than 24% variance in protein and less than 18% variance in yield. Hot conditions during grain fill were likely responsible for the low variance. Yield and protein increased downslope, most likely in response to deeper soils at downslope positions that retained moisture later in the growing season for plant uptake. Hillslope position was deemed inadequate to predict grain protein and yield, but sufficient for directing soil sampling.en
dc.language.isoenen
dc.publisherMontana State University - Bozeman, College of Agricultureen
dc.subject.lcshWheaten
dc.subject.lcshRemote sensingen
dc.subject.lcshSoilsen
dc.subject.lcshPlant geneticsen
dc.titleProtein mapping spring wheat using a mobile near-infrared sensor and terrain modelingen
dc.typeThesisen
dc.rights.holderCopyright 2004 by Corey Grant Meieren
thesis.catalog.ckey1146923en
thesis.degree.committeemembersMembers, Graduate Committee: William F. Quimby; Gerald Nielsenen
thesis.degree.departmentLand Resources & Environmental Sciences.en
thesis.degree.genreThesisen
thesis.degree.nameMSen
thesis.format.extentfirstpage1en
thesis.format.extentlastpage77en
mus.relation.departmentLand Resources & Environmental Sciences.en_US


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