Thesis (M.S.)--Oregon State University, 1982. / Typescript (photocopy). Includes bibliographical references (leaves 80-83). Also available on the World Wide Web.

Thesis (Ph. D.)--University of Wisconsin--Madison, 1961. / Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

No description available.

Soil-plant relationships around an inland, saline slough were investigated. It was found that the release of soluble salts from feldspar minerals in soil and rock materials, and the gradual transfer of salts downslope had led to the salinization of the slough. The salinity of the slough was found to be related to annual and seasonal climatic cycles. High osmotic pressure and salt content of the soil solution adjacent to the slough precluded the growth of non-halophytic plant species. Within the area of soils affected by salts around the slough, it was found that Saltgrass #1, which occupied the zone adjacent to the slough was more tolerant of saline and alkali soil conditions and of prolonged inundation than Saltgrass #2 which grew in the second zone. Although the distribution of halophytes and non-halophytes was related to soil salinity and alkalinity, the distribution of non-halophytic plant communities within the zone of normal soils was controlled by variations in site microclimate due to the configuration of the landscape. Weathering, the nature and formation of the saline slough, and the nature and distribution of the soils and plant communities were found to be mutually dependent and the products of the same five factors: climate, relief, geologic materials, organisms, and time. / Land and Food Systems, Faculty of / Graduate

This item was digitized as part of the Million Books Project led by Carnegie Mellon University and supported by grants from the National Science Foundation (NSF). Cornell University coordinated the participation of land-grant and agricultural libraries in providing historical agricultural information for the digitization project; the University of Arizona Libraries, the College of Agriculture and Life Sciences, and the Office of Arid Lands Studies collaborated in the selection and provision of material for the digitization project.

A research report submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in partial fulfillment of the requirements for the degree of Master of Science (Geographical Information Sciences and Remote Sensing) Johannesburg, 2017 / Soil organic carbon is considered as the most determining indicator of soil fertility. The purpose of this research was to predict the soil organic carbon in the Mokhotlong region, eastern of Lesotho using in situ spectral measurements and random forest regression. Soil reflectance spectra were acquired by a portable field spectrometer. The performance of random forest regression was assessed by comparing it with one of the most popular models in spectroscopy, partial least square regression. Laboratory spectroscopy measurements of the soil samples were analysed for assessing the accuracy of in situ spectroscopy based-models. The effect of the Savitzky−Golay first derivative in improving partial least square regression and random forest regression in both spectral data was also assessed. The results indicated that the random forest regression could accurately predict the soil organic carbon contents on an independent dataset using in situ spectroscopy data (RPD = 3.77, Rp2= 0.88, RMSEP = 0.64%). The overall best predictive model was achieved with the derivative laboratory spectral data using random forest with the optimum number of key wavelengths (RPD = 3.77, Rp2= 0.88, RMSEP = 0.64%). In contrast, partial least square regression was likely to overfit the calibration dataset. Important wavelengths to predict soil organic contents were localised around the visible range (400-700 nm). An implication of this research is that soil organic carbon can accurately be estimated using derivative in situ spectroscopy measurements and random forest regression with key wavelengths. / MT 2017

Thesis (M.S.)--Oregon State University, 1983. / Typescript (photocopy). Includes bibliographical references (leaves 32-33). Also available on the World Wide Web.

No description available.

Thesis (M.S.)--Oregon State University, 1988. / Typescript (photocopy). Mounted photographs. Includes bibliographical references (leaves 100-103). Also available on the World Wide Web.

Thesis (Ph. D.)--Ohio State University, 2009. / Title from first page of PDF file. Includes vita. Includes bibliographical references (p. 91-95).