Ground-based, remotely sensed reflectance and temperature data were collected over differentially irrigated, developing cotton and sorghum canopies in order to investigate interrelations of these parameters; to monitor their temporal changes ; to understand their spatial structure ; and to estimate crop coefficient (KO from canopy reflectance. Spectral reflectance and derived vegetation indices showed ability to significantly discriminate among differential irrigation levels of sorghum canopies, starting the fourth week of growth. All vegetation indices increased as a result of crop development, with the perpendicular vegetation index (PVI ) demonstrating the greatest potential for assessing water stress conditions, whereas, soil indices behaved independently of crop development and water stress. Canopy temperature and derived water stress indices, on the other hand, were in high concordance and were able to detect crop water stress with variable degrees of sensitivity. Experimental variograms revealed that cotton reflectance and temperature were not spatially dependent when all water treatments were included. For the moisture stress treatments, only canopy temperature exhibited spatial dependence early in the period of stress. Sorghum canopy reflectance and temperature demonstrated some spatial structure; however, a drift was suspected due to regularity in the data spatial distribution. Normalized difference (ND), normalized perpendicular vegetation index (NPVI) and normalized green vegetation index (NGVI), for fifty days covering the period from planting to heading, were fitted with a complementary error function equation with minor adjustment. Both NPVI and NGVI displayed a 1:1 relation with interpolated tabular values of basal Kc, whereas ND deviated from the 1:1 relation for the period beyond 30 days after planting. The model was also found to be valid for estimating K(c) for moderately deficit irrigation conditions.

A Coulostatic Impulse Generator (CIG) is an electronic device that transfers electrical charge to and from a pair of electrodes inserted in plant tissue. Six discrete charge transfers can be implemented in any desired sequence. The major purpose of the CIG is to determine the electrochemical constituents of the plant apoplast electrolyte. The objective of this thesis is threefold: (1) to design, construct and test the supervisory circuitry of the CIG, (2) to design, construct and test the interface between the NEC portable computer and the CIG, (3) to generate utility software to control each circuit board in the system. To handle the extreme difference in the timing of the charge transfer (microseconds) and the subsequent plant response a three step timing sequence is employed which permits an independent range of sample times and sample numbers. Data acquired is first stored in RAM in the computer within the CIG and then transferred to the external computer. (Abstract shortened with permission of author.)

The measurement of plant water content is essential to assess stress and disturbance in forest plantations. Traditional techniques to assess plant water content are costly, time consuming and spatially restrictive. Remote sensing techniques offer the alternative of a non destructive and instantaneous method of assessing plant water content over large spatial scales where ground measurements would be impossible on a regular basis. The aim of this research was to assess the relationship between plant water content and reflectance data in Eucalyptus grandis forest stands in KwaZulu-Natal, South Africa. Field reflectance and first derivative reflectance data were correlated with plant water content. The first derivative reflectance performed better than the field reflectance data in estimating plant water content with high correlations in the visible and mid-infrared portions of the electromagnetic spectrum. Several reflectance indices were also tested to evaluate their effectiveness in estimating plant water content and were compared to the red edge position. The red edge position calculated from the first derivative reflectance and from the linear four-point interpolation method performed better than all the water indices tested. It was therefore concluded that the red edge position can be used in association with other water indices as a stable spectral parameter to estimate plant water content on hyperspectral data. The South African satellite SumbandilaSat is due for launch in the near future and it is essential to test the utility of this satellite in estimating plant water content, a study which has not been done before. The field reflectance data from this study was resampled to the SumbandilaSat band settings and was put into a neural network to test its potential in estimating plant water content. The integrated approach involving neural networks and the resampled field spectral data successfully predicted plant water content with a correlation coefficient of 0.74 and a root mean square error (RMSE) of 1.41 on an independent test dataset outperforming the traditional multiple regression method of estimation. The potential of the SumbandilaSat wavebands to estimate plant water content was tested using a sensitivity analysis. The results from the sensitivity analysis indicated that the xanthophyll, blue and near infrared wavebands are the three most important wavebands used by the neural network in estimating plant water content. It was therefore concluded that these three bands of the SumbandilaSat are essential for plant water estimation. In general this study showed the potential of up-scaling field spectral data to the SumbandilaSat, the second South African satellite scheduled for launch in the near future. / Thesis (M.Sc.) - University of KwaZulu-Natal, Pietermaritzburg, 2008.