Agricultural production has observed many changes in technology over the last 20 years. Producers are able to utilize technologies such as site-specific applicators and remotely sensed data to assist with decision making for best management practices which can improve crop production and provide protection to the environment. It is known that plant stress can interfere with photosynthetic reactions within the plant and/or the physical structure of the plant. Common types of stress associated with agricultural crops include herbicide induced stress, nutrient stress, and drought stress from lack of water. Herbicide induced crop stress is not a new problem. However, with increased acreage being planting in varieties/hybrids that contain herbicide resistant traits, herbicide injury to non-target crops will continue to be problematic for producers. With rapid adoption of herbicide-tolerant cropping systems, it is likely that herbicide induced stress will continue to be a major concern. To date, commercially available herbicide-tolerant varieties/hybrids contain traits which allow herbicides like glyphosate and glufosinate-ammonium to be applied as a broadcast application during the growing season. Both glyphosate and glufosinate-ammonium are broad spectrum herbicides which have activity on a large number of plant species, including major crops like non-transgenic soybean, corn, and cotton. Therefore, it is possible for crop stress from herbicide applications to occur in neighboring fields that contain susceptible crop varieties/hybrids. Nutrient and moisture stress as well as stress caused by herbicide applications can interact to influence yields in agricultural fields. If remotely sensed data can be used to accurately identify specific levels of crop stress, it is possible that producers can use this information to better assist them in crop management to maximize yields and protect their investments. This research was conducted to evaluate classification of specific crop stresses utilizing hyperspectral remote sensing.

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Persistence of perennial grass crops is essential to their profitable management. Recently, orchardgrass producers in the Mid-Atlantic have reported a reduction in the persistence and regrowth vigor of their swards. The overall objective was to evaluate which factors play a major role in controlling the persistence of orchardgrass harvested for hay in the Mid-Atlantic. A survey of orchardgrass fields, growth chamber experiment, and field experiment were conducted to that end. The objectives were to: (1) assess soil fertility, management practices, disease status, and climate in relation to producer perceived stand persistence rating, orchardgrass biomass, and soil test thresholds in orchardgrass hayfields in 4 states, (2) examine the interactions of high temperature and low cutting height on the physiology and regrowth of orchardgrass in controlled environments, and (3) evaluate yield, composition, and size/density compensation-corrected productivity of orchardgrass and orchardgrass/alfalfa mixtures harvested to four cutting heights over three years. The survey of hayfields indicated that the sward age, soil organic matter, grazing, manure application, and historical average high temperature were main determinants of stand persistence score. In the growth chamber experiment, regrowth was significantly reduced by the 35°C treatment as compared to 20°C. Low cutting height significantly reduced regrowth in the cool temperature treatment, but no effect of cutting height was detected under heat stress. In the field experiment, yields were highest from plots cut to 5 cm, but orchardgrass cover in these plots thinned through the experiment. Tiller size and density measurements indicated that cutting heights of 10 cm or greater were able to achieve and maintain optimal leaf area while productivity was reduced for the 5 cm treatment. Overall, it is apparent that excessively low cutting heights are a major cause of reduced persistence in orchardgrass swards and that high temperature stress will limit regrowth. These factors likely interact with fertility and disease status, and together cause the premature loss of orchardgrass stands. Efforts should be made to communicate the importance of increased cutting height to producers. Breeding of orchardgrass resistant to fungal pathogens and heat stress may be required to sustain an orchardgrass hay industry in the Mid-Atlantic. / Ph. D.

Detecting stress in plants resulting from different stressors including nitrogen deficiency, salinity, moisture, contamination and diseases, is crucial in crop production. In the Nile Valley, crop production is hindered perhaps more fundamentally by issues of water supply and salinity. Predicting stress in crops by conventional methods is tedious, laborious and costly and is perhaps unreliable in providing a spatial context of stress patterns. Accurate and quick monitoring techniques for crop status to detect stress in crops at early growth stages are needed to maximize crop productivity. In this context, remotely sensed data may provide a useful tool in precision farming. This research aims to evaluate the role of in situ hyperspectral and high spatial resolution satellite remote sensing data to detect stress in wheat and maize crops and assess whether moisture induced stress can be distinguished from salinity induced stress spectrally. A series of five greenhouse based experiments on wheat and maize were undertaken subjecting both crops to a range of salinity and moisture stress levels. Spectroradiometry measurements were collected at different growth stages of each crop to assess the relationship between crop biophysical and biochemical properties and reflectance measurements from plant canopies. Additionally, high spatial resolution satellite images including two QuickBird, one ASTER and two SPOT HRV were acquired in south-west Alexandria, Egypt to assess the potential of high spectral and spatial resolution satellite imagery to detect stress in wheat and maize at local and regional scales. Two field work visits were conducted in Egypt to collect ground reference data and coupled with Hyperion imagery acquisition, during winter and summer seasons of 2007 in March (8-30: wheat) and July (12-17: maize). Despite efforts, Hyperion imagery was not acquired due to factors out with the control of this research. Strong significant correlations between crop properties and different vegetation indices derived from both ground based and satellite platforms were observed. RDVI showed a sensitive index to different wheat properties (r > 0.90 with different biophysical properties). In maize, GNDVIbr and Cgreen had strong significant correlations with maize biophysical properties (r > 0.80). PCA showed the possibility to distinguish between moisture and salinity induced stress at the grain filling stages. The results further showed that a combined approach of high (2-5 m) and moderate (15-20) spatial resolution satellite imagery can provide a better mechanistic interpretation of the distribution and sources of stress, despite the typical small size of fields (20-50 m scale). QuickBird imagery successfully detects stress within field and local scales, whereas SPOT HRV imagery is useful in detecting stress at a regional scale, and therefore, can be a robust tool in identifying issues of crop management at a regional scale. Due to the limited spectral capabilities of high spatial resolution images, distinguishing different sources of stress is not directly possible, and therefore, hyperspectral satellite imagery (e.g. Hyperion or HyspIRI) is required to distinguish between moisture and salinity induced stress. It is evident from the results that remotely sensed data acquired by both in situ hyperspectral and high spatial resolution satellite remote sensing can be used as a useful tool in precision farming in the Nile Valley, Egypt. A combined approach of using reliable high spatial and spectral satellite remote sensing data could provide better insight about stress at local and regional scales. Using this technique as a precision farming and management tool will lead to improved crop productivity by limiting stress and consequently provide a valuable tool in combating issues of food supply at a time of rapid population growth.