APPLICATION OF COMPUTER INTENSIVE METHODS TO EVALUATE THE PERFORMANCE OF A SAMPLING DESIGN FOR USE IN COTTON INSECT PEST MANAGEMENT

A scouting protocol for cotton insect pests was developed which combines high resolution, multispectral remotely sensed imagery with a belt transect that crosses rows of cotton. Imagery was used to determine sample site selection while estimating plant bug abundance in a more than 200 ac. cotton field in 1997. Tarnished plant bug (Lygus lineolaris) counts were acquired using a standard drop cloth for each of eight rows along a transect. The sample data indicated that plant bug population densities spatially vary as a function of different spectral (color) classes present on the imagery. We postulate that such classified images correlate to differences in crop phenology, and plant bug populations (especially from early to mid-season) aggregate themselves by these habitat differences. Therefore, the population dynamics of Lygus, and possibly other species, can be better understood by combining the transect-based sampling plan with remotely sensed imagery. To verify and validate this claim, a computer intensive approach was utilized to simulate the performance of different sampling plans. The comparison is accomplished with a combinatorial algorithm that exhaustively enumerates the original data into unique subsets. These subsets correspond to results that could be expected from the use of traditional or alternative sampling plans and compared to results from the candidate plan actually used. The results of the enumerative analysis show the benefit of multi-band, remotely sensed imagery combined with the use of large sized sample units to improve sampling efficiency (and without the need to have large sample sizes). It is of great benefit that the enumerative algorithm provided answers to questions of interest without having to complete additional fieldwork

A TEMPERATURE MODEL FOR COTTON PHENOLOGY

Agricultural production is becoming more mechanized and based on improved technology, however, many important management applications depend on crop growth stage and growing status. Crop growth rate and developmental stage depends largely on weather conditions since planting and the crop responses to temperature. We conducted experiments in naturally lighted, temperature, carbon dioxide, water and nutrients controlled plant growth chambers. Upland cotton, Gossypium hirsutum L. and pima cotton, G. barbadense L. plants were grown at a range of temperatures from 20/12 to 40/32℃ (day/night) in well watered and fertilized conditions. The plants were monitored daily to determine the rates of flower buds (squares) and flower formation, fruit maturation, and leaf/node formation. Also the duration of leaf and internode expansion was determined. Modern cultivars of these two cotton species develop squares faster at the same temperatures than cultivars used two or three decades earlier. Temperature responses of both species for time to first square, squaring to flowering, mainstem and fruiting branch node formation, and duration of leaf and internode Expansion were nonlinear. A quadratic formula expressing the duration of various developmental stages as functions of average temperature fit the data better than linear equations. Pima cotton square and fruit formation were more sensitive to temperature than upland cotton cultivars. At average temperatures above 27℃ pima cotton developed squares more slowly than upland cotton. The lengths of square and boll maturation periods in both cotton species were directly related to the temperature to which they were exposed. However, pima cotton took more time for these developmental phases compared to upland cotton. The ratio of mainstem nodes formed per fruiting branch node formed was temperature sensitive and nonlinear. Data on these developmental events/processes were used to estimate timing of leaf unfolding, duration of leaf and internode expansion, and several reproductive processes as functions of temperature