Spatial distribution of broadleaf weeds within 14 North Carolina soybean fields was characterized by fitting negative binomial distributions to frequency distributions of weed counts in each field. In most cases, the data could be represented by a negative binomial distribution. Estimated values of the parameter K of this distribution were small, often less than one, indicating a high degree of patchiness. The data also indicated that the population as a whole was patchy. Counts of individual species were positively correlated with each other in some fields and total weed count could be represented by a negative binomial for 12 of the 14 fields.

Broadleaf weeds apparently have patchy distributions within a field while POST control decisions are made assuming a regular spatial distribution. As a result, yield loss from weed competition may be overestimated, possibly leading to mistakes in choosing the optimal control treatment. Data on distribution of broadleaf weeds in 14 soybean fields were used in simulation experiments to investigate the potential for improving decision making with information about weed patchiness. The feasibility of modeling weed distribution in individual fields was also examined. Overall, the cost of assuming a regular distribution when making POST decisions was found to be low. Errors that occurred most often involved recommending more intensive control than was actually required, although in a few cases less intensive control was recommended. Error in the yield loss estimated for the uncontrolled population did not indicate the potential for a mistake in decision making for a field. Accurately modeling distribution of weeds within fields may be difficult as a result of correlations between distributions of individual species within a field and variation in distributions between fields.

A simulation model has been developed that predicts numbers and phenology of a population of codling moth, Cydia pomonella (L.), in an apple orchard. The model is a general insect population model based on the iterative-cohort technique. It operates at two time scales: a fine time scale (one hour) for temperature-dependent physiological processes, and a coarse time scale (one day) for population processes. The population is divided into a specifiable number of stages, and each stage is described by four process functions, which may be of any convenient mathematical form, and may differ among stages. Each stage is divided into cohorts of individuals born or emerged on the same day, and individuals within a cohort are considered probabilistically identical. The model simulates the processes of development, transition among stages, and mortality by using probability distributions representing these processes, and incorporates the effects of pesticides on mortality of the insect. Model output was evaluated by comparison with records of pheromone trap catches of codling moths in commercial apple orchards in North Carolina. The model predicts timing of the first spring flight well, depending on the initial age distribution used. Time between peaks of numbers of adults in the model is about 15 days longer than the observed period between flight peaks in orchards. Sensitivity analysis indicates that this discrepancy may be related to differences between measured ambient temperature and tree canopy temperature. The sensitivities of numbers of insects produced by the model and timing of peaks in numbers present were determined for each of the parameters in the model. The parameters with greatest effect on the model output were those which control the locations of developmental rate functions and survival functions on the temperature scale. In the model, pesticides had a much larger effect on numbers of adults present than records of moths caught in pheromone traps indicate actually occurred, suggesting that moths caught in traps in commercial orchards where effective pesticides are applied may be largely immigrants.

SUMMARY The isolation and identification of the volatile compounds of celery are described. Non‐linear temperature‐programmed gas chromatography was found to give resolution superior to that of either isothermal operation or linear temperature programming. The identification of 24 compounds from celery is reported. Of the 38 compounds thus far identified from celery distillates, the following six compounds are primarily responsible for the characteristic flavor and aroma of celery: 3‐isobutylidene‐3a,4‐dihydrophthalide; 3‐isovalidene‐ 3a,4‐dihydrophthalide; 3‐isobutylidene phthalide; 3‐isovalidene phthalide; cis‐3‐hexen‐l‐yl pyruvate; and diacetyl. The phthalide derivatives are also implicated in the occurrence of certain celery off‐flavors reported in the literature.

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