There is increasing interest in using crop growth models to study soybean (Glycine max L. Merr.) seed yieldand quality. Because the availability of nitrogen (N) during late season growth is a critical factor affecting both seed yieldand quality of the soybean crop, accurate prediction of N balance is important for process oriented models. The objectiveof this study was to evaluate the accuracy of the N balance components of the CROPGRO soybean model for Iowa-grownsoybean, and where appropriate to modify the model in order to improve its accuracy. Field samples of Kenwoodsoybean, taken during reproductive growth in four consecutive seasons (1992-1995), were analyzed for leaf, stem, podwall, and seed N concentration. Soil and weather data from these trials were used to evaluate the ability of CROPGRO topredict N on both land-area and concentration bases for leaf, stem, pod wall, and seed tissues. The original N2-fixationroutine was too sensitive to cool soil temperature, which caused it to underpredict N accumulation in cool seasons. Theoriginal model also predicted remobilization of N from leaf tissue to occur earlier than was observed in the field. Thisreduced predicted photosynthesis which led to underprediction in the rate of N assimilation late in the season. Severalsimple modifications were introduced to enhance accuracy of the model: (1) decrease the lower limit of the range ofoptimum soil temperatures for nodule growth (from 28 to 22C), and nitrogenase activity (from 23 to 20C); (2) decreasethe base temperature of pod set (from 14 to 10C), and increase the base temperature for emergence and early vegetativedevelopment (from 7 to 9C); (3) delay of N remobilization from leaves and stems to seeds; (4) increase the maximum Nconcentration of various tissues to reflect observed values for Kenwood soybean, and set initiation of N remobilization tooccur earlier in pods than in other tissues.
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Sexton et al. (1998) studied this question.