CSM-IXIM: A New Maize Simulation Model for DSSAT Version 4.5

Th e CERES-Maize model is the most widely used maize (Zea mays L.) model and is a recognized reference for comparing new developments in maize growth, development, and yield simulation. Th e objective of this study was to present and evaluate CSMIXIM, a new maize simulation model for DSSAT version 4.5. Code from CSM-CERES-Maize, the modular version of the model, was modifi ed to include a number of model improvements. Model enhancements included the simulation of leaf area, C assimilation and partitioning, ear growth, kernel number, grain yield, and plant N acquisition and distribution. Th e addition of two genetic coeffi cients to simulate per-leaf foliar surface produced 32% smaller root mean square error (RMSE) values estimating leaf area index than did CSM-CERES. Grain yield and total shoot biomass were correctly simulated by both models. Carbon partitioning, however, showed diff erences. Th e CSM-IXIM model simulated leaf mass more accurately, reducing the CSM-CERES error by 44%, but overestimated stem mass, especially aft er stress, resulting in similar average RMSE values as CSM-CERES. Excessive N uptake aft er fertilization events as simulated by CSM-CERES was also corrected, reducing the error by 16%. Th e accuracy of N distribution to stems was improved by 68%. Th ese improvements in CSM-IXIM provided a stable basis for more precise simulation of maize canopy growth and yield and a framework for continuing future model developments

The P-Adaptive BIEM Version in Elastostatics

This paper introduces the p-adaptive version of the boundary element method as a natural extension of the homonymous finite element approach. After a brief introduction to adaptive techniques through their finite element formulation in elastostatics, the concepts are cast into the boundary element environment. Thus, the p-adaptive version of boundary integral methods is shown to be a generalization of already well known ideas. In order to show the power of these numerical procedures, the results of two practical analysis using both methods are presented.

New version of a laboratory impact device for firmness sensing of fruits.

Results of previous studies conducted by different researchers have shown that impact techniques can be used to evaluate firmness (Delwiche et al., 1989; Delwiche et al.;1996; Jaren et al., 1992; Ruiz Altisent et al., 1996). To impact the fruit with a small spherical impactor of known mass and radius of curvature and measure the acceleration of the impactor is a technique described by Chen et al. (1985) and used by several researchers for sensing fruit firmness (Jaren et al., 1992; Correa et al.; 1992). The advantages of this method vs. a force sensor that measures the force as a function of time is that the measured impact-acceleration response is independent of the fruit mass and is less sensitive to the variation in the radius of curvature of the fruit (Chen et al., 1996). Ruiz Altisent et al. (1993) developed and used a 50 g impactor with a 19 mm diameter spherical tip, dropping from different height for fruits (apples, pears, avocados, melons, peaches ...). Another impact device for firmness sensing of fruits was developed by Chen and Ruiz Altisent (1996). They designed and fabricated an experimental low-mass impact sensor for high-speed sensing of fruit firmness. The impactor consisted of a semi-spherical impacting tip attached to the end (near the centre of percussion) of a pivoting arm. Impact is done by swinging the impactor to collide with the fruit. It has been implemented for on-line use. In both devices a small accelerometer is mounted behind the impacting tip. Lateral impactor and vertical impactor have been used in laboratory and the results from non-destructive impact tests have contributed to standardise methods to measure fruit firmness: Barreiro (1992) compared impact parameters and results of Magness-Taylor penetration tests for apples, pears, apricots [and peaches; Agulheiro (1994) studied the behaviour of the impact parameters during seven weeks of cold storage of two melon varieties; Ortiz (1998) used low energy impact and NIR procedures to segregate non crispy, non firm and soft peaches. Steinmetz (1996) compared various non-destructive firmness sensors, based on sound, impact and micro-deformation.