Crop Systems Dynamics: An ecophysiological simulation model by Xinyou Yin

By Xinyou Yin

This e-book provides a customary process-based crop progress version, GECROS (Genotype-by-Environment interplay on CROp development Simulator), lately built in Wageningen. The version makes use of strong but basic algorithms to summarize the present wisdom of person physiological procedures and their interactions and suggestions mechanisms. It was once based from the fundamentals of whole-crop platforms dynamics to include the physiological explanations instead of descriptive algorithms of the emergent outcomes. It additionally makes an attempt to version each one method at a constant point of element, in order that no region is overemphasized and equally no quarter is taken care of in a trivial demeanour. major cognizance has been paid to interactive elements in crop development comparable to photosynthesis-transpiration coupling through stomatal conductance, carbon-nitrogen interplay on leaf zone index, useful stability among shoot and root actions, and interaction among resource provide and sink call for on reserve formation and remobilization. GECROS combines powerful version set of rules, excessive computational potency, and exact version output with minimal variety of enter parameters that require periodical harmful sampling to estimate

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1990) based on a carbon isotope discrimination model (Farquhar 1983). g. Ehleringer and Pearcy (1983). 62 g N g−1 N). Other general model coefficients such as those for respiration (default value cfix = 6 g C g−1 N) were already mentioned in earlier chapters. Values of these model constants are summarized in Table 1. The following section lists those parameters that vary either with crops or with genotypes within a crop. Crop-specific parameters Crop-specific parameters include: • leaf photosynthesis: EJmax, χjn and χvcn; • phenology-related parameters: Tb, To, and Tc; • morphology-related parameter: w, ρ, Dmax, and sla; • biomass composition-related parameters: flip, flig, foac and fmin for seed, YG,V, fc,V, and εg; • nitrogen content-related parameters: nb, ncri0, nSmin, and nRmin.

1989). In the model, D is defined as a state variable initialized at sowing depth, with rate of change as: ∆D = min [ (Dmax – D) / ∆t, ∆WRT / (wRb + kR WRT) ] (45) where, wRb is an input parameter for the critical root weight density (g m−2 cm−1), below which there is no effective water or nutrient extraction, ∆WRT is rate of change in total (living + dead) root weight, kR is an empirical coefficient, accounting for the decline in root weight density with soil depth. The first part of Eqn (45) restricts actual root depth to Dmax; the second part is derived in Appendix J.

Readers should not consider this as absolute classification. It is difficult to put some input coefficients in a category in an absolute term. For example, Dmax in Table 3 represents a crop characteristic, but as already mentioned, it should be considered as genotypespecific if one wants to examine genotype-specific differences in response to drought. Another example is parameter θ, which is, for simplicity, tentatively considered as a constant (Table 1). Its value can vary, depending on data of gas exchange measurements for photosynthesis under various irradiation conditions (constants of this type are marked in Table 1).

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