Abstract
Adequate environmental control for seedling growth is essential in developing a seedling cultivation system. Thisstudy focuses on the model development of a neural network model to investigate the relationship between the quality ofcabbage seedlings and their growth environment. Three different neural models were developed and evaluated. An importantapproach adopted in this work is that the seedling growth is considered as a result of the cumulative effects of many interactinginfluences in the growth process. Thus, a historical growth factor, daily dry matter increase weight in the preceding stage,is included in the model. By integration of schemes for various growth stages and the historical growth factor, the modelcontributes markedly in prediction ability. The error is decreased by 77% (from 33.7% to 7.87%) when the best modeldeveloped in this work is used.
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