The objective of the present study was to simulate the effect of the seasonal variation of climate on the nutritional value and dry matter yield of star grass and its capacity to support milk production alone or with concentrate supplementation in small-scale milk production systems in the tropical regions of Mexico. Two mathematical simulation models were used, the first model simulates the growth and yield of star grass (Cynodon plectostachyus), and the second model simulates the productive performance of dairy cows. Both models were integrated in a decision-making support system (DSSTROP). Model's predictions were validated by a calibration exercise for each data set from three experiments on the effect of concentrate supplementation on milk yield. The DSSTROP predictions and the results from the experiments were compared by regression analysis. The results suggest that the DSSTROP adequately predicts milk production (R2=0.74). The DSSTROP predictions suggest that milk production based solely on star grass may occur only between June to August. The highest milk yield (8.5kg cow-1 day-1) sustained solely on grass was achieved in June, followed by lower yields of <5kg cow-1 day-1 in July and August. Milk production without concentrates can be explained by the positive effects of the rain observed during June to August on grass growth, and to the fact that grass quality is best at the beginning of the rainy season. It is concluded that June to August is the best time of the year for milk production base solely on grass. It also was concluded that the use of large quantities of concentrates by farmers may be justified because milk production with star grass alone may not be possible especially during the dry season.
simulation models; feeding strategies; small-scale milk production
