Two experiments were conducted to evaluate the effects of chromium (Cr) on the growth performance, bone trait, serum traits, and immune responses in broilers. The broilers were fed corn-soybean meal basal diet supplemented with Cr at level of 0 (control), 200, 400, or 800 ppb in the form of chromium picolinate (CrPic). The broilers were fed treated diets for 6 weeks in Exp. 1, but the Cr supplement was removed for the last 3 weeks in Exp. 2. Exp. 1 showed that dietary supplement of Cr did not affect growth performance of the broiler, though improved feed efficiency (p<0.05) was observed during 0 to 3 weeks. Moreover, serum total (p<0.05) and HDL cholesterols (p<0.06) were significantly higher in pooled Cr added group at 6 weeks of age, however, the difference was not significant in Exp. 2. The pooled Cr added group in Exp.1 had significantly lower (p<0.05) alkaline phosphatase activity and higher (p<0.09) calcium at 3 weeks. Significantly lower phosphorus was also observed in Exp. 2. With continued supplement of Cr as in Exp. 1, the alkaline phosphatase activity maintained higher at 6 weeks, as opposed to significantly lower in Exp. 2, which had no further Cr supplement. Higher bone breaking strength was observed in 400 ppb Cr supplemented in Exp. 1, though not significantly different. Serum glucose and triglyceride were not affected by Cr supplement. Antibody against Infectious Bronchitis (IB) was significantly (p<0.05) higher with 400 ppb Cr supplemented, and anti-Newcastle disease (ND) antibody also tended to be higher (p<0.06) in pooled Cr added group at 6 weeks of age in Exp. 1. Peripheral blood blastogenesis activity was not different among the treatments. The results suggest that diet supplemented with 400 ppb CrPic may be beneficial to the broilers.
This paper considers the problem of estimating time-varying parameters which can be parameterized by a series of arbitrary known basis functions. It is shown that this problem is equivalent to the observer design problem for a "matrix" dynamic system. A "matrix" gradient algorithm, which mimics the well-known "vector" gradient algorithm, is proposed to estimate the unknown matrix. The contribution of this paper is to show that convergence of the proposed matrix algorithm is guaranteed by the persistent excitations of both the regressor and the basis functions.
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