Phytase is of importance to the poultry industry because of its ability to hydrolyze phytate and release phosphorus (P) for use by poultry. However, the effect of age on phytase efficacy is not fully understood. A total of 864 day-old broiler chicks were used to investigate the effect of age and feeding length on phytase efficacy using growth performance, mineral utilization, and tibia ash as response criteria of evaluation. The experiment was arranged as a 3 × 2 × 2 factorial in a randomized complete block design with 3 diets including; a positive control (PC; 0.4% non-phytate P (nPP)), a negative control (NC; 0.2% nPP) and a NC diet supplemented with phytase at 2,000 FYT/kg; 2 ages (i.e., days 14 and 22); and 2 feeding lengths (i.e., 2 and 5 D) with 8 replicates each. Birds fed the NC had decreased (P < 0.01) body weight gain and feed efficiency compared with birds fed the PC regardless of age or feeding length. Similarly, birds fed the phytase-supplemented diet had improved (P < 0.01) performance as compared to birds fed the NC regardless of age. There were no significant differences in P utilization between birds fed for 2 to 14 D or 22 D and birds fed for 5 D to both ages. However, phytase was more efficacious at day 14 than day 22 when mineral utilization was considered because the super dose of phytase elicited greater response in birds fed the phytase supplemented diet for 2 D until day 14. In contrast, percentage tibia ash improved (P < 0.01) in birds fed phytase supplemented diet for 5 D at both ages as compared with birds fed for 2 D. In conclusion, testing phytase products, even at high doses, for 2 D during the second week in the life cycle of broiler chicks, can be recommended from the results of this study.
Pubmed ID: 31287893 RIS Download
Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.
Software that can accurately and sensitivity classify short reads of next-generation sequencing (NGS) into protein domain families. It is based on profile HMM and a supervised graph contribution algorithm. Compared to existing tools, it has high sensitivity and specificity in classifying short reads into their native domain families.
View all literature mentions