Interactions between enzyme preparations and trace element sources on growth performance and intestinal health of broiler chicks.

This experiment was conducted to explore the interactions between enzyme preparations and trace element sources on growth performance and intestinal health of broilers chicks. A total of 480 one-day-old healthy male yellow-feather broilers with similar weight were randomly arranged in a 2  ×  2 factorial design with 2 kinds of compound trace element sources (inorganic [I] and organic [O] trace element supplemented with 80, 8, 60, 40, 0.15 mg/kg of Fe, Cu, Mn, Zn, and Se, respectively) and 2 levels of enzyme preparations (0 and 200 mg/kg). The 4 groups named I, O, IE, and OE with 6 replicates and 20 birds per replicate. The trail lasted for 28 days. Results showed that the average weight (ABW), average daily gain (ADG) of broilers in IE and OE groups significantly increased while the F/G significantly decreased as compared with group I and O (P < 0.05). Enzyme preparation supplementation, regardless of the trace element sources, significantly increased the duodenal and jejunal endogenous enzyme (e.g., Try and AACT) activity, and improved the morphology and jejunal barrier function evidenced by the increased villus height and MUC-2 mRNA expression (P < 0.05). Sequencing data manifested that enzyme preparations favorably modulated the cecal microflora by increasing bacterial diversity and abundance of short-chain fatty acid (SCFA)-producing bacteria (e.g., Anaerostipes, Anaerofusis, and Pygmaioactor), while decreasing the abundance of harmful bacteria (e.g., Desulfovibrio). Factorial analysis indicated that there were no interactions between enzyme preparation and trace element sources on growth performance and intestinal health of broiler chicks. In conclusion, dietary supplementation with enzyme preparations, regardless of the trace element sources, could enhance endogenous enzyme activity, improve intestinal morphology and barrier functions, and favorably modulate the cecal microflora, thereby improving the intestinal health and growth performance of broiler chicks.

Efficacy evaluation of novel organic iron complexes in laying hens: effects on laying performance, egg quality, egg iron content, and blood biochemical parameters.

OBJECTIVE: This study was conducted to determine the optimal dose of novel iron amino acid complexes (Fe-Lys-Glu) by measuring laying performance, egg quality, egg iron (Fe) concentrations, and blood biochemical parameters in laying hens. METHODS: A total of 1,260 18-week-old healthy Beijing White laying hens were randomly divided into 7 groups with 12 replicates of 15 birds each. After a 2-wk acclimation to the basal diet, hens were fed diets supplemented with 0 (negative control, the analyzed innate iron content was 75.06 mg/kg), 15, 30, 45, 60, and 75 mg Fe/kg as Fe-Lys-Glu or 45 mg Fe/kg from FeSO4 (positive control) for 24 wk. RESULTS: Results showed that compared with the negative and positive control groups, dietary supplementation with 30 to 75 mg Fe/kg from Fe-Lys-Glu significantly (linear and quadratic, p<0.05) increased the laying rate (LR) and average daily egg weight (ADEW); hens administered 45 to 75 mg Fe/kg as Fe-Lys-Glu showed a remarkable (linear, p<0.05) decrease in feed conversion ratio. There were no significant differences among all groups in egg quality. The iron concentrations in egg yolk and serum were elevated by increasing Fe-Lys-Glu levels, and the highest iron content was found in 75 mg Fe/kg group. In addition, hens fed 45 mg Fe/kg from Fe-Lys-Glu had (linear and quadratic, p<0.05) higher yolk Fe contents than that with the same dosage of FeSO4 supplementation. The red blood cell (RBC) count and hemoglobin content (linear and quadratic, p<0.05) increased obviously in the groups fed with 30 to 75 mg Fe/kg as Fe-Lys-Glu in comparison with the control group. Fe-Lys-Glu supplementation also (linear and quadratic, p<0.05) enhanced the activity of copper/zinc-superoxide dismutase (Cu/Zn-SOD) in serum, as a result, the serum malonaldehyde content (linear and quadratic, p<0.05) decreased in hens received 60 to 75 mg Fe/kg as Fe-Lys-Glu. CONCLUSION: Supplementation Fe-Lys-Glu in laying hens could substitute for FeSO4 and the optimal additive levels of Fe-Lys-Glu are 45 mg Fe/kg in layers diets based on the quadratic regression analysis of LR, ADEW, RBC, and Cu/Zn-SOD.

A statistical assessment of saturation and mobile sampling strategies to estimate long-term average concentrations across urban areas.

The objectives of this study were: (1) to quantify the errors associated with saturation air quality monitoring in estimating the long-term (i.e., annual and 5 yr) mean at a given site from four 2-week measurements, once per season; and (2) to develop a sampling strategy to guide the deployment of mobile air quality facilities for characterizing intraurban gradients of air pollutants, that is, to determine how often a given location should be visited to obtain relatively accurate estimates of the mean air pollutant concentrations. Computer simulations were conducted by randomly sampling ambient monitoring data collected in six Canadian cities at a variety of settings (e.g., population-based sites, near-roadway sites). The 5-yr (1998-2002) dataset consisted of hourly measurements of nitric oxide (NO), nitrogen dioxide (NO2), oxides of nitrogen (NOx), sulfur dioxide (SO2), coarse particulate matter (PM10), fine particulate matter (PM2.5), and CO. The strategy of randomly selecting one 2-week measurement per season to determine the annual or long-term average concentration yields estimates within 30% of the true value 95% of the time for NO2, PM10 and NOx. Larger errors, up to 50%, are expected for NO, SO2, PM2.5, and CO. Combining concentrations from 85 random 1-hr visits per season provides annual and 5-yr average estimates within 30% of the true value with good confidence. Overall, the magnitude of error in the estimates was strongly correlated with the variability of the pollutant. A better estimation can be expected for pollutants known to be less temporally variable and/or over geographic areas where concentrations are less variable. By using multiple sites located in different settings, the relationships determined for estimation error versus number of measurement periods used to determine long-term average are expected to realistically portray the true distribution. Thus, the results should be a good indication of the potential errors one could expect in a variety of different cities, particularly in more northern latitudes.

A Statistical Assessment of Saturation and Mobile Sampling Strategies to Estimate Long-Term Average Concentrations across Urban Areast.

The objectives of this study were: (1) to quantify the errors associated with saturation air quality monitoring in estimating the long-term (i.e., annual and 5 yr) mean at a given site from four 2-week measurements, once per season; and (2) to develop a sampling strategy to guide the deployment of mobile air quality facilities for characterizing intraurban gradients of air pollutants, that is, to determine how often a given location should be visited to obtain relatively accurate estimates of the mean air pollutant concentrations. Computer simulations were conducted by randomly sampling ambient monitoring data collected in six Canadian cities at a variety of settings (e.g., population-based sites, near-roadway sites). The 5-yr (1998-2002) dataset consisted of hourly measurements of nitric oxide (NO), nitrogen dioxide (NO2), oxides of nitrogen (NOx), sulfur dioxide (SO2), coarse particulate matter (PM10), fine particulate matter (PM2.5), and CO. The strategy of randomly selecting one 2-week measurement per season to determine the annual or long-term average concentration yields estimates within 30% of the true value 95% of the time for NO2, PM10 and NOx. Larger errors, up to 50%, are expected for NO, SO2, PM2.5, and CO. Combining concentrations from 85 random 1-hr visits per season provides annual and 5-yr average estimates within 30% of the true value with good confidence. Overall, the magnitude of error in the estimates was strongly correlated with the variability of the pollutant. A better estimation can be expected for pollutants known to be less temporally variable and/or over geographic areas where concentrations are less variable. By using multiple sites located in different settings, the relationships determined for estimation error versus number of measurement periods used to determine long-term average are expected to realistically portray the true distribution. Thus, the results should be a good indication of the potential errors one could expect in a variety of different cities, particularly in more northern latitudes.