18 research outputs found
Effect of mineral-enriched diet and medicinal herbs on Fe, Mn, Zn, and Cu uptake in chicken
<p>Abstract</p> <p>Background</p> <p>The goal of our study was to evaluate the effects of different medicinal herbs rich in polyphenol (Lemon balm, Sage, St. John's wort and Small-flowered Willowherb) used as dietary supplements on bioaccumulation of some essential metals (Fe, Mn, Zn and Cu) in different chicken meats (liver, legs and breast).</p> <p>Results</p> <p>In different type of chicken meats (liver, legs and breast) from chickens fed with diets enriched in minerals and medicinal herbs, beneficial metals (Fe, Mn, Zn and Cu) were analysed by flame atomic absorption spectrometry. Fe is the predominant metal in liver and Zn is the predominant metal in legs and breast chicken meats. The addition of metal salts in the feed influences the accumulations of all metals in the liver, legs and breast chicken meat with specific difference to the type of metal and meat. The greatest influences were observed in legs meat for Fe and Mn. Under the influence of polyphenol-rich medicinal herbs, accumulation of metals in the liver, legs and breast chicken meat presents specific differences for each medicinal herb, to the control group that received a diet supplemented with metal salts only. Great influence on all metal accumulation factors was observed in diet enriched with sage, which had significantly positive effect for all type of chicken meats.</p> <p>Conclusions</p> <p>Under the influence of medicinal herbs rich in different type of polyphenol, accumulation of metals in the liver, legs and breast chicken meat presents significant differences from the group that received a diet supplemented only with metal salts. Each medicinal herb from diet had a specific influence on the accumulation of metals and generally moderate or poor correlations were observed between total phenols and accumulation of metals. This may be due to antagonism between metal ions and presence of other chelating agents (amino acids and protein) from feeding diets which can act as competitor for complexation of metals and influence accumulation of metals in chicken meat.</p> <p><b>Graphical abstract</b></p
STATISTIC ANALYSIS OF MULTIPLE CURVILINEAR REGRESSIONS OF FOUR VARIABLES REGARDING THE EVOLUTION OF THE AVERAGE WEEKLY GAIN AT BROILERS
Depending on four controlable variables used in broilers nutrition: E (energy), P
(protein), L(lysine), M (metyonine+ cystine) have been deduced mathematically
multiple curvilinear regressions showing the evolution of corporal mass during
entire growth period. In this paper, using these regressions, we determine the
average weekly gain of corporal mass. We test using dispersional analysis if there
are significant differences between N.R.C. 1994 and the values given by regressions.
Using correlation report we decide which of these regressions is optimu
THE STATISTIC ANALYSIS OF THREE MATHEMATICAL MODELS REFFERING TO THE EVOLUTION OF BROILERS CORPORAL MASS
The evolution of the broilers corporal mass has been studied depending on the
controllable variables: L(lysine), M(metionine+cystine), obtaining the mathematical
models G1
, G2
, G3
.This work analyses statistically if the values of these models
significantly differ from the control lot G0
.(NRC 1994).Calculating the reports of
correlation we specify which model is considered decisional in broilers nutrition
Correlations between non-starch polysaccharides levels from combined forages with different percentage of wheat and viscosity at intestinal level
SUMMARY The purpose of this paper work is to establish the correlations between soluble non-starch polysaccharides (NSPs), insoluble non-starch polysaccharides (NSPi) and total non-starch polysaccharides (NSPt) levels from combined forages with different wheat inclusion percentage and viscosity at intestinal level. The experiment was made on a period of six weeks on 120 broiler chickens, hybrid ROSS 308, divided in four experimental lots: CL without wheat in the structure of combined forage, EL1 with 10% respectively 20% of wheat, EL2 with 20-30% wheat and EL3 whit 30% and 40% wheat in the first and respectively the second period of growth. The determination of intestinal viscosity was made at 3 weeks by slaughtering the chickens and sampling the duodenal content and respectively at 6 weeks by sampling the content from duodenum and jejunum. To establish the correlation between viscosity at intestinal level and the levels of non-starch polysaccharides from combined forages with different inclusion percentage of wheat were used the simple correlation and curvilinear regression. It can be seen that at duodenum level the viscosity rises with the rising of the wheat inclusion percentage and was with 28.71% greater at experimental lot with 20% wheat in structure of compound feeds and with 53.07% at experimental lot whit 40% wheat in the structure of combined forage. It was found that the correlation coefficients between NSP content and the viscosity at duodenum level at 3 weeks are positive, the greatest correlation coefficient was registered in the case of NSPs (0.995) which indicate that the digestion viscosity at intestinal level is influenced by the forage content in NSPs. At duodenum level the intestinal viscosity rises with the rising of wheat inclusion percentage in the structure of compound feeds and was with 49.04% at experimental lot with 40% wheat percentage. At jejunum level the intestinal viscosity rises with the rising of wheat inclusion percentage in the structure of compound feeds and was with † Corresponding author e-mail address: [email protected] C. Pandur et al. 38 33.15% at experimental lot with 40% wheat percentage comparative with control lot. At 6 weeks the correlation coefficients between the NSP content of combined forages fed to broiler chickens and the viscosity at duodenum level respectively at jejunum level are positive, the greatest correlation coefficient was registered in the case of NSPs (0.942) which indicate that the digestion viscosity at intestinal level is influenced by the forage content in NSPs
