Background and Aim: Birds litter contains unutilized nitrogen in the form of uric acid that is converted into ammonia; a fact that does not only affect poultry performance but also has a negative effect on people's health around the farm and contributes in the environmental degradation. The influence of microclimatic ammonia emissions on Ross and Hubbard broilers reared in different housing systems at two consecutive seasons (fall and winter) was evaluated using a discriminant function analysis to differentiate between Ross and Hubbard breeds.

Materials and Methods: A total number of 400 air samples were collected and analyzed for ammonia levels during the experimental period. Data were analyzed using univariate and multivariate statistical methods.

Results: Ammonia levels were significantly higher (p<0.01) in the Ross compared to the Hubbard breed farm, although no significant differences (p>0.05) were found between the two farms in body weight, body weight gain, feed intake, feed conversion ratio, and performance index (PI) of broilers. Body weight; weight gain and PI had increased values (p<0.01) during fall compared to winter irrespective of broiler breed. Ammonia emissions were positively (although weekly) correlated with the ambient relative humidity (r=0.383; p<0.01), but not with the ambient temperature (r=-0.045; p>0.05). Test of significance of discriminant function analysis did not show a classification based on the studied traits suggesting that they cannot been used as predictor variables. The percentage of correct classification was 52% and it was improved after deletion of highly correlated traits to 57%.

Conclusion: The study revealed that broiler's growth was negatively affected by increased microclimatic ammonia concentrations and recommended the analysis of broilers' growth performance parameters data using multivariate discriminant function analysis.

Keywords: ammonia, broiler, discriminant function analysis, growth performance parameters, humidity, temperature.

1. Akyuz, A. (2009) Effects of some climates parameters of environmentally uncontrollable broiler houses on broiler performance. J. Anim. Vet. Adv., 8: 2608-2612.

2. Czarick, M. and Fairchild, B. (2012) Relative humidity, the best measure of overall poultry house air quality (poultry housing tips), extension article and cooperative extension service. Vol. 24. University of Georgia, USA. p2.

3. Skora, J., Matusiak, K., Wojewodzki, P., Nowak, A., Sulyok, M., Ligocka, A., Okrasa, M., Hermann, J. and Gutarowska, B. (2016) Evaluation of microbiological and chemical contaminants in poultry farms. Int. J. Environ. Res. Public Health, 13(2): 192. [Crossref]

4. Kurvits, T. and Marta, T. (1998) Agricultural NH3 and NOx emissions in Canada. Environ. Sci. Pollut. Res., 102(S1): 187-194. [Crossref]

5. Beker, A., Vanhooser, S.L., Swartzlander, J.H. and Teeter, R.G. (2004) Atmospheric ammonia concentration effects on broiler growth and performance. J. Appl. Poult. Res., 13(1): 5-9. [Crossref]

6. Miles, D.M., Branton, S.L. and Lott, B.D. (2004) Atmospheric ammonia is detrimental to the performance of modern commercial broilers. Poult. Sci., 83(10): 1650-1654. [Crossref]

7. Kristensen, H.H. and Wathes, C.M. (2000) Ammonia and poultry welfare: A review. Worlds Poult. Sci. J., 56(3): 234-245. [Crossref]

8. Brady, W.L. (1986) Measurements of some poultry performance parameter. Vet. Rec., 88: 245-260.

9. Yamani, K.A.O., Rashwan, A.A. and Magdy, M.M. (1997) Effects of copper, zinc and Tafla dietary supplementation on broiler performance. International Conference on Animal, Poultry & Rabbit Production and Health. p457-463.

10. Ndegwa, P.M., Vaddella, V.K., Hristov, A.N. and Joo, H.S. (2009) Measuring concentrations of ammonia in ambient air or exhaust stream using acid traps. J. Environ. Qual., 38(2): 647-653. [Crossref] [PubMed]

11. American Public Health Association; American Water Works Association; Water Environment Federation. (2012) Standard Methods for the Examination of Water and Wastewater. 22th ed. American Water Work Association Publications, Washington, DC.

12. Shayan, Z., Mezerhi, N.M.G., Shayan, L. and Naseri, P. (2016) Prediction of depression in cancer patients with different classification criteria, linear discriminant analysis versus logistic regression. Glob. J. Health Sci., 8(7): 41-46. [Crossref] [PubMed] [PMC]

13. Lachenbruch, P.A. (1979) Discriminant analysis. Biometrics, 35: 69-85. [Crossref]

14. Statistical Analysis Systems Institute. (2006) SAS Online Doc_R, Version 8.02. SAS Institute Inc., Cary, NC, USA.

15. SPSS^® Statistics 20. (2008) Statistical Package for Social Sciences Software Package. SPSS Incorporated, Illinois, USA.

16. Goldstein, D.L. and Skadhauge, E. (2000) Renal and extrarenal regulation of body fluid composition. In: Whittow, G.C., editor. Sturkies Avian Physiology. Academic Press, San Diego, California. p265-297. [Crossref]

17. Becker, J.G. and Graves, R.E. (2014) Ammonia emissions and animal agriculture. In: Proceedings Mid Atlantic Agricultural Ammonia Forum Va. March 16, 2014.

18. Maliselo, P.S. and Nkonde, G.K. (2015) Ammonia production in poultry houses and its effect on the growth of Gallus gallus domestica (broiler chickens): A case study of a small scale poultry house in riverside, Kitwe, Zambia. Int. J. Sci. Technol. Res., 4(4): 141-145.

19. Bueno, L. and Rossi, L.A. (2006) Comparison between air conditioning technologies for raising chickens regarding energy, ambience and productivity.. Rev. Bras. Eng. Agric. Ambient, 10(2): 497-504. [Crossref]

20. Fioretin, L.A. (2006) Reutilization of aviary bed in the context of benchmarking. Avicult. Ind., 97(6): 12-18.

21. Selecciones, A. (1996) Good soil for a long time. Selecciones Avicolas, 38: 97-98.

22. Abreu, V.M.N., de Abreu, P.G., Jaenisch, F.R.F., Coldebella, A. and de Paiva, D.P. (2011) Effect of floor type (dirt or concrete) on litter quality, house environmental conditions, and performance of broilers. Rev. Bras. Cienc. Avic., 13(2): 127-137. [Crossref]

23. Rosario, M.F., Silva, M.A.N., Coelho, A.A.D., Savino, V.J.M. and Dias, C.T.S. (2008) Canonical discriminant analysis applied to broiler chicken performance. Animal, 2(3): 419-424. [Crossref]

24. Garson, G.D. (2012) Discriminant Function Analysis. Statistical Associates Publishers, Asheboro, NC.

25. Sage. (2014) Discriminant Analysis. Ch. 25.

26. Eskindir, A., Kefelegn, K., Tadelle, D. and Banerjee, A. (2013) Phenotypic characterization of indigenous chicken population in Ethiopia. Int. J. Interdiscip. Multidiscip. Stud., 1(1): 24-32.

27. Ogah, D.M. (2013) Canonical discriminant analysis of morphometric traits in indigenous chicken genotypes. Trakia J. Sci., 2: 170-174.

28. Udeh, I. (2014) Canonical correlation analysis relating age at first egg, bodyweight at first egg and weight of first egg with egg production at different periods in a strain of layer type chicken. Glob. J. Anim. Sci. Res., 2(4): 310-314.

29. Jesuyon, O.M.A. and Isidahomen, C. (2015) Canonical discriminant analysis of early maturity traits of parent stock layer strains in the tropics. Arch. Zootech., 18(1): 5-14.

30. Reddish, J.M. and Lilburn, M.S. (2004) A comparison of growth and development patterns in diverse genotypes of broiler: 2. Pullet growth. Poult. Sci., 83: 1072-1076. [Crossref]