Path Analysis for Feed Characteristics on Metabolizable Energy of Naturel Pasture Hay

Yıl 2022, Cilt: 37 Sayı: 2, 331 - 340, 30.06.2022

Cem Tırınk Zehra Sarıçiçek Hasan Önder

https://doi.org/10.7161/omuanajas.980656

Öz

The aim of this study is to examine the direct, indirect and total effects of nutrient content properties on metabolizable energy contents of natural pasture feeds using path analysis. For this aim, the relationship between metabolizable energy and eight feed nutrient characteristics such as acid detergent lignin (ADL), acid detergent fiber (ADF), neutral detergent fiber (NDF), crude fiber, crude protein, ether extract, ash, and the nitrogen-free extract (NFE) was used for 48 grassland plants samples obtained from natural pastures of Ankara. According to the results of path analysis, crude fiber, acid detergent lignin, crude protein, ash, and nitrogen-free extract sustained the most significant effects on metabolizable energy. Also, acid detergent lignin and neutral detergent fiber were negative and significant effect on metabolizable energy. Last of all, to predict metabolizable energy, acid detergent lignin and neutral detergent fiber can be proposed that as prediction criteria.

Anahtar Kelimeler

path analysis, path coefficient, direct effects, indirect effect, Correlation

Destekleyen Kurum

Ministry of Agriculture and Forestry (TAGEM-16 / ARGE-13)

Proje Numarası

TAGEM-16 / ARGE-13

Teşekkür

This work was supported by the Turkish Ministry of Agriculture and Forestry as a TAGEM-16 / ARGE-13 project.

Kaynakça

• Alpar R., 2013. Applied Multivariate Statistical Methods (4th edition): Detay Anatolia Yayıncılık. ISBN: 978-605-5437-42-8.
• AOAC, 1990. Sample Preparation (950.02) Official Methods of Analysis, Association of Official Analytical Chemists, 15th edition, Washington DC, 1990.9;93:217–222.
• Canbolat, O., Karaman, S., 2009. Comparison of in Vitro Gas Production, Organic Matter Digestibility, Relative Feed Value and Metabolizable Energy Contents of Some Legume Forages. Journal of Agricultural Sciences, 15(2), 188-195.
• Epskamp S., 2019. semPlot: Path Diagrams and Visual Analysis of Various SEM Packages’ Output. R package version 1.1.2. https://CRAN.R-project.org/package=semPlo
• Gul S., Keskin M., Guzey Y.Z., Behrem S., Gunduz Z., 2019. Path Analysis of the Relationship Between Weaning Weight and Some Morphological Traits in Awassi Lamb. Kahramanmaras Sutcu Imam University Journal Of Agriculture and Nature, 22 (Suppl 2), 431-435.
• IBM Corp. Released, 2012. IBM SPSS Statistics for Windows, Version 21.0. Armonk, NY: IBM Corp.
• Isci Guneri O., Goktas A., Kayali U., 2016. Path analysis and determining the distribution of indirect effects via simulation. Journal of Applied Statistics, 44:7, 1181-1210.
• Kayali, U., 2013. Path analysis and a simulation study about the distribution of indirect effects. MSc Thesis. Mugla Sitki Kocman University.
• Li C.C., 1975. Path Analysis a Primer, The Boxwood Press, Pacific Grove, CA.
• Lishinski A., 2018 lavaanPlot: Path Diagrams for Lavaan Models via DiagrammeR. R package version 0.5.1. https://CRAN.R-project.org/package=lavaanPlot.
• Menke KH, Raab L, Salewski A, Steingass H, Fritz D, Schneider W., 1979. The estimation of the digestibility and metabolizable energy content of ruminant feeding stuffs from the gas production when they are incubated with rumen liquor in vitro. The Journal of Agricultural Science, 93(1), 217–222.
• Menke KH, Steingass H., 1998. Estimation of the Energetic Feed Value Obtained from Chemical Analysis and in vitro Gas Production Using Rumen Fluid. Animal Research and Development, 28, 7-55.
• Mitchell R.J., 1992. Testing evolutionary and ecological hypotheses using path analysis and structural equation modelling. Functional Ecology, 6(2), 123-129.
• Onder H., Abaci S.H., 2015. Path Analysis for Body Measurements on Body Weight of Saanen Kids. Journal of the Faculty of Veterinary Medicine, Kafkas University, 21(3), 351-354.
• Pedhazur E.J., 1997. Multiple Regression in Behavioral Research: Explanation and Prediction. Harcourt Brace College Publishers. FortWorth, TX.
• R Core Team, 2020. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL: https://www.R-project.org/.
• Revelle, W., 2020. psych: Procedures for Personality and Psychological Research, Northwestern University, Evanston, Illinois, USA, https://CRAN.R-project.org/package=psych Version = 2.0.12,.
• Rohweder DA, Barnes RE, Jorgensen N., 1978. Proposed hay grading standards based on laboratory analysis for evaluating quality. Journal of Animal Science, 47(3), 747-759.
• Rosseel Y., 2012. lavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software, 48(2). 1-36. URL http://www.jstatsoft.org/v48/i02/.
• Saricicek Z., 2020. Determination of botanical composition, nutrient content, feed value and quality parameters in between May-August months of natural grasslands of Ankara province. Black Sea Journal of Agriculture. 3(4), 267-277.
• Sayan Y., Ozkul H., Alcicek A., Coskuntuna L., Onenc S.S., Polat M., 2004. Comparison of the parameters using for determination of metabolizable energy value of the roughages. Journal of Agriculture Faculty of Ege University. 41(2), 167-175.
• Tahtali Y., Sahin, A., Ulutas Z., Sirin E., Abaci S.H., 2011. Determination of Effective Factors for Milk Yield of Brown Swiss Cattle Using by Path Analysis. Journal of the Faculty of Veterinary Medicine, Kafkas University 17(5), 859-864.
• Topal M., Emsen B., Dodologlu A., 2008. Path analysis of honey yield components using different correlation coefficients in caucasian honey bee. Journal of Animal and Veterinary Advances, 7(11), 1440-1443.
• Van Soest PJ., Robertson JB., Lewis BA., 1991. Methods for dietary fiber, neutral detergent fiber, and nonstarch polysaccharides in relation to animal nutrition. Journal of Dairy Science, 74(10), 3583-3597.
• Wright S., 1921. Correlation and causation. Journal of Agricultural Research, 20, 557-558.