skip to main content

ASSESSMENT OF METHANE ESTIMATION FROM VOLATILE FATTY ACID STOICHIOMETRY IN THE RUMEN IN VITRO

*A. Jayanegara  -  Department of Nutrition and Feed Technology, Faculty of Animal Science,, Indonesia
I. Ikhsan  -  Department of Nutrition and Feed Technology, Faculty of Animal Science,, Indonesia
T. Toharmat  -  Department of Nutrition and Feed Technology, Faculty of Animal Science,, Indonesia

Citation Format:
Abstract
Rumen microbes breakdown feed to produce volatile fatty acids (VFA), carbon dioxide, ammoniaand methane (CH4). Metabolic hydrogen in the form of reduced protons is used during CH4 formation aswell as during VFA synthesis. Therefore, VFA concentration in the rumen may stoichiometrically berelated to CH4 emission. The aim of this study was to evaluate methane emission between experimentaland model estimates. Two stoichiometrical models for predicting CH4 from VFA were assessed, i.e.Moss et al. (2000) and Hegarty and Nolan (2007) models. The data sets were obtained from a publishedliterature. Samples used were leaves from 27 tropical plant species. Prediction error was conducted bycomputing root mean square prediction error (RMSPE). Results showed that estimation model of Mosset al. (2000) had lower RMSPE value, i.e. 8.01%, than that of Hegarty and Nolan (2007) model, i.e.10.73%. Variation of methane emission, i.e. the low or high methane can be estimated by VFAcomposition with a sufficient accuracy. Adjusment by considering H2 recovery lowered the biassignificantly. It can be concluded that Moss model had better accuracy in predicting CH4 emission fromVFA composition than that of Hegarty and Nolan model.
Fulltext View|Download
Keywords: Methane. VFA. stoichiometry. estimation

Article Metrics:

Last update:

  1. Manipulation of Rumen Fermentation and Methane Gas Production by Plant Secondary Metabolites (Saponin, Tannin and Essential Oil) – A Review of Ten-Year Studies

    Saied Jafari, Mahdi Ebrahimi, Yong M. Goh, Mohamed A. Rajion, Mohamed F. Jahromi, Wisam S. Al-Jumaili. Annals of Animal Science, 19 (1), 2019. doi: 10.2478/aoas-2018-0037
  2. Application of Meta-Analysis and Machine Learning Methods to the Prediction of Methane Production from In Vitro Mixed Ruminal Micro-Organism Fermentation

    Jennifer L. Ellis, Héctor Alaiz-Moretón, Alberto Navarro-Villa, Emma J. McGeough, Peter Purcell, Christopher D. Powell, Padraig O’Kiely, James France, Secundino López. Animals, 10 (4), 2020. doi: 10.3390/ani10040720
  3. Optimizing protein, energy, and protein degradable ratios to enhance in vitro ruminal fermentation and reduce methane gas emission

    Ezi Masdia Putri, Mardiati Zain, Lili Warly, Hermon, Windu Negara, Alek Ibrahim, Zein Ahmad Baihaqi. IOP Conference Series: Earth and Environmental Science, 1377 (1), 2024. doi: 10.1088/1755-1315/1377/1/012070
  4. The effect of silkworms (Bombyx mori) chitosan on rumen fermentation, methanogenesis, and microbial population in vitro

    Yemima Gresia Sagala, Lincah Andadari, Tri Hadi Handayani, Mohammad Miftakhus Sholikin, Ainissya Fitri, Rusli Fidriyanto, Rohmatussolihat Rohmatussolihat, Roni Ridwan, Wulansih Dwi Astuti, Yantyati Widyastuti, Dilla Mareistia Fassah, Indah Wijayanti, Ki Ageng Sarwono. Veterinary World, 2024. doi: 10.14202/vetworld.2024.1216-1226
  5. Effects of Doses and Different Sources of Tannins on in vitro Ruminal Methane, Volatile Fatty Acids Production and on Bacteria and Protozoa Populations

    R.W.S. Ningrat, Mardiati Zain, Erpomen ., Heny Suryani. Asian Journal of Animal Sciences, 11 (1), 2016. doi: 10.3923/ajas.2017.47.53
  6. Comparative effect of Volvariella volvacea-treated rice straw and purple corn stover fed at different levels on predicted methane production and milk fatty acid profiles in tropical dairy cows

    Benjamad Khonkhaeng, Anusorn Cherdthong, Nawanon Chantaprasarn, Kevin J. Harvatine, Suban Foiklang, Pin Chanjula, Metha Wanapat, Sarong So, Sineenart Polyorach. Livestock Science, 251 , 2021. doi: 10.1016/j.livsci.2021.104626
  7. Supplementation effectivity of cassava and Indigofera zollingeriana leaves extraction on rumen fermentation system of in vitro

    Rizky Ramadhan, Idat Galih Permana, Anuraga Jayanegara, Muhamad Nasir Rofiq, Dimar Sari Wahyuni. INTERNATIONAL CONFERENCE ON BIOLOGY AND APPLIED SCIENCE (ICOBAS), 2120 , 2019. doi: 10.1063/1.5115730
  8. Development of Volatile Fatty Acid and Methane Production Prediction Model Using Ruminant Nutrition Comparison of Algorithms

    Myungsun Park, Sangbuem Cho, Eunjeong Jeon, Nag-Jin Choi. Fermentation, 10 (8), 2024. doi: 10.3390/fermentation10080410

Last update: 2024-12-20 03:18:15

  1. Application of Meta-Analysis and Machine Learning Methods to the Prediction of Methane Production from In Vitro Mixed Ruminal Micro-Organism Fermentation

    Jennifer L. Ellis, Héctor Alaiz-Moretón, Alberto Navarro-Villa, Emma J. McGeough, Peter Purcell, Christopher D. Powell, Padraig O’Kiely, James France, Secundino López. Animals, 10 (4), 2020. doi: 10.3390/ani10040720
  2. Manipulation of rumen fermentation and methane gas production by plant secondary metabolites (saponin, tannin and essential oil) - A review of ten-year studies

    Jafari S.. Annals of Animal Science, 19 (1), 2019. doi: 10.2478/aoas-2018-0037
  3. Addition of purified tannin sources and polyethylene glycol treatment on methane emission and rumen fermentation in Vitro

    Jayanegara A.. Media Peternakan, 38 (1), 2015. doi: 10.5398/medpet.2015.38.1.57
  4. Supplementation effectivity of cassava and Indigofera zollingeriana leaves extraction on rumen fermentation system of in vitro

    Rizky Ramadhan, Idat Galih Permana, Anuraga Jayanegara, Muhamad Nasir Rofiq, Dimar Sari Wahyuni. INTERNATIONAL CONFERENCE ON BIOLOGY AND APPLIED SCIENCE (ICOBAS), 2120 , 2019. doi: 10.1063/1.5115730