greenfeedr: An R package for processing and reporting GreenFeed data

被引:0
|
作者
Martinez-Boggio, Guillermo [1 ]
Lutz, Patrick [2 ]
Harrison, Meredith [2 ]
Weigel, Kent A. [1 ]
Penagaricano, Francisco [1 ]
机构
[1] Univ Wisconsin Madison, Dept Anim & Dairy Sci, Madison, WI 53706 USA
[2] C Lock Inc, Rapid City, SD 57703 USA
来源
JDS COMMUNICATIONS | 2025年 / 6卷 / 02期
关键词
D O I
10.3168/jdsc.2024-0662
中图分类号
S8 [畜牧、 动物医学、狩猎、蚕、蜂];
学科分类号
0905 ;
摘要
Greenhouse gases produced by livestock are important contributors to climate change. The ability to measure large-scale exhaled metabolic gases from cattle using GreenFeed systems will help farmers to reduce enteric emissions while maintaining or increasing cow productivity. GreenFeed units are portable chamber systems that measure individual animal gas production in real time. Thus, the machines generate large amounts of daily data that can be overwhelming for users to process. This challenge motivated us to develop an R package named greenfeedr that offers functions for downloading, processing, and reporting GreenFeed data. Herein, we describe all functions implemented in the greenfeedr R package and present examples based on dairy cow data. The R package has functions for downloading GreenFeed data (get_gfdata), for generating daily and final reports (report_gfdata), for processing daily and final records process_gfdata), and extra functions that help to extract information regarding pellet intakes and daily visits (pellin and viseat). Using our example data with 32 lactating dairy cows, we demonstrated the capabilities of the different functions to generate easy-to-read reports and process large amount of data. Also, we included in the function process_gfdata some parameters that will help users to define the best criteria to process their own GreenFeed data. Overall, greenfeedr represents an important advancement in the management and analysis of GreenFeed data, offering an efficient tool tailored to the needs of the user.
引用
收藏
页数:5
相关论文
共 50 条
  • [1] mefa: an R package for handling and reporting count data
    P. Sólymos
    Community Ecology, 2008, 9 : 125 - 127
  • [2] mefa:: an R package for handling and reporting count data
    Solymos, P.
    COMMUNITY ECOLOGY, 2008, 9 (01) : 125 - 127
  • [3] Processing Ecological Data in R with the mefa Package
    Solymos, Peter
    JOURNAL OF STATISTICAL SOFTWARE, 2009, 29 (08): : 1 - 28
  • [4] The lrd package: An R package and Shiny application for processing lexical data
    Nicholas P. Maxwell
    Mark J. Huff
    Erin M. Buchanan
    Behavior Research Methods, 2022, 54 : 2001 - 2024
  • [5] The lrd package: An R package and Shiny application for processing lexical data
    Maxwell, Nicholas P.
    Huff, Mark J.
    Buchanan, Erin M.
    BEHAVIOR RESEARCH METHODS, 2022, 54 (04) : 2001 - 2024
  • [6] metaboprep: an R package for preanalysis data description and processing
    Hughes, David A.
    Taylor, Kurt
    McBride, Nancy
    Lee, Matthew A.
    Mason, Dan
    Lawlor, Deborah A.
    Timpson, Nicholas J.
    Corbin, Laura J.
    BIOINFORMATICS, 2022, 38 (07) : 1980 - 1987
  • [7] qPCRtools: An R package for qPCR data processing and visualization
    Li, Xiang
    Wang, Yingmin
    Li, Jingyu
    Mei, Xinyue
    Liu, Yixiang
    Huang, Huichuan
    FRONTIERS IN GENETICS, 2022, 13
  • [8] hydrographr: An R package for scalable hydrographic data processing
    Schuerz, Marlene
    Grigoropoulou, Afroditi
    Garcia Marquez, Jaime
    Torres-Cambas, Yusdiel
    Tomiczek, Thomas
    Floury, Mathieu
    Bremerich, Vanessa
    Schuerz, Christoph
    Amatulli, Giuseppe
    Grossart, Hans-Peter
    Domisch, Sami
    METHODS IN ECOLOGY AND EVOLUTION, 2023, 14 (12): : 2953 - 2963
  • [9] move2: R package for processing movement data
    Kranstauber, Bart
    Safi, Kamran
    Scharf, Anne K.
    METHODS IN ECOLOGY AND EVOLUTION, 2024, 15 (09): : 1561 - 1567
  • [10] The seeker R package: simplified fetching and processing of transcriptome data
    Schoenbachler, Joshua L.
    Hughey, Jacob J.
    PEERJ, 2022, 10