CH4goat

Overview

CH4goat is a neural network models for calculate the methane emission from goats 🐐. It contains two black-box model (model1 & model2) using the dataset from Konkuk University.

Installation

# The development version from GitHub:
# install.packages("devtools")
devtools::install_github("adatalab/CH4goat")

Usage

models

The package contains two black-box model derived from the in vivo enteric methane dataset using respiration-metabolism chamber system.

model1
plot(model1)

model2
plot(model2)

base_frame

# making a base frame for predict the methane emission from goats
base_frame(model = 1) # use when using model1 (inputs = DMI, OMI, CPI, NDFI, DDMI, DOMI, DCPI, and DNDFI)
base_frame(model = 2) # use when using model2 (inputs = DMI, OMI, CPI, and NDFI)

# OR read the example excel file

example1 <- readxl::read_excel("model1-example.xlsx")

• model1-example.xlsx
• model2-example.xlsx

normalization

example1_nor <- normalization(data = example1)

compute

# calculating the methane emission from goats using neural network model.
result <- neuralnet::compute(model1, example1_nor)

denormalization

denormalization(result$net.result) # unit is L/d

Notification

This package is under development. Everyone can contribute to this package. If you have the in vivo data of goats and want to progress this model, please contact via email 📧 or github issue

Getting helps

Email: ruminoreticulum@gmail.com