Laser-based detection and predictive modeling of methane concentrations in cattle respiration

This database contains records of methane (CH₄) gas emissions produced by cattle during the respiratory process. The data was collected using a Laser Methane Detector. Measurements were taken during five different field visits, and the corresponding data is stored in the Raw Data folder. Each field visit folder contains several meas_merged_n.csv files, which include information on burp events, reported as ppm emitted over time. Since a single meas_merged_n.csv file can include more than one burp event, a total of 97 events was recorded and labeled in the Event_limits_def.xlsx file.

The Event_limits_def file contains twelve columns. The first two columns, "Visit" and "Measurement", indicate the location of the tagged event. "Visit" refers to the name of the folder corresponding to the field visit where the meas_merged file is stored, while "Measurement" refers to the specific meas_merged file (identified by its number) that contains the event. The "ix_event" column indicates the event number within that file.

Each event was split into two parts: a primary sub-event and a secondary sub-event, which are specified in the "type_event" column. The "start" and "end" columns indicate the time (in seconds) during which the sub-event occurs. The next column corresponds to the number of event from 1 to 97. The next three columns refer to the cow’s "Animal's Position", "Mouth Position", and "Activity" at the time the measurement was taken. Finally, "Measurement Spot" and "Distance" describe where the laser was pointed and the distance between the laser and the measurement spot.

ExpSinosouid and Gaussians model

The ExpSinosouid and Gaussians model folders each contain three files: trues, preds, and params.

- The trues file contains the same records as those in the Raw Data, meaning it replicates the information from the corresponding meas_merged_n.csv files.
- The preds file includes the predictions generated by each model for every event.
- The params file contains the model parameters or coefficients used to generate each prediction. These coefficients can be used to reconstruct the predictive equations.

To visualize or plot any of this data, refer to the PlotsModelVisualization script, which includes Python-based code for plotting the model results.

LogNormal Model

The LogNormal model folder contains 98 .csv files. The LogNormCoeff.csv file includes the coefficients used to represent the fitted curves for each event. The other 97 files correspond to the individual event predictions. Visualization for this model is also supported by the PlotsModelVisualization script. Remember that each event is numbered from 1 to 97 based on the time it was recorded, i.e. event 1 corresponds to "Visit" 1, "meas_merged_1", "ix_event" 1; event 97 corresponds to "Visit" 5th, last meas_merged file or "meas_merged_6" and the last event of that file or "ix_event" 6.