Analyze Non-Nutritive and Empty Bin Visits Within Meals

Analyzes visits within meals to identify and summarize non-nutritive visits (no feed intake but feed available) and empty bin visits (no feed available). Input data must already have meal labels from meal_label_visits().

Usage

meal_non_nutritive_summary(
  data,
  cfg = qc_config(),
  id_col = id_col2(),
  intake_col = intake_col2(),
  start_weight_col = start_weight_col2()
)

Arguments

data

A named list of daily data frames or a single data frame containing visit records with meal labels. Must be output from meal_label_visits(), which adds the required meal_id and meal_start columns.

cfg

A configuration list created by qc_config(). Used to determine calibration error threshold for classifying visits.

id_col

Animal ID column name (default current global value from id_col2())

intake_col

Intake column name (default current global value from intake_col2())

start_weight_col

Start weight column name (default current global value from start_weight_col2())

Value

A data frame (or named list of data frames) with columns:

• date - Date

• [id_col] - Animal identifier

• mean_non_nutritive_per_meal - Average non-nutritive visits per meal

• median_non_nutritive_per_meal - Median non-nutritive visits per meal

• sd_non_nutritive_per_meal - Standard deviation of non-nutritive visits

• mean_empty_bin_per_meal - Average empty bin visits per meal

• median_empty_bin_per_meal - Median empty bin visits per meal

• sd_empty_bin_per_meal - Standard deviation of empty bin visits

• total_non_nutritive_visits - Total non-nutritive visits

• total_empty_bin_visits - Total empty bin visits

• total_meals - Total number of meals

Examples

# Create sample visit data with meal labels
visits <- data.frame(
  date = "2024-01-01",
  cow = c("A", "A", "A", "B", "B"),
  bin = c(1, 2, 3, 1, 2),
  start_weight = c(50, 0.01, 45, 48, 0.02),
  intake = c(2.5, 0.01, 0.02, 3.0, 0.01),
  meal_id = c(1, 1, 1, 1, 1),
  meal_start = as.POSIXct("2024-01-01 08:00:00", tz = "UTC")
)

# Analyze non-nutritive and empty bin visits
meal_visits <- meal_non_nutritive_summary(
  data = visits,
  cfg = qc_config()
)