RBFY Pen-Level DMI Spatial Analysis

Description

This report characterizes spatial patterns of dry matter intake (DMI) across pens at Royal Beef Feedyard using operational data from June 2022 to current. The analytical unit is the pen-week. To be included, a pen-week was required to represent a designated feeding pen with a weekly average of at least 30 animals, have at least five days of feeding records during the week, and maintain consistent lot occupancy throughout the week. Hospital, receiving, processing, sort, and shipping were excluded.

Descriptive DMI heat maps

DMI / animal

DMI as % body weight (BW)

DMI as % metabolic body weight (MBW)

Filterable map by key factors

DMI as % metabolic body weight

June 2022 to current

Combinations pre-computed: 60 

Pen-combination rows:      16049 

summaries = transpose(pen_summaries_ojs)
coords    = transpose(pen_coords_ojs)

// Dropdowns
viewof sex_sel    = Inputs.select(sex_levels_ojs,    {label: "Sex"})
viewof weight_sel = Inputs.select(weight_levels_ojs, {label: "Weight"})
viewof season_sel = Inputs.select(season_levels_ojs, {label: "Season"})

selected = summaries.filter(d =>
  d.sex    === sex_sel    &&
  d.weight === weight_sel &&
  d.season === season_sel
)

// Temporary diagnostic — shows in rendered doc
Inputs.table(selected)

L = require("leaflet@1.9.4/dist/leaflet-src.js")
html`<link rel="stylesheet" href="https://unpkg.com/leaflet@1.9.4/dist/leaflet.css">`

{
  const geojson = JSON.parse(pen_geojson_ojs)

  function makeLookup(sel) {
    return Object.fromEntries(sel.map(d => [d.PEN, d]))
  }

  function getColor(val, minV, maxV) {
    if (val === null || val === undefined || isNaN(val)) return "#808080"
    const t = Math.max(0, Math.min(1, (val - minV) / (maxV - minV)))
    const stops = [
      [215,  48,  39],
      [252, 141,  89],
      [254, 224, 139],
      [255, 255, 191],
      [217, 239, 139],
      [145, 207,  96],
      [ 26, 152,  80]
    ]
    const scaled = t * (stops.length - 1)
    const lo     = Math.floor(scaled)
    const hi     = Math.min(lo + 1, stops.length - 1)
    const frac   = scaled - lo
    const r = Math.round(stops[lo][0] + frac * (stops[hi][0] - stops[lo][0]))
    const g = Math.round(stops[lo][1] + frac * (stops[hi][1] - stops[lo][1]))
    const b = Math.round(stops[lo][2] + frac * (stops[hi][2] - stops[lo][2]))
    return `rgb(${r},${g},${b})`
  }

  const div = document.createElement("div")
  div.style.height = "600px"
  div.style.width  = "100%"
  yield div

  const lats   = coords.map(d => d.lat)
  const lons   = coords.map(d => d.lon)
  const minLat = Math.min(...lats), maxLat = Math.max(...lats)
  const minLon = Math.min(...lons), maxLon = Math.max(...lons)

  const map = L.map(div, { minZoom: 15.25 })
    .fitBounds([[minLat - 0.01, minLon - 0.01],
                [maxLat + 0.01, maxLon + 0.01]])

  map.setMaxBounds([
    [minLat - 0.003, minLon - 0.003],
    [maxLat + 0.003, maxLon + 0.003]
  ])

  L.tileLayer(
    "https://server.arcgisonline.com/ArcGIS/rest/services/World_Imagery/MapServer/tile/{z}/{y}/{x}",
    { attribution: "Tiles © Esri" }
  ).addTo(map)

  let polyLayer = L.geoJSON(null).addTo(map)

  function updateMap(sel) {
    const lkp  = makeLookup(sel)
    const vals = Object.values(lkp)
      .map(d => d.mean_val)
      .filter(v => v !== null && v !== undefined && !isNaN(v))
    const minV = vals.length > 0 ? Math.min(...vals) : 0
    const maxV = vals.length > 0 ? Math.max(...vals) : 1

    polyLayer.clearLayers()
    polyLayer = L.geoJSON(geojson, {
      style: feature => {
        const d   = lkp[feature.properties.pen_id]
        const val = (d && d.mean_val !== null && !isNaN(d.mean_val))
                      ? d.mean_val : null
        return {
          fillColor:   getColor(val, minV, maxV),
          fillOpacity: 0.6,
          color:       "white",
          weight:      1
        }
      },
      onEachFeature: (feature, layer) => {
        const penId   = feature.properties.pen_id
        const d       = lkp[penId]
        const hasData = d && d.mean_val !== null && !isNaN(d.mean_val)
        const fmt     = v => (v !== null && v !== undefined && !isNaN(v))
                               ? Number(v).toFixed(2) : "N/A"
        layer.bindTooltip(
          hasData ? `Pen ${penId}: ${fmt(d.mean_val)}%`
                  : `Pen ${penId}: no data`,
          { direction: "auto" }
        )
        layer.bindPopup(
          hasData
            ? `<b>Pen ${penId}</b><br>
               Mean: ${fmt(d.mean_val)}%<br>
               Median: ${fmt(d.median_val)}%<br>
               SD: ${fmt(d.sd_val)}%<br>
               Pen-weeks: ${d.n_pen_weeks}`
            : `<b>Pen ${penId}</b><br>No data for this selection`
        )
      }
    }).addTo(map)

    const legend = L.control({ position: "bottomright" })
    legend.onAdd = function() {
      const el = L.DomUtil.create("div")
      el.style.cssText = `
        background: white; padding: 8px 10px; border-radius: 4px;
        box-shadow: 0 1px 4px rgba(0,0,0,0.3); font-size: 14px; line-height: 1.6;
      `
      const steps  = 100
      const height = 150
      let bars = ""
      for (let i = steps; i >= 0; i--) {
        const t   = i / steps
        const val = minV + t * (maxV - minV)
        bars += `<div style="width:16px; height:${height/steps}px;
                             background:${getColor(val, minV, maxV)};"></div>`
      }
      const nTicks = 5
      let ticks = ""
      for (let i = nTicks; i >= 0; i--) {
        const t   = i / nTicks
        const val = minV + t * (maxV - minV)
        const top = ((nTicks - i) / nTicks) * height
        ticks += `<div style="position:absolute; top:${top}px; left:22px;
                              font-size:14px; transform:translateY(-50%);">
                    ${val.toFixed(2)}%
                  </div>`
      }
      el.innerHTML = `
        <b style="display:block; margin-bottom:4px;">DMI (% MBW)</b>
        <div style="position:relative; display:flex; align-items:stretch;">
          <div style="display:flex; flex-direction:column;">${bars}</div>
          <div style="position:relative; width:50px;">${ticks}</div>
        </div>
      `
      return el
    }
    if (map._legend) map.removeControl(map._legend)
    map._legend = legend
    legend.addTo(map)
  }

  invalidation.then(() => map.remove())
  updateMap(selected)
}

The color scale anchors to the minimum and maximum values within the currently selected combination (i.e., the legend scale changes with each change to filterable parameters).

Baseline mixed model

Descriptive statistics of outcome and candidate variables

Continuous

Categorical

Rations

Model data prep

Liearity assessment of continuous predictors

Final mixed model

Diagnostics

Blup extraction

Model adjusted heatmap

Color scale limits: ± 1.972 lb/hd/day

Pens beyond color limit: 4