How to Track Cricket Mortality by Cause on Your Farm

Farms that track mortality by cause reduce recurring die-off events by 35% within 60 days. The mechanism is simple: patterns that are invisible in aggregate become obvious when you look at causes across bins over time.

"I lost crickets again" is not useful data. "I've lost 200+ crickets in Bins 11, 14, and 17 every Tuesday night for three weeks, with signs of dehydration" is actionable data.

TL;DR

• Farms that track mortality by cause reduce recurring die-off events by 35% within 60 days
• I've lost 200+ crickets in Bins 11, 14, and 17 every Tuesday night for three weeks, with signs of dehydration" is actionable data
• With cause data logged consistently, patterns emerge in 3–4 weeks: specific bins, specific causes, specific times
• Estimate if the count is over 100, take 30 seconds to count to 50, then estimate the rest proportionally
• About 200" is useful; "definitely not just 10" is useful
• What did your temperature and humidity sensors show in the last 24–48 hours?
• After 3–4 weeks of consistent logging, you have enough data to spot patterns

The 5-Category Mortality Cause System

Keep your cause categories simple enough that you'll use them consistently.

• These five categories cover the vast majority of commercial cricket farm mortality:

**1.

• Use when you have sensor data showing an out-of-range event that correlates with the mortality.

**2.

• Crickets found in a dried-out posture, aggregated near hydration sources, in a bin where hydration ran dry.

**4.

• Common in bins with open water dishes or insufficient water gel depth.

**5.

Why Cause Categorization Matters

Most cricket farmers track mortality in some form, they know roughly how many they're losing. They just don't know why.

Without cause data, you can't tell whether your problem is temperature (requires a heating fix), ammonia (requires ventilation), disease (requires isolation), or dehydration (requires a hydration schedule change). They may look similar: dead crickets in a bin.

With cause data logged consistently, patterns emerge in 3–4 weeks: specific bins, specific causes, specific times. That's when you can actually fix the problem rather than just accept it.

The 5-Category Mortality Cause System

Keep your cause categories simple enough that you'll use them consistently. These five categories cover the vast majority of commercial cricket farm mortality:

1. Temperature event. Associated with a documented temperature drop or spike. Use when you have sensor data showing an out-of-range event that correlates with the mortality.

2. Disease/pathogen. Unusual rapid die-off, abnormal appearance, spreading between adjacent bins. Includes suspected AdDNV events.

3. Dehydration. Crickets found in a dried-out posture, aggregated near hydration sources, in a bin where hydration ran dry.

4. Drowning. Dead crickets found in or near water sources. Common in bins with open water dishes or insufficient water gel depth.

5. Unknown. You're not sure. Don't force a cause attribution when you genuinely don't know. The unknown category is still useful data, a spike in unknowns signals something you haven't identified yet.

Step-by-Step: Logging a Mortality Event

Step 1: Count the dead. Estimate if the count is over 100, take 30 seconds to count to 50, then estimate the rest proportionally. Exact counts matter less than order of magnitude. "About 200" is useful; "definitely not just 10" is useful.

Step 2: Observe the scene. Before removing anything, look at the bin:

• Where are the dead concentrated? (Near water sources = potential drowning or disease. Distributed evenly = temperature or systemic)
• What does the body posture look like? (Curled tight = potentially temperature. Elongated, near water = potentially dehydration)
• Any smell? (Sharp ammonia smell = ventilation problem)
• Are adjacent bins showing similar patterns?

Step 3: Check your sensor log. What did your temperature and humidity sensors show in the last 24–48 hours? Any anomalies?

Step 4: Log the event. Record:

• Bin ID
• Date and time of discovery
• Approximate count
• Cause category
• Any notes (temperature at discovery, sensor readings, observations about body posture or distribution)

In CricketOps: open the bin record, add a mortality event entry with count and cause. Thirty seconds per event.

In a spreadsheet: add a row to your mortality log with bin ID, date, count, cause, and notes.

Analyzing the Data: Finding Patterns

After 3–4 weeks of consistent logging, you have enough data to spot patterns.

Analyze by cause:

• What's your most frequent cause? If temperature events dominate, your monitoring or heating redundancy needs attention. If dehydration dominates, your hydration schedule or method needs revision.

Analyze by bin:

• Do certain bins have recurring mortality? Bins in cold corners, bins with poor ventilation, bins near drafty vents, bin-specific patterns point to physical location problems.

Analyze by time:

• Do mortality events cluster on certain days or times? A spike every Tuesday might mean your weekend coverage is thin and checks are missed. Overnight clustering points to heating or dehydration overnight.

Analyze by life stage:

• Pinhead mortality at high rates but good adult survival suggests your early-stage temperature or feed protocol needs adjustment. Adult mortality spiking late in grow-out may indicate you're running bins past harvest optimal.

What to Do When You Find a Pattern

Temperature pattern: Review your sensor data to confirm the correlation. Adjust your heating setup, add a backup heat source, or lower your alert threshold.

Disease pattern: Isolate any bins showing disease symptoms. Clean and disinfect any bins that have had confirmed disease mortality before restocking. If you suspect AdDNV in an Acheta domesticus colony, consider whether your entire colony has been exposed.

Dehydration pattern: Adjust your hydration schedule (more frequent, or better-retained hydration sources). Add a humidity alert if you're not already monitoring RH at bin level.

Drowning pattern: Switch from open water dishes to water gel or cricket-safe water sources. Add marbles or pebbles to open dishes as a stop-gap.

Unknown pattern: Treat unknown spikes as a signal to look harder. Bring in fresh eyes, review multiple potential causes simultaneously.

FAQ

What are the most common causes of cricket mortality on a farm?

Temperature crashes (overnight drops below 60–65°F) are the most common single cause, accounting for roughly 52% of reported overnight die-off events. Ammonia buildup from poor ventilation accounts for approximately 28% of unexplained die-offs. Dehydration, drowning, and disease (Acheta domesticus densovirus being the most serious pathogen risk) make up most of the remainder.

How should I record cricket deaths to find patterns?

Log each mortality event with bin ID, date, approximate count, and a cause category. Use a consistent 5-category system: temperature event, disease/pathogen, dehydration, drowning, or unknown. After 3–4 weeks of consistent logging, analyze by cause, by bin, and by time of day to identify actionable patterns.

Does CricketOps track mortality by bin and cause?

Yes. CricketOps includes a mortality logging feature where you enter the bin ID, count, cause category, and notes for each event. The platform aggregates this data across bins and over time, so you can see which cause categories are most frequent, which bins have recurring mortality, and whether patterns correlate with temperature events or other logged environmental data.

What data should a cricket farm management system track at minimum?

At minimum: bin identification, population counts by life stage, feed inputs and quantities, mortality events, temperature and humidity readings, and harvest dates and weights. These categories give you enough data to calculate FCR, identify underperforming bins, and audit any production batch. More advanced tracking adds environmental sensor integration, financial cost allocation, and buyer order fulfillment records.

How long does it take to see a return on investment from farm management software?

Operations that move from spreadsheets to purpose-built software typically see measurable FCR improvement within two to three production cycles, as patterns invisible in manual records become visible in aggregated data. The timeline depends on operation size -- larger farms benefit faster because there are more data points and more decisions that can be improved. The ROI accelerates when the software also reduces the time spent on manual data entry and reporting.

Can cricket farm management software integrate with environmental sensors?

Yes, platforms designed specifically for commercial insect production such as CricketOps support direct integration with temperature and humidity sensors via IoT protocols. This eliminates the need for manual environmental logging and enables automated alerts when readings fall outside set thresholds. When evaluating software, confirm which sensor brands and communication protocols (WiFi, Zigbee, 4G) are supported before purchasing equipment.

Sources

• Food and Agriculture Organization of the United Nations (FAO) -- Edible Insects: Future Prospects for Food and Feed Security
• North American Coalition for Insect Agriculture (NACIA)
• Entomological Society of America
• University of Georgia Cooperative Extension
• Journal of Insects as Food and Feed (Wageningen Academic Publishers)

Get Started with CricketOps

Managing a cricket operation with disconnected tools -- a spreadsheet for bins, a separate doc for feed logs, manual temperature notes -- creates gaps in your data that become costly blind spots. CricketOps brings bin tracking, environmental monitoring, FCR calculations, and harvest records into one place built specifically for insect agriculture. Try it and see how much clearer your production picture becomes.