The Relationship Between Feed Consumption and Meat Production in Broiler Farms: Indicators, Empirical Evidence, and Practical Solutions (Focusing on Slaughter Weight of 1.2–1.8 kg)
Abstract
This article concisely and precisely addresses three key questions:
(1) Which indicators quantify the relationship between feed consumed and meat produced,
(2) What ranges for FCR and slaughter weight are indicated by scientific and field evidence, and
(3) How a production unit should practically make decisions to achieve a justifiable and economical slaughter weight. Breed technical documentation, growth studies, and poultry production economics papers form the basis of this work.
1. Key Performance Indicators (KPIs) — Definitions and Practical Importance
- FCR (Feed Conversion Ratio) — The kilograms of feed required to produce 1 kg of live weight gain; the primary economic efficiency indicator.
- ADG (Average Daily Gain) — Average daily weight gain (g/day); determines the length of the rearing period and the speed of capital turnover.
- Dressing % (Carcass Yield Percentage) — The ratio of saleable carcass weight to live weight; typically around 72–75% in commercial broilers and determines direct revenue.
- Mortality, Uniformity, PEF (Performance Efficiency Factor) — Mortality, weight uniformity, and overall performance indicators; increased mortality or reduced uniformity worsens the technical FCR and increases the final cost.
Practical Note:
Among all indicators, FCR and Dressing% have the greatest immediate financial impact because feed constitutes the dominant variable cost, and carcass yield determines gross income.
2. The Quantitative Relationship Between Weight, Age, and FCR — Scientific and Field Evidence
Growth studies show that FCR typically increases gradually with age/weight (i.e., efficiency decreases), and there is a weight point where the “slope of FCR deterioration” steepens. Growth models and field data can approximate the FCR(W) function to predict feed consumption and profit for any live weight W. This behavior has been observed in numerous studies and breed technical reports.
- Empirical Numerical Example (General Sample): Up to approximately 1.2–1.8 kg live weight, the increase in FCR is slow and manageable; beyond ≈2.0–2.3 kg, the slope of FCR increase steepens, and allocated costs along with welfare/mortality risks rise. This pattern has been reported in studies determining optimal slaughter age and papers on finisher diets.
3. A Quantitative-Practical Method for Determining the “Optimal Economic Weight” (Implementable on the Farm)
3.1 Required Input Parameters (Local)
- Feed price (USD/kg or Rial/kg)
- FCR function by weight: FCR(W) — or an FCR table for each weight range
- Local Dressing% (e.g., 72–75%)
- Carcass price (USD/kg) or live price (if customary)
- Overhead and fixed costs per bird (vaccines, labor, energy, etc.)
- Expected mortality rate and its effect on technical FCR
3.2 Basic Formulas (Implementable in Excel)
For each proposed weight W (kg live):
- Weight gain per bird: ΔW = W – W₀ (W₀ = starting weight, usually day-one weight or pullet weight)
- Feed consumption per bird: Feed = FCR(W) × ΔW
- Carcass per bird: Carcass = W × Dressing%
- Revenue per bird: Revenue = Carcass × Price_carcass/kg
- Feed cost per bird: FeedCost = Feed × Price_feed/kg
- Simple profit per bird: Profit = Revenue – FeedCost – Overhead_per_bird
It is sufficient to calculate Profit for the weight range (e.g., 1.2 to 2.8 kg in 0.1 kg steps) and select the maximum. Also, perform sensitivity analysis on feed price and meat price.
3.3 How to Approximate the FCR(W) Function (Practical)
If field data is unavailable, use an empirical approximation (adjustable based on your observations):
- FCR(W) ≈ a + b × W (simple linear) — Calibrate parameters a and b with one or two reference points (e.g., FCR(1.3)=1.4 and FCR(2.3)=1.85).
- Or use nonlinear forms (e.g., exponential/2nd-degree polynomial) if more data is available. Growth studies show that data-driven models (growth curve + feed intake curve) have higher accuracy.
4. Practical Numerical Example (Template—Replaceable with Your Figures)
Sample Assumptions (Regional, changeable):
- Dressing% = 74%
- Price_feed = 0.40 USD/kg
- Price_carcass = 2.00 USD/kg
- Overhead = 0.35 USD/bird
- Linear FCR function approximation: FCR(1.3)=1.40; FCR(1.7)=1.55; FCR(2.3)=1.85 (linear between points)
Calculation for W = 1.4, 1.7, 2.3 (the same previous examples) shows that nominal gross profit may be higher for heavier weights, but when capital turnover, mortality, uniformity loss, and reduced annual production cycles are factored in, annual returns favor the 1.2–1.8 kg range. This result aligns with practical studies and research on optimal age determination.
5. Step-by-Step Practical Guideline (Operational Checklist — For Farm Implementation)
- Install a daily recording system: Weekly sample weighing (1–1.5% of the flock), daily total house feed consumption, daily mortality with cause.
- Calculate daily/weekly KPIs: Cumulative FCR, Technical FCR (including mortality), ADG, PEF, Mortality, Uniformity (weight CV).
- Update the FCR(W) function: Recalibrate the function from actual farm data every four weeks.
- Run sales/price scenarios: For each feed price and carcass price scenario, recalculate the optimal weight.
- Economic slaughter decision: Select a static weight (e.g., 1.5–1.7 kg) for a season and review monthly based on prices.
- Technical control to keep FCR low: Phase feeding, optimizing stocking density, managing temperature/ventilation, water management program, and attention to gut health.
6. Risks and Qualitative/Welfare Considerations
- Heavier weights may reduce carcass quality (non-uniformity, increased breast/leg fat, leg problems, market satisfaction); therefore, quality criteria (market feedback, percentage of returns/rejects) must be incorporated into the economic model.
7. Key Conclusions (Scientific-Practical Summary)
- Field and technical evidence indicates that up to approximately 1.2–1.8 kg live weight, feed efficiency (FCR) increases slowly and capital turnover is high; this range is typically optimal in practice and operationally for price-sensitive markets.
- Practical method: Implementing a simple economic model (using the formulas above), updating it based on farm data and sensitivity analysis, optimizes and justifies slaughter decisions.
- Suggested immediate action: Accurately record weight/feed/mortality data immediately; then implement an Excel model to calculate the optimal weight under local price scenarios.
Selected References (For Citation and Further Review)
- Aviagen — Ross 308 Broiler Performance Objectives (Technical Manual).
- Papers and studies on determining “Optimal Slaughter Age” and cost-benefit analysis (field studies).
- “Data Analytics of Broiler Growth Dynamics and Feed Conversion” — PMC (analysis of growth data, FCR, and modeling recommendations).
- Extension resources and processing guides on Dressing% (academic references).
- Studies on the effect of finisher diet and slaughter age on efficiency and economics (PMC).
