🎒 Yield Gap Analysis
Yield Gap Analysis — potential vs actual yield, constraint analysis, model-based diagnosis, and strategies for closing yield gaps.
This lesson builds core elective concepts in BSc Agriculture with practical applications and exam-oriented clarity.
Yield Gap Analysis
Yield gap is the difference between the potential yield achievable under optimal conditions and the actual yield realised by farmers. Understanding and closing yield gaps is critical for improving food security without expanding cultivated area.
Yield Definitions
| Yield Level | Definition | Determined By |
|---|---|---|
| Potential yield (Yp) | Maximum yield under optimal management with no biotic/abiotic stress | Solar radiation, temperature, CO2, genotype |
| Water-limited yield (Yw) | Yield limited only by water supply (rainfed conditions) | Yp factors + rainfall, soil water holding capacity |
| Actual yield (Ya) | Yield obtained by farmers in their fields | All constraints — pests, nutrients, management, socioeconomic |
| Exploitable yield | Achievable target — typically 80% of Yp or Yw | Best farmer practices under local conditions |
Yield Gap Components
- Yield Gap I = Yp - Yw (water limitation gap)
- Yield Gap II = Yw - Ya (management gap due to nutrients, pests, weeds, sub-optimal practices)
- Technology gap = research station yield - farmer yield
- Extension gap = demonstration plot yield - farmer yield
Constraint Analysis
Major constraints contributing to yield gaps in India:
- Abiotic — drought, heat stress, soil salinity, waterlogging, nutrient deficiency
- Biotic — pests, diseases, weeds, nematodes
- Management — late sowing, sub-optimal plant population, imbalanced fertilisation, poor irrigation scheduling
- Socioeconomic — lack of credit, small farm size, limited access to quality inputs, knowledge gaps
Model-Based Diagnosis
Crop simulation models provide a powerful framework for yield gap analysis:
- Step 1 — Simulate Yp using long-term weather data and optimal management
- Step 2 — Simulate Yw by removing irrigation (rainfed scenario)
- Step 3 — Compare simulated yields with actual farmer yields from surveys or crop-cutting experiments
- Step 4 — Conduct sensitivity analysis to identify which constraints most reduce yield
Example: Wheat Yield Gap in Punjab
| Parameter | Value |
|---|---|
| Simulated Yp | 6.8 t/ha |
| Simulated Yw | 5.5 t/ha |
| Actual farmer yield | 4.5 t/ha |
| Yield Gap I (water) | 1.3 t/ha |
| Yield Gap II (management) | 1.0 t/ha |
| Total yield gap | 2.3 t/ha (34%) |
Global Yield Gap Atlas (GYGA)
The Global Yield Gap Atlas (www.yieldgap.org) is an international initiative that:
- Maps yield gaps for major crops across countries
- Uses consistent methodology with local weather, soil, and management data
- Identifies regions with the largest exploitable yield gaps
- Supports policy decisions on food security investment priorities
Strategies for Closing Yield Gaps
- Improved varieties — drought-tolerant, disease-resistant, high-yielding cultivars
- Precision nutrient management — soil test-based fertilisation, site-specific recommendations
- Water management — micro-irrigation, deficit irrigation scheduling, rainwater harvesting
- Timely operations — optimal sowing window, timely weed and pest management
- Knowledge transfer — extension services, demonstration plots, ICT-based advisory
Yield gap analysis provides the evidence base for targeting interventions where they can have the greatest impact on food production.
Summary Cheat Sheet
| Topic | Key takeaway |
|---|---|
| Main focus | Yield Gap Analysis — potential vs actual yield, constraint analysis, model-based diagnosis, and strategies for closing yield gaps. |
| Section context | Revise this lesson with the rest of System Simulation and Agro-Advisory for stronger conceptual continuity. |
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