- The document outlines a new methodology to measure food losses across the entire agricultural production process, from pre-harvest through post-harvest handling and storage. - Pilot studies in several countries found that food losses ranged significantly depending on the crop and country, with most losses occurring at the farm level due to weather events, pests, and lack of technology adoption. - Current projects are testing interventions like improved seed and fertilizer provision, market-based contracts, and decision support tools to incentivize quality and reduce losses in beans in Guatemala and Honduras.

2. Outline
1. Development of a new methodology
2. Food loss measurement in selected countries / crops.
3. Testing mechanisms to reduce food losses.
4. Future activities

3. Methodology

4. FL estimation methodologies
Macro
approach

6. MacroApproach
14.3 - 15.8 % of the total production (APHLIS, 2014; SSA)
89 Mio tons or 179 KG/ capita (Monier et al., 2010; Eurostat data for EU 27)
MicroApproach
32% of total production & 24% of total calories produced (FAO, 2011; Kummu et al., 2012; Lipinski et al., 2013 worldwide)
48% of total calories produced (Beretta et al., 2013; Switzerland)
53% of total production (Affognon et al., 2015; SSA)
1.4 – 5.9 % of total production
(Kaminski & Christiaensen, 2014; SSA)
28.7% of harvested production – 180 KG/ capital (Venkrant, 2011; US)
32% of total production (Kader, 2009, worldwide)
18.4 Mio ton
(WRAP, 2010; UK)
31% or 60 Mio ton of food supply at
retail (Buzby et al. 2014, US)
All loss and waste is reported per year
5.8 Mio ton (C-tech
Innovations, 2004; UK)
Different
measurements
(methods, stages,
units, etc.)
Wide variability in
the results.
Scarce evidence for
developing
countries.

7. Methodology to Measure Food Losses
Improvements:
• Consider the agricultural process as a whole (pre-harvest, harvest, and post-harvest
losses).
• Value chain approach (farmer, middlemen, processor)
• Not only lost quantities, but also gauge economic value of quality deterioration along
different nodes of the value chain
• Identify most frequent reasons of losses

8. Losses along the production process
Objective: Avoid scrapped food (discarded, poor quality).
Recent emphasis on post-harvest losses (significant variability in the definition of
PHL).
However… food is also scrapped due to:
• Management problems during pre-harvest (field fungal infections in beans / wheat,
earworm affecting maize cobs, etc.)
• At harvest (split potatoes due to poor harvesting techniques)
• Unharvested production (low prices, high labor costs around harvest time)

9. Value Chain Analysis
Production
Post-harvest
& Processing
Distribution
& Logistics
Processing Consumption
Food Losses:
Losses in production (including PHL), distribution,
and processing.
- More prevalent in developing countries
- Representative samples of farmers, middlemen
and processors
Food
Waste
- More prevalent
in developed
countries
- Not covered

10. Assessing quality losses
Food with quality deterioration might not be discarded. But there is ECONOMIC LOSS.
Subjective:
• Self-reported (aggregate) measurement.
Categories:
• Based on visual-scale methodology (by grades)
Attributes:
• Share of the crop affected by undesirable attributes
• Example (beans): humidity, mold, broken grain, weevil perforations, premature grain, etc.
Prices:
• How much lower is the actual sales price compared to the “optimal”?

11. Where do loses occur?
Photo credit: El Diario, Bolivia
Photo credit: The Hindu, India
Photo credit: Victor Agreda
Photo credit: Eduardo Nakasone
Photo credit: Eduardo Nakasone
Photo credit: Eduardo Nakasone
Photo credit: Eduardo Nakasone Photo credit: Eduardo Nakasone
Photo credit: Eduardo Nakasone
In the field?
Post Harvest at farm?
Transportation? Processing?

12. Food Loss Measurement

13. Measurement of Food Losses
(Delgado et al. 2017)
1. Food losses are important (8-26%)
2. Much larger when we account for
quality losses
3. Most food losses happen at the
farm level (56-86%)
4. Main problems identified: weather
related issues, lack of knowledge
of available technologies (pests,
plagues), mechanization and
access to infrastructure, lack of
price incentives.
10%
18%
14%
16%
10%
22%
22%
26%
12%
17%
22%
21%
12%
19%
17%
19%
8%
18%
21% 21%
13%
21%
19%
22%
6%
9% 9% 9%
11%
16%
17%
16%
0%
5%
10%
15%
20%
25%
30%
S C A P S C A P S C A P S C A P S C A P S C A P S C A P S C A P
ECU,
Potato
PER,
Potato
GUA,
Beans
GUA,
Maize
HON,
Beans
HON,
Maize
ETH,
Teff*
CHN,
Wheat
Food Losses (% of value of total production)
Farmer Middleman Processor
Source: Delgado, L., M. Torero and M. Schuster (2017). The reality of food losses: A new
measurement methodology. IFPRI Discussion Paper 01686. Washington, DC: International Food
Policy Research Institute.
Self
reported
Quality
disaggregation

14. When do losses occur at the farm level?
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
20%
S C A S C A S C A S C A S C A S C A S C A S C A
ECU,
Potato
PER,
Potato
GUA,
Beans
GUA,
Maize
HON,
Beans
HON,
Maize
ETH,
Teff
CHN,
Wheat
Food Losses at the Farm Level (% of Total Value)
Pre Harvest / Harvest
Post - Harvest
• Losses are important
in post-harvest
phases… but so are
those in pre-harvest
and harvest stages.
Self
reported
Quality
disaggregation

15. Dissemination
Conferences
Country Events
G20 - FAO

16. Interventions to Reduce Food Losses

17. Ongoing Projects:
From Measurement to Solutions
Three ongoing projects:
• [Market-Based Incentives] Input provision vs. Market-based
contractual agreements (beans, Guatemala and Honduras)
• [Technology Adoption] Hermetic storage bags (maize, Ethiopia -
CIMMYT)
• [Extension] Handheld Farmer Decision Tool (potatoes, Ecuador - CIP)

18. 21.59%
27.58%
48.89%
Excessive rain Lack of rain
Pest, disease, animals Excess of chemicals
Wind Stolen
Source:own data collection from 450 producers in 2016
Guatemala, Beans - Reason for Pre-Harvest Loss
81.45%
18.55%
Poor harvest technique Lack of/costly labor
Source:own data collection from 450 producers in 2016
Guatemala, Beans - Reason for product left in the field
22.56%
44.78%
18.86%
8.75%
5.05%
Plagues, rodents, animals Laborer damages at selection
Laborer damages at harvest Climate (too much sun or rain)
Storage
Source:own data collection from 450 producers in 2016
Guatemala, Beans - Reason for loss at Post-Harvest
14.83%
35.24%
48.75%
Excessive rain Lack of rain
Pest, disease, animals Excess of chemicals
Wind Freeze
Stolen
Source:own data collection from 685 producers in 2016
Honduras, Beans - Reason for Pre-Harvest Loss
98.86%
1.14%
Poor harvest technique Lack of/costly labor
Source:own data collection from 685 producers in 2016
Honduras, beans - Reason for product left in the field
7.03%
65.69%
21.41%
2.93%
2.93%
Plagues, rodents, animals Laborer damages at selection
Laborer damages at harvest Climate (too much sun or rain)
Storage
Source:own data collection from 685 producers in 2016
Honduras, Beans - Reason for loss at Post-Harvest
Reasons of losses among bean farmers in
Guatemala and Honduras

19. Input provision vs. Market-based contractual
agreements in Guatemala and Honduras
Losses among bean farmers in Guatemala and Honduras:
• Pests, diseases, lack of rain
• Other reasons (inefficient harvesting, labor constraints)
Potential policies:
• Provide access to improved inputs (improved seeds, fertilizer)
• Incentivize increases in quality through market-based contracts
Test impact through field experiments
Partnering with public and private sector

20. Honduras
Bean
producers in
baseline
Input
provision
Market-based
contractual
arrangements
Control
Department of
Agriculture and
Livestock (SAG)
Improved seeds
and fertilizer
Experimental Arms Treatment Partner
Quality-
contingent
price premium
Honduran
Institute of
Agricultural
Marketing

21. Guatemala
Bean
producers in
baseline
Input
provision +
Contractual
Agreements
Control
ALBAY (Private
Agro Industrial
Company)
Improved seeds
and fertilizer
Quality-contingent
price premium
Experimental Arms Treatment Partner
Not possible to randomize across three groups
Private sector company interested in beans from particular variety / seed.

22. Data collection – Physical Measures of
Quality (ongoing)
Systematic sampling
of beans in storage
Humidity levels
Assessment of damages in
bean sample

23. Data collection – Physical Measures of
Quality (ongoing)
Presence of insects
Crop damage (attributes)
Weevil perforations Fungus
Broken grain Wrinkled grain

24. Data collection – Endline Household
Survey
Collect Household Survey in June / July
• Similar approach as baseline to measure food losses.
• Assess changes in food losses due to the interventions
• Welfare implications of food losses: Estimate changes in income,
expenditures, etc.
• Complement with physical measures of food losses
• Advance methodological tools: To what extent are survey-based
measures comparable to physical measures?

25. Conclusions and Future Activities

26. Conclusions
New methodology to measure food losses: (a) including the entire production process, (b)
along the value chain, (c) accounting for reductions in quantity and quality, (d) identifying
relevant processes.
Food losses are important: especially important at the farm level and when accounting for
quality.
Need to account not only for post-harvest, but also for pre-harvest and harvest losses
(important for quality, not only yields)
Application to five commodities in six countries… need to expand to gain better
understanding of FL

27. Dissemination of methodology to measure food losses
• Consolidation of methodology as a public good, country workshops
Test additional potential mechanisms to reduce food losses
Expand applications:
• Ghana (SNV-funded): Measurement of FL in the value chains of yam and groundnuts in three
northern regions. Focus on yam and groundnuts.
• Incorporate studies for perishable crops
• T20 approved technical brief to scale up methodology (joint with WB).
▪ Methodology presented at G20 Agricultural Ministerial Meeting
▪ Pilots with WB. Links to loans / TA to solve problems identified through our
methodology
Future Activities

28. Thank you!