The document discusses two research studies examining food loss and waste in Malawi and China. The first study evaluates the impact of hermetic storage bags on smallholder farmers in Malawi to reduce post-harvest losses. The second study aims to quantify greenhouse gas emissions from food loss and waste across China's entire food supply chain and identify mitigation strategies.

1. FOOD LOSS AND WASTE JULY 2019
Understanding Smallholder Farmers’
Post-Harvest Behaviors: Evidence from
Malawi
Tabitha C. Nindi (Purdue University )
CLIFF-GRADS WEBINAR

2. Research problem and objectives
One of the major post-harvest challenges that smallholder
farmers face includes crop damage by molds and storage
pests that can damage up to 30 percent of the grain
stocks in six months.
 Lack of efficient storage technologies results into:
 More post-harvest losses Food insecurity.
 Grain quality loss  reduced market value Lower incomes.
 Exposure to storage chemical and aflatoxin  Compromised
food safety.
Another challenge includes limited access to credit 
Inability for smallholders to increase productivity or invest
in effective technologies that are capital intensive.

3. The Setting
We working with NASFAM farmers from Mchinji and Lilongwe
districts of Central Malawi.
Focusing on grain crops including maize, soybeans,
Groundnuts and common beans.
We introduced and are evaluating the impact of the Purdue
Improved Crop Storage (PICS) bags on reducing post-harvest
losses amongst other outcomes.
• The PICS bag is a low‐cost hermetic storage technology that
farmers could use to store crops throughout the year to take
advantage of seasonal price increases

4. Research Methods
We using clustered Randomized Control Trials to evaluate
causal effects of our interventions on outcomes including post-
harvest losses, food security, expenditure on storage chemicals,
post-harvest labor use and agricultural revenues.
Our interventions include (i) the technology intervention (The
PICS bags), (ii) financial training plus group storage and (iii)
credit intervention.
We are collecting post-intervention data to examine the effects
of our storage interventions and determine effective incentive
mechanisms for farmers to exploit seasonal price fluctuations
and also reduce storage losses.

5. FOOD LOSS AND WASTE JULY 2019
Effects of Amending Soil with Organic Matter on Population Change
of Aspergillus flavus and Antagonistic Microbiome; and on
Aflatoxin Contamination of Groundnut in Malawi
Norah Machinjiri
Haramaya University (Ethiopia)
CLIFF-GRADS WEBINAR

6. Research problem and objectives
• There is no sufficient documentation on how different sources and rates of
organic soil amendments affect the population of aflatoxin producing fungi
and their natural antagonists.
• In addition, the mitigation potential of these sources in relation to their
potential to reduce groundnut-based food loss to aflatoxins has not been
explored
The study will therefore:
• compare the effects of commercial organic fertilizer and farmyard manure
on changes in population of A. flavus, Trichoderma spp. and
Pseudomonas fluorescens
• evaluate the effects of organic matter soil amendments on aflatoxin
contamination in groundnut
• Compare amounts of net carbon retained by soils amended with farmyard
manure and commercial organic fertilizer at varied rates

7. The Setting
Supply chain
• The study identifies the pre-harvest period of the groundnut crop as
the first critical loss point to aflatoxin contamination
Location
• An experiment was laid out at two research stations in the central
region of Malawi: Chitedze Agricultural Research Station (Lilongwe)
and Chitala Agricultural Research sub-Station (Salima)
Intervention
• Farmyard manure (FYM) and commercial organic fertilizer (COF) were
identified as potential organic soil amendments for the reduction of pre-
harvest aflatoxin contamination while enhancing soil carbon
sequestration
• A randomized complete block design with 3 replications was employed
with FYM applied at 0, 2.5, 5.0 & 7 tons/ha; and COF at 0, 0.2, 0.4 &
0.6 tons/ha.

8. Research Methods
GHG emissions
• Soils were sampled prior to amendment with treatments and tested for
organic carbon content.
• Soils have been sampled again after harvest to compare amounts of
net carbon retained across treatments in the season.
FLW estimates
• Food loss estimates will be done qualitatively by testing aflatoxin
content (using ELISA technique) in groundnut samples from all
treatments
• Results will be compared to determine the treatments that result in
tolerable aflatoxin levels ( > 15ppb by Malawian standards).
• Potential food loss to aflatoxins will also be assessed by comparing
population change of Aspergillus flavus and its antagonistic
microbiome across treatments.

9. FOOD LOSS AND WASTE JULY 2019
Quantifying GHG emissions of agrifood chain and associated
food loss and food waste in China
Li Xue
University of Southern Denmark
CLIFF-GRADS WEBINAR

10. Research problem and objectives
• Research problem
What are the patterns and scales of food loss and food waste along the
whole Chinese food supply chain and the associated GHG emissions?
• Research objectives
Quantifying the magnitude of GHG emissions induced by each product
category;
Identifying the hotspots along the food supply chain with the highest
emissions;
Discussing GHG emissions mitigation strategies on the entire food
supply chain.

11. The Setting
• Supply chain
Six processes, including agricultural production, postharvest handling and
storage, processing, distribution, retailing, and consumption. Two markets
(raw food materials and processed food products) and their import and export
flows were also considered.
• Location
China is the most populous country with 22% of the world total population
but only 7% of world’s arable land.
The rural-to-urban migration and increasing living standard lead to diet
structure change.
China is experiencing a high level of food loss and food waste.
• Location Identify any interventions for reducing food loss
and waste and emissions
The implementation of the “Eight Rules” of the Political Bureau of the Central
Committee of the Communist Party of China since 2012.

12. Research Methods
• GHG emissions
Production stage: Considering the emissions resulted from the
production of each food categories.
Other stages: The carbon footprint (CF) coefficients of food were
calculated based on the BCFN Double Pyramid Database (2016).
• FLW estimates
Field study on consumer food waste：conducted field survey and
weighed food waste in restaurants in four case cities (Beijing, Shanghai,
Chengdu, Lhasa) in China.
Field study on supply chain losses of major agrifood products: rice,
wheat, maize, vegetables, etc.
Literature data collection: searched for literature published in Chinese
and English containing food loss or food waste rate of one food
commodity at each process.

13. FOOD LOSS AND WASTE JULY 2019
A Stepping-Stone to the evidence base for the mitigation of
N2O emission from reduced food loss and waste in China and
Myanmar
Xia Liang
The University of Melbourne

14. Research problem and objectives
• What is the problem your research addresses?
What is the potential / How efficiency
for the mitigation of N2O emissions from reduced food loss and waste in
China and Myanmar
• List up to three research objectives
• Develop a standardized methodology for estimating the N2O emissions
along the food supply chains for each major food categories;
• Promote a national estimation of FLW and N2O emissions by integrating
‘big data’ mining, meta-analysis and process-based modelling in China
and Myanmar;
• Expand the evidence base for the mitigation of N2O emissions from
reduced FLW;

15. The Setting
• Supply chain
The supply chains includes 155 crop and 11 livestock commodities, the
major categories are cereal crops; oil crops; pulses; vegetables and
melons; roots and tubers; sugar crops; fruits; tree nuts; other crops;
meat and milk from cattle, buffalo, sheep and goats; meat from pigs;
and meat and eggs from chickens.
• Location
China and Myanmar
• Location Identify any interventions for reducing food loss and waste
and emissions
China: national policies and regulations relevant to food losses and
food waste can be categorized as two groups that address food waste
generation and that deal with food waste treatment by several
government ministries and agencies.
Myanmar: have not identify any interventions

16. Research Methods
N2O emissions
Life cycle assessment (LCA), ecosystem modelling and process-based
modelling , remote sensing, field monitoring, ‘big data’ mining and meta-
analysis.
FLW estimates
Life cycle perspective: “food losses” (pre-consumer stage)
“food waste” (consumer stage)

17. FOOD LOSS AND WASTE JULY 2019
Food waste reduction entrepreneurship initiative and
associated impacts: a Life Cycle Sustainability Assessment
Daniele Eckert Matzembacher
UFRGS, Brazil
CLIFF-GRADS WEBINAR

18. Research problem and objectives
• PhD Student Business
• Marketing standards related to aesthetic issues or packaging defects
cause some products to be rejected, although neither food quality or
safety is affected - aesthetic standards concerning weight, size, shape
and appearance of food product.
• This research aims to measure food waste reduction and associated
sustainability impacts of Brazilian entrepreneurship initiatives in fruits
and vegetables that do not meet retail aesthetic standards
• 1) To quantify the food that would be wasted by the producers – due to
market problems - and that are rescued by the company
• 2) To perform a Life Cycle Assessment (LCA) to identify associated
emission reductions
• 3) To perform a Social-Life Cycle Assessment (S-LCA)
• 4) To perform a Social Return on Investment (SROI)

19. The Setting
• Supply chain: fruits and vegetables
• Location: São Paulo, Brazil
• Problem (cooperation – the company first accepted and now
does not answer – negotiating)

20. Research Methods
GHG emissions
- Life Cycle Assessment (LCA)
Social Impact
- Social-Life Cycle Assessment (S-LCA)
Economic Impact
- Social Return on Investment (SROI)
FLW estimates
- The tree structure - A general framework for food waste
quantification in food services (Mattias Eriksson - Swedish
University of Agricultural Sciences)