A A PHLIS PHLIS f f or improved or improved Food Security Planning Food Security Planning Postharvest Losses Information Syste A A PHLlS PHLlS
Mar 31, 2015
AAPHLISPHLISffor improved or improved
Food Security PlanningFood Security Planning
Postharvest Losses Information SystemAAPHLlSPHLlS
AAPHLIS PHLIS –– the slideshow the slideshow
What is APHLIS and what problems does it address
How you can get PHL estimates from the system
How you can generate your own PHL estimates
The way forward
AAPHLIS PHLIS -- a unique servicea unique service
APHLIS generates estimates of postharvest losses (PHLs) of cereals in East and Southern Africa and is
Based on a network of local experts who submit data and verify loss estimates
Built on a complete survey of the literature on PHLs APHLIS provides ……
Loss estimates by cereal, by country and by province that are updated annually
A display of the data used to derive losses so the system is fully transparent, and
The opportunity to add better loss data so that loss estimation can improve over time
PostharvestPostharvestchainchain
What are Postharvest Losses (PHLs)?What are Postharvest Losses (PHLs)?
PHLs (of cereals) are the cumulative weight losses from production from each link in the postharvest chain (including all grain not fit for human consumption but not PHLs from processing e.g. milling).
Maize % weight losses 2007 from provinces of Zimbabwe and Ethiopia
The ProblemThe Problem
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Soaring food prices and the economic recession are hampering efforts to reduce poverty.
PHLs have negative impacts on hunger, poverty alleviation, income generation and economic growth. Yet the magnitude and location of such losses are poorly understood because PHL figures are
mostly guesstimates relatively difficult to trace for both logic and info source, and the sources themselves may not be very reliable
By improving PHL estimates it will be possible in the short term to -
Improve food security arrangements by calculating food supply estimates more reliably from production figures
….and long-term to target loss reduction interventions at –
the most affected areas (geographically) the most affected links in the postharvest chain or those that would be most cost effective to address, and
The advantages of better PHL estimatesThe advantages of better PHL estimates
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A system for getting better PhL estimatesA system for getting better PhL estimates
The main elements of APHLIS are –
Local expert network providing data and verifying PHLs
Database with access to local experts, by country,
PHL Calculator (model) that estimates losses
Web site for display of loss data by cereal for each country and each province, in tables and in maps
Downloadable calculator for PHL estimation at any geographical scale
Agric. data GIS maps of PHLs etc
Data tables
PHLs by crop country and province
PHL database
PHL calculator
PHL
tables
Calculator spreadsheet
AAPHLIS PHLIS – the System in a nutshell– the System in a nutshell
Download
AAPHLIS PHLIS network of experts network of experts –– its most import its most importanant t resourcesresources
How the PHL calculator worksHow the PHL calculator works
The PHL calculator determines a cumulative weight loss from production using loss figures for each link in the postharvest chain. A set of losses figures for the links of the postharvest chain is called a PHL profile
Harvesting/field drying 6.4
Drying 4.0
Shelling/threshing 1.2
Winnowing -
Transport to store 2.3
Storage 5.3
Transport to market 1.0
Market storage 4.0
Example of a PHL profile for maize grain
Figures taken from the literatureor contributed by network experts
PHL Calculator PHL Calculator contdcontd
PHL profiles are specific for Climate type (A – tropical, B - arid/desert, C – warm temperate) Crop type (different cereals) Scale of farming (subsistence/commercial)
Climate type A C B B A
Crop type Maize Maize Sorghum Millet Rice
Scale of farming Small Large Small Small Small
Harvesting/field drying 6.4 2.0 4.9 3.5 4.3
Drying 4.0 3.5 - - -
Shelling/threshing 1.2 2.3 4.0 2.5 2.6
Winnowing - - - - 2.5
Transport to store 2.3 1.9 2.1 2.5 1.3
Storage 5.3 2.1 2.2 1.1 1.2
Transport to market 1.0 1.0 1.0 1.0 1.0
Market storage 4.0 4.0 4.0 4.0 4.0
Five examples of PHL profiles
PHL Calculator PHL Calculator contdcontd
The PHL profile values are modified according to –
1. Wet/damp weather at harvest2. Length of storage period (0-3, 4-6, >6 months)3. Larger grain borer infestation (for maize only)
… and the PHL calculation takes into account –
4. The number of harvests annually (1, 2 or 3)5. Amount of crop marketed or retained in farm storage
NB PHL values are affected much more by the application of modifiersthan by the initial selection of the PHL profile.
How to get a PHL estimateHow to get a PHL estimate
Two ways to get PHL estimates Consult the tables and/or maps on the
website for losses by region, country or province
Postharvest Losses Information System
Losses estimates
Losses maps (interactive)
Literature
Downloads
PHL Network
About us Contacts Links
Production
Yield
Larger grain borer
Average farm size
Home
Loss tablesLoss tables
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Regional losses for all cereals and by cereal type
Click
Estimated Postharvest Losses (%) 2003 - 2009
Loss tables by cereal type and countryLoss tables by cereal type and country
Click
Estimated Postharvest Losses (%) 2003 - 2009
Loss tables by cereal type and provinceLoss tables by cereal type and province
Click on one of these figuresto get details of the loss calculation
Estimated Postharvest Losses (%) 2003 - 2009
Details of the loss calculation.1. Production data by farm type and losses over seasons
Calculation matrix documenting the PH loss calculationquality of data sources and references to sources
Country: MalawiProvince: Area under National AdministrationClimate: Humid subtropical (Cwa)Year: 2007Crop: Maize
Production
Annual production and losses
Grain remainingLost grain
tonne
Seasonal production and losses
%
Season Farm typeProduction (t) Remaining (%)Losses (t) Production (%)Remaining (t) Losses (%)
Details of the loss calculation2. Factors modifying the PHL profile
Rain at harvest – increases loss at harvest time.
Larger Grain Borer – LGB attack doubles farm storage losses.
Marketed at harvest % - divides the harvest between what is stored on farm and what is sent to market.
Storage duration - loss increases with longer storage periods.
Marketed at harvest (%)
Rain at harvest
Storage duration(months)
Larger grain borer
no data
yes
no data
20
PHL (%) calculation
PHL (%) Calculation: Season: 1 Farm Type: small
Details of the loss calculation3. The PHL profile and loss increments
Stages
Harvesting/fielddryingPlatform drying
Threshing and shellingWinnowingTransport to farmFarm storage
Transport to marketMarket storage
PH profile(adjusted)
Remaining grain Loss increment
Total 58.6 15.7
69.5 4.86.4
66.8 2.84
66 0.81.2
66 0-
64.4 1.52.3
58.6 5.89
58.6 01
58.6 04
Datum not a measured estimate
Data overall specific to maize
Details of the loss calculation4. Quality of the data in the PH profile and references to data sources
1
0
Datum not specific to maize0
Data overall not measured0
The reference toBoxall 1998
Stages Loss figure Reference Cereal Climate Farm type Method
References and individual loss figures % for small farms
Origin of figure
6.45.0
9.55.8
9.92.0
Harvesting/field drying
The PHLs are also displayed on mapsThe PHLs are also displayed on maps
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PHL values in 2007
Maize Sorghum Wheat
There are also maps of LGB by yearThere are also maps of LGB by year
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Locations where Larger Grain Borer (Prostephanus truncatus) wasconsidered to be a significant pest in 2007
AFRICA-PHL LGB 2007
Getting your own PHL estimateGetting your own PHL estimate- using the downloadable calculator- using the downloadable calculator
The downloadable calculator lets you enter your own figures. It can
Work at whatever geographical scale is relevant
See all the details of the calculationAssess the reliability and see the
origin of data Record multiple estimates and
obtain weighted average PHLs
The downloadable calculator – front pageThe downloadable calculator – front page
You can change the default figures (in blue)
Change language
Open calculator
……………………..changing the defaults..changing the defaults
You can change any of the default figures (in blue)
……… ……… observing the calculationobserving the calculation
Cumulative annual loss for one season
PHL profiles for large-scale & small -scale maize farming in Cwa climate
Conclusions Conclusions
APHLIS generates PHL estimates for cereal grains that are -
Transparent in the way they are calculated
Contributed (in part) and verified by local experts
Updated annually with the latest production figures
Based on the primary national unit (i.e. province)
Upgradeable as more (reliable) loss data become available
For the future For the future
For the future APHLIS ……..
Would benefit from an effort to generate more PHL data.
Should be made sustainable by efforts of the international community.
Could be expanded in geographical range (W. Africa, Asia, S. America) and technical content (e.g. pulses)
May be used in new ways, for example as unseasonal rain becomes more common the impact of this on PHLs can be predicted