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