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Components of APHLIS and how postharvest losses are calculated. Composants des APHLIS et des pertes post- récolte comment sont calculées. JRC. EUROPEAN COMMISSSION. What we will cover. What is APHLIS How the PHL calculator works The kinds of figures APHLIS produces

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slide1

Components of APHLIS and how postharvest losses are calculated

Composants des APHLIS et des pertes post-

récolte comment sont calculées

JRC

EUROPEAN COMMISSSION

what we will cover
What we will cover
  • What is APHLIS
  • How the PHL calculator works
  • The kinds of figures APHLIS produces
  • How we assess the quality of the loss estimates
  • Introduce the downloadable calculator
slide3

What is APHLIS?

  • APHLIS is a unique service. It provides estimates of postharvest losses of cereal grains in sub-Saharan Africa.
  • It is based on a network of local experts who submit
  • data and verify loss estimates
  • It gives loss estimates by cereal, by country
  • and by province
  • Loss estimates are updated annually
  • The method and the data used to derive losses are
  • displayed so the system is fully transparent, and
  • Better loss data can easily be added to the system
  • so loss estimation can improve over time
slide4

Components of APHLIS

Network of local experts

East and Southern Africa June 2008

to supply data and

verify PHL estimates

West and Central Africa April 2012

slide5

PHL database

Network of local experts

  • Stores key data
    • Production/yield
    • Rainfall
    • Climatic extremes etc
  • Is accessible by network
  • Annual up-dates
slide6

PHL database

PHL calculator

  • Estimates cumulative weight loss from production
  • Uses figures for loss from literature and from network
  • Network verifies loss estimates
slide7

Data

tables

PHL calculator

PHL

tables

PHLs by crop

country and

provinces

Key agric.

data

GIS maps of

PHLs and

other data

The web site

Displays PHL estimates and key data

http://www.phlosses.net

slide8

Downloads

Data

tables

PHL

tables

PHLs by crop

country and

provinces

Key agric.

data

GIS maps of

PHLs and

other data

Calculator spreadsheet

  • Allows users to enter own figures

Users’ Guide

slide9

How the PHL calculator works

Comment la calculatrice de PHL fonctionne

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

Example of a PHL profile for maize grain

Exemple d\'un profil de PHL pour le grain de maïs

Figures taken

from the literature

or contributed by

network experts

slide10

PHL Calculator contd

  • PHL profiles are specific for
  • Climate type (A – tropical, B - arid/desert, C – warm temperate)
  • Crop type (different cereals)
  • Scale of farming (subsistence/commercial)

Five examples of PHL profiles

phl calculator contd
PHL Calculator contd

The PHL profile values are modified according to –

Wet/damp weather at harvest

Length of storage period (0-3, 4-6, >6 months)

Larger grain borer infestation (for maize only)

… and the PHL calculation takes into account –

The number of harvests annually (1, 2 or 3)

Amount of crop marketed or retained in farm storage

NB PHL values are affected much more by the application of modifiers

than by the initial selection of the PHL profile.

the website
The website

Postharvest Losses Information System

Home

  • Two ways to get PHL estimates
  • Consult the tables and/or maps on the website for losses by region, country or province
  • Download the PHL Calculator spreadsheet to enter user-preferred values for losses at a user defined geographical scale

Losses estimates

Losses maps (interactive)

Literature

Downloads

PHL Network

About us Contacts Links

Production

Yield

Larger grain borer

Average farm size

loss tables
Loss tables

Regional losses for all cereals and by cereal type

Estimated Postharvest Losses (%) 2003 - 2009

Click

loss tables by cereal type and country
Loss tables by cereal type and country

Estimated Postharvest Losses (%) 2003 - 2009

Click

slide15

Loss tables by cereal type and province

Estimated Postharvest Losses (%) 2003 - 2009

Click on one of these figures

to get details of the loss calculation

slide16

Calculation matrix documenting the PH loss calculation

quality of data sources and references to sources

Country: Malawi

Province: Area under National Administration

Climate: Humid subtropical (Cwa)

Year: 2007

Crop: Maize

Details of the loss calculation.

1. Production data by farm type and losses over seasons

Annual production and losses

%

tonne

Production

Grain remaining

Lost grain

Seasonal production and losses

Remaining (%)

Losses (%)

Season

Farm type

Production (t)

Remaining (t)

Losses (t)

Production (%)

slide17

PHL (%) calculation

PHL (%) Calculation: Season: 1 Farm Type: small

20

Marketed at

harvest (%)

Marketed at harvest % - divides the harvest between what is stored on farm and what is sent to market.

Details of the loss

calculation

2. Factors modifying the PHL profile

Rain at harvest – increases loss at harvest time.

no data

Rain at harvest

no data

Storage duration

(months)

Storage duration - loss increases with longer storage periods.

Larger Grain Borer – LGB attack doubles farm storage losses.

yes

Larger grain borer

slide18

Season 2 – smallholder only

no grain marketed, all remains on

farm.

Details of the loss calculation

3. The PHL profile and loss increments

PH profile

(adjusted)

Remaining grain

Loss increment

Stages

Harvesting/field

drying

6.4

93.6

6.4

4

89.8

3.7

Platform drying

Threshing and

shelling

1.2

88.7

1.1

-

88.7

0

Winnowing

Transport to

farm

2.3

86.7

2.1

Farm storage

9

78.9

7.8

Transport to

market

1

78.9

0

Market storage

4

78.9

0

78.9

21.1

27.9

Total

slide19

Details of the loss calculation

4. Quality of the data in the PH profile and references to data sources

Origin of figure

Datum not a measured estimate

Datum not specific to maize

References and individual loss figures % for small farms

Stages

Loss figure

Reference

Cereal

Climate

Farm type

Method

2.0

9.9

5.8

9.5

5.0

Harvesting/field drying

6.4

Data overall specific to maize

The reference to

Boxall 1998

Data overall not measured

there are also maps of lgb by year
There are also maps of LGB by year

Locations where Larger Grain Borer (Prostephanustruncatus) was

considered to be a significant pest in 2007

APhLlS

conclusions
Conclusions
  • In the initial stages, APHLIS may or may not produce loss
  • figures that are different from those currently in use and if they are different there will be no solid evidence that they will be more accurate.
  • However, the new system generates estimates for PHLs of 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
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