Dry weight loss: Gambia - Rice - All years

Metric

	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022
Gambia total	11.9	11.9	11.9	11.9	11.9	11.9	11.9	11.9	11.9	11.9
Banjul	–	–	–	–	–	–	–	–	–	–
Central River	11.9	11.9	11.9	11.9	11.9	11.9	11.9	11.9	11.9	11.9
Lower River	11.9	11.9	11.9	11.9	11.9	11.9	11.9	11.9	11.9	11.9
North Bank	–	–	–	–	–	–	–	–	–	–
Upper River	11.9	11.9	11.9	11.9	11.9	11.9	11.9	11.9	11.9	11.9
Western	11.9	11.9	11.9	11.9	11.9	11.9	11.9	11.9	11.9	11.9

Data version 2.19.3

Dry weight losses

0.0 % 30.0 %

Complete data

Specified to local conditions

Incomplete data

Some contextual data is missing

Minimal data

Postharvest loss profiles only

–No data

Not applicable or no data available

Postharvest losses

APHLIS provides science-based estimates of the amount of postharvest loss (PHL) occurring for the specified crops in each province of each specified country in sub-Saharan Africa.

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Postharvest loss figures which have been measured and reported in the scientific literature for specific crops and locations and years are extracted and used to create PHL profiles of the level of losses occurring at each PH stage for each crop. As contextual factors such as weather, pest incidence, storage duration, production quantities influence the amount of loss that occurs, these factors are used to contextualise the loss estimates for each crop, location, value chain stage, year combination.

Use the filters to select your focal location, crop, year combination, and then select and switch between the different loss metrics offered: Percentage (%); Dry weight loss (t); Financial value of loss (USD).

By clicking on each loss figure, a pop-up will be displayed which lists the references of the scientific studies from which measured loss figures were extracted and used for calculating this loss estimate. By clicking on the crop name, the data-view will change from showing the national postharvest losses to display the losses which occurred for that crop in each province by each year. You can then click on a specific loss figure to display the list of references of the scientific studies from which measured loss figures were extracted and used for calculating this loss estimate, the relevant loss figures for each study are listed and the table indicates whether the loss figure was specific to the crop, climate type, farm type and was measured.

The contextual dataset (e.g. production quantities, rain at harvest, percentage of crop marketed during first 3 months after harvest, farm storage duration, and presence of specific pests) used to contextualise the loss profile for each year can be viewed by clicking on the contextual data tab on the right hand-side of the screen.

Available metrics

Percentage loss (%) the cumulative % loss in weight from production of ready to consume grain incurred during harvesting, drying, handling operations (i.e. threshing, shelling, winnowing), household level storage,transport and market-level storage for the selected location, crop and year.

Dry weight loss (t) this is the ‘absolute weight loss (in tonnes)’ which occurred postharvest for the selected crop, location and year. It is calculated by multiplying the APHLIS percentage loss estimate by the annual production figures for the selected crop, location and year. It is referred to as dry weight loss as it reflects the weight of losses of the dried focal cereal and legume crops.

Financial value of loss (USD) expresses the value of the postharvest weight loss in USD. It is calculated by multiplying the APHLIS percentage loss estimates by the annual production figures by the price (current USD) for the selected crop, location and year.

Other tabs

Nutritional losses: the nutritional value of the postharvest losses
Nutritional impact: postharvest losses expressed in terms of nutritional impact on the total population and on specific focal groups
Financial impact: postharvest losses expressed in terms of their financial impact on the economy

Help us improve APHLIS

We are always looking to improve our postharvest loss estimates. If you know of any interesting studies, or if you have any field or contextual data that we could include in our algorithm, please email us on info@aphlis.net.