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Estimated Postharvest Losses (%) 2003 - 2023

The figures quoted in the tables below are estimates of cumulative weight loss from production incurred during harvesting, drying, handling operations, farm storage, transport and market storage. The loss values for each link in the postharvest chain are taken from the scientific literature and are modified by several seasonal factors that vary from year to year and are submitted by the APHLIS network. More details can be found in the ‘Understanding APHLIS’ manual and the ‘Weight Loss Review’ article. The first loss table gives a regional weighted average PHL by crop. By clicking on the various country links it is possible to see the PHL by crop for country and then for each province. By clicking on a provincial loss figures it is possible to display the key data used in the calculation, including the seasonal data. The figures used for estimating the PHLs are displayed and a quality assessment is given of these figures as to whether they are specific to the cereal type, farm type and climate in question and the bibliographical source of the data can also be traced in a full reference list.

for Rice in : Tanzania

Provinces of Tanzania

Click on a loss figure in the table below to see in detail how the figure was derived. Send us your comments if you have the feeling that the underlying data and assumptions could be improved.

Please sent your comments to info(at)phlosses.net.

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Province 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023
Arusha 10.910.910.910.910.910.910.910.910.910.9  -    -    -    -    -    -    -    -    -    -    -  
Dar-Es-Salaam 11.911.911.911.911.911.911.911.9  -  11.9  -    -    -    -    -    -    -    -    -    -    -  
Dodoma 11.911.911.911.911.911.911.911.911.911.9  -    -    -    -    -    -    -    -    -    -    -  
Iringa 11.911.911.911.911.911.911.911.911.911.9  -    -    -    -    -    -    -    -    -    -    -  
Kagera 11.911.911.911.911.911.911.911.911.911.9  -    -    -    -    -    -    -    -    -    -    -  
Kaskazini-Pemba   -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -  
Kaskazini-Unguja   -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -  
Kigoma 11.911.911.911.911.911.911.911.9  -  11.9  -    -    -    -    -    -    -    -    -    -    -  
Kilimanjaro 11.911.911.911.911.911.911.911.911.911.9  -    -    -    -    -    -    -    -    -    -    -  
Kusini-Pemba   -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -  
Kusini Unguja   -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -  
Lake Victoria   -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -  
Lindi 11.911.911.911.911.911.911.911.911.911.9  -    -    -    -    -    -    -    -    -    -    -  
Manyara 10.910.910.910.910.910.910.910.910.910.9  -    -    -    -    -    -    -    -    -    -    -  
Mara 11.911.911.911.911.911.911.911.911.911.9  -    -    -    -    -    -    -    -    -    -    -  
Mbeya 10.910.910.910.910.910.910.910.910.910.9  -    -    -    -    -    -    -    -    -    -    -  
Mjini-Magharibi   -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -  
Morogoro 11.911.911.911.911.911.911.911.911.911.9  -    -    -    -    -    -    -    -    -    -    -  
Mtwara 11.911.911.911.911.911.911.911.911.911.9  -    -    -    -    -    -    -    -    -    -    -  
Mwanza 11.911.911.911.911.911.911.911.911.911.9  -    -    -    -    -    -    -    -    -    -    -  
Pwani 11.911.911.911.911.9  -    -  11.911.9  -    -    -    -    -    -    -    -    -    -    -    -  
Rukwa 11.911.911.911.911.911.911.911.911.911.9  -    -    -    -    -    -    -    -    -    -    -  
Ruvuma 11.911.911.911.911.911.911.911.911.911.9  -    -    -    -    -    -    -    -    -    -    -  
Shinyanga 11.911.911.911.911.911.911.911.9  -  11.9  -    -    -    -    -    -    -    -    -    -    -  
Singida 10.910.910.910.910.910.910.910.9  -  10.9  -    -    -    -    -    -    -    -    -    -    -  
Tabora 11.911.911.911.911.911.911.911.911.911.9  -    -    -    -    -    -    -    -    -    -    -  
Tanga 11.911.911.911.911.911.911.911.911.911.9  -    -    -    -    -    -    -    -    -    -    -  
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Estimated Postharvest Losses (t) 2003 - 2023

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Province 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023
Arusha 9733441579061146319531614962128572221911332  -    -    -    -    -    -    -    -    -    -    -  
Dar-Es-Salaam 6841621111104910841062300293  -  335  -    -    -    -    -    -    -    -    -    -    -  
Dodoma 4473022902943042981043896745965  -    -    -    -    -    -    -    -    -    -    -  
Iringa 1913152214611483153215011666143211961542  -    -    -    -    -    -    -    -    -    -    -  
Kagera 774383332133715383937621035889669958  -    -    -    -    -    -    -    -    -    -    -  
Kaskazini-Pemba   -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -  
Kaskazini-Unguja   -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -  
Kigoma 3748941727168217381703104737661  -  9695  -    -    -    -    -    -    -    -    -    -    -  
Kilimanjaro 2098329340304400454744552034174816411883  -    -    -    -    -    -    -    -    -    -    -  
Kusini-Pemba   -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -  
Kusini Unguja   -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -  
Lake Victoria   -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -  
Lindi 114732713411422147016912383204813272206  -    -    -    -    -    -    -    -    -    -    -  
Manyara 97319892228226123372290312268202289  -    -    -    -    -    -    -    -    -    -    -  
Mara 106038373839393122681280289  -    -    -    -    -    -    -    -    -    -    -  
Mbeya 13740182891436914039145091421614464124291512213389  -    -    -    -    -    -    -    -    -    -    -  
Mjini-Magharibi   -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -    -  
Morogoro 1829496361395513098135361326222200190781434620551  -    -    -    -    -    -    -    -    -    -    -  
Mtwara 2722238422892323240123529107782634338430  -    -    -    -    -    -    -    -    -    -    -  
Mwanza 122291009010437138877793783819116164271583117696  -    -    -    -    -    -    -    -    -    -    -  
Pwani 14292370401235623681  -    -  312204970  -    -    -    -    -    -    -    -    -    -    -    -  
Rukwa 5832555053295408558959531502812914734513911  -    -    -    -    -    -    -    -    -    -    -  
Ruvuma 218224423423824524111083642655476922  -    -    -    -    -    -    -    -    -    -    -  
Shinyanga 5120937875021492713053127891539513230  -  13179  -    -    -    -    -    -    -    -    -    -    -  
Singida 1921681574135012211196518445  -  479  -    -    -    -    -    -    -    -    -    -    -  
Tabora 7130129281303214180185621673019384166571881017408  -    -    -    -    -    -    -    -    -    -    -  
Tanga 13009479098318588416324543415755854  -    -    -    -    -    -    -    -    -    -    -  
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Weighted average

  • Country : Tanzania
  • Province : Tanga
  • Climate : Tropical savanna (Aw)
  • Year : 2005
  • Crop : Rice


Annual production and losses
  tonne %
Production 7630 100
Grain remaining 6721 88.1
Lost grain 909 11.9

Seasonal production and losses
Season Farm Type Production (t) Remaining (t) Losses (t) Production (%) Remaining (%) Losses (%)
1 small 7630 6721 909 100.0 88.1 11.9
Seasonal: 7630 6721 909 100.0 88.1 11.9

NB Annual averages are a weighted average of the seasons

PHL (%) Calculation

PHL (%) Calculation: Season: 1 Farm Type: small
Grain marketed within the first three months after harvest (%) no data
If data is missing (no data) it is assumed that for subsistence farmers all grain is stored whereas for commercial farmers all grain is marketed.

Note: Figures in this table are farm type specific (small or large farms). The value Grain marketed within the first three months after harvest (%) is used to determine the percentage of total production that is stored and marketed by this type of farm in this particular season (Season 1, Season 2 etc). The calculation only considers the portion that is produced by this type of farm. Consequently, the figures below for Stored (%) and Marketed (%) will only add up to 100% if all grain in a particular season is produced on this farm type. Otherwise the corresponding percent figures for the other farm type, in the same season, must be included to arrive at a sum of 100%.
Rain at harvest no data
If weather is damp at harvest, leading to exceptional mould damage to the crop, then the value is yes and the Harvesting/field drying losses figure in the PHL profile is replaced by 16.3%.
Storage duration (months) no data
Effect of storage duration:
  1. 0-3 months % figure for storage is 0 (zero)
  2. 3-6 months the % figure of the PHL profile is divided by 2
  3. More than 6 months or in case of missing data (no data) the % figure in the general profile is used
Larger Grain Borer no data
If the crop is maize and the value is yes then the Farm storage loss figure in the PHL profile is multiplied by 2.
  Destination Stored (%) Marketed (%)
    100 0
Stages PHL profile (adjusted) Remaining grain Loss increment Remaining grain Loss increment
Harvesting/field drying 4.4 95.6 4.4 0 0
Platform drying 0 95.6 0 0 0
Threshing and Shelling 3.1 92.6 3 0 0
Winnowing 2.5 90.3 2.3 0 0
Transport to farm 1.3 89.2 1.1 0 0
Farm storage 1.2 88.1 1.1 0 0
Transport to market 1 88.1 0 0 0
Market storage 2.7 88.1 0 0 0
Total   88.1 11.9 0 0

PHL profile: Data quality display and references to sources

PHL profiles are used to calculate losses, each profile consists of a series of values, one for each link in the postharvest chain. Each value in the PHL profile is formed from the average of several figures drawn from the available literature. All these figures are shown individually in the tables below. Separate PHL profiles are given for small farms and large (commercial) farms. The reliability of each datum contributing to the calculation of each PHL profile value is displayed in the table below. The assessment is based on how specific the figure is to the situation in which it is being used. To do this, each figure is assessed according to whether it is from the same Cereal type (maize, rice etc), same Climate type (is from same Koeppen code), same Farm type (from a small farm or large commercial farm), and if the Method of loss assessment was an actual measurement of loss or was a questionnaire survey or guesstimate. The result of the assessment is indicated using the red/0 and green/1 system as follows -

0 A datum used in the calculation of a PHL profile value is not specific to this situation or is from a questionnaire survey or a guesstimate, i.e. is not measured.

1 A datum used in the calculation of a PHL profile value is specific to this situation or is measured.

PHL profile figures based on more 'green/1' data are considered to be more reliable than those based on more 'red/0' data. Against each PHL profile value the number of 'red/0' and 'green/1' assessments is averaged, and displayed in bold, to give a general assessment of the value. Frequently some parts of the profile are more reliable than others, especially those where more loss data are available from the literature.

References and individual loss figures % for small farms
  Origin of figure
Stages Loss figure Reference Cereal Climate Farm type Method
  4.0 Calverley D.J.B. - 1996 Title:
A study of loss assessment in eleven projects in Asia concerned with rice.
Source:
Rome, FAO ( (PFL/INS/001).
Author:
Calverley D.J.B.
Year of publication: 1996
Geo focus: Asia
1 0 1 1
  2.0 Huq F. - 1980 Title:
Rice in Bangladesh: An empirical analysis of farm level food losses in five post-harvest operations.
Source:
In: Grain quality improvement - Proceedings of the 3rd annual workshop on grains post-harvest technology. Kuala Lumpur, Malaysia, 29-31 January 1980. 245-262. - also see - Greeley M. (1982) Pinpointing post-harvest losses. Ceres 15 (1), 30-37.
Author:
Huq F. and Greeley M.
Year of publication: 1980
Geo focus: Bangladesh
1 1 1 1
  6.9 Repoblika Malagasy - 1987 Title:
Enquete sur les pertes de paddy apres recolte.
Source:
Ministere de la production agricole et de la reforme agraire. Pp 17 + tables
Author:
Repoblika Malagasy
Year of publication: 1987
Geo focus: Madagascar
1 1 1 1
  4.0 Smit C. - 1985 Title:
Post-harvest losses of some staples crops at farm level in Africa. Report on the regional workshop on national programming and intercountry co-operation prevention of food losses Volume II.
Source:
UN Food and Agriculture Organisation, African Regional Centre for Technology, Dakar Senegal 6-10 May 1985. pp. 124-137.
Author:
Smit C.
Year of publication: 1985
Geo focus: Africa
1 1 1 1
  3.8 Appiah F. - 2011 Title:
Post harvest losses of rice from harvesting to milling in Ghana.
Source:
Journal of Stored Products and Postharvest Research 2(4), pp. 64-71.
Author:
Appiah F., Guisse R. and Dartey P.K.A.
Year of publication: 2011
Geo focus: Ghana
1 1 1 0
  5.8 Ofusu T. - 1998 Title:
Improving the competitiveness and marketability of locally-produced rice in Ghana. 3. An assessment of rice post-harvest systems.
Source:
Department for International Development (DFID), Crop Postharvest Programme, Project R6688. pp 37
Author:
Ofusu T., Manful JT, Boxall R.
Year of publication: 1998
Geo focus: Ghana
1 1 1 1
Harvesting/field drying 4.4   1 1 1 1
  1.0 Calverley D.J.B. - 1996 Title:
A study of loss assessment in eleven projects in Asia concerned with rice.
Source:
Rome, FAO ( (PFL/INS/001).
Author:
Calverley D.J.B.
Year of publication: 1996
Geo focus: Asia
1 0 1 1
  1.8 Huq F. - 1980 Title:
Rice in Bangladesh: An empirical analysis of farm level food losses in five post-harvest operations.
Source:
In: Grain quality improvement - Proceedings of the 3rd annual workshop on grains post-harvest technology. Kuala Lumpur, Malaysia, 29-31 January 1980. 245-262. - also see - Greeley M. (1982) Pinpointing post-harvest losses. Ceres 15 (1), 30-37.
Author:
Huq F. and Greeley M.
Year of publication: 1980
Geo focus: Bangladesh
1 1 1 1
  1.3 Kidane - 1989 Title:
Food grain losses in tradional storage facilities in three areas of Ethiopia.
Source:
In: Proceedings of 'Towards a food and nutrition strategy for Ethiopia'. Alemaya University of Agriculture, 8-12 December 1986, Alemaya, Ethiopia.
Author:
Kidane, Y. and Habteyes Y.
Year of publication: 1989
Geo focus: Ethiopia
1 0 1 0
  6.5 Repoblika Malagasy - 1987 Title:
Enquete sur les pertes de paddy apres recolte.
Source:
Ministere de la production agricole et de la reforme agraire. Pp 17 + tables
Author:
Repoblika Malagasy
Year of publication: 1987
Geo focus: Madagascar
1 1 1 1
  2.3 Smit C. - 1985 Title:
Post-harvest losses of some staples crops at farm level in Africa. Report on the regional workshop on national programming and intercountry co-operation prevention of food losses Volume II.
Source:
UN Food and Agriculture Organisation, African Regional Centre for Technology, Dakar Senegal 6-10 May 1985. pp. 124-137.
Author:
Smit C.
Year of publication: 1985
Geo focus: Africa
1 1 1 1
  3.0 Singano C. - 2008 Title:
Singano C. (pers comm.) Principal Agricultural Research Scientist, Department of Agricultural Research Services, Malawi.
Source:
Ppers comm. Principal Agricultural Research Scientist, Department of Agricultural Research Services, Malawi.
Author:
Singano C.
Year of publication: 2008
Geo focus: Malawi
1 0 1 0
  6.1 Appiah F. - 2011 Title:
Post harvest losses of rice from harvesting to milling in Ghana.
Source:
Journal of Stored Products and Postharvest Research 2(4), pp. 64-71.
Author:
Appiah F., Guisse R. and Dartey P.K.A.
Year of publication: 2011
Geo focus: Ghana
1 1 1 0
Threshing and Shelling 3.1   1 1 1 1
  2.5 Repoblika Malagasy - 1987 Title:
Enquete sur les pertes de paddy apres recolte.
Source:
Ministere de la production agricole et de la reforme agraire. Pp 17 + tables
Author:
Repoblika Malagasy
Year of publication: 1987
Geo focus: Madagascar
1 1 1 1
Winnowing 2.5   1 1 1 1
  0.5 Huq F. - 1980 Title:
Rice in Bangladesh: An empirical analysis of farm level food losses in five post-harvest operations.
Source:
In: Grain quality improvement - Proceedings of the 3rd annual workshop on grains post-harvest technology. Kuala Lumpur, Malaysia, 29-31 January 1980. 245-262. - also see - Greeley M. (1982) Pinpointing post-harvest losses. Ceres 15 (1), 30-37.
Author:
Huq F. and Greeley M.
Year of publication: 1980
Geo focus: Bangladesh
1 1 1 1
  1.0 Kidane - 1989 Title:
Food grain losses in tradional storage facilities in three areas of Ethiopia.
Source:
In: Proceedings of 'Towards a food and nutrition strategy for Ethiopia'. Alemaya University of Agriculture, 8-12 December 1986, Alemaya, Ethiopia.
Author:
Kidane, Y. and Habteyes Y.
Year of publication: 1989
Geo focus: Ethiopia
1 0 1 0
  2.3 Repoblika Malagasy - 1987 Title:
Enquete sur les pertes de paddy apres recolte.
Source:
Ministere de la production agricole et de la reforme agraire. Pp 17 + tables
Author:
Repoblika Malagasy
Year of publication: 1987
Geo focus: Madagascar
1 1 1 1
Transport to farm 1.3   1 1 1 1
  1.4 Calverley D.J.B. - 1996 Title:
A study of loss assessment in eleven projects in Asia concerned with rice.
Source:
Rome, FAO ( (PFL/INS/001).
Author:
Calverley D.J.B.
Year of publication: 1996
Geo focus: Asia
1 1 1 1
  1.0 Huq F. - 1980 Title:
Rice in Bangladesh: An empirical analysis of farm level food losses in five post-harvest operations.
Source:
In: Grain quality improvement - Proceedings of the 3rd annual workshop on grains post-harvest technology. Kuala Lumpur, Malaysia, 29-31 January 1980. 245-262. - also see - Greeley M. (1982) Pinpointing post-harvest losses. Ceres 15 (1), 30-37.
Author:
Huq F. and Greeley M.
Year of publication: 1980
Geo focus: Bangladesh
1 1 1 1
Farm storage 1.2   1 1 1 1
  1.0 Odogola W.R. - 1991 Title:
Post harvest management and storage of maize.
Source:
UNDP/OPS Regional Programme, Harare December 1991. (very useful background on post-harvest handling)
Author:
Odogola W.R. and Henriksson R.
Year of publication: 1991
Geo focus: Africa
0 0 1 0
Transport to market 1.0   0 0 1 0
  4.0 Boxall R.A. - 1998 Title:
Grains post-harvest loss assessment in Ethiopia.
Source:
Final report NRI Report No 2377. Natural Resources Institute, Chatham, UK. pp 44.
Author:
Boxall RA
Year of publication: 1998
Geo focus: Ethiopia
0 0 1 0
  1.3 Egyir I.S. - 2011 Title:
M&E System for post harvest losses (Pilot Study)
Source:
Policy Planning, Monitoring and Evaluation Directorate, Ministry of Food and Agriculture, Ghana. Final Report. Pp. 106
Author:
Egyir I.S., Sarpong D.B. and Obeng-Ofori D.
Year of publication: 2011
Geo focus: Ghana
0 1 1 0
Market storage 2.7   0 1 1 0