Contextual data: Madagascar - Rice - All years

‹ 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022
Madagascar total 3,610,626 3,977,863 3,722,303 3,815,849 3,100,504 4,030,000 4,231,146 4,232,042 3,952,493 3,952,493
Alaotra-Mangoro   342,888 507,954 319,936 357,401 240,465 507,000 564,800 603,807 451,108 451,108  
Amoron'i Mania   135,534 154,166 142,209 168,759 136,781 105,000 131,203 120,422 135,806 135,806  
Analamanga   301,118 238,415 173,572 183,501 146,268 257,000 326,739 337,507 260,911 260,911  
Analanjirofo   128,861 116,275 123,438 117,661 118,647 205,000 280,780 234,404 137,681 137,681  
Androy   29,198 20,000 4,200 1,825 2,712 5,000 12,453 5,414 20,524 20,524  
Anôsy   74,100 50,000 33,970 12,297 13,527 108,000 132,955 11,629 68,869 68,869  
Atsimo-Andrefana (South-West)   139,370 111,496 122,983 76,421 61,032 84,000 153,600 81,265 141,845 141,845  
Atsimo-Atsinanana (South-East)   47,935 39,473 31,436 35,793 16,211 100,000 101,767 161,282 90,071 90,071  
Atsinanana (East)   96,385 110,909 103,145 83,568 41,028 101,000 52,361 131,500 110,446 110,446  
Betsiboka   72,752 98,654 71,773 43,064 23,452 56,000 35,401 87,930 89,369 89,369  
Boeny   129,782 167,448 209,989 155,413 91,965 312,000 452,648 215,796 224,874 224,874  
Bongolava   200,645 210,413 198,487 201,048 207,579 261,000 58,119 55,073 167,346 167,346  
Diana   78,104 112,874 82,646 91,969 81,300 135,000 194,460 57,449 105,417 105,417  
Haute Matsiatra (Upper Matsiatra)   222,726 243,255 218,930 183,791 156,700 168,000 156,565 160,136 249,797 249,797  
Ihorombe   21,072 20,910 25,713 10,285 9,740 37,000 23,166 5,367 32,040 32,040  
Itasy   377,243 442,223 464,501 535,616 477,912 175,000 286,209 320,954 319,945 319,945  
Melaky   55,053 59,320 77,116 58,492 51,312 110,000 143,531 129,480 75,387 75,387  
Menabe   108,211 86,274 61,113 60,160 45,089 192,000 179,559 149,969 111,904 111,904  
Sava   130,035 178,204 213,845 277,998 250,949 229,000 172,736 265,819 188,834 188,834  
Sofia   143,274 198,742 229,437 203,718 171,717 336,000 227,167 439,033 299,181 299,181  
Vakinankaratra   661,255 662,085 695,961 837,102 718,589 402,000 352,959 453,651 510,748 510,748  
Vatovavy-Fitovinany   115,085 148,773 117,903 119,967 37,529 145,000 191,968 204,155 160,390 160,390  

Data version 2.19.3

Contextual data

Collected data

Values obtained from primary and secondary sources

Approximated data

Values approximated based on other data for same location

–No data

Not applicable or no data available

LGB Larger Grain Borer (Prostephanus truncatus) read more ›

Storage beetle pest of maize and dried cassava

Contextual data

Contextual factors relate to local conditions and practices that may affect losses on a seasonal or annual basis, such as weather, pest incidence, grain drying conditions and the length of household-level storage.

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APHLIS network and team members collect this data from official sources (e.g. ministries of agriculture and statistics offices), published research studies and national surveys etc, or by interviewing farmers, extension workers or other key informants. This data enables APHLIS to apply the relevant loss figures from the PHL profiles depending on seasonal circumstances, and convert percentage losses into absolute losses (in tonnes) using the production figures. Based on the postharvest loss profiles and contextual factors, APHLIS estimates postharvest losses at the provincial, national and regional levels.

The contextual dataset includes production quantities (t), whether it rained at harvest, the percentage of the crop marketed during first 3 months after harvest, household-level storage duration, and presence of specific pests (for example the larger grain borer, LGB, Prostephanus truncatus) which are used to contextualise the loss profile for each year. The importance of different types of contextual factors may vary between crops, and data for the most relevant contextual factors is shown and used in the loss estimate calculations.

For specific crop, location, year combinations where contextual data is not available, approximated data has been used. This is calculated based on the contextualised data which has been provided for the same location. Approximated contextual data is shown in grey. 

Read more about how APHLIS estimates losses ›

Contextual factors

Production quantity (t) the quantity of grain produced on small and large farms for each growing season.

Rain at harvest whether or not there is damp weather at time of harvest which would make drying the grain difficult. If there is rain at harvest then the value for the harvesting link in the PHL profile is increased.

% sold during first 3 months the proportion of grain that is marketed within the first three months, i.e. that will not enter farm storage for any significant time. This proportion of the production will not be subject to farm storage losses but instead will be affected by transport and market storage losses.

Household-level storage duration (months) the length of time that grain was stored at household-level. If household-level storage is less than 3 months then household-level storage loss is reduced to 0%, if 3 to 6 months it will be only 50% of the loss profile figure, or if 6 months or more than 100% of the household-level storage loss is applied.

LGB presence in the case of maize, whether or not LGB (the larger grain borer, Prostephanus truncatus) is expected to be a significant pest. If LGB is a serious pest in that particular season then storage losses are multiplied by 2.

Season

In locations where there is more than one growing season each year, seasonal production data for each of the growing seasons is inputted. These are labelled as first, second, third season.

Farm type

In locations where there are both smallholder farms and large-scale commercial farms, the contextual data is shown for each of these types.

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