Number of meat-producing herd mares at the end of the year, 2021–2022
The number of meat herd mares in Russia changed over the two-year period, and these columns reflect the 2021 and 2022 totals. Rows are categorized by federal districts and individual constituent entities, including the Russian Federation as a whole. The data show the livestock population across different parts of the country at the end of the reporting period
Dynamics of meat herd mare populations in Russia at the end of 2021 and 2022
Set in numbers
Rosstat data for 2021–2022. Series: 71, period: 2. Breakdown by items: RUSSIAN FEDERATION — Agricultural organisations; RUSSIAN FEDERATION — Peasant (farm) households …; CENTRAL FEDERAL DISTRICT — Agricultural organ…; Tver Region — Agricultural organisations; SOUTHERN FEDERAL DISTRICT — Agricultural organisations and others
Republic of Adygea — Agricultural organisations: the indicator rose from 7 to 1,000 million between 2021–2022 — by 142.9 million times. Of the 23 largest rows, 16 increased, 7 decreased
All table numbers are series: 71
How to read this table
Comparing annual indicators helps track changes in animal population within a specific region or district. The list includes both national totals and data for the Southern Federal District and the Republic of Adygea. Each row corresponds to a specific territorial unit, facilitating the search for a particular area
What is visible in these numbers
Five largest values: Republic of Adygea — Agricultural organ… (1,000 million), Rostov Region — Agricultural organ… (1,000 million), RUSSIAN FEDERATION — Peasant (farm…) (166,494), RUSSIAN FEDERATION — Agricultural o… (63,804), VOLGA FEDERAL DISTRICT — Peasant (… (25,721). The gap between the largest and smallest is 23.8 million times. The top five account for 100% of the total across all items — the distribution is heavily skewed toward the top
Observations are annual and cover 2 periods. Cells with numbers: 50 out of 50 (100%), i.e., the table is almost entirely filled
The same indicator for other periods
These series cannot be stitched together Over the common period 2021 values diverge — Rosstat recalculated the indicator using a revised methodology. They cannot be combined into a single chart: a break would appear at the junction, which did not actually occur
| Indicator for 2021 | here | in the adjacent series | divergence |
|---|---|---|---|
| Российская федерация — Сельскохозяйственные организации | 63 706,0 | 63 706,0 | +0,0 |
| Российская федерация — Крестьянские (фермерские) хозяйства и индивидуальные предприниматели | 161 721,0 | 161 721,0 | +0,0 |
| Центральный федеральный округ — Сельскохозяйственные организации | 846,0 | 846,0 | +0,0 |
| Тверская область — Сельскохозяйственные организации | 846,0 | 846,0 | +0,0 |
| Северо-западный федеральный округ — Крестьянские (фермерские) хозяйства и индивидуальные предприниматели | 35,0 | 35,0 | +0,0 |
| Архангельская область — Крестьянские (фермерские) хозяйства и индивидуальные предприниматели | 35,0 | 35,0 | +0,0 |
| Архангельская область (без автономного округа) — Крестьянские (фермерские) хозяйства и индивидуальные предприниматели | 35,0 | 35,0 | +0,0 |
| Южный федеральный округ — Сельскохозяйственные организации | 4 160,0 | 4 160,0 | +0,0 |
| Южный федеральный округ — Крестьянские (фермерские) хозяйства и индивидуальные предприниматели | 13 724,0 | 13 724,0 | +0,0 |
| Республика Адыгея — Сельскохозяйственные организации | 7,0 | 999 999 999,0 | +999 999 992,0 |
| Республика Адыгея — Крестьянские (фермерские) хозяйства и индивидуальные предприниматели | 50,0 | 50,0 | +0,0 |
| Республика Калмыкия — Сельскохозяйственные организации | 1 786,0 | 1 786,0 | +0,0 |
More in the section Bulletins on the state of agriculture (electronic versions)»
Period and application
Data are published in electronic bulletins on the state of agriculture. The information covers the 2021–2022 period and is suitable for analyzing livestock and meat horse breeding development. Data are updated according to the Rosstat thematic bulletin release schedule
How it is calculated
Data on sown areas, yield and livestock are used in planning raw material procurement, crop assessment and forecasting food prices
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