Continuation
The number of agricultural machines in the country's farms is presented in this dataset. The indicators record the availability of specialized machinery, including grain harvesters and windrowers, by federal district and for the Russian Federation as a whole. The information reflects the current fleet of equipment at the disposal of the agricultural sector without accounting for year-on-year dynamics
Distribution of grain harvesters and windrowers by federal districts and regions of Russia
Set in numbers
Rosstat data. Rows: 57, indicators: 7. Table rows: Russian Federation; Volga Federal District; Central Federal District; Voronezh Oblast; Moscow Oblast and others
Five largest values: Russian Federation (1 230), Volga Federal District (319), Central Federal District (271), Siberian Federal District (239), Southern Federal District (188). The gap between the largest and smallest is 246 times. The top five account for 78.2% of the sum for all positions — the distribution is heavily skewed toward the top
All table numbers are series: 57
| Series | Комбайны: — зерноуборочные | Комбайны: — кукурузоуборочные | Комбайны: — кормоуборочные | Комбайны: — льноуборочные | Комбайны: — картофелеуборочные | Свеклоуборочные машины (без ботвоуборочных) | Жатки валковые |
|---|---|---|---|---|---|---|---|
| Российская Федерация | 1 230,00 | 13,00 | 188,00 | — | 8,00 | 7,00 | 682,00 |
| Центральный федеральный округ | 271,00 | — | 35,00 | — | — | — | 125,00 |
| Белгородская область | 48,00 | — | — | — | — | — | 14,00 |
| Брянская область | 4,00 | — | — | — | — | — | — |
| Владимирская область | 6,00 | — | — | — | — | — | — |
| Воронежская область | 55,00 | — | 6,00 | — | — | — | 22,00 |
| Калужская область | — | — | — | — | — | — | 4,00 |
| Костромская область | — | — | 4,00 | — | — | — | — |
| Курская область | 10,00 | — | — | — | — | — | — |
| Липецкая область | 11,00 | — | — | — | — | — | — |
| Московская область | 5,00 | — | 3,00 | — | — | — | 8,00 |
| Орловская область | 33,00 | — | — | — | — | — | 17,00 |
| Рязанская область | 18,00 | — | 4,00 | — | — | — | 12,00 |
| Тамбовская область | 44,00 | — | 3,00 | — | — | — | 33,00 |
| Тульская область | 24,00 | — | — | — | — | — | — |
| Ярославская область | 3,00 | — | 5,00 | — | — | — | — |
| Северо-Западный федеральный округ | — | — | 18,00 | — | — | — | 4,00 |
| Вологодская область | — | — | 9,00 | — | — | — | 4,00 |
| Ленинградская область | — | — | 7,00 | — | — | — | — |
| Южный федеральный округ | 188,00 | — | 8,00 | — | — | — | 65,00 |
| Республика Калмыкия | 3,00 | — | — | — | — | — | — |
| Краснодарский край | 57,00 | — | 5,00 | — | — | — | 11,00 |
| Волгоградская область | 28,00 | — | — | — | — | — | 20,00 |
| Ростовская область | 95,00 | — | — | — | — | — | 30,00 |
| Северо-Кавказский федеральный округ | 93,00 | — | — | — | — | — | 34,00 |
| Ставропольский край | — | — | — | — | — | — | 27,00 |
| Приволжский федеральный округ | 319,00 | 9,00 | 76,00 | — | — | 3,00 | 201,00 |
| Республика Башкортостан | 43,00 | — | 9,00 | — | — | — | 24,00 |
| Республика Марий Эл | — | — | 4,00 | — | — | — | — |
| Республика Мордовия | 42,00 | — | — | — | — | — | 4,00 |
| Республика Татарстан | 12,00 | — | 9,00 | — | — | — | — |
| Удмуртская Республика | 14,00 | — | 22,00 | — | — | — | 13,00 |
| Чувашская Республика | 11,00 | — | 4,00 | — | — | — | 5,00 |
| Пермский край | — | — | 5,00 | — | — | — | 4,00 |
| Кировская область | 9,00 | — | 6,00 | — | — | — | 7,00 |
| Нижегородская область | 22,00 | — | 12,00 | — | — | — | 12,00 |
| Оренбургская область | 30,00 | — | — | — | — | — | 49,00 |
| Пензенская область | 19,00 | — | — | — | — | — | 4,00 |
| Самарская область | 37,00 | — | — | — | — | — | 36,00 |
| Саратовская область | 44,00 | — | — | — | — | — | 25,00 |
| Ульяновская область | 29,00 | — | — | — | — | — | 13,00 |
| Уральский федеральный округ | 49,00 | — | 13,00 | — | — | — | 39,00 |
| Курганская область | 16,00 | — | — | — | — | — | 17,00 |
| Свердловская область | 13,00 | — | 7,00 | — | — | — | 14,00 |
| Тюменская область | 12,00 | — | — | — | — | — | 4,00 |
| Тюменская область (без автономных округов) | 12,00 | — | — | — | — | — | 4,00 |
| Челябинская область | 8,00 | — | 4,00 | — | — | — | 4,00 |
| Сибирский федеральный округ | 239,00 | — | 32,00 | — | — | — | 175,00 |
| Алтайский край | 81,00 | — | 8,00 | — | — | — | 84,00 |
| Красноярский край | 27,00 | — | 6,00 | — | — | — | — |
| Кемеровская область | 25,00 | — | — | — | — | — | 15,00 |
| Новосибирская область | 60,00 | — | 9,00 | — | — | — | 48,00 |
| Омская область | 20,00 | — | 3,00 | — | — | — | 16,00 |
| Томская область | 6,00 | — | — | — | — | — | — |
| Дальневосточный федеральный округ | 67,00 | — | — | — | — | — | 39,00 |
| Приморский край | 23,00 | — | — | — | — | — | — |
| Амурская область | 29,00 | — | — | — | — | — | 10,00 |
How to read this table
Rows group information by geography, highlighting the Russian Federation, the Volga, and the Central federal districts. Columns detail types of machinery, such as harvesters and windrowers. To analyze agricultural equipment supply, compare values across different districts and consider the total number of units nationwide, such as the 1230 grain harvesters and 682 windrowers available on a national scale
What is visible in these numbers
What is measured: Combine harvesters: — grain; Combine harvesters: — maize; Combine harvesters: — forage; Combine harvesters: — flax; Combine harvesters: — potato; Beet harvesters (excluding haulm harvesters); Windrow headers
76 out of 175 possible values are filled (43.4%). There are many gaps: a significant portion of the positions were included in the observation only in certain periods, and such series should be compared with caution
The same indicator in other breakdowns (47)
More in the section Bulletins on the state of agriculture (electronic versions)»
Period and application
The data is static and represents a snapshot without time periods. Information is updated according to the schedule for publishing agricultural status bulletins. The statistics are useful for agribusiness specialists, analysts, and government representatives to assess the technical equipment of farms in different parts of the country
How it is calculated
Sown areas show what will be abundant and what will be scarce several months before it is reflected on the shelf
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