Depreciation of agricultural machinery written off per year (continued)
The number of written-off grain harvesters or beet harvesters can be used to estimate fleet renewal rates in the agricultural sector. The list contains sixty rows, with data categorized by equipment type, ranging from combines to specialized beet harvesters. The data covers the entire Russian Federation, as well as the Central and Southern Federal Districts
Annual agricultural machinery write-offs due to wear by machine type and district
Set in numbers
Rosstat data. Rows: 60, indicators: 7. Shown by items: Russian Federation; Central Federal District; Southern Federal District; Volga Federal District; Kursk Oblast and others
The five largest values: Russian Federation (1 258), Volga Federal District (422), Southern Federal District (267), Siberian Federal District (217), Central Federal District (190). The gap between the largest and smallest is 209.7 times. The top five account for 72.1% of the total for all items — the distribution is heavily skewed towards the top
All table numbers are series: 60
| Series | Комбайны: — зерноуборочные | Комбайны: — кукурузоуборочные | Комбайны: — кормоуборочные | Комбайны: — льноуборочные | Комбайны: — картофелеуборочные | Жатки валковые | Свеклоуборочные машины (без ботвоуборочных) |
|---|---|---|---|---|---|---|---|
| Российская Федерация | 1 258,00 | 19,00 | 382,00 | 10,00 | 65,00 | 804,00 | 51,00 |
| Центральный федеральный округ | 190,00 | 5,00 | 75,00 | — | 23,00 | 146,00 | 25,00 |
| Белгородская область | 22,00 | — | 7,00 | — | — | 52,00 | — |
| Брянская область | 6,00 | — | 4,00 | — | — | — | — |
| Владимирская область | 6,00 | — | 5,00 | — | — | 5,00 | — |
| Воронежская область | 33,00 | — | 7,00 | — | — | 16,00 | — |
| Ивановская область | 3,00 | — | — | — | — | — | — |
| Курская область | 22,00 | — | 10,00 | — | — | 6,00 | 7,00 |
| Липецкая область | 3,00 | — | — | — | — | — | — |
| Московская область | 5,00 | — | 18,00 | — | 7,00 | 7,00 | — |
| Орловская область | 13,00 | — | — | — | — | 5,00 | — |
| Рязанская область | 25,00 | — | 7,00 | — | — | 18,00 | — |
| Смоленская область | — | — | 3,00 | — | — | — | — |
| Тамбовская область | 23,00 | — | — | — | — | 19,00 | 9,00 |
| Тульская область | 12,00 | — | 4,00 | — | — | 5,00 | — |
| Ярославская область | 5,00 | — | — | — | — | — | — |
| Северо-Западный федеральный округ | 8,00 | — | 36,00 | — | 3,00 | — | — |
| Вологодская область | 3,00 | — | 15,00 | — | — | — | — |
| Ленинградская область | — | — | 11,00 | — | — | — | — |
| Южный федеральный округ | 243,00 | 11,00 | 28,00 | — | 4,00 | 267,00 | — |
| Республика Крым | 7,00 | — | — | — | — | — | — |
| Краснодарский край | 61,00 | 6,00 | 11,00 | — | — | 143,00 | — |
| Волгоградская область | 64,00 | — | 4,00 | — | — | 49,00 | — |
| Ростовская область | 100,00 | — | 8,00 | — | — | 69,00 | — |
| Северо-Кавказский федеральный округ | 95,00 | — | 14,00 | — | — | 23,00 | — |
| Республика Дагестан | 8,00 | — | — | — | — | — | — |
| Ставропольский край | 81,00 | — | 12,00 | — | — | — | — |
| Приволжский федеральный округ | 422,00 | — | 139,00 | — | 14,00 | 186,00 | 13,00 |
| Республика Башкортостан | 73,00 | — | 29,00 | — | — | 32,00 | 5,00 |
| Республика Марий Эл | 5,00 | — | — | — | — | — | — |
| Республика Мордовия | 17,00 | — | 5,00 | — | — | 5,00 | — |
| Республика Татарстан (Татарстан) | 79,00 | — | 23,00 | — | — | 21,00 | 3,00 |
| Удмуртская Республика | 18,00 | — | 17,00 | — | — | 14,00 | — |
| Чувашская Республика - Чувашия | 12,00 | — | 5,00 | — | 4,00 | 6,00 | — |
| Пермский край | 25,00 | — | 10,00 | — | — | — | — |
| Кировская область | 23,00 | — | 15,00 | — | — | — | — |
| Нижегородская область | 19,00 | — | 9,00 | — | — | 4,00 | — |
| Оренбургская область | 50,00 | — | 9,00 | — | — | 26,00 | — |
| Пензенская область | 10,00 | — | — | — | — | 5,00 | — |
| Самарская область | 32,00 | — | 5,00 | — | — | 17,00 | — |
| Саратовская область | 27,00 | — | 7,00 | — | — | 24,00 | — |
| Ульяновская область | 32,00 | — | — | — | — | 27,00 | — |
| Уральский федеральный округ | 45,00 | — | 16,00 | — | 7,00 | 28,00 | — |
| Курганская область | 8,00 | — | — | — | — | — | — |
| Свердловская область | 13,00 | — | 8,00 | — | — | 10,00 | — |
| Тюменская область | 13,00 | — | 4,00 | — | — | 8,00 | — |
| Тюменская область (без автономных округов) | 13,00 | — | 4,00 | — | — | 8,00 | — |
| Челябинская область | 11,00 | — | — | — | — | 10,00 | — |
| Сибирский федеральный округ | 217,00 | — | 68,00 | — | 6,00 | 124,00 | — |
| Алтайский край | 75,00 | — | 16,00 | — | — | 44,00 | — |
| Красноярский край | 52,00 | — | 10,00 | — | — | 8,00 | — |
| Иркутская область | — | — | 4,00 | — | — | 16,00 | — |
| Кемеровская область - Кузбасс | 7,00 | — | — | — | — | 4,00 | — |
| Новосибирская область | 33,00 | — | 18,00 | — | — | 31,00 | — |
| Омская область | 23,00 | — | 15,00 | — | — | 21,00 | — |
| Томская область | 15,00 | — | — | — | — | — | — |
| Дальневосточный федеральный округ | 38,00 | — | 6,00 | — | 8,00 | 19,00 | — |
| Забайкальский край | 4,00 | — | — | — | — | — | — |
| Приморский край | 5,00 | — | — | — | — | — | — |
| Амурская область | 25,00 | — | — | — | — | 6,00 | — |
How to read this table
The table rows allow for comparison of write-off volumes across different machine types and geographic zones. National indicators can be compared with results from the Central or Southern Federal Districts to identify regional patterns in equipment wear. Each machine category is listed in a separate row for ease of analysis
What is visible in these numbers
The dataset contains the following indicators: Combines: — grain harvesters; Combines: — corn harvesters; Combines: — forage harvesters; Combines: — flax harvesters; Combines: — potato harvesters; Windrowers; Beet harvesters (excluding haulm harvesters)
95 out of 175 possible values are filled (54.3%). There are many gaps — some items were observed only in certain periods, which should be taken into account when comparing
The same indicator in other breakdowns (3)
More in the section Bulletins on the state of agriculture (electronic versions)»
Period and application
The data is compiled from agricultural status bulletins. The information is presented as a cross-section without specific year assignments, providing a current overview by equipment type. This information is useful for agricultural holdings and fleet management specialists
How it is calculated
Sown area data shows what will be abundant and what will be scarce several months before it is reflected on the shelf
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