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Share of sugar beet production by legal form of organisation

· snapshot · rows: 31 · periods: 5 · section: Bulletins on the state of agriculture (electronic versions)

The share of sugar beet production varies across farm types, ranging from large enterprises to peasant farms and individual entrepreneurs. The table rows represent various territorial levels, including the Russian Federation as a whole, federal districts, and individual regions. The indicators show the production structure as a percentage across all farm categories presented in the columns

shown 25 largest of 31

Share of sugar beet production by farm type in Russian regions

Russian Federation 100.0 Central Federal District 100.0 Belgorod Region 100.0 Voronezh Region 100.0 Kursk Region 100.0 Belgorod Region 100.0 Volga Federal District 100.0 Republic of Mordovia 100.0 Republic of Tatarstan 100.0 Chuvash Republic 100.0 Nizhny Novgorod Region 100.0 Oryol Region 100.0 Tambov Region 100.0 Tula Region 100.0 Southern Federal District 100.0 Krasnodar Territory 100.0 Rostov Region 100.0 North Caucasus Federal District 100.0 Karachay-Cherkess Republic 100.0 Chechen Republic 100.0 Stavropol Territory 100.0 Republic of Bashkortostan 100.0 Penza Oblast 100.0 Saratov Region 100.0 Ulyanovsk Region 100.0
how it will look

Set in numbers

The table is a snapshot — 31 series shown across 5 breakdowns. 130 values in total.

The largest value belongs to “Karachay-Cherkess Republic” — 46.7; the smallest is “Oryol Region” at 0.492. The gap between them is 94.9-fold.

All table numbers are series: 31
Series Хозяйства всех категорийСельскохозяйственные организациииз них: малые предприятияХозяйства населенияКрестьянские (фермерские) хозяйства и индивидуальные предприниматели
Российская федерация 100,00 91,06 8,92 0,13 8,81
Центральный федеральный округ 100,00 95,41 5,33 0,24 4,35
Белгородская область 100,00 95,93 1,16 0,06 4,01
Брянская область 100,00 999 999 999,00 — — 14,03
Воронежская область 100,00 999 999 999,00 5,26 999 999 999,00 6,20
Курская область 100,00 97,05 5,54 0,00 2,95
Липецкая область 100,00 93,50 2,20 0,06 6,44
Орловская область 100,00 99,51 4,77 — 0,49
Рязанская область 100,00 100,00 17,48 — —
Тамбовская область 100,00 96,67 10,25 — 3,33
Тульская область 100,00 96,17 11,45 — 3,83
Южный федеральный округ 100,00 85,79 11,42 — 14,21
Краснодарский край 100,00 86,96 10,82 — 13,04
Волгоградская область 100,00 999 999 999,00 — — —
Ростовская область 100,00 999 999 999,00 19,38 — 29,18
Северо-кавказский федеральный округ 100,00 84,82 16,31 — 15,18
Карачаево-Черкесская Республика 100,00 53,32 12,85 — 46,68
Чеченская Республика 100,00 96,78 92,17 — 3,22
Ставропольский край 100,00 87,88 15,06 — 12,13
Приволжский федеральный округ 100,00 86,18 15,91 0,02 13,80
Республика Башкортостан 100,00 79,86 20,29 — 20,15
Республика Мордовия 100,00 96,49 16,74 0,09 3,42
Республика Татарстан 100,00 87,04 19,57 0,02 12,94
Чувашская Республика 100,00 91,71 91,71 1,02 7,28
Нижегородская область 100,00 86,96 1,73 0,00 13,04
Оренбургская область 100,00 999 999 999,00 999 999 999,00 — —
Пензенская область 100,00 90,10 999 999 999,00 — 9,90
Саратовская область 100,00 999 999 999,00 49,39 — 31,33
Ульяновская область 100,00 69,45 47,03 — 30,55
Сибирский федеральный округ 100,00 98,20 0,55 — 1,80
Алтайский край 100,00 98,20 0,55 — 1,80

How to read this table

The comparison is presented by columns, using all farm categories as a baseline, followed by specific organizational and legal forms. These values show the share of total output provided by farmers or other farm types within specific regions. For example, the nationwide share of peasant and individual farms is 8.811 percent

What is visible in these numbers

The table is 89% filled: Rosstat does not publish every cell, and the gaps are left as they are rather than interpolated.

The same indicator in other breakdowns (1)

More in the section Bulletins on the state of agriculture (electronic versions)»

Period and application

Data is compiled from agricultural bulletins and covers various constituent entities of the country. The data is relevant for analyzing the structure of the agricultural sector and the distribution of production capacity. This information is useful for agro-industrial complex specialists and government officials