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RU

Share of sown areas of sugar beet by organisational-legal forms

· snapshot · rows: 30 · periods: 5 · section: Bulletins on the state of agriculture (electronic versions)

This distribution shows the share of sugar beet areas held by different types of farms. The table rows cover the Russian Federation, federal districts, and specific regions, while the columns show the shares of all farm categories, agricultural organizations, households, and farmers. Data are presented in percentages and reflect the land-use structure for the crop at the time of the reporting period

shown 25 largest of 30

Chart showing the distribution of sugar beet sown areas by legal form of farm in percent

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

Set in numbers

The table is a snapshot — 30 series shown across 5 breakdowns. 119 values in total.

“Republic of Adygea” leads the table with 100, “Oryol Region” closes it with 0.057. The gap between them is 1,759-fold.

All table numbers are series: 30
Series Хозяйства всех категорийСельскохозяйственные организациииз них: малые предприятияХозяйства населенияКрестьянские (фермерские) хозяйства и индивидуальные предприниматели
Российская Федерация 100,00 89,37 11,24 0,05 10,58
Центральный федеральный округ 100,00 94,02 7,43 0,08 5,90
Белгородская область 100,00 95,23 — 0,06 4,70
Брянская область 100,00 90,47 — — —
Воронежская область 100,00 92,00 6,66 0,37 7,63
Курская область 100,00 94,53 7,51 — 5,47
Липецкая область 100,00 91,30 4,01 0,01 8,69
Орловская область 100,00 99,94 6,25 — 0,06
Рязанская область 100,00 100,00 69,97 — —
Тамбовская область 100,00 93,99 8,75 — 6,01
Тульская область 100,00 98,63 50,29 — 1,37
Южный федеральный округ 100,00 81,29 11,81 0,00 18,71
Республика Адыгея (Адыгея) 100,00 100,00 100,00 — —
Краснодарский край 100,00 82,72 10,95 0,00 17,28
Ростовская область 100,00 63,82 19,44 — —
Северо-Кавказский федеральный округ 100,00 82,28 13,37 — 17,72
Карачаево-Черкесская Республика 100,00 62,81 52,70 — 37,19
Ставропольский край 100,00 84,28 9,33 — 15,72
Приволжский федеральный округ 100,00 85,31 22,38 0,02 14,67
Республика Башкортостан 100,00 88,64 48,48 — 11,36
Республика Мордовия 100,00 93,72 21,41 0,07 6,21
Республика Татарстан (Татарстан) 100,00 88,74 12,43 0,04 11,22
Чувашская Республика - Чувашия 100,00 37,92 37,92 — —
Нижегородская область 100,00 82,21 2,70 0,00 17,79
Оренбургская область 100,00 100,00 100,00 — —
Пензенская область 100,00 84,39 9,01 — 15,61
Саратовская область 100,00 72,54 39,97 — 27,46
Ульяновская область 100,00 60,18 46,78 — 39,82
Сибирский федеральный округ 100,00 100,00 — — —
Алтайский край 100,00 100,00 — — —

How to read this table

Indicators can be compared horizontally across different legal forms of farm ownership. For Russia, the total is 100 percent, with peasant and farm enterprises accounting for 10.575426 percent. The differences between rows illustrate the distribution of the crop between large agricultural holdings and small-scale producers across different parts of the country

What is visible in these numbers

Only 86% of the cells carry a value — empty cells are missing in the source publication and are not filled in here.

The same indicator in other breakdowns (2)

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

Period and application

The data are published as part of agricultural status bulletins. This information is relevant for agribusiness specialists, economists, and those analyzing regional crop production structures. The data structure allows for an assessment of the role of private and large-scale enterprises in sugar beet production