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Share of sown areas of sugar beet by legal organizational form

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

This breakdown shows the share of total sugar beet crops by various farm types. The table rows represent different levels: from the entire country and federal districts to specific regions, such as Belgorod Oblast. The columns categorize farms by their legal form, allowing for a comparison of the contribution of large agricultural organizations and small farms to crop production

shown 25 largest of 31

Chart showing the share of sugar beet sown area by farm type in the regions of the RF

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 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 Chuvash Republic - Chuvashia 100.0 Nizhny Novgorod Region 100.0 Oryol Region 100.0 Tambov Region 100.0 Tula Region 100.0 Rostov 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 Siberian Federal District 100.0
how it will look

Set in numbers

The table is a snapshot — 31 series shown across 5 breakdowns. 131 values in total.

The largest value belongs to “Saratov Region” — 43.6; the smallest is “Oryol Region” at 0.218. The gap between them is 200-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 91,35 9,68 0,12 8,54
Центральный федеральный округ 100,00 95,54 5,99 0,21 4,25
Белгородская область 100,00 96,56 2,72 0,08 3,37
Брянская область 100,00 93,01 — — 6,99
Воронежская область 100,00 93,62 4,85 0,85 5,53
Курская область 100,00 96,44 4,24 0,00 3,56
Липецкая область 100,00 94,00 2,93 0,08 5,92
Орловская область 100,00 99,78 4,64 — 0,22
Рязанская область 100,00 100,00 76,45 — —
Тамбовская область 100,00 95,79 9,38 — 4,21
Тульская область 100,00 97,21 19,56 — 2,79
Южный федеральный округ 100,00 86,72 13,15 0,00 13,28
Краснодарский край 100,00 88,25 12,79 0,00 11,75
Волгоградская область 100,00 100,00 — — —
Ростовская область 100,00 68,17 18,48 — 31,83
Северо-Кавказский федеральный округ 100,00 84,63 10,92 — 15,37
Республика Ингушетия 100,00 80,85 — — 19,15
Карачаево-Черкесская Республика 100,00 62,20 22,85 — 37,80
Ставропольский край 100,00 88,36 9,03 — 11,64
Приволжский федеральный округ 100,00 84,97 17,07 0,03 15,00
Республика Башкортостан 100,00 78,67 29,81 — 21,33
Республика Мордовия 100,00 95,06 16,46 0,12 4,82
Республика Татарстан (Татарстан) 100,00 89,25 10,12 0,05 10,70
Чувашская Республика - Чувашия 100,00 68,52 68,52 0,98 30,49
Нижегородская область 100,00 82,99 5,21 0,00 17,01
Оренбургская область 100,00 100,00 100,00 — —
Пензенская область 100,00 89,77 2,89 — 10,23
Саратовская область 100,00 56,44 39,93 — 43,56
Ульяновская область 100,00 69,94 56,00 — 30,06
Сибирский федеральный округ 100,00 98,31 0,72 — 1,69
Алтайский край 100,00 98,31 0,72 — 1,69

How to read this table

Comparing indicators by ownership type helps identify the primary beet producers in a specific constituent entity. While one column includes all categories of farms, others present only agricultural organizations or peasant and individual entrepreneurs. This enables an assessment of the regional agricultural sector's specialization and the concentration of sown area among different producer groups

What is visible in these numbers

The table is 90% 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

The statistics are provided as a single snapshot rather than a time series. This information is useful for agronomists, investors, and agricultural management specialists to analyze land fund structures and assess sugar beet production potential across various legal forms throughout Russia