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Share of sown areas of sugar beet in farms of various forms

· snapshot · rows: 32 · periods: 5 · section: Bulletins on the state of agriculture (electronic versions)

The percentage share of sugar beet area varies by farm type, as shown in the table by comparing all farm categories with specific groups, including farmers. Rows are organized by territory, ranging from Russian Federation-wide indicators to specific constituent entities, such as Belgorod Oblast. The data reflects the structure of sown areas across different organizational and legal forms, without time-series data

shown 25 largest of 32

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

Russian Federation 100.0 Central Federal District 100.0 Belgorod Region 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 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 Republic of Ingushetia 100.0 Kabardino-Balkarian Republic 100.0 Chuvash Republic - Chuvashia 100.0
how it will look

Set in numbers

32 series, arranged across 5 breakdowns rather than over time. 114 values in total.

“Republic of Ingushetia” leads the table with 100, “Oryol Region” closes it with 1.1. The gap between them is 89.6-fold.

All table numbers are series: 32
Series Хозяйства всех категорийСельскохозяйственные организациииз них: малые предприятияХозяйства населенияКрестьянские (фермерские) хозяйства и индивидуальные предприниматели
Российская Федерация 100,00 88,58 11,72 0,07 11,35
Центральный федеральный округ 100,00 93,86 7,41 0,12 6,02
Белгородская область 100,00 95,26 3,29 0,07 4,67
Брянская область 100,00 — — — —
Воронежская область 100,00 92,26 7,12 0,54 7,20
Курская область 100,00 94,24 6,43 — 5,76
Липецкая область 100,00 91,20 4,16 0,01 8,80
Орловская область 100,00 98,88 4,80 — 1,12
Рязанская область 100,00 — — — —
Тамбовская область 100,00 93,84 10,10 — 6,16
Тульская область 100,00 98,63 32,45 — 1,37
Южный федеральный округ 100,00 82,06 12,03 0,00 17,94
Республика Адыгея (Адыгея) 100,00 — — — —
Краснодарский край 100,00 83,94 11,42 0,00 16,06
Ростовская область 100,00 — — — —
Северо-Кавказский федеральный округ 100,00 82,12 16,70 — 17,88
Республика Ингушетия 100,00 — — — 100,00
Кабардино-Балкарская Республика 100,00 100,00 — — —
Карачаево-Черкесская Республика 100,00 67,49 67,49 — 32,51
Ставропольский край 100,00 84,44 8,73 — 15,56
Приволжский федеральный округ 100,00 81,88 22,35 0,02 18,10
Республика Башкортостан 100,00 79,53 41,85 — 20,47
Республика Мордовия 100,00 94,08 22,16 0,08 5,84
Республика Татарстан (Татарстан) 100,00 85,84 11,11 0,04 14,12
Чувашская Республика - Чувашия 100,00 — — — 66,75
Нижегородская область 100,00 86,80 7,52 0,00 13,20
Оренбургская область 100,00 — — — —
Пензенская область 100,00 83,32 6,41 — 16,68
Саратовская область 100,00 65,02 45,44 — 34,98
Ульяновская область 100,00 60,59 42,66 — 39,41
Сибирский федеральный округ 100,00 100,00 — — —
Алтайский край 100,00 100,00 — — —

How to read this table

Comparing rows helps identify which farm types hold a larger share of sugar beet and where production is lower. National averages can be compared with results from specific federal districts or oblasts to observe regional variations in area distribution. Differences between all farm categories and specific groups, such as peasant or farm holdings, allow for assessing the scale of small-scale participation in crop production

What is visible in these numbers

Only 84% 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 statistics are relevant for analyzing crop production structure and land resource distribution in the agro-industrial complex. Regional and district data are useful for farmers, investors, and agricultural production planners. The information is published within Rosstat's agricultural bulletins and is presented in percentages