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Gross harvest of cauliflower and broccoli in Russia

· dynamics annual · rows: 138 · periods: 2 · section: Bulletins on the state of agriculture (electronic versions)

Cauliflower and broccoli harvest volumes for 2021 and 2022 are broken down by country, federal districts, and individual regions. The rows allow for comparing indicators between RF subjects and districts to identify higher harvest areas. Data covers all types of farms and records the gross harvest for the two years presented in the columns

shown 25 largest of 138

Chart of gross cauliflower and broccoli harvest by region for 2021 and 2022

unchanged Russian Federation — All categories of farms · 2022: 221.5 · 2021: 215.5 · +5.96 Russian Federation… categories of farmsRussian Federation — All categories of farms +5.96 Southern Federal District — All types of households · 2022: 28.0 · 2021: 22.0 · +5.95 Southern Federal… types of householdsSouthern Federal District — All types of households +5.95 Krasnodar Territory — Holdings of all categories · 2022: 19.8 · 2021: 16.6 · +3.25 Krasnodar Territor… of all categoriesKrasnodar Territory — Holdings of all categories +3.25 Republic of Crimea — households of all categories · 2022: 6.59 · 2021: 3.71 · +2.88 Republic of… of all categoriesRepublic of Crimea — households of all categories +2.88 Volga Federal District — All categories of economic entities · 2022: 39.0 · 2021: 36.7 · +2.31 Volga Federal… of economic entitiesVolga Federal District — All categories of economic entities +2.31 Belgorod Region — all categories of farms · 2022: 12.8 · 2021: 11.0 · +1.76 Belgorod Region — all categories of farms +1.76 Kursk Oblast — All categories of farms · 2022: 5.07 · 2021: 4.90 · +0.17 Kursk Oblast — All categories of farms +0.17 Bryansk Region — all categories of farms · 2022: 1.24 · 2021: 1.10 · +0.14 Bryansk Region — all categories of farms +0.14 Kaluga Region — all categories of farms · 2022: 4.28 · 2021: 4.24 · +0.04 Kaluga Region — all categories of farms +0.04 Orel Oblast — All categories of farms · 2022: 2.77 · 2021: 2.75 · +0.02 Orel Oblast — All categories of farms +0.02 Vladimir Region — all categories of farms · 2022: 1.46 · 2021: 1.53 · −0.07 Vladimir Region — all categories of farms −0.07 Sevastopol — All types of households · 2022: 0.32 · 2021: 0.40 · −0.08 Sevastopol — All types of households −0.08 Volgograd Region — All categories of farms · 2022: 1.28 · 2021: 1.36 · −0.09 Volgograd Region — All categories of farms −0.09 Lipetsk Region — all categories of farms · 2022: 1.44 · 2021: 1.53 · −0.09 Lipetsk Region — all categories of farms −0.09 Smolensk Oblast — All categories of farms · 2022: 0.98 · 2021: 1.15 · −0.17 Smolensk Oblast — All categories of farms −0.17 Republic of Bashkortostan — All categories of farms · 2022: 8.99 · 2021: 9.22 · −0.23 Republic of… categories of farmsRepublic of Bashkortostan — All categories of farms −0.23 Ryazan Region — all categories of farms · 2022: 1.79 · 2021: 2.07 · −0.28 Ryazan Region — all categories of farms −0.28 Tver Region — all categories of farms · 2022: 1.17 · 2021: 1.57 · −0.40 Tver Region — all categories of farms −0.40 Voronezh Region — all categories of farms · 2022: 28.6 · 2021: 29.2 · −0.61 Voronezh Region — all categories of farms −0.61 Kaliningrad region — All categories of farms · 2022: 3.03 · 2021: 3.65 · −0.62 Kaliningrad… categories of farmsKaliningrad region — All categories of farms −0.62 Tambov Region — all categories of farms · 2022: 10.5 · 2021: 11.3 · −0.78 Tambov Region — all categories of farms −0.78 Moscow Region — all categories of farms · 2022: 23.5 · 2021: 26.1 · −2.53 Moscow Region — all categories of farms −2.53 Central Federal District — All categories of farms · 2022: 96.2 · 2021: 98.9 · −2.66 Central Federal… categories of farmsCentral Federal District — All categories of farms −2.66 Leningrad Region — All types of households · 2022: 1.85 · 2021: 6.69 · −4.84 Leningrad Region — All types of households −4.84 Northwestern Federal District — All categories of farms · 2022: 4.90 · 2021: 10.3 · −5.45 Northwestern… categories of farmsNorthwestern Federal District — All categories of farms −5.45
how it will look

Set in numbers

Rosstat data for 2021–2022. Rows: 138, periods: 2. Shown by positions: Russian Federation — All categories of farms; Central Federal District — All categories of farms; Belgorod Oblast — All categories of farms; Bryansk Oblast — All categories of farms; Vladimir Oblast — All categories of farms and others

Russian Federation — All categories of farms: the indicator rose from 215.5 to 221.5 for 2021–2022 — by 2.76%. Of the 25 largest rows, 10 increased, 15 decreased

All table numbers are series: 138
Series 20212022
Самарская область — Хозяйства всех категорий — 0,33
Саратовская область — Хозяйства населения — 1,99
Саратовская область — Хозяйства всех категорий 2,23 1,99
Ульяновская область — Крестьянские (фермерские) хозяйства и индивидуальные предприниматели — 2,31
Ульяновская область — Хозяйства всех категорий — 2,31
Уральский федеральный округ — Хозяйства населения — 12,98
Уральский федеральный округ — Хозяйства всех категорий 11,87 13,06
Курганская область — Хозяйства населения — 5,56
Курганская область — Хозяйства всех категорий 7,00 5,56
Свердловская область — Хозяйства населения — 7,42
Свердловская область — Хозяйства всех категорий — 7,42
Сибирский федеральный округ — Хозяйства населения — 29,14
Сибирский федеральный округ — Хозяйства всех категорий 28,74 29,14
Республика Алтай — Хозяйства населения — 0,76
Республика Алтай — Хозяйства всех категорий — 0,76
Республика Хакасия — Хозяйства населения — 1,80
Республика Хакасия — Хозяйства всех категорий 1,78 1,80
Алтайский край — Хозяйства населения — 7,85
Алтайский край — Хозяйства всех категорий 8,68 7,85
Кемеровская область - Кузбасс — Хозяйства населения — 6,03
Кемеровская область - Кузбасс — Хозяйства всех категорий 7,62 6,03
Новосибирская область — Хозяйства населения — 8,07
Новосибирская область — Хозяйства всех категорий 5,07 8,07
Омская область — Хозяйства населения — 3,23
Омская область — Хозяйства всех категорий 4,14 3,23
Томская область — Хозяйства населения — 1,40
Томская область — Хозяйства всех категорий 1,45 1,40
Дальневосточный федеральный округ — Хозяйства населения — 11,16
Дальневосточный федеральный округ — Хозяйства всех категорий 6,97 11,17
Камчатский край — Хозяйства населения — 1,39
Камчатский край — Хозяйства всех категорий 1,14 1,40
Приморский край — Хозяйства населения — 3,67
Приморский край — Хозяйства всех категорий 3,67 3,67
Хабаровский край — Хозяйства населения — 6,07
Хабаровский край — Хозяйства всех категорий 1,71 6,07
Магаданская область — Хозяйства населения — 0,03
Магаданская область — Хозяйства всех категорий 0,05 0,04
Сахалинская область — Хозяйства всех категорий 0,40 —

How to read this table

The row structure allows for comparing agricultural performance across different parts of the country, from the total for the Russian Federation to specific federal districts. Comparing 2021 and 2022 values helps track changes in vegetable production volumes across regions. The list contains 61 rows, including national totals and territorial divisions

What is visible in these numbers

Five largest values: Russian Federation — All categories of farms (221.5), Central Federal District — All categories of farms (98.9), Volga Federal District — All categories of farms (39), Voronezh Oblast — All categories of farms (29.2), Southern Federal District — All categories of farms (28). The gap between the largest and smallest is 549.8 times. The top five account for 76.3% of the total for all positions — the distribution is heavily skewed toward the top

Observations are annual, with 2 observation periods in the dataset. There are 50 values in the table out of 50 possible, which is 100% — almost no empty cells remain

The same indicator for other periods

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

Period and application

Statistics are compiled based on electronic agricultural bulletins. The data is relevant for 2021 and 2022 and can be used by agribusiness companies or vegetable market analysts. Information is published by Rosstat as a cross-section without connection to long-term time series

How it is calculated

Data on sown areas, yield and livestock numbers are used in planning raw material procurement, crop yield assessment and forecasting food prices