Pome fruit crop yields per hectare are recorded for the entire Russian Federation, individual federal districts, and specific regions. The rows in the list vary by territorial coverage, allowing for comparison between major agricultural regions and national averages. The data covers two agricultural periods: 2023 and 2024
Chart of pome fruit crop yields by Russian region, 2023 and 2024
Rosstat data for 2023–2024. Rows: 350, periods: 2. Breakdown by positions: Russian Federation — All categories of farms; Central Federal District — All categories of farms; Belgorod Region — All categories of farms; Bryansk Region — All categories of farms; Vladimir Region — All categories of farms and others
Tver Region — All categories of farms: the indicator fell from 244.2 to 23.6 for 2023–2024 — by a factor of 10.3. Of the 25 largest rows, 5 increased, 20 decreased
Crop production efficiency can be compared by examining the difference between national totals and data for individual districts or constituent entities. This highlights which territories lead in crop yields and which fall below the average. The columns provide values for the last two years, enabling an assessment of the current state of the industry by region
What is visible in these numbers
Five largest values: Tver Region — All categories of farms (244.2), Kursk Region — All categories of farms (213.7), Lipetsk Region — All categories of farms (195.5), Russian Federation — All categories of farms (182.1), Belgorod Region — All categories of farms (174.8). The top five account for 34.8% of the total sum across all positions
Observations are annual and cover 2 periods. Cells with numbers: 50 out of 50 (100%) — missing values are virtually absent
Agricultural status bulletins serve as the source of this data. They are updated annually and are relevant for agricultural enterprises, agrifood investors, and production planners. The information is available in digital format and includes 89 rows across various administrative levels
How it is calculated
Data on sown areas, yield and livestock are used in planning raw material procurement, crop assessment and forecasting food prices
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