In 2023, Ukraine's production of grain and leguminous crops was approximately ** million metric tons, roughly three times that of potatoes. All types of crops saw a decrease in production in 2022 when the Russia-Ukraine war began.

Ukraine Agricultural Production: Grain Crops data was reported at 61,917.000 Ton th in 2017. This records a decrease from the previous number of 66,088.000 Ton th for 2016. Ukraine Agricultural Production: Grain Crops data is updated yearly, averaging 39,488.500 Ton th from Dec 1980 (Median) to 2017, with 38 observations. The data reached an all-time high of 66,088.000 Ton th in 2016 and a record low of 20,234.000 Ton th in 2003. Ukraine Agricultural Production: Grain Crops data remains active status in CEIC and is reported by State Statistics Service of Ukraine. The data is categorized under Global Database’s Ukraine – Table UA.B014: Agricultural Production: by Region: Annual.

Ukraine: Crop production index (2004-2006 = 100): The latest value from 2022 is 90.1 index points, a decline from 121.7 index points in 2021. In comparison, the world average is 108.4 index points, based on data from 188 countries. Historically, the average for Ukraine from 1992 to 2022 is 74.7 index points. The minimum value, 40.7 index points, was reached in 1999 while the maximum of 121.7 index points was recorded in 2021.

Over *** million hectares of agricultural land in Ukraine were under winter wheat cultivation in 2021. Furthermore, the area under sunflower seeds and maize was *** million hectares and *** million hectares, respectively. In 2021, agriculture made up approximately ** percent of Ukraine's gross domestic product (GDP).

Crop production index of Ukraine sank by 26.00% from 121.7 index in 2021 to 90.1 index in 2022. Since the 1.58% growth in 2019, crop production index plummeted by 20.18% in 2022. Crop production index shows agricultural production for each year relative to the base period 2004-2006. It includes all crops except fodder crops. Regional and income group aggregates for the FAO's production indexes are calculated from the underlying values in international dollars, normalized to the base period 2004-2006.

Ukraine: Crop production index (2004-2006 = 100): Pour cet indicateur, FAO fournit des données pour la Ukraine de 1992 à 2022. La valeur moyenne pour Ukraine pendant cette période était de 74.7 index points avec un minimum de 40.7 index points en 1999 et un maximum de 121.7 index points en 2021.

Ukraine Sown Area: Fodder Crops: ow Corn For Silage & Green Fodder data was reported at 286.000 ha th in 2017. This records an increase from the previous number of 284.000 ha th for 2016. Ukraine Sown Area: Fodder Crops: ow Corn For Silage & Green Fodder data is updated yearly, averaging 1,168.000 ha th from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 4,637.000 ha th in 1990 and a record low of 284.000 ha th in 2016. Ukraine Sown Area: Fodder Crops: ow Corn For Silage & Green Fodder data remains active status in CEIC and is reported by State Statistics Service of Ukraine. The data is categorized under Global Database’s Ukraine – Table UA.B019: Agricultural Total Land Area and Sown Area.

Production of major crops - barley, maize, wheat, soybeans, and sunflowers - by oblast for Ukraine 2015-2023. Data from 2022 is mapped while other years are accessible through the attribute tables or the specially configured pop-up windows for each crop.

Ukraine Agricultural Product Sales Volume: Grain Crops: Wheat data was reported at 16,920.600 Ton th in 2016. This records a decrease from the previous number of 17,630.700 Ton th for 2015. Ukraine Agricultural Product Sales Volume: Grain Crops: Wheat data is updated yearly, averaging 10,444.000 Ton th from Dec 1995 (Median) to 2016, with 22 observations. The data reached an all-time high of 17,630.700 Ton th in 2015 and a record low of 2,186.900 Ton th in 2003. Ukraine Agricultural Product Sales Volume: Grain Crops: Wheat data remains active status in CEIC and is reported by State Statistics Service of Ukraine. The data is categorized under Global Database’s Ukraine – Table UA.B018: Agricultural Product Sales Volume.

Ukraine Agricultural Production Yield: Grain Crops data was reported at 42.500 Centner/ha in 2017. This records a decrease from the previous number of 46.100 Centner/ha for 2016. Ukraine Agricultural Production Yield: Grain Crops data is updated yearly, averaging 26.850 Centner/ha from Dec 1980 (Median) to 2017, with 38 observations. The data reached an all-time high of 46.100 Centner/ha in 2016 and a record low of 18.200 Centner/ha in 2003. Ukraine Agricultural Production Yield: Grain Crops data remains active status in CEIC and is reported by State Statistics Service of Ukraine. The data is categorized under Global Database’s Ukraine – Table UA.B015: Agricultural Production Yield.

Ukraine UA: Production Index: 2014-2016: Crop data was reported at 90.060 2014-2016=100 in 2022. This records a decrease from the previous number of 121.710 2014-2016=100 for 2021. Ukraine UA: Production Index: 2014-2016: Crop data is updated yearly, averaging 68.570 2014-2016=100 from Dec 1992 (Median) to 2022, with 31 observations. The data reached an all-time high of 121.710 2014-2016=100 in 2021 and a record low of 40.710 2014-2016=100 in 1999. Ukraine UA: Production Index: 2014-2016: Crop data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ukraine – Table UA.World Bank.WDI: Agricultural Production Index. Crop production index shows agricultural production for each year relative to the base period 2014-2016. It includes all crops except fodder crops. Regional and income group aggregates for the FAO's production indexes are calculated from the underlying values in international dollars, normalized to the base period 2014-2016.;Food and Agriculture Organization, electronic files and web site.;Weighted average;

Ukraine was expected to produce **** million metric tons of wheat in the marketing year 2024/25. That would mark a slight decrease compared to the previous year. Ukraine is one of the leading wheat-producing regions worldwide.

Ukraine Fertilizer & Crop Inputs Market valued at USD 2.5 Bn, driven by agricultural productivity, sustainable practices, and soil health awareness.

Ukraine UA: Production Index: 2004-2006: Crop data was reported at 192.240 2004-2006=100 in 2016. This records an increase from the previous number of 159.320 2004-2006=100 for 2015. Ukraine UA: Production Index: 2004-2006: Crop data is updated yearly, averaging 99.440 2004-2006=100 from Dec 1992 (Median) to 2016, with 25 observations. The data reached an all-time high of 192.240 2004-2006=100 in 2016 and a record low of 62.790 2004-2006=100 in 1999. Ukraine UA: Production Index: 2004-2006: Crop data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ukraine – Table UA.World Bank.WDI: Agricultural Production Index. Crop production index shows agricultural production for each year relative to the base period 2004-2006. It includes all crops except fodder crops. Regional and income group aggregates for the FAO's production indexes are calculated from the underlying values in international dollars, normalized to the base period 2004-2006.; ; Food and Agriculture Organization, electronic files and web site.; Weighted average;

The Irrigated Lands data comes from USSS-AB and is being used for research at Kansas State University. The dataset is for the 5 major crops in Ukraine which are maize, wheat, barley, sunflowers, and soybeans. For each major crop, there are 3 categories. Those categories are Harvested Area (thsd.ha), Volume of Production (thsd.centner), and Yield (centner per ha of the harvested area). Here is the Metadata for this Data:Oblast = OblastMaize_Har = Maize Harvested Area, (thsd.ha)Maize_Vol = Maize Volume of Production, (thsd.centners)Maize_Yie = Maize Yield, (centner per ha of the harvested area)Wheat_Har = Wheat Harvested Area, (thsd.ha)Wheat_Vol = Wheat Volume of Production, (thsd.centners)Wheat_Yie = Wheat Yield, (centner per ha of the harvested area)\Barley_Ha = Barley Harvested Area, (thsd.ha)Barley_Vo = Barley Volume of Production, (thsd.centners)Barley_Yi = Barley Yield, (centner per ha of the harvested area)Sunflower_ = Sunflower Harvested Area, (thsd.ha)Sunflower1 = Sunflower Volume of Production, (thsd.centners)Sunflower_1 = Sunflower Yield, (centner per ha of the harvested area)Soybean_H = Soybean Harvested Area, (thsd.ha)Soybean_V = Soybean Volume of Production, (thsd.centners)Soybean_Y = Soybean Yield, (centner per ha of the harvested area)

Corn futures saw modest gains to start the week amidst market volatility. Analysts expect higher yields and production in the upcoming USDA report, while global supply dynamics remain in focus.

Between July 2022 and March 2023, Ukraine imported over *** thousand metric tons of oilseed crops to Poland. The highest imports were recorded in August 2022, at nearly *** thousand metric tons.

Abstract

Syngenta is committed to increasing crop productivity and to using limited resources such as land, water and inputs more efficiently. Since 2014, Syngenta has been measuring trends in agricultural input efficiency on a global network of real farms. The Good Growth Plan dataset shows aggregated productivity and resource efficiency indicators by harvest year. The data has been collected from more than 4,000 farms and covers more than 20 different crops in 46 countries. The data (except USA data and for Barley in UK, Germany, Poland, Czech Republic, France and Spain) was collected, consolidated and reported by Kynetec (previously Market Probe), an independent market research agency. It can be used as benchmarks for crop yield and input efficiency.

Geographic coverage

National coverage

Analysis unit

Agricultural holdings

Kind of data

Sample survey data [ssd]

Sampling procedure

A. Sample design Farms are grouped in clusters, which represent a crop grown in an area with homogenous agro- ecological conditions and include comparable types of farms. The sample includes reference and benchmark farms. The reference farms were selected by Syngenta and the benchmark farms were randomly selected by Kynetec within the same cluster.

B. Sample size Sample sizes for each cluster are determined with the aim to measure statistically significant increases in crop efficiency over time. This is done by Kynetec based on target productivity increases and assumptions regarding the variability of farm metrics in each cluster. The smaller the expected increase, the larger the sample size needed to measure significant differences over time. Variability within clusters is assumed based on public research and expert opinion. In addition, growers are also grouped in clusters as a means of keeping variances under control, as well as distinguishing between growers in terms of crop size, region and technological level. A minimum sample size of 20 interviews per cluster is needed. The minimum number of reference farms is 5 of 20. The optimal number of reference farms is 10 of 20 (balanced sample).

C. Selection procedure The respondents were picked randomly using a “quota based random sampling” procedure. Growers were first randomly selected and then checked if they complied with the quotas for crops, region, farm size etc. To avoid clustering high number of interviews at one sampling point, interviewers were instructed to do a maximum of 5 interviews in one village.

BF Screened from Ukraine were selected based on the following criterion:

(a) smallholder maize growers Grain corn
Region: Cherkassy & Kiev

(b) smallholder sunflower growers
Region: Vinnitsa, Kiev & Cherkassy

Mode of data collection

Face-to-face [f2f]

Research instrument

Data collection tool for 2019 covered the following information:

(A) PRE- HARVEST INFORMATION

PART I: Screening PART II: Contact Information PART III: Farm Characteristics a. Biodiversity conservation b. Soil conservation c. Soil erosion d. Description of growing area e. Training on crop cultivation and safety measures PART IV: Farming Practices - Before Harvest a. Planting and fruit development - Field crops b. Planting and fruit development - Tree crops c. Planting and fruit development - Sugarcane d. Planting and fruit development - Cauliflower e. Seed treatment

(B) HARVEST INFORMATION

PART V: Farming Practices - After Harvest a. Fertilizer usage b. Crop protection products c. Harvest timing & quality per crop - Field crops d. Harvest timing & quality per crop - Tree crops e. Harvest timing & quality per crop - Sugarcane f. Harvest timing & quality per crop - Banana g. After harvest PART VI - Other inputs - After Harvest a. Input costs b. Abiotic stress c. Irrigation

See all questionnaires in external materials tab.

Cleaning operations

Data processing:

Kynetec uses SPSS (Statistical Package for the Social Sciences) for data entry, cleaning, analysis, and reporting. After collection, the farm data is entered into a local database, reviewed, and quality-checked by the local Kynetec agency. In the case of missing values or inconsistencies, farmers are re-contacted. In some cases, grower data is verified with local experts (e.g. retailers) to ensure data accuracy and validity. After country-level cleaning, the farm-level data is submitted to the global Kynetec headquarters for processing. In the case of missing values or inconsistences, the local Kynetec office was re-contacted to clarify and solve issues.

Quality assurance Various consistency checks and internal controls are implemented throughout the entire data collection and reporting process in order to ensure unbiased, high quality data.

• Screening: Each grower is screened and selected by Kynetec based on cluster-specific criteria to ensure a comparable group of growers within each cluster. This helps keeping variability low.

• Evaluation of the questionnaire: The questionnaire aligns with the global objective of the project and is adapted to the local context (e.g. interviewers and growers should understand what is asked). Each year the questionnaire is evaluated based on several criteria, and updated where needed.

• Briefing of interviewers: Each year, local interviewers - familiar with the local context of farming -are thoroughly briefed to fully comprehend the questionnaire to obtain unbiased, accurate answers from respondents.

• Cross-validation of the answers: o Kynetec captures all growers' responses through a digital data-entry tool. Various logical and consistency checks are automated in this tool (e.g. total crop size in hectares cannot be larger than farm size) o Kynetec cross validates the answers of the growers in three different ways: 1. Within the grower (check if growers respond consistently during the interview) 2. Across years (check if growers respond consistently throughout the years) 3. Within cluster (compare a grower's responses with those of others in the group)

o All the above mentioned inconsistencies are followed up by contacting the growers and asking them to verify their answers. The data is updated after verification. All updates are tracked.

• Check and discuss evolutions and patterns: Global evolutions are calculated, discussed and reviewed on a monthly basis jointly by Kynetec and Syngenta.

• Sensitivity analysis: sensitivity analysis is conducted to evaluate the global results in terms of outliers, retention rates and overall statistical robustness. The results of the sensitivity analysis are discussed jointly by Kynetec and Syngenta.

• It is recommended that users interested in using the administrative level 1 variable in the location dataset use this variable with care and crosscheck it with the postal code variable.

Data appraisal

Due to the above mentioned checks, irregularities in fertilizer usage data were discovered which had to be corrected:

For data collection wave 2014, respondents were asked to give a total estimate of the fertilizer NPK-rates that were applied in the fields. From 2015 onwards, the questionnaire was redesigned to be more precise and obtain data by individual fertilizer products. The new method of measuring fertilizer inputs leads to more accurate results, but also makes a year-on-year comparison difficult. After evaluating several solutions to this problems, 2014 fertilizer usage (NPK input) was re-estimated by calculating a weighted average of fertilizer usage in the following years.

Ukraine Sown Area: Summer Crops data was reported at 7,223.000 ha th in 2016. This records an increase from the previous number of 6,835.000 ha th for 2015. Ukraine Sown Area: Summer Crops data is updated yearly, averaging 7,464.000 ha th from Dec 1990 (Median) to 2016, with 27 observations. The data reached an all-time high of 9,622.000 ha th in 2003 and a record low of 5,471.000 ha th in 1992. Ukraine Sown Area: Summer Crops data remains active status in CEIC and is reported by State Statistics Service of Ukraine. The data is categorized under Global Database’s Ukraine – Table UA.B019: Agricultural Total Land Area and Sown Area.

Cereal yield of Ukraine sank by 15.41% from 5,455 kg per hectare in 2021 to 4,614 kg per hectare in 2022. Since the 2.65% increase in 2019, cereal yield slumped by 7.27% in 2022. Cereal yield, measured as kilograms per hectare of harvested land, includes wheat, rice, maize, barley, oats, rye, millet, sorghum, buckwheat, and mixed grains. Production data on cereals relate to crops harvested for dry grain only. Cereal crops harvested for hay or harvested green for food, feed, or silage and those used for grazing are excluded. The FAO allocates production data to the calendar year in which the bulk of the harvest took place. Most of a crop harvested near the end of a year will be used in the following year.