Urea fell to 439.75 USD/T on August 19, 2025, down 0.17% from the previous day. Over the past month, Urea's price has fallen 1.18%, but it is still 40.72% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. This dataset includes a chart with historical data for Urea.

Urea prices in , June, 2025 For that commodity indicator, we provide data from January 1960 to June 2025. The average value during that period was 171.5 USD per metric ton with a minimum of 16 USD per metric ton in January 1971 and a maximum of 925 USD per metric ton in April 2022. | TheGlobalEconomy.com

The price of urea stood at 358 U.S. dollars per metric ton in 2023, the highest value in the period investigated. The price of this commodity was forecast to decrease in the following year, to then drop annually to amount to 325 dollars per ton in 2025.

Subsidized urea price (median-USD kg-1), percentage of the non-subsidized urea price, and number of observations per country (values between parenthesis). Slope (USD kg-1) of the regression models between subsidized and non-subsidized prices.

The average retail price of granular urea amounted to about 1,581 Philippine pesos per 50 kilogram bag as of December 2024. The average retail price of urea peaked in 2021 and 2022.

China Retail Price: Agri Material: Urea, N 46%: Domestic Made data was reported at 2.250 RMB/kg in Mar 2025. This records a decrease from the previous number of 2.290 RMB/kg for Feb 2025. China Retail Price: Agri Material: Urea, N 46%: Domestic Made data is updated monthly, averaging 2.110 RMB/kg from Jan 2007 (Median) to Mar 2025, with 219 observations. The data reached an all-time high of 3.350 RMB/kg in Jun 2022 and a record low of 1.620 RMB/kg in Oct 2016. China Retail Price: Agri Material: Urea, N 46%: Domestic Made data remains active status in CEIC and is reported by Price Monitoring Center, NDRC. The data is categorized under China Premium Database’s Price – Table CN.PA: Price Monitoring Center, NDRC: Retail Price: Agricultural Material.

Retail Price: Fertilizer: Urea: Philippines data was reported at 1,075.864 PHP/50 kg in Oct 2018. This records an increase from the previous number of 1,055.360 PHP/50 kg for Sep 2018. Retail Price: Fertilizer: Urea: Philippines data is updated monthly, averaging 1,032.125 PHP/50 kg from Jan 2006 (Median) to Oct 2018, with 154 observations. The data reached an all-time high of 1,933.350 PHP/50 kg in Sep 2008 and a record low of 879.000 PHP/50 kg in Feb 2006. Retail Price: Fertilizer: Urea: Philippines data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.P002: Retail Price: Fertilizers.

We compiled fertilizer price data for eighteen countries in West and East Africa from two data sources: (1) Africa Fertilizer (Africa Fertilizer, 2018) and (2) the Living Standards Measurement Study-Integrated Surveys on Agriculture (henceforth LSMS-ISA) (World Bank, 2018). Africa Fertilizer reports prices over time for major towns in different countries. Prices are for 25 kg or 50 kg bags and expressed in the national currency. We compiled 7823 observations for 878 locations in seventeen countries: Benin, Burundi, Burkina Faso, Côte d’Ivoire, Ghana, Kenya, Mali, Malawi, Mozambique, Niger, Nigeria, Rwanda, Senegal, Togo, Tanzania, Uganda, and Zambia from 2010-2018. We used the town name to assign geographic coordinates to each location. Africa Fertilizer reported non-subsidized and subsidized prices for several countries. LSMS-ISA is a nationally representative multi-topic household survey implemented in eight countries in SSA: Burkina Faso, Ethiopia, Malawi, Mali, Niger, Nigeria, Tanzania, Uganda (World Bank, 2018).

Ammonia emission from animal production is a major environmental problem and has impacts on the animal health and working environment inside production houses. Ammonia is formed in manure by the enzymatic degradation of urinary urea and catalyzed by urease that is present in feces. We have determined and compared the urease activity in feces and manure (a urine and feces mixture) from pigs and cattle at 25°C by using Michaelis-Menten kinetics. To obtain accurate estimates of kinetic parameters Vmax and K'm, we used a 5 min reaction time to determine the initial reaction velocities based on total ammoniacal nitrogen (TAN) concentrations. The resulting Vmax value (mmol urea hydrolyzed per kg wet feces per min) was 2.06±0.08 mmol urea/kg/min and 0.80±0.04 mmol urea/kg/min for pig feces and cattle feces, respectively. The K'm values were 32.59±5.65 mmol urea/l and 15.43±2.94 mmol urea/l for pig feces and cattle feces, respectively. Thus, our results reveal that both the Vmax and K'm values of the urease activity for pig feces are more than 2-fold higher than those for cattle feces. The difference in urea hydrolysis rates between animal species is even more significant in fresh manure. The initial velocities of TAN formation are 1.53 mM/min and 0.33 mM/min for pig and cattle manure, respectively. Furthermore, our investigation shows that the maximum urease activity for pig feces occurs at approximately pH 7, and in cattle feces it is closer to pH 8, indicating that the predominant fecal ureolytic bacteria species differ between animal species. We believe that our study contributes to a better understanding of the urea hydrolysis process in manure and provides a basis for more accurate and animal-specific prediction models for urea hydrolysis rates and ammonia concentration in manures and thus can be used to predict ammonia volatilization rates from animal production.

This industry is operating under difficult market conditions. This is primarily due to intensifying regulation, which is noticeably restricting the use of fertilisers by farmers and is particularly evident in the EU Fertiliser Products Regulation from 2019. In addition, changeable weather conditions are having a negative impact on the sector, at least in the short term. In the longer term, difficult growing conditions tend to favour the sale of fertilisers. The disruptions in supply chains in the wake of the coronavirus crisis and the conflict in Ukraine have led to a sharp rise in the prices of key input and energy products such as natural gas, which resulted in a significant increase in fertiliser prices worldwide between 2020 and 2022. Since 2023, the trend towards falling energy and commodity prices has seen a normalisation of sales development. Overall, industry turnover has risen by an average of 1.9% per year since 2019.Weak commodity prices and subdued European demand for fertilisers are likely to have a negative impact on industry sales in 2024. In addition, one of the industry's most important customer markets, the cultivation of cereals, pulses and oilseeds in Germany, is likely to record a decline in sales in the current year, not least due to the very wet weather conditions in the first half of 2024, which is likely to have a negative impact on demand for fertilisers. Compared to the previous year, industry turnover in 2024 is expected to fall by 16.5% to €5.7 billion.Despite the increasingly strict regulations on fertilisers and the expansion of organic farming in Germany, industry turnover is expected to grow by an average of 0.5% per year over the next five years. It is expected to reach 5.8 billion euros in 2029. Due to the high energy prices in Germany compared to other countries, competition from foreign suppliers is likely to intensify over the next five years.

The dataset consists of tables of means, with statistical differences indicated where they are significant, for measured crop performance, fertilizer N recovery and use efficiency at 6 field sites from Mackay to Freshwater. Runoff losses of N are also shown from sites at Freshwater and Silkwood.

**This dataset is currently under embargo until the project end date.

Optimizing fertilizer nitrogen (N) application rates to both sustain high levels of productivity and minimize any impacts on the surrounding ecosystem is challenging, especially under monsoonal wet season conditions in northern Australia. The inability of existing application strategies and fertilizer N products to achieve synchrony of mineral N supply with crop demand, or prevent rapid formation of nitrate-N (that is vulnerable to loss via gaseous or aqueous loss pathways) increases risks of inefficient N use. A blend of enhanced efficiency fertilizers (EEFs) with different modes of action has the best chance of lowering the risk of N losses and increasing crop N recovery, providing an opportunity to reduce fertilizer N rates without increasing the risks of productivity loss. Six field trials were established from Mackay to the wet tropics, with data collected from consecutive ratoon crops at each site. Yields and indices of N use efficiency were developed for crops receiving urea-N at rates equivalent to that derived from the local SIX EASY STEPS guidelines, or as urea or a blend of EEF’s applied at N rates calculated using a block-specific yield target (PZYP) based on mill records.

Methods:

The project established a total of six field sites after the 2016 crop harvest, with all experiments commencing after harvest of the 1st or 2nd ratoon. The experimental design and plot size varied with site. In Silkwood, Freshwater and the Burdekin, plots consisted of large scale strips 6-8 cane rows wide and the length of the cane block, with yield (and in the case of Silkwood and Freshwater, runoff water quality) collected from the whole treated strip. The Burdekin trial contained three replicate strips of each treatment, but due to the extensive water quality monitoring equipment requirements at Silkwood and Freshwater, treatments were not replicated. At all other sites, trials consisted of smaller plot, replicated experiments in a randomized block design. Plot size was at least 6 cane rows wide 30m long, and all treatments were replicated four times.

The basis of fertilizer rates was either the District Yield Potential (DYP, currently used to determine the fertilizer N rates in 6ES) or the Productivity Zone Yield Potential (PZYP, used to determine N rates aligned to a spatially relevant yield target). The PZYP was calculated from the mean yield from block or satellite records over two or more crop cycles, plus 2 standard error of that mean. As all sites were established in ratoon crops, plant crop yields were generally excluded from this calculation, especially where those yields were markedly higher than yields of the ratoons. In situations where large variation in yields occurred between La Nina and normal or drier seasons (e.g. in the wet tropics), separate PZYP targets were calculated to reflect the expected seasonal forecast (i.e. lower PZYP targets in forecast La Nina conditions). Each site hosted a Nil N treatment each year (fertilizer N was withheld for that growing season), but these plots/strips were relocated to new plot/strip locations annually. Having the Nil N treatment always located on a plot with a history of fertilizer N application provided a realistic assessment of the soil N supply which the fertilizer N application was designed to augment.

Crop harvest and fertilizer application were conducted as per grower normal practice at each location, although at all sites there were no crops harvested in the 1st round. This was considered desirable, as it was expected that the best chance to assess the risks of reduced N rates and the efficacy of EEF’s would be under conditions where fertilizer N losses were more likely to occur (i.e., where the onset of the monsoonal wet season occurred before the crop had finished the majority of biomass N accumulation).

Fertilizer N sources The same fertilizer N sources were used at each site. The fertilizer N standard was taken as granular urea, which was applied during the month following harvest of the preceding ratoon. This was compared to an EEF blend consisting of 1/3 urea coated with the nitrification inhibitor 3,4-dimethylpyrazole phosphate (DMPP, marketed commercially as Entec®) and 2/3 polymer-coated urea with a reported 90-day release period (product of Everris Pty Ltd and marketed as Agromaster Tropical®). This blend was chosen as the best possible combination of products that would protect fertilizer N from risk of loss – initially by retaining the N in the NH4-N form, and subsequently by slowing the release of urea-N into the soil solution.

Both products were applied using either stool-split (Burdekin, Freshwater, Mackay and Silkwood) or subsurface side-dress (Tully) fertilizer applicators, although it should be noted that on occasions the stool-split applicators did not always effectively close the fertilizer trench and cover the fertilizer band with soil. This suboptimal application strategy contributed to some confounding of the benefits of EEF use in some seasons due to greater loss risks to both the atmosphere and in runoff. Fertilizer N recovery, crop yield and indices of fertilizer N use efficiency

Fresh and dry biomass and crop N content were determined from hand-cut biomass samples collected from 7-10 months after fertilizer application, on the assumption that at this stage, the crop N content would be at a maximum, and most relevant to the yield-determining processes. Crop N was partitioned between leaf/cabbage/dead leaf and stalks at that time. In situations where biomass sampling was conducted a little earlier than desirable (e.g. due to an impending cyclone), smaller numbers of whole stalk samples were again collected for dry matter and N concentration immediately prior to harvest (to determine the partitioning of N between harvested and non-harvested portions of the crop), and stalk N concentration from the final harvest was used in combination with cane yields to estimate crop N removal. Yields were determined by commercial harvest in the case of the large strip plots, with the bins collected from each strip weighed and ccs determined at the mill. In the case of the small plot trials, yields were determined from small plot hand harvesting and ccs was determined by near infrared spectroscopy.

A number of indices of N use efficiency were calculated from these data including –

-Agronomic Efficiency of fertilizer N use (AgronEffN) = Fertilizer N rate/(YieldN1 – YieldN0) = kg fertilizer N required to produce an additional tonne of cane yield. In this calculation, YieldN1 is the cane yield at fertilizer rate N1, while YieldN0 is the yield with no N applied.

-Nitrogen uptake efficiency (NUpE) = (Crop N1 – Crop N0)/Fertilizer N rate = the additional crop N uptake/kg fertilizer N applied. In this calculation, N1 is the biomass N content for N rate 1, while N0 is the biomass N content with no applied N fertilizer.

-Nitrogen Utilization Efficiency (NUtE) = Yield/Crop N content = t cane produced/kg of crop N uptake. This figure is a very useful indicator of trial sites where yield is constrained by factors other than N (e.g. waterlogging).

Runoff and drainage losses of N Surface water runoff and drainage below the root zone (1 m depth) were monitored in four of the fertilizer rate treatments at Silkwood and Freshwater sites. In addition, strategic sampling in the farm drain around the Silkwood block was undertaken. Surface water samples were collected by automated samplers, with sampling undertaken across the hydrograph (Freshwater) or as an integrated composite of runoff from each individual runoff event (Silkwood). Runoff samples were analysed for sediment, total nitrogen, urea, ammonium-N, and nitrate-N (in addition to other constituents). Drainage samples were collected from 5 lysimeter barrels in each of the treatments with runoff monitoring (totalling 20 barrels) on a weekly to monthly basis at Silkwood. Drainage samples were analysed for nitrate-N and ammonium-N concentrations.

Limitations of the data - Data collectively represent variable soil types and seasonal conditions, so extrapolation from particular sites to other seasons, regions or soil types should be undertaken with extreme caution. Similarly, the performance of the EEF fertilizer blend used in this study is specific to the products used, and extrapolation to a broader range of EEF technologies would not be appropriate.

Format: The data consists of a series of spreadsheets containing crop summary data for each successive crop season at all sites. As of March 2019, the dataset is complete for 2 crop seasons at all sites. Data are presented as treatment means with statistical significance (P<0.05) indicated where appropriate.

Data Dictionary:

-EEF – Enhanced Efficiency Fertilizer. In the context of these trials, refers to a blend of 1/3 urea coated with the nitrification inhibitor DMPP (Entec ®) and 2/3 polymer coated urea (Agromaster Tropical ®) with a reported 90d release period.

-Agronomic Efficiency of fertilizer N use (AgronEffN) = Fertilizer N rate/(YieldN1 – YieldN0) = kg fertilizer N required to produce an additional tonne of cane yield. In this calculation, YieldN1 is the cane yield at fertilizer rate N1, while YieldN0 is the yield with no N applied.

-Nitrogen uptake efficiency (NUpE) = (Crop N1 – Crop N0)/Fertilizer N rate = the additional crop N uptake/kg fertilizer N applied. In this calculation, N1 is the biomass N content for N rate 1, while N0 is the biomass N content with no applied N fertilizer.

-Nitrogen Utilization Efficiency (NUtE) = Yield/Crop N

Abstract The objective of this work was to evaluate the losses of N-NH3 by volatilization and the agronomic efficiency of a mixture of urea with natural zeolite, as topdressing fertilization, in an area for the commercial production of roses (Rosa spp.). The treatments were: two rates of urea (60 and 120 kg ha-1), with and without zeolite. The N sources were applied directly to soil surface, and volatilization was determined using a free semi-open static chamber. The quantitative and qualitative variables of the collected flower stems were used to determine the agronomical efficiency of the fertilizers. The zeolite mixture reduces N-NH3 losses in 30%, compared with the commercial urea fertilizer, and shows a higher agronomic efficiency, resulting in an increase of 25 dozen of flower stems per each kilogram of N applied.

The objective of this experiment was to investigate the role of different N fertilization rates and the use of the nitrification inhibitor 3,4-dimethylpyrazole phosphate (DMPP, commercially sold as Entec) in reducing N2O emissions from subtropical maize systems over summer. At the same time, particular attention was given to the yield response shown by the different treatments, in order to evaluate the respective economical sustainability and N2O intensity. The field experiment was set up in Kingaroy ( S-E QLD), on a euchrozems Ferrosol soil, using a randomized complete three-block design (three replicates per treatment). The four treatments encompassed three different fertilization rates and two types of Urea (conventional and DMPP urea): control treatment (L1: 40 kg-N ha-1 -conv. urea), sub-optimal N rate (L2: 100 kg-N ha-1 –conv. urea) and optimal N rate (L3: 160 kg-N ha-1 –conv. urea, L4: 160 kg-N ha-1 –DMPP urea). The N2O emissions were measured from planting (December 20th 2011) to harvest (June 20th 2012) with a fully automated greenhouse gas measuring system. In order to gain optimum understanding of the dynamics influencing greenhouse gas production and release in agricultural soils, the air temperature and the soil moisture inside the measuring chambers were constantly monitored. To compare the "environmental" performances of the four treatments with agronomical sustainability grain yields were also determined.

ABSTRACT Response of taro to amount of nitrogen applied and time of application has been the subject of discussion. The objective of this study was to evaluate the effect of nitrogen topdressing on taro yield. Two experiments were conducted in Oratórios - MG from September 2010 to July 2011 (Year 1) and from September 2011 to July 2012 (Year 2). Both experiments were arranged in a randomized block design, with four replications. The treatments consisted of five N rates (0; 40; 60; 80 and 160 kg ha-1) applied as topdressing at urea form. The corms of Japanese clone (BGH 5925) were planted in the 0.90 x 0.30 m spacing. In the two experimental years, yield increased in almost all corm classes with the increase in N rates. The estimated maximum yields of marketable corms were 22.23 Mg ha-1 in Year 1 and 9.81 Mg ha-1 in Year 2, with 109 and 118 kg ha-1 of N, respectively. The total number of corms per plant was similar in both years (16.45 corms/plant in Year 1 and 17.76 corms/plant in Year 2). Unmarketable corms represented 35.32 and 46.51% of the total per plant, in Year 1 and Year 2, respectively, indicating less corm growth in Year 2. The curve of taro response to topdressing N rates was similar in the two years and, the estimates were influenced by the difference in rainfall between the years. With the management of nitrogen fertilization, the maximum yield of marketable taro corms was achieved with N rates varying from 109 to 118 kg ha-1.

The objective of this experiment was to investigate the role of different N fertilization rates and the use of the nitrification inhibitor 3,4-dimethylpyrazole phosphate (DMPP, commercially sold as Entec) in reducing N2O emissions from subtropical wheat systems over winter. At the same time, particular attention was given to the yield response shown by the different treatments, in order to evaluate the respective economical sustainability and N2O intensity. The field experiment was set up in Kingaroy ( S-E QLD), on a euchrozems Ferrosol soil, using a randomized complete three-block design (three replicates per treatment). The four treatments encompassed three different fertilization rates and two types of Urea (conventional and DMPP urea): control treatment (L1: 0 kg-N ha-1), sub-optimal N rate (L2: 20 kg-N ha-1 –conv. urea) and optimal N rate (L3: 80 kg-N ha-1 –conv. Urea, L4: 80 kg-N ha-1 –DMPP urea). The N2O emissions were measured from planting (July 8th) to harvest (November 27th 2011) with a fully automated greenhouse gas measuring system. In order to gain optimum understanding of the dynamics influencing greenhouse gas production and release in agricultural soils, the air temperature and the soil moisture inside the measuring chambers were constantly monitored. To compare the "environmental" performances of the four treatments with agronomical sustainability grain yields were also determined.

ABSTRACT Nitrogen (N) is the most limiting nutrient for growth of forage grasses, especially in conditions of low water availability. Therefore, it is important to evaluate the effect of N fertilization and irrigation on the accumulation of carbon (C) and carbon dioxide (CO2) by marandu grass in the Cerrado Paulista, in the rainy and dry seasons. Experiments were conducted to evaluate N fertilization in each season, with and without irrigation. Five N rates were used (0, 50, 100, 150 and 200 kg ha-1 per cutting), using urea as N source, totaling 0, 300, 600, 900 and 1200 kg ha-1 in the rainy season and 0, 100, 200, 300 and 400 kg ha-1 in the dry season. The experiments were arranged in a split-plot randomized block design. There was no significant interaction (p > 0.05) between N and time of fertilization in the irrigated experiment. However, N promoted a quadratic effect in organic matter production (OMP), accumulation of C and CO2 by marandu grass, while there was no influence of the seasons. In the non-irrigated experiment, the interaction between N rates and seasons was significant (p < 0.05) only for the rainy season. Organic matter production and C and CO2 accumulation was greater in the rainy season than in the dry season. Irrigation provided increases of approximately 20% in C and CO2 accumulation. The use of N and irrigation increases the accumulation of C and CO2 by marandu grass, and this increase is higher during the rainy season.

Abstract: The objective of this work was to evaluate corn agronomic traits in a cultivation subjected to different N rates, during the fall-winter (off-season) and spring-summer crop seasons, and N recovery from fertilizer. The experiment was set up in a randomized complete block design with four replicates, in a 5x2 factorial arrangement, with the following treatments: five N topdressing rates - 0, 30, 60, 90, and 120 kg ha-1 -, using urea as source; and two crop seasons, fall-winter and spring-summer. The following variables were determined: plant height, height of the first ear insertion, number of grains per ear, diameter and length of ear, 1,000-grain weight, N concentration in the leaves and grains, grain-protein concentration, grain yield, N recovery from fertilizer, and soil-N supply. Nitrogen rates in the fertilizer in the fall-winter season had no effect on grain yield, although corn agronomic traits showed a greater reliance on fertilizer-N rates in that season than in the spring-summer, which is a season associated to a greater capacity of soil-N supply to plants. The quantification of soil-N supply enabled knowing the nutrient dynamics during the fall-winter and the spring-summer seasons, which may be useful to guide N fertilization of corn.