The research, led by Andrii Dankevych of the National University of Food Technology in Kyiv together with colleagues from Ukraine, Lithuania and Uganda, set out to test whether sunflower husk ash, or SHA, could serve as a genuine secondary mineral resource within a circular economy. The logic is elegantly simple. Sunflower plants draw potassium, phosphorus, calcium, magnesium and sulfur out of the soil as they grow. When the husks are burned for energy, those minerals are not destroyed; they are concentrated in the ash. Returning that ash to farmland effectively closes a nutrient loop that industrial agriculture has traditionally left wide open, sending minerals off-site and replacing them with mined, energy-intensive synthetic fertilizers.

The chemistry of the ash-based fertilizer is central to the story. According to the study, the SHA fertilizer contained 30 percent potassium oxide, 5 percent phosphorus pentoxide, 9 percent calcium oxide, 10 percent magnesium oxide and 4 percent sulfur. Notably, it contained no chlorine at all. That composition matters for two reasons. First, the high potassium fraction makes it a credible alternative or supplement to conventional potash fertilizers, which are among the most geopolitically sensitive and price-volatile inputs in modern farming. Second, the absence of chloride is an advantage for crops such as potato, tomato and cucumber, which are known to be sensitive to chloride accumulation in soil.

To test the fertilizer under real field conditions rather than in pots or greenhouses, the team conducted experiments during one growing season at the Slobozhanske Experimental Field of the National Scientific Center O.N. Sokolovsky Institute for Soil Science and Agrochemistry Research in Ukraine. The soil was a typical heavy loam chernozem, the famously fertile black earth that underpins much of Eastern Europe’s agricultural output. Seven crops were evaluated side by side: barley, maize, sunflower, potato, tomato, table beet and cucumber. Each crop occupied a plot of 0.1 hectares, allowing the researchers to observe how the ash-based fertilizer performed across a genuinely diverse rotation of cereals, oilseeds, tubers and vegetables.

The experimental design compared four treatments for each crop: an unfertilized control, a conventional NPK 16:16:16 mineral fertilizer, and the SHA-based fertilizer applied at two rates, 200 and 300 kilograms per hectare. The ash fertilizer was delivered in two ways, as a basal application and during pre-sowing cultivation, so the researchers could see whether timing and placement influenced performance. Yield, soil agrochemical properties and selected quality parameters of the harvested products were then measured, and the data were processed using descriptive and comparative statistical methods, including arithmetic means and absolute and relative differences between treatments.

The headline result is that plots treated with the SHA-based fertilizer yielded approximately 10 to 18 percent more than the unfertilized controls. Just as important for long-term soil health, the content of mobile phosphorus and exchangeable potassium in the soil rose by roughly 10 to 22 percent following treatment. Soil pH shifted by approximately 0.3 to 0.5 units, a change consistent with the liming-like effect of the calcium and magnesium oxides in the ash, which can help buffer acidity in intensively farmed soils. Beyond quantity, the researchers also recorded improvements in quality parameters of the produce itself, including higher dry matter, protein and fat content in the harvested crops, suggesting that the ash-derived nutrients were genuinely feeding the plants rather than merely sitting in the soil.

The authors are careful, and rightly so, about the limits of what a single-season, single-site trial can prove. Because all the data came from one growing season at one experimental station, the results reflect the specific soil, climatic and experimental conditions of the study and should be interpreted descriptively rather than as statistically significant effects. That caveat is standard scientific caution, but it is also a roadmap: the team explicitly calls for further studies in different natural and climatic zones and on soils with different properties to establish whether the yield gains and soil improvements hold up more broadly. Multi-year trials would also be needed to confirm that repeated ash application does not lead to unwanted accumulations of trace elements, a question that remains open for many waste-derived fertilizers.

Even with those caveats, the scale of the opportunity is hard to ignore. Ukraine is one of the world’s largest sunflower producers, and the husk that remains after oil extraction is widely burned in boilers as biomass fuel. That combustion, while renewable in energy terms, produces ash streams exceeding 100 thousand tonnes per year that currently must be landfilled or otherwise disposed of, at cost to processors and with no agronomic return. If even a fraction of that ash were diverted into fertilizer production, it would simultaneously reduce waste disposal volumes, displace demand for imported or mined potassium and phosphorus, and return nutrients to the very fields that grew the crop. This is the circular economy in its most literal form: minerals harvested from the soil, used in processing, burned for energy, and then sent home again.

The study also carries broader implications for the bioeconomy beyond Ukraine. Sunflower is grown commercially across Europe, the Black Sea region, Argentina and elsewhere, and husk ash is a ubiquitous by-product of the oilseed industry wherever husks are used as fuel. The Ukrainian findings provide initial field evidence that this ash stream, rather than being a niche curiosity, can function as a standardized fertilizer input with a defined nutrient profile. Because the ash is essentially a concentrated, chlorine-free potassium source with secondary phosphorus, calcium, magnesium and sulfur, it could be blended or granulated with other materials to create tailored formulations for chloride-sensitive crops, organic-adjacent production systems, or regions where conventional potash supplies are expensive or unreliable.

What makes the work resonate beyond agronomy is its framing of waste as a design flaw rather than an inevitability. The researchers argue that valorizing sunflower processing residues can contribute to added value, increased agricultural production and the implementation of environmental initiatives all at once, turning a disposal liability into a revenue stream and a soil amendment in a single move. As fertilizer prices remain volatile and the environmental footprint of synthetic nutrient production draws increasing scrutiny, studies like this one point toward a pragmatic middle path: not a rejection of mineral fertilizers, but a smarter, more circular sourcing of them. The next seasons of field trials will determine whether sunflower husk ash can graduate from promising one-site evidence to a dependable ingredient of sustainable agriculture. For now, the message from the chernozem of eastern Ukraine is clear: the minerals that leave the farm in a sunflower seed do not have to be gone for good.

Subject of Research: Use of sunflower husk ash as a secondary mineral resource for fertilizer production in circular-economy agriculture

Article Title: Agricultural waste valorization in the circular economy using sunflower husk ash as a secondary resource

Article References: Dankevych, A., Nitsenko, V., Dankevych, V., Ogbu, E. F., Lastauskaitė, A., & Kapelista, I. (2026). Agricultural waste valorization in the circular economy using sunflower husk ash as a secondary resource. Discover Sustainability. https://doi.org/10.1007/s43621-026-04879-y

Image Credits: AI Generated

DOI: 10.1007/s43621-026-04879-y

Keywords: sunflower husk ash, circular economy, agricultural waste valorization, fertilizer, crop yield, soil nutrients, chernozem, potassium, biomass energy, sustainable agriculture, Ukraine, bioeconomy

The research team, led by Augusto Cesar Laviola de Oliveira and Natalia dos Santos Renato, built their analysis around Thompson’s model, a semi-empirical formulation dating to 1972 that describes how grain dries in thick layers under low airflow and near-ambient temperatures. The model divides a silo’s grain column into thin virtual layers and, hour by hour, balances the energy and moisture exchanged between the drying air and the beans. Heat exchange is treated as adiabatic, and equilibrium moisture is calculated with the modified Halsey equation, while psychrometric properties of the air follow standards from the American Society of Agricultural Engineers. The algorithm iterates until the relative humidity of the air and grain converge within a tolerance of half a percent, using a secant-method approach that the authors found robust across the vast majority of conditions.

To ground the simulation in reality, the team adopted a standardized storage silo, about 18 meters in diameter and nearly 13 meters tall, holding 2,675 metric tons of soybeans at an initial moisture content of 20 percent wet basis. Drying was considered complete when the topmost layer reached the target of 13 percent, the level needed to prevent fungal contamination during storage. Real weather drove every simulation: dry bulb temperature, relative humidity, and atmospheric pressure recorded at INMET automatic weather stations across four harvests, from 2012/13 to 2021/22. After preprocessing and convergence checks, the database contained 55,798 valid simulation samples spanning the Brazilian territory from January through August of each crop year.

The results reveal how dramatically climate shapes the energy bill. Electricity demand, which powers the fans that push air through the grain, proved relatively stable, ranging from about 72,800 to 97,900 kilowatt-hours for a standard silo load depending on the day simulated. Thermal energy, supplied by burning liquefied petroleum gas when ambient air is too humid to finish the job, swung far more wildly, from roughly 46,000 to 156,000 kilowatt-hours. On the cheapest drying days the air was warm and dry; on the most expensive, cold and saturated. Multiple regression confirmed that every variable mattered: rising temperature cut both electrical and thermal demand, rising humidity raised them, and atmospheric pressure pushed electricity up while nudging gas consumption down, all with p-values near zero.

Geography compounds the climate effect. Using inverse-distance-weighted interpolation in QGIS, the team converted point simulations into continuous national maps and extracted statistics for all 27 states. The Midwest, home to Mato Grosso, Brazil’s largest soybean producer, accounted for 42 to 44 percent of national demand, with Mato Grosso alone requiring between 1.3 and 2.7 terawatt-hours per harvest. The South followed closely, where winter humidity pushes demand to its national peak: Rio Grande do Sul recorded the highest specific demand, up to 130 kilowatt-hours per ton of grain. In the Northeast, by contrast, hot dry air does much of the work for free, with Piauí posting the lowest specific demand at under 54 kilowatt-hours per ton.

Statistical analysis of variance added a temporal dimension. For most states, energy demand fluctuated significantly from month to month but remained stable across harvests, suggesting that a single average year can represent long-term planning. The South showed a steady climb in demand from January to August as autumn and winter arrived, while states in the Center-West and North trended downward over the same period. Only Acre, Amazonas, and Rio Grande do Norte showed significant differences between harvests, hinting at shifting climate patterns in those regions.

The study then asked whether the crop could pay its own energy bill. Soybean hulls, about 5 percent of grain mass and normally sold as animal feed, carry a calorific value that, when briquetted and burned in a Rankine cycle at 37 percent efficiency, can generate roughly 1.18 megawatt-hours of electricity per ton. Nationally, that generation could technically cover the entire electrical demand of the drying sector. Coverage varies sharply by state: Piauí and Bahia could produce more than 100 percent of their needs, while Rio Grande do Sul and Paraná would fall short at 42 to 88 percent, and Mato Grosso would land between 61 and 128 percent depending on the year.

The carbon arithmetic is equally compelling. Accounting for carbon dioxide released by grain respiration during drying, by LPG combustion, and by the electricity drawn from the grid, then crediting the emissions avoided by hull-based cogeneration, the national balance ranges from a net sequestration of about 595,000 tons of carbon dioxide to net emissions of about 778,000 tons. In favorable states and years, drying soybeans could actually remove carbon from the atmosphere; in others, it remains a modest source. The economics stay manageable either way: energy costs run from about 4.37 dollars per ton in Piauí to 14.73 dollars in Acre, or between 0.99 and 3.79 percent of the soybean’s market value per 60-kilogram bag.

Perhaps the most forward-looking contribution is the artificial intelligence layer. The team trained feed-forward neural networks on the 55,798 Thompson simulations, using temperature, humidity, and pressure as inputs to predict electrical, thermal, and total energy demand. With 90 neurons in the hidden layers for the electrical and thermal models and 30 for total energy, the networks achieved coefficients of determination above 0.997, with root mean square errors as low as 0.27 percent for electricity. In independent validation, deviations from the deterministic model stayed within roughly 2.4 percent. Because the neural surrogate runs in a fraction of the time and avoids the convergence failures that occasionally plague Thompson’s formulation, it opens the door to real-time decision support, letting operators adjust fan and burner settings as weather shifts.

The authors are careful to note the framework’s boundaries: by holding silo geometry, fan efficiency, and airflow constant, they isolated climate as the driver of demand, leaving operational optimization for future sensitivity studies. But the template travels well. Any country or crop with representative weather and production data could rerun the same pipeline, from deterministic physics to geospatial statistics to machine learning. For Brazil, whose electricity matrix remains nearly 62 percent hydroelectric and increasingly exposed to climate volatility, the message is clear: the humble act of drying grain is a national-scale energy enterprise, and the residue left behind after cleaning the crop may be the cheapest, cleanest way to power it.

Subject of Research: Energy demand modeling of low-temperature soybean drying in Brazil

Article Title: Analysis and modeling of energy demand in the low-temperature drying process of soybean in Brazil

Article References: Oliveira, A. C. L. D., Oliveira, V. H. L. D., Silva, L. C. D., Moraes, C. A., & Renato, N. D. S. (2026). Analysis and modeling of energy demand in the low-temperature drying process of soybean in Brazil. Cleaner Engineering and Technology, 34, Article 101313. https://doi.org/10.1016/j.clet.2026.101313

Image Credits: AI Generated

DOI: 10.1016/j.clet.2026.101313

Keywords: soybean drying, low-temperature drying, energy demand, Thompson model, artificial neural networks, geospatial analysis, biomass energy, soybean hulls, carbon emissions, Brazil, agribusiness, energy efficiency