Limited effects of crop foliar Si fertilization on a marginal soil under a future climate scenario

Growing crops on marginal lands is a promising solution to alleviate the increasing pressure on agricultural land in Europe. Such crops will however be at the same time exposed to increased drought and pathogen prevalence, on already challenging soil conditions. Some sustainable practices, such as Silicon (Si) foliar fertilization, have been proposed to alleviate these two stress factors, but have not been tested under controlled, future climate conditions. We hypothesized that Si foliar fertilization would be beneficial for crops under future climate, and would have cascading beneficial effects on ecosystem processes, as many of them are directly dependent on plant health. We tested this hypothesis by exposing spring barley growing on marginal soil macrocosms (three with, three without Si treatment) to 2070 climate projections in an ecotron facility. Using the high-capacity monitoring of the ecotron, we estimated C, water, and N budgets of every macrocosm. Additionally, we measured crop yield, the biomass of each plant organ, and characterized bacterial communities using metabarcoding. Despite being exposed to water stress conditions, plants did not produce more biomass with the foliar Si fertilization, whatever the organ considered. Evapotranspiration (ET) was unaffected, as well as water quality and bacterial communities. However, in the 10-day period following two of the three Si applications, we measured a significant increase in C sequestration, when climate conditions where significantly drier, while ET remained the same. We interpreted these results as a less significant effect of Si treatment than expected as compared with literature, which could be explained by the high CO2 levels under future climate, that reduces need for stomata opening, and therefore sensitivity to drought. We conclude that making marginal soils climate proof using foliar Si treatments may not be a sufficient strategy, at least in this type of nutrient-poor, dry, sandy soil.

Predicting Maize Theoretical Methane Yield in Combination with Ground and UAV Remote Data Using Machine Learning

The accurate, timely, and non-destructive estimation of maize total-above ground biomass (TAB) and theoretical biochemical methane potential (TBMP) under different phenological stages is a substantial part of agricultural remote sensing. The assimilation of UAV and machine learning (ML) data may be successfully applied in predicting maize TAB and TBMP; however, in the Nordic-Baltic region, these technologies are not fully exploited. Therefore, in this study, during the maize growing period, we tracked unmanned aerial vehicle (UAV) based multispectral bands (blue, red, green, red edge, and infrared) at the main phenological stages. In the next step, we calculated UAV-based vegetation indices, which were combined with field measurements and different ML models, including generalized linear, random forest, as well as support vector machines. The results showed that the best ML predictions were obtained during the maize blister (R2)-Dough (R4) growth period when the prediction models managed to explain 88-95% of TAB and 88-97% TBMP variation. However, for the practical usage of farmers, the earliest suitable timing for adequate TAB and TBMP prediction in the Nordic-Baltic area is stage V7-V10. We conclude that UAV techniques in combination with ML models were successfully applied for maize TAB and TBMP estimation, but similar research should be continued for further improvements.

Relaunch cropping on marginal soils by incorporating amendments and beneficial trace elements in an interdisciplinary approach

In the EU and world-wide, agriculture is in transition. Whilst we just converted conventional farming imprinted by the post-war food demand and heavy agrochemical usage into integrated and sustainable farming with optimized production, we now have to focus on even smarter agricultural management. Enhanced nutrient efficiency and resistance to pests/pathogens combined with a greener footprint will be crucial for future sustainable farming and its wider environment. Future land use must embrace efficient production and utilization of biomass for improved economic, environmental, and social outcomes, as subsumed under the EU Green Deal, including also sites that have so far been considered as marginal and excluded from production. Another frontier is to supply high-quality food and feed to increase the nutrient density of staple crops. In diets of over two-thirds of the world's population, more than one micronutrient (Fe, Zn, I or Se) is lacking. To improve nutritious values of crops, it will be necessary to combine integrated, systems-based approaches of land management with sustainable redevelopment of agriculture, including central ecosystem services, on so far neglected sites: neglected grassland, set aside land, and marginal lands, paying attention to their connectivity with natural areas. Here we need new integrative approaches which allow the application of different instruments to provide us not only with biomass of sufficient quality and quantity in a site specific manner, but also to improve soil ecological services, e.g. soil C sequestration, water quality, habitat and soil resistance to erosion, while keeping fertilization as low as possible. Such instruments may include the application of different forms of high carbon amendments, the application of macro- and microelements to improve crop performance and quality as well as a targeted manipulation of the soil microbiome. Under certain caveats, the potential of such sites can be unlocked by innovative production systems, ready for the sustainable production of crops enriched in micronutrients and providing services within a circular economy.

Future climate change will accelerate maize phenological development and increase yield in the Nemoral climate

Climate change will bring warmer and wetter conditions and more frequent extreme events in the Nemoral climate zone. These changes are expected to affect maize growth and yields. In this study, we applied the AgroC model to assess climate change impact on changes in growing environmental conditions, growing season length, yield and potential yield losses due to multiple abiotic stresses. The model was calibrated and validated using data from dedicated field experiments conducted in Lithuania during four meteorologically contrasting years (2015, 2016, 2017 and 2019). We simulated the climate impacts on rainfed maize for long-term future climate conditions from 2020 to 2100 under the RCP2.6 (low), RCP4.5 (medium) and RCP8.5 (high) emission scenarios. As a result, we found that air temperature, sum of growing degree days and amount of precipitation during the growing season of maize will increase, especially under medium and higher emission scenarios (RCP4.5 and RCP8.5), with significantly positive effect on yields. The simulation results showed that average maize grain yield will increase under RCP2.6 by 69 kg ha^-1 per decade, under RCP4.5 by 197 kg ha^-1 per decade and under RCP8.5 by 304 kg ha^-1 per decade. The future potential maize yield reveals a progressive increase with a surplus of +10.2% under RCP4.5 and +14.4% under RCP8.5, while under RCP2.6 the increase of potential yield during the same period will be statistically not significant. The yield gap under RCP2.6 and RCP4.5 will fluctuate within a rather narrow range and under RCP8.5, it will decrease.

Screening of chemical composition and risk index of different origin composts produced in Lithuania

The application of composts could be accompanied by potential hazards to soil and humans, caused by heavy metals and organic persistent pollutants. A total of 115 compost samples from four different origins (green waste composts, sewage sludge composts, mixed municipal waste composts after mechanical-biological treatment and mixed municipal waste compost) were collected to analyse the chemical composition, nutrients levels, seven heavy metals, 15 polycyclic aromatic hydrocarbons (PAHs) and seven polychlorobiphenyls (PCBs). Simulation models were used to estimate the heavy metal accumulation risk in soil and to evaluate the potential ecological risk to environment. After analysing chemical parameters of compost quality, it was found that sewage sludge composts contained the highest amounts of nitrogen (2.98%), phosphorus (4.44%) and organic matter (47.6%), and the highest potassium content (1.20%) was found in mixed municipal composts after mechanical-biological treatment. After having tested all the composts, green waste composts had the lowest content of the following nutrients: nitrogen, phosphorus, potassium and sulphur. High molecular weight PAHs dominated in green waste, sewage sludge and mixed municipal waste composts, and the opposite tendency was observed on mixed municipal waste composts after mechanical-biological treatment; low molecular weight PAHs were abundant. It was determined that, according to the total amount of 15 PAHs (16.54 mg kg^-1 d.w.) and 7 PCBs (233.53 μg kg^-1 d.w.), the most contaminated composts were produced from mixed municipal waste. As it was expected, the lowest level of PCBs (13.85 μg kg^-1 d.w.) was found in green waste composts. Monte Carlo simulations showed that the shortest period in which zinc concentration in soil could increase twice is 2 years when applying continuously mixed municipal waste compost after mechanical-biological treatment. Based on Monte Carlo simulation results from repeated application of green waste composts, mixed municipal waste compost and mixed municipal waste compost after mechanical-biological treatment could double the soil background level of copper in 6 and 3 years respectively. Reducing the content of heavy metals in composts would be of great significance for minimising the damage caused by them.