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There is increasing interest in how the application of biochar to soils influences nutrient transformations in agricultural, forest, and reclamation settings.

Rice flour and rice starch were single‐screw extruded and selected product properties were determined. Neural network (NN) models were developed for prediction of individual product properties, which performed better than the regression models. Multiple input and multiple output (MIMO) models were developed to simultaneously predict five product properties or three product properties from three input parameters; they were extremely efficient in predictions with values of R 2 > 0.95. All models were feedforward backpropagation NN with three‐layered networks with logistic activation function for the hidden layer and the output layers. Also, model parameters were very similar except for the number of neurons in the hidden layer. MIMO models for predicting product properties from three input parameters had the same architecture and parameters for both rice starch and rice flour.

Proteins play a crucial role in many soil processes, however, standardised methods to extract soluble protein from soil are lacking. The aim of this study was to compare the ability of different extractants to quantify the recovery of soluble proteins from three soil types (Cambisol, Ferralsol and Histosol) with contrasting clay and organic matter contents. Known amounts of plant-derived 14C-labelled soluble proteins were incubated with soil and then extracted with solutions of contrasting pH, concentration and polarity. Protein recovery proved highly solvent and soil dependent (Histosol > Cambisol > Ferralsol) and no single extractant was capable of complete protein recovery. In comparison to deionised water (10-60% of the total protein recovered), maximal recovery was observed with NaOH (0.1 M; 61-80%) and Na-pyrophosphate (0.05 M, pH 7.0; 45-75% recovery). We conclude that the dependence of protein recovery on both extractant and soil type prevents direct comparison of studies using different recovery methods, particularly if no extraction controls are used. We present recommendations for a standard protein extraction protocol.

The priming effect, i.e., the changes in soil organic matter (SOM) decomposition following fresh organic carbon (C) inputs is known to influence C storage in terrestrial ecosystems. Microplastics (particle size <5 mm) are ubiquitous in soils due to the increasing use and often inadequate end-of-life management of plastics. Conventional polyethylene and bio-degradable (PHBV) plastics contain large amounts of C within their molecular structure, which can be assimilated by microorganisms. However, the extent and direction of the potential priming effect induced by microplastics is unclear. As such, we added 14C-labeled glucose to investigate how background polyethylene and PHBV microplastics (1 %, w/w) affect SOM decomposition and its potential microbial mechanisms in a short-term. The cumulative CO2 emission in soil contaminated with PHBV was 42–53 % higher than under Polyethylene contaminated soil after 60-day incubation. Addition of glucose increased SOM decomposition and induced a positive priming effect, as a consequence, caused a negative net soil C balance (−59 to −132 μg C g−1 soil) regardless of microplastic types. K-strategists dominated in the PHBV-contaminated soils and induced 72 % higher positive priming effects as compared to Polyethylene-contaminated soils (160 vs. 92 μg C g−1 soil). This was attributed to the enhanced decomposition of recalcitrant SOM to acquire nitrogen. The stronger priming effect associated in PHBVs can be attributed to cooperative decomposition among fungi and bacteria, which metabolize more recalcitrant C in PHBV. Moreover, comparatively higher calorespirometric ratios, lower substrate use efficiency, and larger enzyme activity but shorter turnover time of enzymes indicated that soil contaminated with PHBV release more energy, and have a more efficient microbial catabolism and are more efficient in SOM decomposition and nutrient resource uptake. Overall, microplastics, (especially bio-degradable microplastics) can alter biogeochemical cycles with significant negative consequences for C sequestration via increasing SOM decomposition in agricultural soils and for regional and global C budgets.

In southern China, co-incorporating winter green manure and rice straw has proven to be a practical and economically viable strategy that enhances soil carbon (C) sequestration and agricultural productivity in rice paddies. However, the issue of how to control the greenhouse gas (GHG) emissions in paddy fields owing to the incorporation of substantial organic matter remains a bottleneck. A 2-year field experiment was conducted, which included five treatments: conventional water management with no residue (CK) and with co-incorporation of green manure and rice straw (GM+Rs), delayed flooding by 5, 10, and 15 days after the co-incorporation of green manure and rice straw (GM+Rs-DW5, GM+Rs-DW10, and GM+Rs-DW15) before transplanting rice seedlings. The delayed flooding treatments reduced the 2-year average CH4 emissions by 40.9%–60.8% compared with GM+Rs. The delayed flooding inhibited the growth of methanogens and CH4 emissions, which was linked to a reduction of dissolved organic carbon (DOC) concentration in surface water. The lowest C footprint (4.05 t CO2-eq ha−1) as well as the yield-scaled C footprint (0.6 kg CO2-eq kg−1) were observed in the GM+Rs-DW10 treatment, both even lower than those in CK (15.11 t CO2-eq ha − 1 and 2.1 kg CO2-eq kg−1). Moreover, the GM+Rs-DW10 treatment led to an increase in net ecosystem economic benefit (NEEB) of 3750 and 2870 CNY ha−1 than CK and GM+Rs over a 2-year period. Collectively, delayed flooding with green manure and rice straw incorporation is conducive to achieving high NEEB and low risk of GHG emissions. This finding provides important and novel insights for eco-efficient rice production.

Conventional and bio-organic fertilizers play an important role in maintaining soil health and promoting crop growth. However, the effect of organic fertilizers on the prevalence of antibiotic resistance genes (ARGs) in the vegetable cropping system has been largely overlooked. In this study, we investigated the impacts of soil properties and biotic factors on ARG profiles by analyzing ARG and bacterial communities in vegetable copping soils with a long-term history of manure and bio-organic fertilizer application. The ARG abundance in the soil was significantly increased by 116% with manure application compared to synthetic NPK fertilizer application. This finding was corroborated by our meta-analysis that the longer the duration of manure application, the greater the response of increased soil ARG abundance. However, bio-organic fertilizers containing Trichoderma spp. Significantly reduced ARG contamination by 31% compared to manure application. About half of the ARG variation was explained by changes in bacterial abundance and structure, followed by soil properties. The mitigation of ARG by Trichoderma spp. Is achieved by altering the structure of the bacterial community and weakening the close association between bacteria and ARG prevalence. Taken together, these findings shed light on the contribution of bio-organic fertilizers in mitigating ARG contamination in agricultural soils, which can help manage the ecological risk posed by ARG inputs associated with manure application.

[1] Proteinaceous and peptidic nitrogen is a potential direct nutrient source for both plants and microbes in the soil, without prior degradation to amino acids and mineralization. We used a series of five sites along an elevation gradient from 15 m a.s.l. to 710 m a.s.l. along which primary productivity decreases to investigate peptide utilization rates by soil microbes. Using 14C-labeled L-alanine, L-dialanine, and L-trialanine in a series of incubation experiments, we show that peptides are directly and rapidly assimilated by soil microbes, and that they are utilized for both biomass production and respiration. Alanine, dialanine, and trialanine were mineralized rapidly by soil microbes from the five sites along the gradient. Across all five sites, dialanine and trialanine were mineralized faster than alanine. In competition experiments, a 100-fold excess of alanine had no effect on the rate of trialanine mineralization in four of the five sites, and the same excess of trialanine had no effect on alanine mineralization. This is indicative of uptake of the intact peptide by the soil microbial community. Our findings have implications for understanding terrestrial nitrogen cycling because they point to a short-circuit whereby large peptides and proteins need only be extracellularly cleaved to short chain length peptides before direct assimilation by microbes.

The impact of soil parent material on soil chemical conditions, needle composition and tree growth

Microplastic pollution seriously affects global agroecosystems, strongly influencing soil processes and crop growth. Microplastics impact could be size-dependent, yet relevant field experiments are scarce. We conducted a field experiment in a soil-maize agroecosystem to assess interactions between microplastic types and sizes. Microplastics were added to soils used for maize cultivation: either polyethylene or polystyrene, of 75, 150, or 300 µm size. Overall, we found that microplastic contamination led to increased soil carbon, nitrogen and biogeochemical cycling. Polyethylene contamination was generally more detrimental than polystyrene. Smallest polyethylene microplastics (75 µm) were associated with two-fold raised CO2 and N2O emissions – hypothetically via raised microbial metabolic rates. Increased net greenhouse gases emissions were calculated to raise soil global warming potential of soils. We infer that MPs-associated emissions arose from altered soil processes. Polyethylene of 75 µm size caused the greatest reduction in soil carbon and nitrogen pools (1–1.5 %), with lesser impacts of larger microplastics. These smallest polyethylene microplastics caused the greatest declines in maize productivity (∼ 2-fold), but had no significant impact on harvest index. Scanning electron microscopy indicated that microplastics were taken up by the roots of maize plants, then also translocated to stems and leaves. These results raise serious concerns for the impact of microplastics pollution on future soil bio-geochemical cycling, food security and climate change. As microplastics will progressively degrade to smaller sizes, the environmental and agricultural impacts of current microplastics contamination of soils could increase over time; exacerbating potential planetary boundary threats.

We construct a Bayesian estimator for the dilution of a wastewater sample. When wastewater is diluted by rainwater an estimate of the level of dilution is required if we are to normalise sample measurements of disease markers such as SARS-CoV-2 RNA. We consider the situation where flow measurements are available, but will regularly be unreliable because of the action of combined sewer outflows (CSOs) and wastewater storage tanks, which divert wastewater away from treatment plants when the flow is excessive. However, we also have proxies for the flow from various chemical markers (e.g.\ phosphate, ammonium, electrical conductivity), whose level per unit of population is fixed. The new flow estimator has multiple advantages compared to existing procedures: credible intervals for the estimates; optimal weighting of the chemical markers; systematic handling of missing and censored values; and model based smoothing without lags.

The frequency and intensity of extreme weather events (e.g. flood, drought) are predicted to increase for the foreseeable future and it is expected that these will negatively impact upon agroecosystem functioning. Our understanding of how grassland ecosystems respond to extreme weather events occurring at different times of the year, however, is lacking. To better understand the seasonal response of grassland to flooding, we subjected an agricultural grassland to an 8-week extreme flood event at three different temperatures (5 °C-winter, 15 °C-spring/autumn and 25°C-summer) and then followed its subsequent recovery for 9 weeks after floodwater removal. We focused on key indicators of ecosystem functioning including primary production, nutrient cycling, greenhouse gas (GHG) emissions, ammonia (NH3) volatilization, and soil microbial communities. The experiment used intact soil mesocosms (1 kg) with indigenous vegetation collected from a grassland with no previous history of flooding. Flooding reduced biomass production by 18% at 5 °C, 50% at 15 °C and 95% at 25 °C. Flooding also significantly disrupted elemental cycling (nitrogen, phosphorus and carbon) as evidenced by an increased release of P, Fe and NH4 + into the soil and overlying floodwater and large amounts of CH4 and NH3 released to the atmosphere (mainly during the flooding). These effects were more pronounced at higher temperatures (e.g. 45–700 kg CH4 C ha−1 and 1–5 kg NH3 N ha−1 at 15 and 25 °C, respectively). In addition, after floodwater removal this NH4 + was rapidly nitrified leading to large losses of N2O (1.0–14.2 kg N2ON ha−1 at 5–25 °C, respectively). Especially at higher temperatures, flooding resulted in a reduction in soil microbial biomass (more than 58% of the equivalent unflooded treatment at 25 °C) and changes in microbial community structure (assessed by PLFAs). Further, some of these changes persisted after flood removal including a loss of actinomycetes, arbuscular mycorrhizal fungi and fungi. Overall, we conclude that ecosystem responses to extreme weather events are critically dependent on temperature with those occurring at higher temperatures having a greater negative impact than those at the lowest temperature (5 °C). The large potential release of CH4 and N2O also suggests that flood events should be considered as a potential source of GHGs when comparing top-down and bottom-up calculations of national inventories, and that further work is needed to better refine GHG emission estimates for these events.