Support Crop Production Research Articles

Improved nitrogen fertilizer management reduces nitrous oxide emissions in a northern Prairie cropland.

Arable croplands are a significant source of nitrous oxide (N2O) emissions, largely due to nitrogen (N) fertilizer applications to support crop production. Nevertheless, there is limited research on the N2O dynamics from canola-wheat rotations in the semi-arid northern Prairies, an important agricultural region. Here, we present micrometeorological N2O fluxes measured from January 2021 to April 2024 in Saskatchewan, Canada, to evaluate the impact of N fertilizer management on the year-round N2O emissions from a canola-wheat rotation. A combination of two 4R (Right Source, Right Rate, Right Time, Right Place) N management practices - a reduced N rate and an enhanced efficiency N fertilizer source - was compared to common fertilizer management practices for the region. Two periods at high risk for N2O flux events were identified, after N fertilizer applications and the following spring thaw, with the magnitude of emissions varying over the multi-year period. As for cumulative emissions, the growing season (GS) N2O emissions were 50 % of annual emissions, presenting an opportunity to mitigate N2O emissions through improved N fertilizer management. Indeed, the improved 4R N management reduced N2O emissions by 57 % over the entire study period without impacting yields. The reduction in GS N2O emissions resulted from the 4R N management lowering mean N2O flux at times of high WFPS (>50 %). The non-growing season (NGS) N2O accounted for 11-67 % of annual emissions. Fall soil nitrate levels were a strong explanatory variable of NGS emissions (r2 = 0.69, r2 = 0.39), but the rate of change and magnitude of NGS emissions depended on thawing conditions - lower for drier thaws, higher for wetter thaws. Ultimately, better N fertilizer management reduces cumulative N2O emissions from cropping systems when practiced for several years.

Microalgae-Based Crop Support Technologies Show Multifaceted Promise Well-Suited to Looming Threats

This review summarises the available evidence on the prospects for using microalgae or their extracts to support crop production. The evidence is limited but suggests technological promise in several distinct ways, namely, higher core productivity, enhanced resilience to biotic and abiotic stresses, and better-quality produce. The different efficacy pathways of these microalgal technologies were examined to assess their scope to help address key farmer priorities. Their scope to help farmers face climate change and land degradation was a particular focus, given the magnitude of these threats. These microalgal technologies are framed in terms of their pertinence to farmer priorities due to the centrality of farmers to food systems. Notably, farmers’ technology adoption decisions are key to food system outcomes. The findings reported suggest that these crop support technologies could potentially deliver major benefits to farmers, consumers, and the environment. For the moment, however, this emerging literature remains largely neglected. Possible reasons for this are considered, as are potential ways forward. The review focuses particularly on the two most researched and widely available microalgae, the genera Arthrospira and Chlorella, in the interest of highlighting options farmers could adopt rapidly while research on the wider body of microalgae-based crop technologies continues.

Mitigation of Nitrogen Losses in a Plant-Soil System through Incorporation of Nanocellulose and Zinc-Modified Nanocellulose.

Most nitrogen (N) applied to plants as fertilizer is lost through leaching. Here, nanocellulose was used in mitigating N leaching loss. Lettuce-cropped soil was treated with unmodified or Zn-modified nanocellulose (1-2% by wt) in combination with NPK, compared with urea and NPK-only treatments. Consecutive leaching, plant growth, plant N uptake, and soil nitrogen retention were assessed. Nanocellulose + NPK significantly (p ≤ 0.05) reduced N leaching, compared with urea and NPK-only. 1-and-2 wt % nanocellulose, as well as Zn-modified 1-and-2 wt % nanocellulose, reduced N leaching by 45, 38, 39, and 49% compared with urea and by 43, 36, 37, and 47% compared with NPK-only, respectively. Nitrogen leached mainly as NO3- (98.4%). Compared with urea and NPK, lettuce shoot mass was significantly (p ≤ 0.05) increased by 30-42% and by 44-57%, respectively, by all nanocellulose treatments, except for the Zn-modified 1 wt % nanocellulose. Leached N negatively correlated to biomass yield. Soil N retention was enhanced by the pristine and Zn-modified nanocelluloses between 27 and 94%. Demonstrably, nanocellulose can be utilized for mitigating N loss in soil and supporting crop production, resource management, and environmental sustainability.

Reference soil groups map of Ethiopia based on legacy data and machine learning-technique: EthioSoilGrids 1.0

Abstract. Up-to-date digital soil resource information and its comprehensive understanding are crucial to supporting crop production and sustainable agricultural development. Generating such information through conventional approaches consumes time and resources, and is difficult for developing countries. In Ethiopia, the soil resource map that was in use is qualitative, dated (since 1984), and small scaled (1 : 2 M), which limit its practical applicability. Yet, a large legacy soil profile dataset accumulated over time and the emerging machine-learning modeling approaches can help in generating a high-quality quantitative digital soil map that can provide better soil information. Thus, a group of researchers formed a Coalition of the Willing for soil and agronomy data-sharing and collated about 20 000 soil profile data and stored them in a central database. The data were cleaned and harmonized using the latest soil profile data template and 14 681 profile data were prepared for modeling. Random forest was used to develop a continuous quantitative digital map of 18 World Reference Base (WRB) soil groups at 250 m resolution by integrating environmental covariates representing major soil-forming factors. The map was validated by experts through a rigorous process involving senior soil specialists or pedologists checking the map based on purposely selected district-level geographic windows across Ethiopia. The map is expected to be of tremendous value for soil management and other land-based development planning, given its improved spatial resolution and quantitative digital representation.

Ensifer adhaerens strain OV14 seed application enhances Triticum aestivum L. and Brassica napus L. development

Given the challenges imposed by climate change and societal challenges, the European Union established ambitious goals as part of its Farm to Fork (F2F) strategy. Focussed on accelerating the transition to systems of sustainable food production, processing and consumption, a key element of F2F is to reduce the use of fertilisers by at least 20% and plant protection products by up to 50% by 2030. In recent years, a substantial body of research has highlighted the potential impact of microbial-based applications to support crop production practices through both biotic/abiotic stresses via maintaining or even improving yields and reducing reliance on intensive chemical inputs. Here, we have characterised the ability of a new soil-borne free-living bacterium strain Ensifer adhaerens OV14 (EaOV14) to significantly enhance crop vigour index by up to 50% for monocot (wheat, Triticum aestivum L., p < 0.0001) and by up to 40% for dicot (oilseed rape, Brassica napus L., p < 0.0001) species under in-vitro conditions (n = 360 seedlings/treatment). The beneficial effect was further studied under controlled glasshouse growing conditions (n = 60 plants/treatment) where EaOV14 induced significantly increased seed yield of spring oilseed rape compared to the controls (p < 0.0001). Moreover, using bespoke rhizoboxes, enhanced root architecture (density, roots orientation, roots thickness etc.) was observed for spring oilseed rape and winter wheat, with the median number of roots 55% and 33% higher for oilseed rape and wheat respectively, following EaOV14 seed treatment compared to the control. In addition, EaOV14 treatment increased root tip formation and root volume, suggesting the formation of a more robust root system architecture post-seed treatment. However, like other microbial formulations, the trade-offs associated with field translation, such as loss or limited functionality due to inoculum formulation or environmental distress, need further investigation. Moreover, the delivery method requires further optimisation to identify the optimal inoculum formulation that will maximise the expected beneficial impact on yield under field growing conditions.

Armed conflicts and household food insecurity: Effects and mechanisms

AbstractDespite extensive studies on the effects of armed conflict on household dietary diversity, food security, and nutritional outcomes, the underlying pathways remain underexplored. A better understanding of these mechanisms could unpack the subsequent effects of conflict‐induced food insecurity and oft‐reported nutritional shortcoming, as well as identify which policy interventions hold promise. We study the effects of terrorist violence in Burkina Faso on household dietary diversity, as proxied by food consumption scores (FCS), and investigate the underlying mechanisms. For this purpose, we combine nationally representative 5‐years panel data on households with spatial conflict data. We find negative and significant effects of conflict intensity on household food consumption scores. The decline in household FCS is a result of significant decreased dietary diversity in both food production and purchases. Although households in rural areas partially offset these reductions by food assistance, those reliant solely on farming as livelihoods remain the most affected. Further investigations show evidence that per‐capita farm income and food expenditure are pathways linking the intensity of armed conflict to reduced FCS in food purchases, whereas reduced dietary diversity in food production results from decline in crop production. Additional specification tests support our main findings, offering insights that can help policymakers faced with similar scaled‐armed conflicts. For instance, conflict‐sensitive interventions aimed at supporting crop production and farm income for affected households could effectively improve their dietary diversity and overall food security in a post‐conflict environment.

Evaluation of land use impact on soil quality in Samaru College of Agriculture, Northern Guinea Savanna, Nigeria

Abstract Land use changes influence soil quality, which is of fundamental importance in sustainable crop production and environmental management. This study evaluated land use impact on soil quality at Samaru College of Agriculture farm, Ahmadu Bello University, Zaria, Nigeria. The land use types were Tomato/Pepper, Grapevine/Fluted pumpkin, Mango/Orange, and Guava/Mango. A profile pit was dug in each land unit. Soil samples were collected from genetic horizons, prepared, and analysed in the laboratory using standard methods. Sand, silt, and clay differed significantly (p &lt; 0.05) among the land uses. The soil texture varied from clay loam to clay. Bulk density (BD) was significantly (p &lt; 0.05) higher under Mango/Orange and Guava/Mango than other land use types. The soil reaction (pH) ranged from 5.0 to 5.8 and was strongly to moderately acidic. Soil organic carbon was low (&lt; 10 g/kg), total nitrogen values of 0.19 – 0.24 g/kg were low, and available phosphorus values of 1.8 – 27.4 mg/kg were rated low to high across the land use types. Soils under the Grapevine/Fluted pumpkin land use type were significantly higher in organic carbon, exchangeable potassium, sodium, and effective cation exchange capacity than the other land use types. Soil quality under Grapevine/Fluted pumpkin was rated best (80 %), whereas soil quality under Tomato/Pepper land use type was the worst (40 %). The soils were low-to-high in quality and had a higher potential to support crop production if management practices that encourage the build-up of nutrients in the soil system were adopted. The application of manure, liming materials, and phosphorus-based fertilisers is advocated.

Effects of landscape simplicity on crop yield: A reanalysis of a global database.

Ecological theory on diversity suggests that agriculture requires sufficient biodiversity, ecological function, and critical ecosystem services to remain sustainable and resilient. As such, research related to the effect of ecosystem services and diversity on crop yields has increased significantly in the past decade. One such study by Dainese and colleagues that presented a global synthesis of a compiled database of 1,475 crop experiments related to pollination and pest control ecosystem services and crop yields quickly garnered attention in the literature with more than 540 citations since its publication in 2019. Given the strong influence of this study on the research on diversity and agricultural production, we conduct a reanalysis on the publicly available dataset from the global synthesis study to test the robustness of findings to modeling approach and assumptions. In our reanalysis we apply ordinary least squares regression methods rather than Bayesian path analysis to the same data to examine the robustness of observed field-scale landscape diversity-ecosystem services-crop yield relationships. The result of our reanalysis supports the findings of Dainese and colleagues, illustrating the robustness of findings that suggest that increasing landscape simplicity is associated with lower rates of pollination and pest control ecosystem service provisioning and lower crop yields. However, our analyses also suggest that provisioning of pollination and pest control services account for only a small fraction of the total effect of landscape simplicity on crop yields. Furthermore, we find that management and soil health may mediate the effects of landscape simplicity on ecosystem services and crop yields. While our results complement previous findings for landscape simplicity and ecosystem services, they also indicate that above and below ground ecosystem services are not mutually exclusive but concurrently contribute to support crop production in agriculture.

Evaluating main drivers of terrestrial water storage depletion in the agro-pastoral ecotone of northern China

With the heightened threat of declining terrestrial groundwater, determining the effects of changing environments on terrestrial water storage anomaly (TWSA) is essential for water resource management. As a critical element of the water cycle, the multi-effects of the natural and artificial factors on TWSA were still not fully understood and quantified. Using multiple high-resolution data products and the structural equation model (SEM), this study discussed how climate, vegetation, and human activities affected terrestrial water storage (TWS) in the West Liao River basin (WLRB), China, from 1990 to 2020. The results confirmed that vegetation showed a greening trend while TWS depleted at 5.93 cm/10a in the WLRB. TWS in greening areas has a negative correlation with vegetation growth. The decline in TWS is mainly dominated by precipitation and runoff variability. By influencing eco-hydrological cycle processes, climate change and human activities affect TWS through direct and indirect(by influencing NDVI) pathways. Land use change, manifested as conversion of grassland into cropland, contributed to the most decline of TWS (51.2 %). Moreover, the crop yield increasing, climate warming, and vegetation greening could lead to TWS depletion. Spatially, the overexploitation of the groundwater for irrigation to support crop production was probably the most critical cause of TWS depletion over upstream of the WLRB. Furthermore, in the West Liao Plain, the intensified vegetation greenness also led to the increasing ecosystem water demand, resulting in the decrease of TWS. This study improves our understanding of the interaction of the basinal eco-hydrological system and provides a hint that reducing groundwater extraction and implementing agriculture fallow is essential to recovering water storage and alleviating the water resource crisis in the agro-pastoral ecotone.

Plant growth‐promoting rhizobacteria mediate soil hydro‐physical properties: An investigation with Bacillus subtilis and its mutants

AbstractPlant growth‐promoting rhizobacteria and other soil bacteria have the potential to improve soil hydro‐physical properties and processes through the production of extracellular polymeric substances (EPS). However, the mechanisms by which EPS mediates changes in soil properties and processes remain incompletely understood, partly due to variations in EPS composition produced under different environmental conditions. In this study, we investigated the influence of different bacterial traits on intrinsic soil properties and processes of evaporation and infiltration using sand treated with the wild‐type Bacillus subtilis variant (UD1022) and its two mutant variants, – and srf. The – mutant suppresses EPS production through alterations in the eps and tasA genes, while the srf mutant lacks the gene for surfactin production. Experimental results confirmed that the solution viscosity of the – mutant was the lowest and the solution surface tension of the srf mutant was the highest among the three tested bacteria strains. The distinct intrinsic properties of EPS produced by these bacterial strains resulted in varied hydro‐physical responses in the treated sand. Key influences included modifications in wettability, hydraulic decoupling (or mixed wettability), and aggregation, which collectively led to reduced evaporation rates and heterogeneous water distribution during infiltration in the bacteria‐treated sands. Our findings advance the understanding of the role bacterial EPS play in vadose zone hydrology and offer insights for the development of sustainable strategies for increasing water retention, supporting crop production in arid regions, and facilitating land restoration.

A new interval meta-goal programming for sustainable planning of agricultural water-land use nexus

Meta-Goal Programming (MGP) is a simultaneous cognitive evaluation of the degree of achievements for original decision goals considered in a GP model. However, in most real-world situations, environmental coefficients and related parameters are not easily available. In such a situation, the decision-maker must consider various conflicting targets in a framework of uncertain aspiration levels at the same time. On the other side, Interval Programming (IP) is a method used to increase the range of available decision-maker preference structures in GP. In the perspective of solving the conflicts between agriculture and water use towards sustainability, this paper proposes an Interval Meta-Goal Programming Model (IMGPM) dealing with imprecision in data that covers interval coefficients, target intervals, and interval bounds of meta-goals. This novel methodology has been tested in a study area in Iran to validate its added value in solving conflicting uses of natural resources by economic sectors. This integration together with its application for sustainable optimal cropping patterns (agroecosystem planning) represents a novelty in the field of ecological modeling. The management solutions of our method in terms of land allocation are different from those in Sen and Pal (2013) model. In the case of Iran, many socio-ecological-economic strategies and policies should be necessary for improving the agricultural sector. More specifically, on the basis of rainfall amounts and spatial patterns, this approach can represent a decision-support system able to define strategies for additional water storage useful to support crop production. Furthermore, the availability of water together with the sustainable use of fertilizers can mitigate the risk of land degradation, guaranteeing people employment, food security, and economic profits. Although the present methodology seems to solve the problem of multi-goals decision-making, the inclusion of spatial relationships is able to introduce dependencies between the management of land use in adjacent areas, making the present approach nearer to real-world functioning.

Land use changes associated with declining honey bee health across temperate North America

Urbanization and agricultural intensification continue to reshape landscapes, altering the habitat available to wildlife and threatening species of both economic and conservation concern. The honey bee, Apis mellifera, is a pollinator of economic importance to North American agriculture yet managed colonies are burdened by poor health and high annual mortality. Understanding the factors influencing this species is critical for improving colony health and supporting crop production. We used a nationwide cohort of 638 managed Canadian colonies to study the dominant drivers of colony health and overwintering mortality. We found that fall colony weight—a major predictor of overwintering survival—was strongly associated with landscape composition. Among four broadly defined land cover types, we discovered that urban and forested land covers were the least valuable sources of habitat for colonies, as inferred from fall colony weight measurements. Agricultural land appeared to provide habitat quality of slightly greater value, while herbaceous land cover was most strongly positively associated with fall colony weight. Herbaceous land cover also exhibited an associational effect size which was strongly statistically distinguishable from those of urban and forested land. Our research indicates that recent and ongoing land-use changes exacerbate modern apicultural challenges, and suggests variation in nutrition or floral resource availability plays a major role in modulating honey bee health. Our work highlights the need for additional research investigating whether land use change-associated alterations in floral resource availability increase the potential for resource competition between pollinator species.

Contrasting patterns and drivers of soil micronutrient availability in paddy and maize fields of eastern China

Micronutrient deficiencies, known as ‘hidden hunger’, harm the growth and development of plants and people alike. However, less attention has been paid to soil micronutrients, the main source of micronutrients for plants and humans, than macronutrients (e.g. N and P availability). Understanding the geographic distribution of soil micronutrients across different agricultural fields is critical to support crop production and quality. Here we investigated the micronutrient composition (total and available copper, iron, manganese and zinc) of parallel 114 maize and rice fields in major crop production regions of eastern China. We found that available iron, copper and manganese were significantly higher in paddy soils than in maize soils, and total zinc was significantly higher in maize soils than in paddy soils. There was geospatial variation in the composition of micronutrients across latitudinal gradients and crop types. Soil organic matter and pH drove geographic variation of available micronutrient concentrations and ratio of total to available micronutrient, which were specific to micronutrient and crop type. Available Fe was decoupled with environment and total metal in paddy fields. Our study sheds light on the distribution patterns and environmental drivers of soil micronutrients in eastern China, and provides theoretical guidance for agricultural practice and fertilization management.

Wheat leaf traits monitoring based on machine learning algorithms and high-resolution satellite imagery

The leaf, which is a crucial indicator for evaluating crop status, plays an important role in plants' functions. Determining and monitoring leaf parameters can facilitate the detection and estimation of crop yield, which is essential for food security. Crop monitoring by remote sensing technology is critical to support crop production, especially over large scales. In this study, we developed a methodology to estimate leaf parameters based entirely on vegetation indices (VIs) from remotely sensed imagery in wheat under different management practices. Therefore, the current study aimed to examine the utility of VIs calculated from the sentinel-2 data in estimating the Leaf area index (LAI) and leaf parameters at wheat farms using machine learning algorithms. Leaf parameters included leaf dry weight (LDW), specific leaf area (SLA) and leaf specific weight (SLW), and machine learning algorithms were SVM (support vector machine), ANN (artificial neural network) and DNN (deep neural network). Leaf parameters were measured at several developmental stages of wheat in two contrasting environments in the southern Iran. The results demonstrated that the DNN algorithm could efficiently predict leaf parameters in the southern Iran with an overall precision of >72%, which assessed the potential of employing DNN to achieve the temporal and spatial distribution data of wheat based on the Sentinel-2 imagery. The validation of the DNN model generally showed high accuracy (R = 0.80, RMSE = 1.19, and MAE = 0.98) between observed and estimated LAI values when this model was used. NDVI was also highly sensitive to wheat LDW and SLA parameters, with a good correlation between field measurements and those predicted by the DNN model from sentinel-2 imagery, with the R values of 0.66 and 0.85, respectively. Further, NDVI and PVI (Perpendicular Vegetation Index) were linearly correlated with SLW across both temporal and spatial scales (R = 0.79). Among VIs considered from sentinel-2 imagery to predict wheat leaf parameters, NDVI was more sensitive than other VIs. This research, thus, indicated that using sentinel-2 data within a DNN model could provide a comparatively precise and robust prediction of leaf parameters and yield valuable insights into crop management with high temporal and spatial accuracy.

Development of Decision Support System (DSS) for Greenhouse Ventilation and Cooling Control

The confined heat created by the sunlight and ambient temperature is one of the obstacles to greenhouses in the tropics. A conservatory in tropical regions thus requires a proper ventilation and cooling system to provide an ideal greenhouse temperature to support crop production. The main objective of this study is to develop a Decision Support System (DSS) for optimum greenhouse ventilation and cooling control. An equation model to predict the temperature inside was developed by considering heat generation and heat loss inside the greenhouse. The accuracy of the equation model was validated with secondary data from the on-field greenhouse by statistical evaluation metrics. The statistical evaluation proved that the equation model is good with 2.11°C of Root Mean Square Error (RMSE), 6.22% of Percent BIAS (PBIAS) and 0.94 of Nash-Sutcliffe efficiency (NSE) value. A DSS using Microsoft Excel with Visual Basic for Applications (VBA) is developed based on the equation model to provide the ventilation and cooling system information. Input required for the DSS is a climatic condition, dimension and covering greenhouse material. The output of the DSS is the temperature inside the greenhouse, natural ventilation design, forced ventilation, active cooling system design using an evaporative pad and fan, and fogging system. The DSS can be used as an approach for ventilation and cooling design recommendation for the optimum temperature inside the greenhouse.

Onion (Allium cepa L.) Performance as Influenced by Manure and Fertilizer in Titanium Mined Soils

Mining is an important economic activity that promotes income generation, job creation, and industrialization globally. In spite its economic importance, it is classified as land degradation form that disrupts natural ecosystem through loss of biota and soil health. Paucity of information regarding the performance of reclaimed mined soils in supporting crop production abound in Kenya. To contribute to this knowledge gap, a study was conducted at Base titanium limited -Kwale to investigate the response of performance of bulb onions (red creole onion variety) to farmyard manure and inorganic fertilizer application on post mined soils. The experiment was laid out in a Randomized Complete Block Design (RCBD) with three replicates Treatments included: inorganic fertilizer, farmyard manure, inorganic fertilizer +farmyard manure and control. Obtained data that included: soil characterization, onion growth and yield parameters was subjected to analysis of variance (ANOVA) using R packages and means separated using the Fisher&amp;rsquo;s protected least significant difference (LSD) at (P&amp;le;0.05). Results showed that the soils had low TN, exchangeable P, K, S, Bo and Cu levels. Manure+ fertilizer significantly (P&amp;le;0.05) increased plant height by 38%, bulb diameter by 44%, neck thickness by 19.5% total bulb yield by 89% and marketable yield by 88% compared to control. A significant positive relationship between manure, fertilizer, fertilizer+ manure with plant height, number of leaves, bulb diameter, neck thickness and total yield was observed indicating that manure + fertilizer can support optimal onion production in these post mined soils. Further research is however, required to ascertain production approaches that promote sustainable soil development and onion yield.

Smart Irrigation Technique Using IOT

Abstract: Agriculture plays an imperative role in the country’s development. In our country, more than 72% of people depend upon farming which is one third of the population invests in farming. Thus, the challenges and issues concerning agriculture need to be focused to hinder the country development. The only recommended solution to this issue is modernizing agriculture using smart technologies. In agriculture, irrigation is one of the processes which support crop production by supplying needed water to the soil. A Sensor-based automated irrigation system provides a promising solution to manage agricultural activity. This research article provides a vast study on the irrigation system in smart agriculture. Keywords: Smart Agriculture, Smart Irrigation, Internet of Things, Sensors, Water Management, ESP32, Automation.

Towards integrated pest and pollinator management in tropical crops.

Biotic pollination and pest control are two critical insect-mediated ecosystem services that support crop production. Although management of both services is usually treated separately, the new paradigm of Integrated Pest and Pollinator Management (IPPM) suggests synergetic benefits by considering them together. We reviewed the management practices in two major tropical perennial crops: cocoa and coffee, to assess IPPM applications under the tropics. We found potential synergies and antagonisms among crop pest and pollination management, however, very few studies considered these interactions. Interestingly, we also found management practices focusing mainly on a single service mediated by insects although species can show multiple ecological functions as pests, natural enemies, or pollinators. The tropics represent a promising area for the implementation of IPPM and future research should address this concept to move towards a more sustainable agriculture.

Macroplastic Fragment Contamination of Agricultural Soils Supports a Distinct Microbial Hotspot

Agricultural plastics support crop production and quality by reducing weeds, improving irrigation efficiency, and regulating soil conditions, but can also become a soil pollutant. While microplastic effects on soil function are increasingly well-understood, the impacts of agricultural macroplastic (&amp;gt;5 mm) contamination on soils are poorly documented. Prolonged exposure to plastic macrofragments may alter microbial decomposer community structure and function, since plastic can directly affect edaphic factors while leaching novel compounds. To better characterize how plastic contamination influences the soil habitat, we sampled three farms characterized by agricultural plastic pollution in Monterey County, CA, United States. Using a randomized block design, we collected surface soil samples from the fields (“bulk PC soil”) to compare with soil directly in contact with the remaining polyethylene (PE) mulch and polyvinyl chloride (PVC) dripline fragments (“plastic-associated soil”). Soil directly associated with plastic fragments was hypothesized to have reduced microbial biomass and decomposer activities relative to the bulk soil, due to a greater likelihood of toxicity. In contrast to our expectations, we found that both PE and PVC macrofragments support a distinct microbial habitat that hosts a larger, more efficient microbial biomass with greater labile nutrient pools than the surrounding bulk soil. Because of the scope of macroplastic pollution likely occurring in agricultural soils, our findings suggest that this novel plastisphere habitat may significantly alter ecological functions critical to agricultural soils over time by encouraging microbial colonization within plastic debris.

Biochar mitigated more N-related global warming potential in rice season than that in wheat season: An investigation from ten-year biochar-amended rice-wheat cropping system of China

Rice–wheat cropping system (RWCS), the major rice-based cropping system, constitutes a significant source of N-related greenhouse gas (GHG) emission due to the unique wet-dry alternation process. Biochar is often highlighted as a potential solution for reducing fertilizer N losses, hence, understanding its effects on Ngr emissions (mainly NH3 and N2O) under wet-dry conditions is critical to inform strategies for GHG mitigation. This study investigated the responses of NH3 and N2O emissions to biochar amendments during rice and wheat seasons based on in situ measurements under ten-year successive straw biochar application in RWCS. Our results indicated that 43.7% and 89.9% of N2O and NH3 emissions were emitted during rice season and 56.3% and 10.1% during wheat season, respectively. Long-term biochar amendment was found to play significant role in mitigating NH3 emissions (38.6–43.9%), which could be attributed to the disappearance of liming effect of aged-biochar on flooding water and decreased NH4+ concentrations in the soil. However, considerable variation of N2O emissions were observed in RWCS. Biochar showed a significant decreasing effect on the net global warming potential related to N2O and NH3 emissions (GWPN) in rice season (16.1–89.6%), and slight increased tendency in wheat season (1.43–13.1%) primarily due to its positive effects on N2O emission. Biochar amendment mainly BC22.5, significantly increased above-ground yields by 9.22% in rice season. Thus, it is a low carbon-producing and sustainable crop management method that can support crop production, C sequestration, and GHG mitigation in rice season under RWCS from the viewpoint of the Ngr mitigation. Our results suggest that emission patterns of N2O and NH3 varied with wet-dry alternation under the disturbance of long-term biochar amendment in RWCS; moreover, long-term biochar application exhibited significant potential for mitigating soil Ngr losses in rice season for RWCS.