Abandoned farmlands are increasing due to socio-economic changes and land marginalization, and they require sustainable land management practices. Biocrusts are a common cover on the topsoil of abandoned farmlands and play an important role in improving soil stability and erosion resistance. The critical functions of biocrusts are known to mostly rely on their biofilaments and extracellular polymeric substances (EPS), but how these components act at microscopic scale is still unknown, while rheological methods are able to provide new insights into biocrust microstructural stability at particle scale. Here, bare soil and two representative types of biocrusts (cyanobacterial and moss crusts) developed on sandy (Ustipsamments) and sandy loam (Haplustepts) soils in abandoned farmlands in the northern Chinese Loess Plateau were collected at a sampling depth of 2 cm. Changes in the rheological properties of the biocrusts were analyzed with respect to their biofilament network and EPS contents to provide possible explanations. The rheological results showed that compared with bare soil, storage and loss moduli were decreased by the biocrusts on sandy soil, but they were increased by the biocrusts on sandy loam soil. Other rheological parameters tau max, gamma L, gamma YP, and Iz of biocrusts on both soils were significantly higher than those of bare soil, showing higher viscoelasticity. And the moss crusts had about 10 times higher rheological property values than the cyanobacterial crusts. Analysis from SEM images showed that the moss crusts had higher biofilament network parameters than the cyanobacterial crusts, including nodes, crosslink density, branches, branching ratio and mesh index, and biofilament density, indicating that the biofilament network structure in the moss crusts was more compact and complex in contrast to the cyanobacterial crusts. Additionally, EPS content of the moss crusts was higher than that of the cyanobacterial crusts on both soils. Overall, the crosslink density, biofilament density, and EPS content of the biocrusts were significantly and positively correlated with their gamma YP and Iz. The interaction between crosslink density and biofilament density contributed 73.2 % of gamma YP, and that between crosslink density and EPS content contributed 84.0 % of Iz. Our findings highlight the biocrusts-induced changes of abandoned farmland soil rheological properties in drylands, and the importance of biocrust biofilament network and EPS in maintaining abandoned farmland soil microstructural stability to resist soil water/wind erosion and degradation, providing a new perspective for sustainable management of abandoned farmlands.

Soil compaction caused by heavy agricultural machinery poses a significant challenge to sustainable farming by degrading soil health, reducing crop productivity, and disrupting environmental dynamics. Field traffic optimization can help abate compaction, yet conventional algorithms have mostly focused on minimizing route length while overlooking soil compaction dynamics in their cost function. This study introduces Soil2Cover, an approach that combines controlled traffic farming principles with the SoilFlex model to minimize soil compaction by optimizing machinery paths. Soil2Cover prioritizes the frequency of machinery passes over specific areas, while integrating soil mechanical properties to quantify compaction impacts. Results from tests on 1000 fields demonstrate that our approach achieves a reduction in route length of up to 4-6% while reducing the soil compaction on headlands by up to 30% in both single-crop and intercropping scenarios. The optimized routes improve crop yields whilst reducing operational costs, lowering fuel consumption and decreasing the overall environmental footprint of agricultural production. The implementation code will be released with the third version of Fields2Cover, an open-source library for the coverage path planning problem in agricultural settings.

Early water stress detection is important for water use yield and sustainability. Traditional methods using the Internet of Things (IoT), such as soil moisture sensors, usually do not provide timely alerts, causing inefficient water use and, in some cases, crop damage. This research presents an innovative early water stress detection method in lettuce plants using Thermal Infrared (TIR) and RGB images in a controlled lab setting. The proposed method integrates advanced image processing techniques, including background elimination via Hue-Saturation- Value (HSV) thresholds, wavelet denoising for thermal image enhancement, RGB-TIR fusion using Principal Component Analysis (PCA), and Gaussian Mixture Model (GMM) clustering to segment stress regions. The leaves stressed areas annotated in the RGB image through yellow pseudo-coloring. This approach is predicated on the fact that when stomata close, transpiration decreases, which causes an increase in the temperature of the affected area. Experimental results reveal that this new approach can detect water stress up to 84 h earlier than conventional soil humidity sensors. Also, a comparative analysis was conducted where key components of the proposed hybrid framework were omitted. The results show inconsistent and inaccurate stress detection when excluding wavelet denoising and PCA fusion. A comparative analysis of image processing performed on a single- board computer (SBC) and through cloud computing over 5 G showed that SBC was 8.27% faster than cloud computing over a 5 G connection. The proposed method offers a more timely and accurate identification of water stress and promises significant benefits in improving crop yield and reducing water usage in indoor farming.

The safe application of farm dairy effluent (FDE) to land has proven to be a challenge for dairy farmers and regulatory authorities throughout New Zealand. Poorly performing FDE systems can have deleterious effects on water quality because contaminants such as phosphorus, nitrogen and faecal microbes enter receiving waters with minimal attenuation by soil. We present a decision framework that supports good management of effluent, particularly during its application to land. The framework considers how FDE management can be tailored to account for soil and landscape features of a location that pose varying levels of contaminant transport risk. High risk soils and landscapes are vulnerable to direct losses via preferential and/or overland flow pathways and include sloping land (e.g. slopes greater than 7 degrees) and soils with mole drainage, coarse structure, poor natural drainage or low surface infiltration rates. Soil types that are well-drained with fine structure typically exhibit matrix flow characteristics and represent a relatively low risk of direct contaminant loss following FDE application. Our framework provides guidance on FDE application timings, rates and depths to different landform and soil types so that direct losses of contaminants to water are minimal and the opportunity for plant uptake of nutrients is enabled. Some potential limitations for using the framework include the potentially severe effects of animal treading damage during wet conditions that can reduce soil hydrological function and consequently increase the risk of overland flow of applied FDE. The spatial distribution of such treading damage should be considered in the framework's application. Another limitation is our limited understanding of the effects of soil hydrophobicity on FDE infiltration and application of the framework.

This paper discusses the challenges of installing monopile offshore wind foundations in bedrock and introduces a new hybrid-monopile design as an alternative to rock-socketed monopiles. The performance of the hybridmonopile is evaluated through 1-dimension beam-spring theory and 3-dimension Finite Element analyses, with a focus on soil-foundation interaction and cyclic loading behaviour. The hybrid-monopile design is optimized and validated at two offshore sites in Korea. It is shown that optimized design can reduce required monopile penetration to avoid rock-socketed monopiles. The hybrid-monopile design shows a positive impact on reducing lateral pile displacement and rotation, particularly in soft ground conditions. The suggested 3D FE (Finite element) design approach and optimization with an additional seabed-level support structure can reliably avoid the need for rock-socketed monopiles.

Spent mushroom substrate (SMS), a waste product from mushroom cultivation, in addition to being rich in essential nutrients for crop growth, contains actively growing mushroom mycelia and metabolites that suppress some plant pathogens and pests. SMS thus has potential for fostering the suppressiveness of soil-borne pathogens of farms. This study determined the potential of using the spent Pleurotus ostreatus substrate (SPoS) to suppress the plant-parasitic nematode Radopholus similis in bananas. R. similis is the most economically important nematode in bananas worldwide. The effect of SPoS on R. similis was assessed through two in vivo (potted plants) experiments between May 2023 and June 2024. Five-month-old East African highland banana (genome AAA) plantlets that are highly susceptible to R. similis were used. In the first experiment, the plantlets were established in 3 L pots containing (i) pre-sterilized soil, (ii) pre-sterilized soil inoculated with nematodes, (iii) pre-sterilized soil mixed with 30% (v/v) SPoS, (iv) pre-sterilized soil mixed with 30% (v/v) SPoS followed by nematode inoculation, (v) SPoS without soil, and (vi) SPoS without soil inoculated with nematodes. The SPoS was already decomposed; thus, it may or may not have contained active mycelia. The nematodes were introduced two weeks after the SPoS application. In the second experiment, SPoS was introduced two weeks after nematode inoculation. The SPoS treatments without soil were not evaluated in the second experiment. Both experiments were monitored over a three-month period. Each screenhouse treatment contained four plants and was replicated thrice. In the first experiment, data were collected on changes in soil nutrient content, below- and aboveground biomass, root deaths, root necrosis due to nematode damage, and R. similis population in root tissues and soil. In the second experiment, data were collected on root deaths and the number of nematodes in root tissues and the soil. The SPoS improved crop biomass yield, reduced root damage, and colonization by R. similis. The potential of SPoS to improve the management of R. similis and banana production under field conditions needs to be determined.

Agricultural land has long been regarded as a resource for food production, but over time, the effects of climate change have reduced the ability of soil to produce food efficiently. Nowadays, farmers have moved from traditional to modern techniques of farming. Across the globe, plastic mulching has become widely used on farmlands. According to a few studies, the breakdown of plastic mulches releases microplastics (MPs) into the soil. Despite studies reporting the presence of MPs in soils, there are limited studies on the sources and impacts on soil organisms, plant growth, fruits, and human health. This study evaluated research articles collected from the Web of Science to assess the origin of MP in soil and crops and its effects on soil organisms, plants, and humans. It was observed that MPs come from different sources such as waste water, organic fertilizer, irrigation water, sewage, and sludge. Plastic mulching, which can spread across agricultural fields at varying depths, is the dominant source. Furthermore, it was observed that MPs alter crop quality, reduce the leaf count of wheat, and decrease the root length of crops such as maize, water spinach, black gram, and garden cress. MP can decrease the abundance of soil microarthropods and nematodes, damage the intestinal walls of earthworms, and reduce the feeding and excretion of snails. MP causes liver damage, inflammation, respiratory irritation, and immunological issues. Ultimately, these contaminants (MPs) can transfer and have been detected in fruits and vegetables, which pose adverse effects on human health.

Climate change and its impact on agricultural production due to the occurrence of extreme weather events appear to be more imminent and severe than ever, presenting a global challenge that necessitates collective efforts to mitigate its effects.There have been many practical and modelling studies so far to estimate the extent of climate change and possible damages on agricultural production, suggesting that water availability may decrease by 50% and agricultural productivity between 10 and 30% in the coming years ahead. Though there have been many studies to estimate the possible level of damage by the climate change on the production of many agricultural crops, no study has been conducted on the greenhouse tomato production. Therefore, this study was conducted to discover the effects of extreme high temperatures during the 2022-2023 growing season on the high-tech Turkish tomato greenhouse industry through a survey. The results showed that all greenhouses lost yield, ranging from 6 to 53%, with an average of 12.5%. Survey data revealed that irrigation and fog system water consumption increased by 29.32% and 31.42%, respectively, while fertilizer and electricity consumption rose by 23.66% and 19%. Some 76.5% of the growers declared difficulty in climate control, 11.7% reported tomato cluster losses with no information on yield loss, 9% experienced yield losses despite no cluster losses, and 61.7% observed a decline in tomato quality, leading to reduced sales prices. Considering these findings, it is recommended that greenhouses must adopt advanced climate control technologies, expand fog system capacities, and integrate renewable energy sources to enhance resilience against climate-induced challenges. Additionally, improving water-use efficiency, optimizing cooling strategies, using new and climate-resistant varieties and adjusting cropping seasons could help mitigate yield losses due to extreme temperatures. The study results offer extremely valuable insights into greenhouse production for researchers, technology developers, and policymakers for the mitigation of climate change effects and the development of more sustainable production systems.

To minimize environmental damage, conserve global diminishing fertilizer reserves, all while maximizing food production, it is essential that farmers apply phosphate fertilizers at the optimal rate. The purpose of this study is to assess grower attitudes and behavior, with respect to proper application of phosphorus, and to investigate how certain exogenous factors might influence such applications. Data were analyzed from a survey conducted in North Carolina, USA, with 122 farmer participants. The findings reveal that annual phosphorus applications consistently exceed recommendations, which indicates overapplication, leading to economic inefficiency and environmental concerns. Overapplication is neither due to knowledge gaps in nutrient concentrations in the soil nor the lack of interest in soil sampling, as 99% of farmers submit soil tests as frequently or more frequently than every two years. Only 36% of growers indicated that they would not apply phosphorus if their soil report indicated that levels were sufficient, and that none was required. Additionally, overapplication is not strongly influenced by price effects, as only nine percent of growers abandoned applications in 2021, following a dramatic spike doubling fertilizer prices. The adoption of reduced phosphate fertilization will depend on strong local trusted technical assistance and continued extension education.

Offshore wind turbines are subjected to long-term cyclic loads, and the seabed materials surrounding the foundation are susceptible to failure, which affects the safe construction and normal operation of offshore wind turbines. The existing studies of the cyclic mechanical properties of submarine soils focus on the accumulation strain and liquefaction, and few targeted studies are conducted on the hysteresis loop under cyclic loads. Therefore, 78 representative submarine soil samples from four offshore wind farms are tested in the study, and the cyclic behaviors under different confining pressures and CSR are investigated. The experiments reveal two unique development modes and specify the critical CSR of five submarine soil martials under different testing conductions. Based on the dynamic triaxial test results, the machine learning-based partition models for cyclic development mode were established, and the discrimination accuracy of the hysteresis loop were discussed. This study found that the RF model has a better generalization ability and higher accuracy than the GBDT model in discriminating the hysteresis loop of submarine soil, the RF model has achieved a prediction accuracy of 0.96 and a recall of 0.95 on the test dataset, which provides an important theoretical basis and technical support for the design and construction of offshore wind turbines.