Search Results (2,062)

With the increasing production of municipal sewage sludge (MSS) worldwide, the development of efficient and sustainable strategies for its management is crucial. Pyrolysis of MSS offers several benefits, including volume reduction, pathogen elimination, and energy recovery through the production of biochar, syngas, and bio-oil. However, the process can be limited by the composition of the MSS, which can affect the quality of the biochar. Co-pyrolysis has emerged as a promising solution for the sustainable management of MSS, reducing the toxicity of biochar and improving its physical and chemical properties to expand its potential applications. This review discusses the status of MSS as a feedstock for biochar production. It describes the types and properties of various co-substrates grouped according to European biochar certification requirements, including those from forestry and wood processing, agriculture, food processing residues, recycling, anaerobic digestion, and other sources. In addition, the review addresses the optimization of co-pyrolysis conditions, including the type of furnace, mixing ratio of MSS and co-substrate, co-pyrolysis temperature, residence time, heating rate, type of inert gas, and flow rate. This overview shows the potential of different biomass types for the upgrading of MSS biochar and provides a basis for research into new co-substrates. This approach not only mitigates the environmental impact of MSS but also contributes to the wider goal of achieving a circular economy in MSS management. Full article

The cultivation of the Chinese mitten crab (Eriocheir sinensis) is an important component of China’s aquaculture industry and also a field of concern worldwide. It focuses on the selection of high-quality, disease-free juvenile crabs. However, the early maturity rate of more than 18.2% and the mortality rate of more than 60% make it difficult to select suitable juveniles for adult culture. The juveniles exhibit subtle distinguishing features, and the methods for differentiating between sexes vary significantly; without training from professional breeders, it is challenging for laypersons to identify and select the appropriate juveniles. Therefore, we propose a task-aligned detection algorithm for identifying one-year-old precocious Chinese mitten crabs, named R-TNET. Initially, the required images were obtained by capturing key frames, and then they were annotated and preprocessed by professionals to build a training dataset. Subsequently, the ResNeXt network was selected as the backbone feature extraction network, with Convolutional Block Attention Modules (CBAMs) and a Deformable Convolution Network (DCN) embedded in its residual blocks to enhance its capability to extract complex features. Adaptive spatial feature fusion (ASFF) was then integrated into the feature fusion network to preserve the detailed features of small targets such as one-year-old precocious Chinese mitten crab juveniles. Finally, based on the detection head proposed by task-aligned one-stage object detection, the parameters of its anchor alignment metric were adjusted to detect, locate, and classify the crab juveniles. The experimental results showed that this method achieves a mean average precision (mAP) of 88.78% and an F1-score of 97.89%. This exceeded the best-performing mainstream object detection algorithm, YOLOv7, by 4.17% in mAP and 1.77% in the F1-score. Ultimately, in practical application scenarios, the algorithm effectively identified one-year-old precocious Chinese mitten crabs, providing technical support for the automated selection of high-quality crab juveniles in the cultivation process, thereby promoting the rapid development of aquaculture and agricultural intelligence in China. Full article

The accurate identification of corn leaf diseases is crucial for preventing disease spread and improving corn yield. Plant leaf images are often affected by factors such as complex backgrounds, climate, light, and sample data imbalance. To address these issues, we propose a lightweight convolutional neural network, ICS-ResNet, based on ResNet50. This network incorporates improved spatial and channel attention modules as well as a deep separable residual structure to enhance recognition accuracy. (1) The residual connections in the ResNet network prevent gradient loss during deep network training. (2) The improved channel attention (ICA) and spatial attention (ISA) modules fully utilize semantic information from different feature layers to accurately localize key features of the network. (3) To reduce the number of parameters and lower computational costs, we replace traditional convolutional computation with a depth-separable residual structure. (4) We also employ cosine annealing to dynamically adjust the learning rate, enhancing the network’s training stability, improving model convergence, and preventing local optima. Experiments on the corn dataset in Plant Village compare the proposed ICS-ResNet with eight popular networks: CSPNet, InceptionNet_v3, EfficientNet, ShuffleNet, MobileNet, ResNet50, ResNet101 and ResNet152. The results show that the ICS-ResNet achieves an accuracy of 98.87%, which is 5.03%, 3.18%, 1.13%, 1.81%, 1.13%, 0.68%, 0.44% and 0.60% higher than the other networks, respectively. Furthermore, the number of parameters and computations are reduced by 69.21% and 54.88%, respectively, compared to the original ResNet50 network, significantly improving the efficiency of corn leaf disease classification. The study provides strong technical support for sustainable agriculture and the promotion of agricultural science and technology innovation. Full article

To prevent the degradation of light-textured soils, it is advisable to use them for grasslands. These soil management systems help with the faster accumulation of soil organic carbon (SOC), thereby improving the soil’s properties and reducing carbon emissions from agricultural land. In this experiment, we studied the distribution of multi-component perennial grass roots in the Arenosol profile and their impact on SOC sequestration in temperate climate zones. Our research aimed to identify differences in root biomass at depths of 0–15 cm, 15–30 cm, and 30–50 cm and to assess their correlation with SOC and dissolved organic carbon (DOC) in the soil. The roots, shoots, and soil samples of fertilized and unfertilized grasslands were collected at the flowering stage and after the final grass harvest two years in a row. Our findings revealed that, in sandy loam Arenosol rich in stones, 12.4–15.9 Mg ha⁻¹ of root biomass was accumulated at 0–50 cm of soil depth. The application of NPK fertilizers did not significantly affect grass root biomass, but significantly affected shoot biomass. Most roots (84–88%) were concentrated in the 0–15 cm layer. On average, 5.10–6.62 Mg ha⁻¹ of organic carbon (OC) was stored in the roots of perennial grasses within 0–50 cm of soil depth. We found that the SOC content in the 0–50 cm soil layer correlated more strongly (r = 0.62, p < 0.001) with C accumulated in the roots of the corresponding layer than with shoot biomass (r = 0.41, p = 0.04). However, a significant correlation was found between DOC and shoot biomass (r = 0.68, p < 0.001) and between DOC and the biomass of residues (r = 0.71, p < 0.001), explaining the significant increase in DOC in the 30–50 cm soil layer and indicating the leaching of mobile soil organic matter (SOM) substances from the above-ground biomass using fertilizers. Full article

Citrus fruits, particularly mandarins, are highly valued globally for their nutritional benefits and versatile culinary uses. However, the challenge of post-harvest decay, primarily due to blue mold (Penicillium italicum) infections, results in significant food losses and necessitates effective preservation strategies. Traditional methods often rely on fungicides, raising concerns about chemical residues and environmental impact. This study investigates the efficacy of ozone as an alternative approach to controlling blue mold in mandarins. Various gaseous ozone treatments were tested, including single, double, and triple treatments, with durations ranging from 10 to 60 min and concentrations from 3.3 to 20 ppm. Additionally, ozonated water treatments were evaluated with concentrations of 2, 4, and 6 ppm. To simulate a realistic infestation scenario, mandarins were artificially infected with P. italicum spores before undergoing both gaseous ozone and ozonated water treatments. The storage conditions for the mandarins were meticulously controlled, maintaining a humidity level of 50–60% and a temperature range of 10–12 °C. Each fruit was analyzed, and the presence of P. italicum infection was determined two and three weeks after the ozonation. Results indicated that ozone treatments significantly reduced mold growth, with gaseous ozone demonstrating efficacy rates up to 97.5% and ozonated water treatments achieving preservation rates between 95% and 97%. These results underscore ozone’s potential as a safe, efficient, and sustainable alternative to conventional fungicides, offering promising solutions for extending the shelf life of mandarins. Further research is recommended to optimize ozone treatment parameters, assess long-term effects on fruit quality and nutritional content, and refine application techniques to harness ozone’s potential in citrus fruit preservation fully. This approach not only addresses food security challenges but also aligns with global efforts to reduce chemical inputs in agriculture and promote environmentally sustainable practices. Full article

The present study investigates the interactions between eight glucosinolate hydrolysis products (GHPs) sourced from broccoli by-products and the detoxifying enzymes of Botrytis cinerea, namely eburicol 14-alpha-demethylase (CYP51) and glutathione-S-transferase (GST), through in silico analysis. Additionally, in vitro assays were conducted to explore the impact of these compounds on fungal growth. Our findings reveal that GHPs exhibit greater efficacy in inhibiting conidia germination compared to mycelium growth. Furthermore, the results demonstrate the antifungal activity of glucosinolate hydrolysis products derived from various parts of the broccoli plant, including inflorescences, leaves, and stems, against B. cinerea. Importantly, the results suggest that these hydrolysis products interact with the detoxifying enzymes of the fungus, potentially contributing to their antifungal properties. Extracts rich in GHPs, particularly iberin and indole-GHPs, derived from broccoli by-products emerge as promising candidates for biofungicidal applications, offering a sustainable and novel approach to plant protection by harnessing bioactive compounds from agricultural residues. Full article

The development of restoration technology and meadows, improvement of run-down pastures, and productivity improvement of old crops of perennial grasses is an urgent problem in agriculture. The tillage traction force in seeder designing and manufacturing is an important indicator of energy efficiency. The objective of this work is to reduce traction force and ensure seeding depth uniformity by justifying the optimal chisel parameters of a grain–fertilizer–grass seeder for direct seeding in sod. The Box–Behnken method was applied to investigate the traction force dependence on the seeder velocity, seed embedding depth, chisel width, and mounting angle. The obtained optimal parameters of coulters were justified by the finite element method. Structural and technological parameters were checked using the smoothed-particle hydrodynamics method on the deformation and wear of the seeder working body. The revealed optimal coulter parameters were as follows: chisel width was 20–20.97 mm, chisel length was 145–148.9 mm, mounting angle was 75°–81.6°, and achieved minimum traction force was 720 N. These parameters ensure the quality of grass seed embedding in the sod. The theoretical data of traction force (8.27–8.39 kN) are in accordance with the experimental (8.28–8.63 kN) data under field conditions. These findings are efficient in agrotechnical and mechanical predictions regarding the occurrence of chisel residual stresses and the working lifetime of the part. Full article

The accurate extraction of agricultural parcels from remote sensing images is crucial for advanced agricultural management and monitoring systems. Existing methods primarily emphasize regional accuracy over boundary quality, often resulting in fragmented outputs due to uniform crop types, diverse agricultural practices, and environmental variations. To address these issues, this paper proposes DSTBA-Net, an end-to-end encoder–decoder architecture. Initially, we introduce a Dual-Stream Feature Extraction (DSFE) mechanism within the encoder, which consists of Residual Blocks and Boundary Feature Guidance (BFG) to separately process image and boundary data. The extracted features are then fused in the Global Feature Fusion Module (GFFM), utilizing Transformer technology to further integrate global and detailed information. In the decoder, we employ Feature Compensation Recovery (FCR) to restore critical information lost during the encoding process. Additionally, the network is optimized using a boundary-aware weighted loss strategy. DSTBA-Net aims to achieve high precision in agricultural parcel segmentation and accurate boundary extraction. To evaluate the model’s effectiveness, we conducted experiments on agricultural parcel extraction in Denmark (Europe) and Shandong (Asia). Both quantitative and qualitative analyses show that DSTBA-Net outperforms comparative methods, offering significant advantages in agricultural parcel extraction. Full article

Safe drinking water is essential to a healthy lifestyle and has been recognised as a human right by numerous countries. However, the realisation of this right remains largely aspirational, particularly in impoverished nations that lack adequate resources for water quality testing. Kenya, a Sub-Saharan country, bears the brunt of this challenge. Pesticide imports in Kenya increased by 144% from 2015 to 2018, with sales data indicating that 76% of these pesticides are classified as highly hazardous. This trend continues to rise. Over 70% of Kenya’s population resides in rural areas, with 75% of the rural population engaged in agriculture and using pesticides. Agriculture is the country’s main economic activity, contributing over 30% of its gross domestic product (GDP). The situation is further exacerbated by the lack of monitoring for pesticide residues in surface water and groundwater, coupled with the absence of piped water infrastructure in rural areas. Consequently, contamination levels are high, as agricultural runoff is a major contaminant of surface water and groundwater. The increased use of pesticides to enhance agricultural productivity exacerbates environmental degradation and harms water ecosystems, adversely affecting public health. This study proposes the development of a wireless sensor system that utilizes radio-frequency identification (RFID), Long-range (LoRa) protocol and a global system for mobile communications (GSM) for monitoring pesticide prevalence in groundwater sources. From the system design, individuals with limited literacy skills, advanced age, or non-expert users can utilize it with ease. The reliability of the LoRa protocol in transmitting data packets is thoroughly investigated to ensure effective communication. The system features a user-friendly interface for straightforward data input and facilitates broader access to information by employing various remote wireless sensing methods. Full article

In this study, we explored the efficacy of random forest algorithms in downscaling CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data) precipitation data to predict Argane stand traits. Nonparametric regression integrated original CHIRPS data with environmental variables, demonstrating enhanced accuracy aligned with ground rain gauge observations after residual correction. Furthermore, we explored the performance of range machine learning algorithms, encompassing XGBoost, GBDT, RF, DT, SVR, LR and ANN, in predicting the Leaf Area Index (LAI) and crop yield of Argane trees using condition index-based drought indices such as PCI, VCI, TCI and ETCI derived from multi-sensor satellites. The results demonstrated the superiority of XGBoost in estimating these parameters, with drought indices used as input. XGBoost-based crop yield achieved a higher R² value of 0.94 and a lower RMSE of 6.25 kg/ha. Similarly, the XGBoost-based LAI model showed the highest level of accuracy, with an R² of 0.62 and an RMSE of 0.67. The XGBoost model demonstrated superior performance in predicting the crop yield and LAI estimation of Argania sinosa, followed by GBDT, RF and ANN. Additionally, the study employed the Combined Drought Index (CDI) to monitor agricultural and meteorological drought over two decades, by combining four key parameters, PCI, VCI, TCI and ETCI, validating its accuracy through comparison with other drought indices. CDI exhibited positive correlations with VHI, SPI and crop yield, with a particularly strong and statistically significant correlation observed with VHI (r = 0.83). Therefore, CDI was recommended as an effective method and index for assessing and monitoring drought across Argane forest stands area. The findings demonstrated the potential of advanced machine learning models for improving precipitation data resolution and enhancing agricultural drought monitoring, contributing to better land and hydrological management. Full article

To determine the link between hygroscopicity and the constituent chemical composition of real biomass-burning atmospheric particles, we collected and analyzed aerosols during wheat-straw (April–May), rice-straw (October–November), and no-burning periods (August–September) in 2008 and 2009 in Patiala, Punjab. A hygroscopicity tandem differential mobility analyzer (HTDMA) system was used to measure hygroscopicity at ~5 to ~95% relative humidity (RH) of aerosolized 100 nm particles generated from the water extracts of PM_0.4 burning and no-burning aerosol samples. The chemical analyses of the extracts show that organic carbon and water-soluble inorganic-ion concentrations are 2 to 3 times higher in crop-residue burning aerosol samples compared to no-burning aerosols, suggesting the substantial contribution of biomass burning to the carbonaceous aerosols at the sampling site. We observed that aerosolized 100 nm particles collected during the crop-residue burning period show higher and more variable hygroscopic growth factor (g(RH)) ranging from 1.21 to 1.68 at 85% RH, compared to no-burning samples (1.27 to 1.33). Interestingly, crop-residue burning particles also show considerable shrinkage in their size (i.e., g(RH) < 1) at lower RH (<50%) in the dehumidification mode. The increased level of major inorganic ions in biomass-burning period aerosols is a possible reason for higher g(RH) as well as the observed particle shrinkage. Overall, the measured g(RH), together with the correlation observed between aerosol water content and ionic-species volume fraction, and the study of the abundance of individual constituent ionic species suggests that inorganic salts and their proportion in aerosol particles primarily governed the aerosol hygroscopicity. Full article

Soil salinity is the major constraint for cropping system intensification in the coastal region of the Ganges Delta. Salts build up on the soil surface, as well as in the crop root zone, due to the capillary rise in underground brackish water, hampering the growth and development of crops and resulting in mortality and low yields. We studied, for three years (2020–2021 to 2022–2023), the effect of conservation agricultural practices (zero tillage planting, crop residue recycling, and crop rotations) on the major soil properties (soil salinity and organic carbon status), crop performance (yield and economics), and water footprint. Conservation agricultural practices significantly reduce soil salinity, build soil organic carbon, reduce water footprint, and increase the profitability of cropping systems compared to tillage-intensive conventional practices. Under conventional agriculture, the sole cropping of rice is more profitable than double and triple cropping systems. Full article

This study explored the impact of starter-assisted fermentation on apple blossoms to enhance their potential as a source of antioxidant and antifungal molecules. Fructobacillus fructosus PL22 and Wickerhamomyces anomalus GY1 were chosen as starters owing to their origin and promising ability to modify plant secondary metabolites. An initial assessment through microbiological and physicochemical analyses showed superior outcomes for starter-assisted fermentation compared to the spontaneous process. Enzymatic hydrolysis of proteins, primarily controlled by starters, orchestrated the generation of new low-molecular-weight peptides. W. anomalus GY1 also induced modifications in the phenolic profile, generating a diverse array of bioactive metabolites. These metabolic changes, particularly the release of potentially bioactive peptides, were associated with significant antioxidant activity and marked antifungal efficacy against three common mold species. Our results shed light on the potential of microbial starters to valorize agricultural wastes and convert them into a valuable resource for industry. Full article

The increasing demand for sustainable agricultural practices aimed at reducing carbon dioxide emissions has driven the exploration of converting viticulture residues into biochar. This study investigates the potential technological applications of biochar as a filler for the production of electrically conductive composite materials, suitable to Bipolar Plate (BP) manufacturing. Grape seeds (GSs), defatted grape seeds (DGSs), wood stems (WSs), and whole grape seeds (WGSs) were converted into biochar samples through low-temperature (300 °C) pyrolysis for 3 or 24 h. The composition and thermal stability of biochar were evaluated through thermogravimetric analysis (TG), which provided valuable insights into interpreting the in-plane conductivity (IPC) values of the BP samples. Pyrolyzed GS and DGS biochar samples demonstrated enhanced thermal stability and conferred higher IPC values compared to WS counterparts. This indicates a clear correlation between the formation of carbon-rich structures during pyrolysis and overall electrical conductivity. In contrast, pyrolyzed WGSs produced BP samples with lower IPC values due to the presence of lipids, which were not effectively degraded by the low-temperature pyrolysis. Full article

An energy supply crisis is impacting all the branches, including the agriculture and food industry. The wise and responsible utilization of plant raw materials already cultivated is becoming a must in the country’s economy. Not only the waste of the resources included but also the environmental challenge are concerns behind the not exploited food production by-streams and leftovers’ valorization. Fruits and vegetables’ out of the market quality “beauty” standards are still valuable sources of nutritious compounds. The conversion of raw materials into edible products can be provided by many techniques, with three-dimensional printing being the most individualized one. The main objective of this review was to summarize the existing efforts for the valorization of fruits and vegetable residuals into edible 3D inks and then 3D printed products. The clustering analysis was used for the separation of certain research approaches in fruit and vegetable wastes exploitation for 3D printing inks’ formulation. As the multilayer deposit technique is strongly dependent on the printing conditions and 3D ink formulation, therefore the tabularized description was included presenting the nozzle diameter, printing speed and other conditions specified. Full article