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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Abderahman Rejeb; Karim Rejeb; Andrea Appolloni; Sandeep Jagtap; +4 Authors

    As the fusion of the Internet of Things (IoT) and blockchain technology advances, it is increasingly shaping diverse fields. The potential of this convergence to fortify security, enhance privacy, and streamline operations has ignited considerable academic interest, resulting in an impressive body of literature. However, there is a noticeable scarcity of studies employing Latent Dirichlet Allocation (LDA) to dissect and categorize this field. This review paper endeavours to bridge this gap by meticulously analysing a dataset of 4455 journal articles drawn solely from the Scopus database, cantered around IoT and blockchain applications. Utilizing LDA, we have extracted 14 distinct topics from the collection, offering a broad view of the research themes in this interdisciplinary domain. Our exploration underscores an upswing in research pertaining to IoT and blockchain, emphasizing the rising prominence of this technological amalgamation. Among the most recurrent themes are IoT and blockchain integration in supply chain management and blockchain in healthcare data management and security, indicating the significant potential of this convergence to transform supply chains and secure healthcare data. Meanwhile, the less frequently discussed topics include access control and management in blockchain-based IoT systems and energy efficiency in wireless sensor networks using blockchain and IoT. To the best of our knowledge, this paper is the first to apply LDA in the context of IoT and blockchain research, providing unique perspectives on the existing literature. Moreover, our findings pave the way for proposed future research directions, stimulating further investigation into the less explored aspects and sustaining the growth of this dynamic field.

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    Internet of Things and Cyber-Physical Systems
    Article . 2024 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
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    Cranfield CERES
    Article . 2023
    License: CC BY
    Data sources: Cranfield CERES
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Internet of Things a...arrow_drop_down
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      Internet of Things and Cyber-Physical Systems
      Article . 2024 . Peer-reviewed
      License: CC BY
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      Cranfield CERES
      Article . 2023
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    Authors: Shehbaz Ali; Naveed Ahmad; Mudasir A. Dar; Sehrish Manan; +10 Authors

    This review delves into the mesmerizing technology of nano-agrochemicals, specifically pesticides and herbicides, and their potential to aid in the achievement of UN SDG 17, which aims to reduce hunger and poverty globally. The global market for conventional pesticides and herbicides is expected to reach USD 82.9 billion by 2027, growing 2.7% annually, with North America, Europe, and the Asia–Pacific region being the biggest markets. However, the extensive use of chemical pesticides has proven adverse effects on human health as well as the ecosystem. Therefore, the efficacy, mechanisms, and environmental impacts of conventional pesticides require sustainable alternatives for effective pest management. Undoubtedly, nano-agrochemicals have the potential to completely transform agriculture by increasing crop yields with reduced environmental contamination. The present review discusses the effectiveness and environmental impact of nanopesticides as promising strategies for sustainable agriculture. It provides a concise overview of green nano-agrochemical synthesis and agricultural applications, and the efficacy of nano-agrochemicals against pests including insects and weeds. Nano-agrochemical pesticides are investigated due to their unique size and exceptional performance advantages over conventional ones. Here, we have focused on the environmental risks and current state of nano-agrochemicals, emphasizing the need for further investigations. The review also draws the attention of agriculturists and stakeholders to the current trends of nanomaterial use in agriculture especially for reducing plant diseases and pests. A discussion of the pros and cons of nano-agrochemicals is paramount for their application in sustainable agriculture.

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    Plants
    Article . 2023
    Data sources: DOAJ
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    Plants
    Article . 2023 . Peer-reviewed
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      Plants
      Article . 2023
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      Plants
      Article . 2023 . Peer-reviewed
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    Authors: H. Byju; K. A. Rubeena; C. T. Shifa; T. R. Athira; +20 Authors

    Habitat fragmentation and degradation in natural wetlands has resulted in declines in the populations of shorebirds in the Indian subcontinent. Shorebirds rely on these wetlands as wintering or stop-over sites along the southern extent of the Central Asian Flyway. Shorebirds are known to utilize agroecosystems as alternate foraging habitats. The suitability of agroecosystems as foraging areas for overwintering migratory shorebirds has not been well studied in the Indian subcontinent. We conducted a comprehensive assessment of published literature and compiled field observations to investigate the importance of inland and coastal agroecosystems for shorebirds in India. We assessed the shorebird populations at natural wetlands: mudflats and mangroves of Kadalundi Vallikkunnu Community Reserve (KVCR) and Puthuvypu sand beach, as well as adjacent agroecosystems on the west coast of India, including Sanketham Wetlands, Manthalakkadavu, Vazhakkad, Elamaram, Kodinhi, and Kooriyad. On the east coast, we assessed the natural wetland habitats of Valinokkam, Point Calimere, and Pichavaram and evaluated inland agroecosystems in regions, such as Jammu and Kashmir, Punjab, Rajasthan, Gujarat, Uttar Pradesh, Tamil Nadu, and Kerala. Fifty-three shorebird species utilize diverse agroecosystems from various parts of India. While studies on the use of agroecosystems by shorebirds are limited on the east coast, evidence suggests that major wintering sites are adjacent to paddy fields, fostering substantial shorebird diversity. In Pichavaram, Point Calimere, and Gulf of Mannar regions, 22 shorebird species utilize agroecosystems, including the notable near-threatened Eurasian Curlew. Seventeen of these species are winter arrivals, highlighting the crucial role agroecosystems play as stopover areas. On the west coast, 19 shorebird species appear to utilize agroecosystems in Kooriyad, Manthalakkadavu, Vazhakkad, Sanketham Wetlands, Elamaram, and Kodinhi. Few species use agricultural fields in the north (Jammu and Kashmir). Paddy fields, that are flooded as part of the cropping cycle, support diverse prey species, such as macroinvertebrates, amphibians, and small fish, that could attract and support migratory shorebirds. Agricultural practices like fallowing, flooding, and ploughing could further increase the abundance and accessibility of prey for shorebirds, drawing them in greater numbers. It is crucial to recognize that unsustainable and unethical agricultural methods could detrimentally affect shorebird numbers. The accumulation of pesticide residues and the contamination from heavy metals could also threaten shorebirds. As a result, there is an urgent need for detailed research to better evaluate the importance of agroecosystems in supporting resident or migratory shorebirds. Systematic studies that explain the population dynamics, habitat selection trends, habitat utilization, and the over-summering behavior of the migratory birds at agroecosystems are needed. Implementing sustainable conservation strategies and adopting environmentally friendly agricultural practices are essential to support the rich biodiversity of the region.

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    Diversity
    Article . 2023 . Peer-reviewed
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    Diversity
    Article . 2023
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      Diversity
      Article . 2023 . Peer-reviewed
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      Diversity
      Article . 2023
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    Authors: Ons BenRhouma; Chiheb Rebai; Manel Ben-Romdhane; Dario Di Cara; +2 Authors

    In the neighborhood area network (NAN), the advanced metering infrastructure (AMI) enables a bidirectional connection between the smart meter (SM) and the data concentrator (DC). Sensors, such as smart meter nodes or environmental sensor nodes, play a crucial role in measuring and transmitting data to central units for advanced monitoring, management, and analysis of energy consumption. Wired and wireless communication technologies are used to implement the AMI-NAN. This paper delves into a novel approach for optimizing the choice of communication medium, air for radio frequency (RF) or power lines for power line communication (PLC), between the SM and DC in the context of the AMI-NAN. The authors methodically select the specific technologies, RF and NB-PLC (narrowband power line communication), and meticulously characterize their attributes. Then, a comparative analysis spanning rural, urban, and industrial settings is conducted to evaluate the proposed method. The overall reliability performance of the AMI-NAN system requires a packet error rate (PER) lower than 10%. To this end, an efficient approach is introduced to assess and enhance the reliability of NB-PLC and RF for AMI-NAN applications. Simulation results demonstrate that wireless communication is the optimal choice for the rural scenario, especially for a signal-to-noise ratio (SNR) lower than 25 dB. However, in urban environments characterized by higher SNR values and moderately dense networks, NB-PLC gains prominence. In denser networks, it outperforms wireless communication, exhibiting a remarkable 10 dB gain for a bit error rate (BER) of 10−3. Moreover, in industrial zones characterized by intricate network topologies and non-linear loads, the power line channel emerges as the optimal choice for data transmission.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Sensorsarrow_drop_down
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    Sensors
    Article . 2023
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    Sensors
    Article . 2023 . Peer-reviewed
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      Article . 2023
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      Sensors
      Article . 2023 . Peer-reviewed
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    Authors: Ahmed Skhiri; Karim Gabsi; Ahmed Z. Dewidar; Mohamed A. Mattar;

    The Christiansen Uniformity Coefficient (CUC) describes the distribution of water in a sprinkler system. In this study, two types of models were developed to predict the Christiansen Uniformity Coefficient (CUC) of sprinkler irrigation systems: Artificial Neural Network (ANN), specifically the feed-forward neural networks, and multiple linear regression (MLR) models. The models were trained on a dataset of published research on the CUC of sprinkler irrigation systems, which included data on a variety of design, operating, and meteorological condition variables. In order to build the predictive model of CUC, 10 input parameters were used including sprinkler height (H), working pressure (P), nozzle diameter (D and da), sprinkler line spacing (SL), sprinkler spacing (SS), wind speed (WS), wind direction (WD), temperature (T), and relative humidity (RH). Fifty percent (50%) of the data was used to train ANN models and the remaining data for cross-validation (25%) and for testing (25%). Multiple linear regression models were built using the training data. Four statistical criteria were used to evaluate the model’s predictive quality: the correlation coefficient (R), the index of agreement (d), the root mean square error (RMSE), and the mean absolute error (MAE). Statistical analysis demonstrated that the best predictive ability was obtained when the models (ANN and MLR) utilized all the input variables. The results demonstrated that the accuracy of ANN models, predicting the CUC of sprinkler irrigation systems, is higher than that of the MLR ones. During the training stage, the ANN models were more accurate in predicting CUC than MLR, with higher R (0.999) and d (0.999) values and lower MAE (0.167) and RMSE (0.456) values. The R values of the MLR model fluctuated between 0.226 and 0.960, the d values oscillated from 0.174 to 0.979, the MAE values were in the range of 2.458% and 10.792%, and the RMSE values fluctuated from 2.923% to 13.393%. Furthermore, the study revealed that WS and WD are the most influential climatic parameters. The ANN model can be used to develop more accurate tools for predicting the CUC of sprinkler irrigation systems. This can help farmers to design and operate their irrigation systems more efficiently, which can save them time and money.

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    Agronomy
    Article . 2023
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    Agronomy
    Article . 2023 . Peer-reviewed
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      Agronomy
      Article . 2023
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      Agronomy
      Article . 2023 . Peer-reviewed
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    Authors: Salem Marzougui; Mongi Ben Younes;

    Heading date, plant height, and spike-related phenotypes are key traits that affect the yield potential and adaptation of barley to Mediterranean environments. These traits are controlled by a complex network of genes as well as environmental effects. Marker-trait associations (MTAs) were performed using a set of 361 barley genotypes, evaluated phenotypically for three years under semi-arid conditions. In total, 24 MTAs were detected using the recently developed GWAS method (BLINK) at –log p ≥ 5. These included one MTA with awn length (Awl) on chromosome 2H; twelve MTAs with heading date (HD) distributed over all chromosomes except 4H; three MTAs with grains per spike (GPS) on chromosomes 1H, 2H, and 6H; six MTAs were detected for plant height (PH) on 2H (2), 3H, 4H, 6H, and 7H; and two MTAs with spike length (SL) on 3H and 7H. The results showed novel and known associations between specific SNP markers and heading date, plant height, and spike-related traits, suggesting that these markers can be used in breeding programs to improve these traits in barley. This study provides valuable information for breeders and geneticists working to develop new barley varieties that are better adapted to semi-arid climates and have improved yield and quality characteristics.

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    Authors: Elkadri Lefi; Mounawer Badri; Samouna Ben Hamed; Sihem Talbi; +3 Authors

    In this study, we evaluated the impact of brown seaweed extract (Ecklonia maxima) on the morphology and physiology of three different plant species. We conducted experiments using two types of fertilizers: an artificial fertilizer (0.1 g/L) and a biological extract of brown seaweed (Ecklonia maxima) at two concentrations (C1 at 1 mL/L and C2 at 2.5 mL/L). For melon, the application of C1 resulted in significant improvements in photosynthesis parameters, total chlorophyll content, and overall plant growth. When C2 was applied, it further enhanced these parameters, leading to a notable increase in shoot phytomass. In the case of cucumber, C1 led to increased resource allocation towards stems and leaves. Conversely, C2 increased the number of green leaves and contributed to higher shoot phytomass. For tomato plants, the application of C1 resulted in a slight increase in photosynthesis, but it did not significantly impact leaf growth. On the other hand, C2 induced a modest increase in photosynthesis, chlorophyll content, and root growth. In summary, our findings indicate that brown seaweed extract has a discernible influence on the physiology of the studied plants. However, the specific effects on resource allocation largely depend on the plant species and the concentration of the extract applied.

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    Agronomy
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    Authors: Taoufik Hermassi; Mohamed Lassaad Kotti; Fathia Jarray;

    Soil degradation and erosion in semi-arid regions can significantly impact agricultural development, environmental sustainability, and hydrological balance. Understanding the impacts of land use changes and soil and water conservation (SWC) technique implementation on soil erosion and sediment yield is critical to planning effective watershed management. This study aims to evaluate the impacts of environmental changes in the Merguellil watershed (Central Tunisia) over the last forty years. To achieve this, remote sensing techniques and a geographic information system (GIS) will be employed to classify Landsat images from 1980 to 2020. Additionally, the Revised Universal Soil Loss Equation model will be utilized to estimate soil erosion rates, while the sediment delivery distributed model will be employed for sediment yield modeling. Spatiotemporal changes in land use and land cover and in areas treated with SWC techniques were analyzed as the main factors influencing changes in erosion and sediment yield. The combined impact of land use change and SWC techniques resulted in a decrease in the annual soil erosion rate from 18 to 16 t/ha/year between 1980 and 2020 and in sediment yield from 9.65 to 8.95 t/ha/year for the same period. According to the model’s predictions, both soil erosion and sediment yield will experience a slight increase with further degradation of natural vegetation and a reduction in the efficiency of SWC works. This emphasizes the importance of continued efforts in adopting and sustaining SWC techniques, as well as preserving natural vegetation cover, to proactively combat soil degradation and its adverse effects on the environment and communities. Continuous dedication to these measures is crucial to preserving our ecosystem, promoting sustainable practices, and protecting the well-being of both the environment and society.

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    Applied Sciences
    Article . 2023
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    Applied Sciences
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    Authors: Hayet Beltayef; Mouna Mechri; Wafa Saidi; Taqi Raza; +7 Authors

    The overuse of chemical pesticides and fertilizers in crop farming has led to a decrease in crop quality and negative impacts on soil and the environment. It is crucial to adopt alternative strategies to maintain soil and environmental quality while enhancing crop growth and yield. To explore this, a study was conducted under greenhouse conditions to investigate the effect of Rhizobium tropici CIAT 899 alone, as well as in association with mycorrhizae (Rhizophagus irregularis) and endophytic fungus (Serendipita indica), on the growth, yield, and nutrient status of snap bean plants. At harvest, the rhizobial strain CIAT 899 demonstrated the highest effectiveness. It significantly increased the number of nodules in both Contender and Garrafal Enana varieties by 6.97% and 14.81%, respectively, compared with the control without inoculation. Furthermore, the results indicated that co-inoculation of Rhizobium and symbiotic fungi had positive effects on nitrogen content, phosphorus availability, and overall plant growth. Regardless of the variety, plants inoculated with R. tropici CIAT 899 and Serendipita indica exhibited the highest values for plant growth parameters. This combination resulted in 168% and 135% increases in root dry biomass, as well as 140% and 225% increases in the number of pods for Contender and Garrafal Enana, respectively, compared with the control at harvest. Additionally, this study highlights the potential benefits of combining R. tropici with either Serendipita indica or Rhizophagus irregularis in terms of nitrogen and phosphorus uptake. These symbiotic microorganisms demonstrated synergistic interactions with snap bean plants, leading to improved mineral nutrition and enhanced growth. Overall, these findings suggest that utilizing these symbiotic microorganisms can effectively enhance the mineral nutrition and growth of snap bean plants.

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    Authors: Sarra Salem; Aissam Gaagai; Imed Ben Slimene; Amor Moussa; +11 Authors

    In the Zeroud basin, a diverse array of methodologies were employed to assess, simulate, and predict the quality of groundwater intended for irrigation. These methodologies included the irrigation water quality indices (IWQIs); intricate statistical analysis involving multiple variables, supported with GIS techniques; an artificial neural network (ANN) model; and an XGBoost regression model. Extensive physicochemical examinations were performed on groundwater samples to elucidate their compositional attributes. The results showed that the abundance order of ions was Na+ > Ca2+ > Mg2+ > K+ and SO42− > HCO3− > Cl−. The groundwater facies reflected Ca-Mg-SO4, Na-Cl, and mixed Ca-Mg-Cl/SO4 water types. A cluster analysis (CA) and principal component analysis (PCA), along with ionic ratios, detected three different water characteristics. The mechanisms controlling water chemistry revealed water–rock interaction, dolomite dissolution, evaporation, and ion exchange. The assessment of groundwater quality for agriculture with respect IWQIs, such as the irrigation water quality index (IWQI), sodium adsorption ratio (SAR), sodium percentage (Na%), soluble sodium percentage (SSP), potential salinity (PS), and residual sodium carbonate (RSC), revealed that the domination of the water samples was valuable for agriculture. However, the IWQI and PS fell between high-to-severe restrictions and injurious-to-unsatisfactory. The ANN and XGBoost regression models showed robust results for predicting IWQIs. For example, ANN-HyC-9 emerged as the most precise forecasting framework according to its outcomes, as it showcased the most robust link between prime attributes and IWQI. The nine attributes of this model hold immense significance in IWQI prediction. The R2 values for its training and testing data stood at 0.999 (RMSE = 0.375) and 0.823 (RMSE = 3.168), respectively. These findings indicate that XGB-HyC-3 emerged as the most accurate forecasting model, displaying a stronger connection between IWQI and its exceptional characteristics. When predicting IWQI, approximately three of the model’s attributes played a pivotal role. Notably, the model yielded R2 values of 0.999 (RMSE = 0.001) and 0.913 (RMSE = 2.217) for the training and testing datasets, respectively. Overall, these results offer significant details for decision-makers in managing water quality and can support the long-term use of water resources.

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    Water
    Article . 2023 . Peer-reviewed
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Abderahman Rejeb; Karim Rejeb; Andrea Appolloni; Sandeep Jagtap; +4 Authors

    As the fusion of the Internet of Things (IoT) and blockchain technology advances, it is increasingly shaping diverse fields. The potential of this convergence to fortify security, enhance privacy, and streamline operations has ignited considerable academic interest, resulting in an impressive body of literature. However, there is a noticeable scarcity of studies employing Latent Dirichlet Allocation (LDA) to dissect and categorize this field. This review paper endeavours to bridge this gap by meticulously analysing a dataset of 4455 journal articles drawn solely from the Scopus database, cantered around IoT and blockchain applications. Utilizing LDA, we have extracted 14 distinct topics from the collection, offering a broad view of the research themes in this interdisciplinary domain. Our exploration underscores an upswing in research pertaining to IoT and blockchain, emphasizing the rising prominence of this technological amalgamation. Among the most recurrent themes are IoT and blockchain integration in supply chain management and blockchain in healthcare data management and security, indicating the significant potential of this convergence to transform supply chains and secure healthcare data. Meanwhile, the less frequently discussed topics include access control and management in blockchain-based IoT systems and energy efficiency in wireless sensor networks using blockchain and IoT. To the best of our knowledge, this paper is the first to apply LDA in the context of IoT and blockchain research, providing unique perspectives on the existing literature. Moreover, our findings pave the way for proposed future research directions, stimulating further investigation into the less explored aspects and sustaining the growth of this dynamic field.

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    Internet of Things and Cyber-Physical Systems
    Article . 2024 . Peer-reviewed
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    Cranfield CERES
    Article . 2023
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      Internet of Things and Cyber-Physical Systems
      Article . 2024 . Peer-reviewed
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      Cranfield CERES
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    Authors: Shehbaz Ali; Naveed Ahmad; Mudasir A. Dar; Sehrish Manan; +10 Authors

    This review delves into the mesmerizing technology of nano-agrochemicals, specifically pesticides and herbicides, and their potential to aid in the achievement of UN SDG 17, which aims to reduce hunger and poverty globally. The global market for conventional pesticides and herbicides is expected to reach USD 82.9 billion by 2027, growing 2.7% annually, with North America, Europe, and the Asia–Pacific region being the biggest markets. However, the extensive use of chemical pesticides has proven adverse effects on human health as well as the ecosystem. Therefore, the efficacy, mechanisms, and environmental impacts of conventional pesticides require sustainable alternatives for effective pest management. Undoubtedly, nano-agrochemicals have the potential to completely transform agriculture by increasing crop yields with reduced environmental contamination. The present review discusses the effectiveness and environmental impact of nanopesticides as promising strategies for sustainable agriculture. It provides a concise overview of green nano-agrochemical synthesis and agricultural applications, and the efficacy of nano-agrochemicals against pests including insects and weeds. Nano-agrochemical pesticides are investigated due to their unique size and exceptional performance advantages over conventional ones. Here, we have focused on the environmental risks and current state of nano-agrochemicals, emphasizing the need for further investigations. The review also draws the attention of agriculturists and stakeholders to the current trends of nanomaterial use in agriculture especially for reducing plant diseases and pests. A discussion of the pros and cons of nano-agrochemicals is paramount for their application in sustainable agriculture.

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    Plants
    Article . 2023
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    Plants
    Article . 2023 . Peer-reviewed
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      Plants
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    Authors: H. Byju; K. A. Rubeena; C. T. Shifa; T. R. Athira; +20 Authors

    Habitat fragmentation and degradation in natural wetlands has resulted in declines in the populations of shorebirds in the Indian subcontinent. Shorebirds rely on these wetlands as wintering or stop-over sites along the southern extent of the Central Asian Flyway. Shorebirds are known to utilize agroecosystems as alternate foraging habitats. The suitability of agroecosystems as foraging areas for overwintering migratory shorebirds has not been well studied in the Indian subcontinent. We conducted a comprehensive assessment of published literature and compiled field observations to investigate the importance of inland and coastal agroecosystems for shorebirds in India. We assessed the shorebird populations at natural wetlands: mudflats and mangroves of Kadalundi Vallikkunnu Community Reserve (KVCR) and Puthuvypu sand beach, as well as adjacent agroecosystems on the west coast of India, including Sanketham Wetlands, Manthalakkadavu, Vazhakkad, Elamaram, Kodinhi, and Kooriyad. On the east coast, we assessed the natural wetland habitats of Valinokkam, Point Calimere, and Pichavaram and evaluated inland agroecosystems in regions, such as Jammu and Kashmir, Punjab, Rajasthan, Gujarat, Uttar Pradesh, Tamil Nadu, and Kerala. Fifty-three shorebird species utilize diverse agroecosystems from various parts of India. While studies on the use of agroecosystems by shorebirds are limited on the east coast, evidence suggests that major wintering sites are adjacent to paddy fields, fostering substantial shorebird diversity. In Pichavaram, Point Calimere, and Gulf of Mannar regions, 22 shorebird species utilize agroecosystems, including the notable near-threatened Eurasian Curlew. Seventeen of these species are winter arrivals, highlighting the crucial role agroecosystems play as stopover areas. On the west coast, 19 shorebird species appear to utilize agroecosystems in Kooriyad, Manthalakkadavu, Vazhakkad, Sanketham Wetlands, Elamaram, and Kodinhi. Few species use agricultural fields in the north (Jammu and Kashmir). Paddy fields, that are flooded as part of the cropping cycle, support diverse prey species, such as macroinvertebrates, amphibians, and small fish, that could attract and support migratory shorebirds. Agricultural practices like fallowing, flooding, and ploughing could further increase the abundance and accessibility of prey for shorebirds, drawing them in greater numbers. It is crucial to recognize that unsustainable and unethical agricultural methods could detrimentally affect shorebird numbers. The accumulation of pesticide residues and the contamination from heavy metals could also threaten shorebirds. As a result, there is an urgent need for detailed research to better evaluate the importance of agroecosystems in supporting resident or migratory shorebirds. Systematic studies that explain the population dynamics, habitat selection trends, habitat utilization, and the over-summering behavior of the migratory birds at agroecosystems are needed. Implementing sustainable conservation strategies and adopting environmentally friendly agricultural practices are essential to support the rich biodiversity of the region.

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    Diversity
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      Diversity
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    Authors: Ons BenRhouma; Chiheb Rebai; Manel Ben-Romdhane; Dario Di Cara; +2 Authors

    In the neighborhood area network (NAN), the advanced metering infrastructure (AMI) enables a bidirectional connection between the smart meter (SM) and the data concentrator (DC). Sensors, such as smart meter nodes or environmental sensor nodes, play a crucial role in measuring and transmitting data to central units for advanced monitoring, management, and analysis of energy consumption. Wired and wireless communication technologies are used to implement the AMI-NAN. This paper delves into a novel approach for optimizing the choice of communication medium, air for radio frequency (RF) or power lines for power line communication (PLC), between the SM and DC in the context of the AMI-NAN. The authors methodically select the specific technologies, RF and NB-PLC (narrowband power line communication), and meticulously characterize their attributes. Then, a comparative analysis spanning rural, urban, and industrial settings is conducted to evaluate the proposed method. The overall reliability performance of the AMI-NAN system requires a packet error rate (PER) lower than 10%. To this end, an efficient approach is introduced to assess and enhance the reliability of NB-PLC and RF for AMI-NAN applications. Simulation results demonstrate that wireless communication is the optimal choice for the rural scenario, especially for a signal-to-noise ratio (SNR) lower than 25 dB. However, in urban environments characterized by higher SNR values and moderately dense networks, NB-PLC gains prominence. In denser networks, it outperforms wireless communication, exhibiting a remarkable 10 dB gain for a bit error rate (BER) of 10−3. Moreover, in industrial zones characterized by intricate network topologies and non-linear loads, the power line channel emerges as the optimal choice for data transmission.

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    Sensors
    Article . 2023
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    Sensors
    Article . 2023 . Peer-reviewed
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      Sensors
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    Authors: Ahmed Skhiri; Karim Gabsi; Ahmed Z. Dewidar; Mohamed A. Mattar;

    The Christiansen Uniformity Coefficient (CUC) describes the distribution of water in a sprinkler system. In this study, two types of models were developed to predict the Christiansen Uniformity Coefficient (CUC) of sprinkler irrigation systems: Artificial Neural Network (ANN), specifically the feed-forward neural networks, and multiple linear regression (MLR) models. The models were trained on a dataset of published research on the CUC of sprinkler irrigation systems, which included data on a variety of design, operating, and meteorological condition variables. In order to build the predictive model of CUC, 10 input parameters were used including sprinkler height (H), working pressure (P), nozzle diameter (D and da), sprinkler line spacing (SL), sprinkler spacing (SS), wind speed (WS), wind direction (WD), temperature (T), and relative humidity (RH). Fifty percent (50%) of the data was used to train ANN models and the remaining data for cross-validation (25%) and for testing (25%). Multiple linear regression models were built using the training data. Four statistical criteria were used to evaluate the model’s predictive quality: the correlation coefficient (R), the index of agreement (d), the root mean square error (RMSE), and the mean absolute error (MAE). Statistical analysis demonstrated that the best predictive ability was obtained when the models (ANN and MLR) utilized all the input variables. The results demonstrated that the accuracy of ANN models, predicting the CUC of sprinkler irrigation systems, is higher than that of the MLR ones. During the training stage, the ANN models were more accurate in predicting CUC than MLR, with higher R (0.999) and d (0.999) values and lower MAE (0.167) and RMSE (0.456) values. The R values of the MLR model fluctuated between 0.226 and 0.960, the d values oscillated from 0.174 to 0.979, the MAE values were in the range of 2.458% and 10.792%, and the RMSE values fluctuated from 2.923% to 13.393%. Furthermore, the study revealed that WS and WD are the most influential climatic parameters. The ANN model can be used to develop more accurate tools for predicting the CUC of sprinkler irrigation systems. This can help farmers to design and operate their irrigation systems more efficiently, which can save them time and money.

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    Authors: Salem Marzougui; Mongi Ben Younes;

    Heading date, plant height, and spike-related phenotypes are key traits that affect the yield potential and adaptation of barley to Mediterranean environments. These traits are controlled by a complex network of genes as well as environmental effects. Marker-trait associations (MTAs) were performed using a set of 361 barley genotypes, evaluated phenotypically for three years under semi-arid conditions. In total, 24 MTAs were detected using the recently developed GWAS method (BLINK) at –log p ≥ 5. These included one MTA with awn length (Awl) on chromosome 2H; twelve MTAs with heading date (HD) distributed over all chromosomes except 4H; three MTAs with grains per spike (GPS) on chromosomes 1H, 2H, and 6H; six MTAs were detected for plant height (PH) on 2H (2), 3H, 4H, 6H, and 7H; and two MTAs with spike length (SL) on 3H and 7H. The results showed novel and known associations between specific SNP markers and heading date, plant height, and spike-related traits, suggesting that these markers can be used in breeding programs to improve these traits in barley. This study provides valuable information for breeders and geneticists working to develop new barley varieties that are better adapted to semi-arid climates and have improved yield and quality characteristics.

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      Agronomy
      Article . 2023 . Peer-reviewed
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    Authors: Elkadri Lefi; Mounawer Badri; Samouna Ben Hamed; Sihem Talbi; +3 Authors

    In this study, we evaluated the impact of brown seaweed extract (Ecklonia maxima) on the morphology and physiology of three different plant species. We conducted experiments using two types of fertilizers: an artificial fertilizer (0.1 g/L) and a biological extract of brown seaweed (Ecklonia maxima) at two concentrations (C1 at 1 mL/L and C2 at 2.5 mL/L). For melon, the application of C1 resulted in significant improvements in photosynthesis parameters, total chlorophyll content, and overall plant growth. When C2 was applied, it further enhanced these parameters, leading to a notable increase in shoot phytomass. In the case of cucumber, C1 led to increased resource allocation towards stems and leaves. Conversely, C2 increased the number of green leaves and contributed to higher shoot phytomass. For tomato plants, the application of C1 resulted in a slight increase in photosynthesis, but it did not significantly impact leaf growth. On the other hand, C2 induced a modest increase in photosynthesis, chlorophyll content, and root growth. In summary, our findings indicate that brown seaweed extract has a discernible influence on the physiology of the studied plants. However, the specific effects on resource allocation largely depend on the plant species and the concentration of the extract applied.

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    Agronomy
    Article . 2023 . Peer-reviewed
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    Agronomy
    Article . 2023
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      Agronomy
      Article . 2023 . Peer-reviewed
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      Agronomy
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    Authors: Taoufik Hermassi; Mohamed Lassaad Kotti; Fathia Jarray;

    Soil degradation and erosion in semi-arid regions can significantly impact agricultural development, environmental sustainability, and hydrological balance. Understanding the impacts of land use changes and soil and water conservation (SWC) technique implementation on soil erosion and sediment yield is critical to planning effective watershed management. This study aims to evaluate the impacts of environmental changes in the Merguellil watershed (Central Tunisia) over the last forty years. To achieve this, remote sensing techniques and a geographic information system (GIS) will be employed to classify Landsat images from 1980 to 2020. Additionally, the Revised Universal Soil Loss Equation model will be utilized to estimate soil erosion rates, while the sediment delivery distributed model will be employed for sediment yield modeling. Spatiotemporal changes in land use and land cover and in areas treated with SWC techniques were analyzed as the main factors influencing changes in erosion and sediment yield. The combined impact of land use change and SWC techniques resulted in a decrease in the annual soil erosion rate from 18 to 16 t/ha/year between 1980 and 2020 and in sediment yield from 9.65 to 8.95 t/ha/year for the same period. According to the model’s predictions, both soil erosion and sediment yield will experience a slight increase with further degradation of natural vegetation and a reduction in the efficiency of SWC works. This emphasizes the importance of continued efforts in adopting and sustaining SWC techniques, as well as preserving natural vegetation cover, to proactively combat soil degradation and its adverse effects on the environment and communities. Continuous dedication to these measures is crucial to preserving our ecosystem, promoting sustainable practices, and protecting the well-being of both the environment and society.

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    Applied Sciences
    Article . 2023
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    Applied Sciences
    Article . 2023 . Peer-reviewed
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      Applied Sciences
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      Applied Sciences
      Article . 2023 . Peer-reviewed
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    Authors: Hayet Beltayef; Mouna Mechri; Wafa Saidi; Taqi Raza; +7 Authors

    The overuse of chemical pesticides and fertilizers in crop farming has led to a decrease in crop quality and negative impacts on soil and the environment. It is crucial to adopt alternative strategies to maintain soil and environmental quality while enhancing crop growth and yield. To explore this, a study was conducted under greenhouse conditions to investigate the effect of Rhizobium tropici CIAT 899 alone, as well as in association with mycorrhizae (Rhizophagus irregularis) and endophytic fungus (Serendipita indica), on the growth, yield, and nutrient status of snap bean plants. At harvest, the rhizobial strain CIAT 899 demonstrated the highest effectiveness. It significantly increased the number of nodules in both Contender and Garrafal Enana varieties by 6.97% and 14.81%, respectively, compared with the control without inoculation. Furthermore, the results indicated that co-inoculation of Rhizobium and symbiotic fungi had positive effects on nitrogen content, phosphorus availability, and overall plant growth. Regardless of the variety, plants inoculated with R. tropici CIAT 899 and Serendipita indica exhibited the highest values for plant growth parameters. This combination resulted in 168% and 135% increases in root dry biomass, as well as 140% and 225% increases in the number of pods for Contender and Garrafal Enana, respectively, compared with the control at harvest. Additionally, this study highlights the potential benefits of combining R. tropici with either Serendipita indica or Rhizophagus irregularis in terms of nitrogen and phosphorus uptake. These symbiotic microorganisms demonstrated synergistic interactions with snap bean plants, leading to improved mineral nutrition and enhanced growth. Overall, these findings suggest that utilizing these symbiotic microorganisms can effectively enhance the mineral nutrition and growth of snap bean plants.

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    Agronomy
    Article . 2023
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    Agronomy
    Article . 2023 . Peer-reviewed
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      Agronomy
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      Agronomy
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    Authors: Sarra Salem; Aissam Gaagai; Imed Ben Slimene; Amor Moussa; +11 Authors

    In the Zeroud basin, a diverse array of methodologies were employed to assess, simulate, and predict the quality of groundwater intended for irrigation. These methodologies included the irrigation water quality indices (IWQIs); intricate statistical analysis involving multiple variables, supported with GIS techniques; an artificial neural network (ANN) model; and an XGBoost regression model. Extensive physicochemical examinations were performed on groundwater samples to elucidate their compositional attributes. The results showed that the abundance order of ions was Na+ > Ca2+ > Mg2+ > K+ and SO42− > HCO3− > Cl−. The groundwater facies reflected Ca-Mg-SO4, Na-Cl, and mixed Ca-Mg-Cl/SO4 water types. A cluster analysis (CA) and principal component analysis (PCA), along with ionic ratios, detected three different water characteristics. The mechanisms controlling water chemistry revealed water–rock interaction, dolomite dissolution, evaporation, and ion exchange. The assessment of groundwater quality for agriculture with respect IWQIs, such as the irrigation water quality index (IWQI), sodium adsorption ratio (SAR), sodium percentage (Na%), soluble sodium percentage (SSP), potential salinity (PS), and residual sodium carbonate (RSC), revealed that the domination of the water samples was valuable for agriculture. However, the IWQI and PS fell between high-to-severe restrictions and injurious-to-unsatisfactory. The ANN and XGBoost regression models showed robust results for predicting IWQIs. For example, ANN-HyC-9 emerged as the most precise forecasting framework according to its outcomes, as it showcased the most robust link between prime attributes and IWQI. The nine attributes of this model hold immense significance in IWQI prediction. The R2 values for its training and testing data stood at 0.999 (RMSE = 0.375) and 0.823 (RMSE = 3.168), respectively. These findings indicate that XGB-HyC-3 emerged as the most accurate forecasting model, displaying a stronger connection between IWQI and its exceptional characteristics. When predicting IWQI, approximately three of the model’s attributes played a pivotal role. Notably, the model yielded R2 values of 0.999 (RMSE = 0.001) and 0.913 (RMSE = 2.217) for the training and testing datasets, respectively. Overall, these results offer significant details for decision-makers in managing water quality and can support the long-term use of water resources.

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    Water
    Article . 2023 . Peer-reviewed
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    Water
    Article . 2023
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