Displaying publications 61 - 80 of 597 in total

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  1. Exploring the potential of vermicompost as a sustainable strategy in circular economy: improving plants' bioactive properties and boosting agricultural yield and quality
    Kamar Zaman AM, Yaacob JS
    Environ Sci Pollut Res Int, 2022 Feb;29(9):12948-12964.
    PMID: 35034296 DOI: 10.1007/s11356-021-18006-z
    Consumption of natural resources and waste generation continues to rise as the human population increases. Ever since the industrial revolution, consumers have been adopting a linear economy model based on the 'take-make-dispose' approach. Raw materials are extracted to be converted into products and finally discarded as wastes. Consequently, this practice is unsustainable because it causes a massive increase in waste production. The root problems of the linear system can be addressed by transitioning to a circular economy. Circular economy is an economic model in which wastes from one product are recycled and used as resources for other processes. This literature review discovers the potential of vermicompost as a sustainable strategy in circular economy and highlights the benefits of vermicompost in ensuring food security, particularly in improving agricultural yield and quality, as well as boosting crop's nutritional quality. Vermicompost has the potential to be used in a variety of ways in the circular economy, including for agricultural sustainability, managing waste, pollutant remediation, biogas production and animal feed production. The recycling of organic wastes to produce vermicompost can benefit both the consumers and environment, thus paving the way towards a more sustainable agriculture for the future.
    Matched MeSH terms: Agriculture*
  2. Fulltext Microbial Contributions for Rice Production: From Conventional Crop Management to the Use of 'Omics' Technologies
    Doni F, Suhaimi NSM, Mispan MS, Fathurrahman F, Marzuki BM, Kusmoro J, et al.
    Int J Mol Sci, 2022 Jan 10;23(2).
    PMID: 35054923 DOI: 10.3390/ijms23020737
    Rice, the main staple food for about half of the world's population, has had the growth of its production stagnate in the last two decades. One of the ways to further improve rice production is to enhance the associations between rice plants and the microbiome that exists around, on, and inside the plant. This article reviews recent developments in understanding how microorganisms exert positive influences on plant growth, production, and health, focusing particularly on rice. A variety of microbial species and taxa reside in the rhizosphere and the phyllosphere of plants and also have multiple roles as symbiotic endophytes while living within plant tissues and even cells. They alter the morphology of host plants, enhance their growth, health, and yield, and reduce their vulnerability to biotic and abiotic stresses. The findings of both agronomic and molecular analysis show ways in which microorganisms regulate the growth, physiological traits, and molecular signaling within rice plants. However, many significant scientific questions remain to be resolved. Advancements in high-throughput multi-omics technologies can be used to elucidate mechanisms involved in microbial-rice plant associations. Prospectively, the use of microbial inoculants and associated approaches offers some new, cost-effective, and more eco-friendly practices for increasing rice production.
    Matched MeSH terms: Agriculture
  3. Sustainable approaches for removing Rhodamine B dye using agricultural waste adsorbents: A review
    Al-Gheethi AA, Azhar QM, Senthil Kumar P, Yusuf AA, Al-Buriahi AK, Radin Mohamed RMS, et al.
    Chemosphere, 2022 Jan;287(Pt 2):132080.
    PMID: 34509011 DOI: 10.1016/j.chemosphere.2021.132080
    Rhodamine B (RhB) is among the toxic dyes due to the carcinogenic, neurotoxic effects and ability to cause several diseases for humans. The adsorption with agricultural waste adsorbent recorded high performance for the RhB removal. The current review aimed to explore the efficiency of different adsorbents which have been used in the few last years for removing RhB dye from wastewater. The data of adsorption of RhB using agricultural wastes were collected from the Scopus database in the period between 2015 and 2021. The use of agricultural wastes and adsorbents as a replacement for the activated has received high attention among researchers. The RhB removal methods by microbial enzymes and biomass occurred between 76 and 90.1%. In comparison, the adsorption with agricultural wastes such as activated carbon white sugar reached 98% within 12 min. The adsorption process has a wide range of pH (3-10) due to the zwitterionic forms of RhB. Gmelina aborea leaf activated carbon is among the agriculture wastes absorbents that exhibited 1000 mg g-1 of the adsorption capacity. It appeared that the agricultural wastes adsorbents have a high potential for removing RhB from the wastewater.
    Matched MeSH terms: Agriculture
  4. Advances in solid-state fermentation for bioconversion of agricultural wastes to value-added products: Opportunities and challenges
    Chilakamarry CR, Mimi Sakinah AM, Zularisam AW, Sirohi R, Khilji IA, Ahmad N, et al.
    Bioresour Technol, 2022 Jan;343:126065.
    PMID: 34624472 DOI: 10.1016/j.biortech.2021.126065
    The increase in solid waste has become a common problem and causes environmental pollution worldwide. A green approach to valorise solid waste for sustainable development is required. Agricultural residues are considered suitable for conversion into profitable products through solid-state fermentation (SSF). Agricultural wastes have high organic content that is used as potential substrates to produce value-added products through SSF. The importance of process variables used in solid-phase fermentation is described. The applications of SSF developed products in the food industry as flavouring agents, acidifiers, preservatives and flavour enhancers. SSF produces secondary metabolites and essential enzymes. Wastes from agricultural residues are used as bioremediation agents, biofuels and biocontrol agents through microbial processing. In this review paper, the value addition of agricultural wastes by SSF through green processing is discussed with the current knowledge on the scenarios, sustainability opportunities and future directions of a circular economy for solid waste utilisation.
    Matched MeSH terms: Agriculture
  5. Fulltext Data-driven models for atmospheric air temperature forecasting at a continental climate region
    Alomar MK, Khaleel F, Aljumaily MM, Masood A, Razali SFM, AlSaadi MA, et al.
    PLoS One, 2022;17(11):e0277079.
    PMID: 36327280 DOI: 10.1371/journal.pone.0277079
    Atmospheric air temperature is the most crucial metrological parameter. Despite its influence on multiple fields such as hydrology, the environment, irrigation, and agriculture, this parameter describes climate change and global warming quite well. Thus, accurate and timely air temperature forecasting is essential because it provides more important information that can be relied on for future planning. In this study, four Data-Driven Approaches, Support Vector Regression (SVR), Regression Tree (RT), Quantile Regression Tree (QRT), ARIMA, Random Forest (RF), and Gradient Boosting Regression (GBR), have been applied to forecast short-, and mid-term air temperature (daily, and weekly) over North America under continental climatic conditions. The time-series data is relatively long (2000 to 2021), 70% of the data are used for model calibration (2000 to 2015), and the rest are used for validation. The autocorrelation and partial autocorrelation functions have been used to select the best input combination for the forecasting models. The quality of predicting models is evaluated using several statistical measures and graphical comparisons. For daily scale, the SVR has generated more accurate estimates than other models, Root Mean Square Error (RMSE = 3.592°C), Correlation Coefficient (R = 0.964), Mean Absolute Error (MAE = 2.745°C), and Thiels' U-statistics (U = 0.127). Besides, the study found that both RT and SVR performed very well in predicting weekly temperature. This study discovered that the duration of the employed data and its dispersion and volatility from month to month substantially influence the predictive models' efficacy. Furthermore, the second scenario is conducted using the randomization method to divide the data into training and testing phases. The study found the performance of the models in the second scenario to be much better than the first one, indicating that climate change affects the temperature pattern of the studied station. The findings offered technical support for generating high-resolution daily and weekly temperature forecasts using Data-Driven Methodologies.
    Matched MeSH terms: Agriculture
  6. Fulltext The new abnormal: Identifying and ranking anomalies in the land trade market
    Interdonato R, Bourgoin J, Grislain Q, Tagarelli A
    PLoS One, 2022;17(12):e0277608.
    PMID: 36454792 DOI: 10.1371/journal.pone.0277608
    Large-scale national and transnational commercial land transactions, or Large-Scale Land Acquisitions (LSLAs), have been gaining a lot of academic attention since the late 2000s and since the reported rush for land, resulting in turn from an increase in demand for arable land. If many data exist to characterize land deals, the analysis of investment networks remain limited and predominantly portrays power asymmetries between countries from the Global North investing in the Global South. The aim of this work is to perform a deeper investigation on the land trade market, specifically focusing on cases that do not follow such narratives. For instance, almost 25% of the countries included in the transnational land trade network do not follow a strict investor/target dichotomy, thus being characterized by a double role, i.e., they both acquire and cede land in the transnational context. In order to globally acknowledge for what was currently considered as abnormal cases, we model open access data about LSLAs extracted from the Land Matrix Initiative (LMI) open-access database into a network graph, and adapt an eigenvector based centrality method originally conceived for online social networks, namely LurkerRank, to identify and rank anomalous profiles in the land trade market. We take into account three different network snapshots: a multi-sector network (including all the transnational deals in the LMI database), and three networks referring to specific investment sectors (agriculture,mines and biofuels). Experimental results show that emerging economies (e.g., China and Malaysia) play a central role in the land trade market, by creating alternative dynamics that escape the classic North/South one. Our analyses also show how African countries that are often seen as targets of land trade transactions in a specific sector, may often acquire foreign land in the context of investments in the same sector (i.e., Zimbabwe for biofuels and the Democratic Republic of Congo for the mining sector).
    Matched MeSH terms: Agriculture*
  7. Fulltext Impact of organization decision making styles and safety accountability on occupational health and safety implementation: The moderating role of mimetic motives
    Nadeem MA, Surienty L, Haque MM
    Front Public Health, 2022;10:1004767.
    PMID: 36452948 DOI: 10.3389/fpubh.2022.1004767
    The agriculture sector is a traditional economic pillar of many emerging economies. However, it is facing greater occupational health and safety (OHS) challenges in Pakistan, and its performance is continuously decreasing. An effective OHS implementation provides better control over OHS challenges and may help to restore its former glory. Therefore, this study aims to explore different organizational decision-making styles and safety accountability to put OHS into practice in this sector. Based on institutional theory, a theoretical framework was developed. Two hundred and eighty-seven agriculture farms in Punjab, Pakistan were surveyed and analyzed using SmartPLS 3.3.7. The findings revealed that implementation styles (rational and incremental) and safety accountability positively impact OHS implementation. Similarly, the moderating role of mimetic motives was found positively significant in the relationship between rational style and OHS implementation, and negatively significant in the relationship between incremental style and OHS implementation. While no moderating effect of mimetic motive was found between safety accountability and OHS implementation. This study suggested that OHS implementation should not be viewed as a social or technical issue alone. Strategic arrangements should be made at the organizational level to gain better control over OHS challenges by considering the institutional environment in which the organization operates.
    Matched MeSH terms: Agriculture
  8. Trade-related water scarcity risk under the Belt and Road Initiative
    Wang L, Li Y, Liang S, Xu M, Qu S
    Sci Total Environ, 2021 Dec 20;801:149781.
    PMID: 34467898 DOI: 10.1016/j.scitotenv.2021.149781
    Increasing trade cooperation under the Belt and Road (B&R) Initiative has promoted economic development and intensified the water scarcity risk transmission between China and countries along the route (B&R countries). Local water scarcity risk (LWSR, the potential direct production losses induced by local water scarcity) can transcend geographical boundaries through global supply chains and influence production activities in downstream economies. To understand the vulnerability of the Initiative to water scarcity, we investigated the impacts of LWSR in China and B&R countries on each other's economies during 2001-2013, using a global environmentally extended multi-regional input-output model. Results reveal that more than 80% of China's trade-related water scarcity risk imports (TWSR imports, the vulnerability to foreign water scarcity risk through imports) originates from B&R countries. The share of TWSR from China in total imports of B&R countries has steadily increased. In particular, India, Thailand, Iran, Pakistan and Kazakhstan have the largest TWSR exports (LWSR in each nation transmitted to other nations through its exports) to China, while South Korea, Thailand, Malaysia, Singapore and Indonesia have the largest imports from China. Water scarcity to their Agriculture sectors is responsible for TWSR transmission between them. Our study can contribute to the policy-making of governments and firms involved in mitigating the supply chain wide water scarcity risk. It also reveals the need for nations to collectively manage water resources to achieve sustainable development.
    Matched MeSH terms: Agriculture
  9. Short and long-run causal effects of agriculture, forestry, and other land use on greenhouse gas emissions: evidence from China using VECM approach
    Si R, Aziz N, Raza A
    Environ Sci Pollut Res Int, 2021 Dec;28(45):64419-64430.
    PMID: 34312755 DOI: 10.1007/s11356-021-15474-1
    Climate change caused by different anthropogenic activities is a subject of attention globally. There is a concern on how to maintain a clean environment and at the same time achieve optimal use of land. To this end, this study examines the causal effects of land use including agricultural, forestry, and other land categories on greenhouse gas (GHG) emissions. The data for China is collected over the period 1990 to 2012 for the empirical examination. By employing vector error correction model (VECM), it is found that there is significant long-run causality among variables. However, in the short run expectedly, only land under agriculture has strong causality with the GHG emissions. The results in case of variance decomposition analysis highlight that land under agriculture and other use significantly causes the GHG emissions in the long run. Further, impulse responses of variables are also measured with the Cholesky one standard deviation. The results are robust and support the argument that different land uses cause GHG emissions in China. The study provides insights for policy makers to improve the activities occurring on agricultural and other land uses. Assessment of overall potential, including bio energy, needs to include analysis of trade-offs and feedbacks with land-use competition. Many positive linkages with sustainable development and with adaptation exist but are case and site specific as they depend on scale, scope, and pace of implementation.
    Matched MeSH terms: Agriculture
  10. Proposing an ecologically viable and economically sound farming system using a matrix-based geo-informatics approach
    Senanayake S, Pradhan B, Huete A, Brennan J
    Sci Total Environ, 2021 Nov 10;794:148788.
    PMID: 34323751 DOI: 10.1016/j.scitotenv.2021.148788
    Healthy farming systems play a vital role in improving agricultural productivity and sustainable food production. The present study aimed to propose an efficient framework to evaluate ecologically viable and economically sound farming systems using a matrix-based analytic hierarchy process (AHP) and weighted linear combination method with geo-informatics tools. The proposed framework has been developed and tested in the Central Highlands of Sri Lanka. Results reveal that more than 50% of farming systems demonstrated moderate status in terms of ecological and economic aspects. However, two vulnerable farming systems on the western slopes of the Central Highlands, named WL1a and WM1a, were identified as very poor status. These farming systems should be a top priority for restoration planning and soil conservation to prevent further deterioration. Findings indicate that a combination of ecologically viable (nine indicators) and economical sound (four indicators) criteria are a practical method to scrutinize farming systems and decision making on soil conservation and sustainable land management. In addition, this research introduces a novel approach to delineate the farming systems based on agro-ecological regions and cropping areas using geo-informatics technology. This framework and methodology can be employed to evaluate the farming systems of other parts of the country and elsewhere to identify ecologically viable and economically sound farming systems concerning soil erosion hazards. The proposed approach addresses a new dimension of the decision-making process by evaluating the farming systems relating to soil erosion hazards and suggests introducing policies on priority-based planning for conservation with low-cost strategies for sustainable land management.
    Matched MeSH terms: Agriculture*
  11. Fulltext Optimal virtual water flows for improved food security in water-scarce countries
    Maroufpoor S, Bozorg-Haddad O, Maroufpoor E, Gerbens-Leenes PW, Loáiciga HA, Savic D, et al.
    Sci Rep, 2021 10 25;11(1):21027.
    PMID: 34697363 DOI: 10.1038/s41598-021-00500-6
    The worsening water scarcity has imposed a significant stress on food production in many parts of the world. This stress becomes more critical when countries seek self-sufficiency. A literature review shows that food self-sufficiency has not been assessed as the main factor in determining the optimal cultivation patterns. However, food self-sufficiency is one of the main policies of these countries and requires the most attention and concentration. Previous works have focused on the virtual water trade to meet regional food demand and to calculate trade flows. The potential of the trade network can be exploited to improve the cropping pattern to ensure food and water security. To this end, and based on the research gaps mentioned, this study develops a method to link intra-country trade networks, food security, and total water footprints (WFs) to improve food security. The method is applied in Iran, a water-scarce country. The study shows that 781 × 106 m3 of water could be saved by creating a trade network. Results of the balanced trade network are input to a multi-objective optimization model to improve cropping patterns based on the objectives of achieving food security and preventing water crises. The method provides 400 management scenarios to improve cropping patterns considering 51 main crops in Iran. Results show a range of improvements in food security (19-45%) and a decrease in WFs (2-3%). The selected scenario for Iran would reduce the blue water footprint by 1207 × 106 m3, and reduce the cropland area by 19 × 103 ha. This methodology allows decision makers to develop policies that achieve food security under limited water resources in arid and semi-arid regions.
    Matched MeSH terms: Agriculture
  12. Fulltext Drought Vulnerability Assessment Using Geospatial Techniques in Southern Queensland, Australia
    Hoque M, Pradhan B, Ahmed N, Alamri A
    Sensors (Basel), 2021 Oct 18;21(20).
    PMID: 34696109 DOI: 10.3390/s21206896
    In Australia, droughts are recurring events that tremendously affect environmental, agricultural and socio-economic activities. Southern Queensland is one of the most drought-prone regions in Australia. Consequently, a comprehensive drought vulnerability mapping is essential to generate a drought vulnerability map that can help develop and implement drought mitigation strategies. The study aimed to prepare a comprehensive drought vulnerability map that combines drought categories using geospatial techniques and to assess the spatial extent of the vulnerability of droughts in southern Queensland. A total of 14 drought-influencing criteria were selected for three drought categories, specifically, meteorological, hydrological and agricultural. The specific criteria spatial layers were prepared and weighted using the fuzzy analytical hierarchy process. Individual categories of drought vulnerability maps were prepared from their specific indices. Finally, the overall drought vulnerability map was generated by combining the indices using spatial analysis. Results revealed that approximately 79.60% of the southern Queensland region is moderately to extremely vulnerable to drought. The findings of this study were validated successfully through the receiver operating characteristics curve (ROC) and the area under the curve (AUC) approach using previous historical drought records. Results can be helpful for decision makers to develop and apply proactive drought mitigation strategies.
    Matched MeSH terms: Agriculture*
  13. Omics technologies used in pesticide residue detection and mitigation in crop
    Goh MS, Lam SD, Yang Y, Naqiuddin M, Addis SNK, Yong WTL, et al.
    J Hazard Mater, 2021 10 15;420:126624.
    PMID: 34329083 DOI: 10.1016/j.jhazmat.2021.126624
    In agriculture, the convenience and efficacy of chemical pesticides have become inevitable to manage cultivated crop production. Here, we review the worldwide use of pesticides based on their categories, mode of actions and toxicity. Excessive use of pesticides may lead to hazardous pesticide residues in crops, causing adverse effects on human health and the environment. A wide range of high-tech-analytical methods are available to analyse pesticide residues. However, they are mostly time-consuming and inconvenient for on-site detection, calling for the development of biosensors that detect cellular changes in crops. Such new detection methods that combine biological and physicochemical knowledge may overcome the shortage in current farming to develop sustainable systems that support environmental and human health. This review also comprehensively compiles domestic pesticide residues removal tips from vegetables and fruits. Synthetic pesticide alternatives such as biopesticide and nanopesticide are greener to the environment. However, its safety assessment for large-scale application needs careful evaluation. Lastly, we strongly call for reversions of pesticide application trends based on the changing climate, which is lacking in the current scenario.
    Matched MeSH terms: Agriculture
  14. Farmers' attitudes towards GM crops and their predictors
    Mustapa MAC, Batcha MFN, Amin L, Arham AF, Mahadi Z, Yusoff NAM, et al.
    J Sci Food Agric, 2021 Oct;101(13):5457-5468.
    PMID: 33709409 DOI: 10.1002/jsfa.11194
    BACKGROUND: Genetically modified (GM) crops have become a controversial global issue since their commercialization in 1996. However, despite technological advancements, only a few studies have investigated farmers' attitudes towards GM crops in Malaysia. Therefore, this study aims to analyse such attitudes and their determining factors. A validated questionnaire was distributed to farmers in the Cameron Highlands, Pahang (n = 176). SPSS software was used to analyse the descriptive statistics of the farmers' attitudes to GM crops, while SmartPLS software was used to determine the predictors.

    RESULTS: Descriptive analysis shows that the farmers claimed to have a high level of self-efficacy, and perceived GM crops as possessing high benefits which translate into a highly positive attitude towards GM crops. However, at the same time, they rated GM crops as involving moderate risks and would incur moderate costs to farm, as well as acknowledging a low level of support from the government. The structural equation model (SEM) analysis demonstrates that five factors have been identified as direct predictors of attitude to GM crops: government support (ß = 0.364, P 

    Matched MeSH terms: Agriculture/economics
  15. Improving sustainability and mitigating environmental impacts of agro-biowaste compost fertilizer by pelletizing-drying
    Sarlaki E, Kermani AM, Kianmehr MH, Asefpour Vakilian K, Hosseinzadeh-Bandbafha H, Ma NL, et al.
    Environ Pollut, 2021 Sep 15;285:117412.
    PMID: 34051566 DOI: 10.1016/j.envpol.2021.117412
    The use of agro-biowaste compost fertilizers in agriculture is beneficial from technical, financial, and environmental perspectives. Nevertheless, the physical, mechanical, and agronomical attributes of agro-biowaste compost fertilizers should be engineered to reduce their storage, handling, and utilization costs and environmental impacts. Pelletizing and drying are promising techniques to achieve these goals. In the present work, the effects of process parameters, including compost particle size/moisture content, pelletizing compression ratio, and drying air temperature/velocity, were investigated on the density, specific crushing energy, and moisture diffusion of agro-biowaste compost pellet. The Taguchi technique was applied to understand the effects of independent parameters on the output responses, while the optimal pellet properties were found using the iterative thresholding method. The soil and plant (sweet basil) response to the optimal biocompost pellet was experimentally evaluated. The farm application of the optimal pellet was also compared with the untreated agro-biowaste compost using the life cycle assessment approach to investigate the potential environmental impact mitigation of the pelletizing and drying processes. Generally, the compost moisture content was the most influential factor on the density and specific crushing energy of the dried pellet, while the moisture diffusion of the wet pellet during the drying process was significantly influenced by the pelletizing compression ratio. The density, specific crushing energy, and moisture diffusion of agro-biowaste compost pellet at the optimal conditions were 1242.49 kg/m3, 0.5054 MJ/t, and 8.2 × 10-8 m2/s, respectively. The optimal biocompost pellet could release 80% of its nitrogen content evenly over 98 days, while this value was 28 days for the chemical urea fertilizer. Besides, the optimal pellet could significantly improve the agronomical attributes of the sweet basil plant compared with the untreated biocompost. The applied strategy could collectively mitigate the weighted environmental impact of farm application of the agro-biowaste compost by more than 63%. This reduction could be attributed to the fact that the pelletizing-drying processes could avoid methane emissions from the untreated agro-biowaste compost during the farm application. Overall, pelletizing-drying of the agro-biowaste compost could be regarded as a promising strategy to improve the environmental and agronomical performance of farm application of organic biofertilizers.
    Matched MeSH terms: Agriculture
  16. Fulltext Deep Q-Learning and Preference Based Multi-Agent System for Sustainable Agricultural Market
    Pérez-Pons ME, Alonso RS, García O, Marreiros G, Corchado JM
    Sensors (Basel), 2021 Aug 04;21(16).
    PMID: 34450717 DOI: 10.3390/s21165276
    Yearly population growth will lead to a significant increase in agricultural production in the coming years. Twenty-first century agricultural producers will be facing the challenge of achieving food security and efficiency. This must be achieved while ensuring sustainable agricultural systems and overcoming the problems posed by climate change, depletion of water resources, and the potential for increased erosion and loss of productivity due to extreme weather conditions. Those environmental consequences will directly affect the price setting process. In view of the price oscillations and the lack of transparent information for buyers, a multi-agent system (MAS) is presented in this article. It supports the making of decisions in the purchase of sustainable agricultural products. The proposed MAS consists of a system that supports decision-making when choosing a supplier on the basis of certain preference-based parameters aimed at measuring the sustainability of a supplier and a deep Q-learning agent for agricultural future market price forecast. Therefore, different agri-environmental indicators (AEIs) have been considered, as well as the use of edge computing technologies to reduce costs of data transfer to the cloud. The presented MAS combines price setting optimizations and user preferences in regards to accessing, filtering, and integrating information. The agents filter and fuse information relevant to a user according to supplier attributes and a dynamic environment. The results presented in this paper allow a user to choose the supplier that best suits their preferences as well as to gain insight on agricultural future markets price oscillations through a deep Q-learning agent.
    Matched MeSH terms: Agriculture*
  17. Metal-organic frameworks for pesticidal persistent organic pollutants detection and adsorption - A mini review
    Wagner M, Andrew Lin KY, Oh WD, Lisak G
    J Hazard Mater, 2021 07 05;413:125325.
    PMID: 33601143 DOI: 10.1016/j.jhazmat.2021.125325
    The global population growth demands intensification of anthropogenic processes, thus leading to inter alia pollution of both land and aquatic environments with toxic organic compounds. Particularly harmful synthetic compounds are classified as persistent organic pollutants (POPs). Their relatively high chemical resistance resulted in a worldwide ban or strict control on the use of POPs. The majority of POPs were commonly used as pesticides, and unfortunately, some of them are still utilized as an aid in agricultural practices. Therefore, environmental monitoring in terms of reliable detection and quantification of pesticidal POPs is an ever-increasing need. Chemical sensors and adsorption materials crafted for specific pesticide operate on host-guest interactions should provide selectivity and sensitivity, thus leading to the detection of target molecule down to the nanomolar range. This could be achieved with materials exhibiting a very large active surface area, well-defined structure, and high stability. The novel materials studied in that context are metal-organic frameworks (MOFs). The structure of various MOFs can be functionalized to provide desired host-guest interactions. In this mini-review, we critically discuss the application of MOFs for the detection and adsorption of selected pesticides that are classified as POPs according to the Stockholm Convention.
    Matched MeSH terms: Agriculture
  18. Fulltext Dielectric response of nitrogen in soil amended with chicken litter biochar and urea under Oryza sativa L. cultivation
    Maru A, Ahmed OH, Primus WC, Jeffary AV
    Sci Rep, 2021 06 15;11(1):12545.
    PMID: 34131184 DOI: 10.1038/s41598-021-91426-6
    Unbalanced utilization of nitrogen (N) rice not economically viable neither is this practice environmental friendly. Co-application of biochar and urea could reduce the unbalanced use of this N fertilizer in rice cultivation. Thus, a field study was carried out to: (i) determine the effects of chicken litter biochar and urea fertilization on N concentration in soil solution of a cultivated rice (MR219) using dielectric measurement at a low frequency and (ii) correlate soil dielectric conductivity with rice grain yield at maturity. Dielectric response of the soil samples at 20, 40, 55, and 75 days after transplanting were determined using an inductance-capacitance-resistance meter HIOKI 3522-50 LCR HiTESTER. Selected soil chemical properties and yield were determined using standard procedures. The dielectric conductivity and permittivity of the soil samples measured before transplanting the rice seedlings were higher than those for the soil samples after transplanting. This was due to the inherent nitrogen of the chicken litter biochar and the low nitrogen uptake at the transplanting stage. The soil N response increased with increasing measurement frequency and N concentration. The permittivity of the soil samples was inversely proportional to frequency but directly proportional to N concentration in the soil solution. The estimated contents of N in the soil using the dielectric conductivity approach at 1000 Hz decreased with increasing days of fertilization and the results were similar to those of soil NH4+ determined using chemical analysis. The conductivity measured within 1000 Hz and 100,000 Hz correlated positively with the rice grain yield suggesting that nitrogen concentration of the soil can be used to estimate grain yield of the cultivated rice plants.
    Matched MeSH terms: Agriculture
  19. Fulltext Recent Advances on Detection of Insecticides Using Optical Sensors
    Fauzi NIM, Fen YW, Omar NAS, Hashim HS
    Sensors (Basel), 2021 Jun 03;21(11).
    PMID: 34204853 DOI: 10.3390/s21113856
    Insecticides are enormously important to industry requirements and market demands in agriculture. Despite their usefulness, these insecticides can pose a dangerous risk to the safety of food, environment and all living things through various mechanisms of action. Concern about the environmental impact of repeated use of insecticides has prompted many researchers to develop rapid, economical, uncomplicated and user-friendly analytical method for the detection of insecticides. In this regards, optical sensors are considered as favorable methods for insecticides analysis because of their special features including rapid detection time, low cost, easy to use and high selectivity and sensitivity. In this review, current progresses of incorporation between recognition elements and optical sensors for insecticide detection are discussed and evaluated well, by categorizing it based on insecticide chemical classes, including the range of detection and limit of detection. Additionally, this review aims to provide powerful insights to researchers for the future development of optical sensors in the detection of insecticides.
    Matched MeSH terms: Agriculture
  20. Baseline distribution and sources of selected agricultural runoff in the bottom water of an active cockle farming area, Bagan Pasir, Perak, Malaysia
    Joni AAM, Mohamat-Yusuff F, Noor NAM, Mohamed KN, Ash'aari ZH, Kusin FM, et al.
    Mar Pollut Bull, 2021 Jun;167:112276.
    PMID: 33901978 DOI: 10.1016/j.marpolbul.2021.112276
    This paper aims to study the spatial and temporal patterns of selected agricultural runoff, specifically in terms of glyphosate, nitrate, and ammonia in bottom water, as well as their possible sources, within an active cockle farming area in Bagan Pasir, Perak, Malaysia. Samples were taken along the cockle farming area from March to November 2019. Glyphosate was analyzed using HPLC with both extraction and derivatization methods using 9-fluorenyl-methyl chloroformate (FMOC-Cl), while nitrate and ammonia levels were determined using the standard Hach method. Generally, glyphosate, nitrate, and ammonia were present within the study site with the average concentration of 37.44 ± 12.27 μg/l, 1.65 ± 0.52 mg/l, and 0.37 ± 0.19 mg/l, respectively. The results suggest that glyphosate and nitrate might be derived from an inland source, while a uniform and low level of ammonia suggested might originate from lithogenic origins. Continuous monitoring remains encouraged.
    Matched MeSH terms: Agriculture
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