Pesticide screening of surface water and soil along the Mekong River in Cambodia

Ngin, Putheary; Haglund, Peter; Proum, Sorya; Fick, Jerker

doi:10.1016/j.scitotenv.2023.169312

Cited by 3 publications

(1 citation statement)

References 66 publications

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“…Academic research highlights that many rivers, lakes, springs, and other surface water bodies, especially in densely populated areas, are extensively contaminated [3,4]. The irrigation of agricultural land with river water has been identified as a cause for the presence of various chemical substances in plants, which exhibit toxic and genotoxic activities [5,6]. A significant proportion of Kazakhstan rivers are continuously affected by pollution from heavy metals and organic substances [7][8][9].…”

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confidence: 99%

Mutagenic activity of water samples from Kaskelen River (Kazakhstan) on plant test systems

Jenisbayeva,

Lovinskaya,

Dauletbayeva

2024

BIO Web Conf.

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Rivers are pivotal in the life processes of all living organisms, including humans. The engagement of rivers in daily human economic endeavours has precipitated and continues to precipitate disturbances in the ecological equilibrium, long-established by the forces of evolution. Consequently, providing clean, high-quality water is paramount for sustaining all life forms. This investigation aimed to examine the mutagenic potential of water samples from the Kaskelen River, which is subjected to anthropogenic influences, employing plant-based test subjects. The water’s mutagenic properties were assessed through an assay for chromosomal aberrations (utilizing the metaphase approach) on Hordeum vulgare L. The results demonstrated a statistically significant decline in the mitotic index under all experimental conditions compared to the negative control (p<0.05), indicating the cytotoxic effects of the water samples under study. Further analysis of the water’s mutagenic activity elucidated its capacity to induce structural mutations within the root meristem cells of barley, manifesting a significant uptick in the frequency of chromosomal aberrations relative to the negative control (p<0.05). The extensive array of observed chromosomal rearrangements underscores the existence of mutagenic agents in the river’s water, possessing a broad spectrum of effects.

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Section: Introductionmentioning

confidence: 99%

Mutagenic activity of water samples from Kaskelen River (Kazakhstan) on plant test systems

Jenisbayeva,

Lovinskaya,

Dauletbayeva

2024

BIO Web Conf.

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Economic Fruit Trees Recognition in Hillsides: A CNN-Based Approach Using Enhanced UAV Imagery

Hooshyar,

Li,

Chun Tang

et al. 2024

IEEE Access

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Managing sloping terrains worldwide presents a significant challenge due to the lack of structured management practices, particularly when integrating various fruit trees in irregular arrangements. This study addresses the complexity arising from mixed cultivation by proposing a solution utilizing Unmanned Aerial Vehicle (UAV) imagery for tree species recognition and fruit tree classification. Our approach involves equipping UAVs with multispectral and optical cameras to capture imagery over experimental sloping terrain. The collected data undergoes processing for classifying different types of fruit trees, roads, and buildings through Orthophoto images. Convolutional Neural Networks (CNN) are employed for image recognition in challenging hillside terrains, with deep neural network methods, specifically VGG-16, VGG-19, and ResNet-50, being applied and compared. VGG-16 achieved significant accuracy in multispectral imagery analysis. Subsequently, various image fusion techniques, including Brovey, Hue-Saturation-Value, Principal Components Analysis (PCA), and Gram-Schmidt, were explored, with PCA demonstrating superior performance. The study revealed that image fusion, particularly with near-infrared or red-edge bands, significantly enhanced prediction accuracy compared to standalone multispectral imagery. The combination of visible-band fused imagery with additional spectral bands yielded the highest accuracy, improving overall prediction accuracy from 0.76 to 0.92. This research provides valuable insights applicable to diverse regions grappling with challenges in managing sloping terrains and mixed fruit tree cultivation.INDEX TERMS Convolutional neural network, fruit trees classification, image fusion, multispectral imagery, unmanned aerial vehicle.

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Concentrations of Organochlorine, Organophosphorus, and Pyrethroid Pesticides in Rivers Worldwide (2014–2024): A Review

López-Benítez,

Guevara-Lara,

Domínguez-Crespo

et al. 2024

Sustainability

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The extensive use of pesticides has led to the contamination of natural resources, sometimes causing significant and irreversible damage to the environment and human health. Even though the use of many pesticides is banned, these compounds are still being found in rivers worldwide. In this review, 205 documents have been selected to provide an overview of pesticide contamination in rivers over the last 10 years (2014–2024). After these documents were examined, information of 47 river systems was organized according to the types of pesticides most frequently detected, including organochloride, organophosphorus, and pyrethroid compounds. A total of 156 compounds were classified, showing that 46% of these rivers contain organochlorine compounds, while 40% exhibit organophosphorus pesticides. Aldrin, hexachlorocyclohexane, and endosulfan were the predominant organochlorine pesticides with concentration values between 0.4 and 37 × 105 ng L−1. Chlorpyrifos, malathion, and diazinon were the main organophosphorus pesticides with concentrations between 1 and 11 × 105 ng L−1. Comparing the pesticide concentrations with standard guidelines, we found that the Ganga River in India (90 ng L−1), the Owan and Okura Rivers in Nigeria (210 and 9 × 103 ng L−1), and the Dong Nai River in Vietnam (68 ng L−1) exceed the permissible levels of aldrin (30 ng L−1).

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Pesticide screening of surface water and soil along the Mekong River in Cambodia

Cited by 3 publications

References 66 publications

Mutagenic activity of water samples from Kaskelen River (Kazakhstan) on plant test systems

Mutagenic activity of water samples from Kaskelen River (Kazakhstan) on plant test systems

Economic Fruit Trees Recognition in Hillsides: A CNN-Based Approach Using Enhanced UAV Imagery

Concentrations of Organochlorine, Organophosphorus, and Pyrethroid Pesticides in Rivers Worldwide (2014–2024): A Review

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