Recycling and Elimination of Wastes obtained from Agriculture by using Nanotechnology: Nanosensors

Ma, Alvarado; On, Guzmán; Nm, Solís; Vega-Baudrit, José Roberto

doi:10.15406/ijbsbe.2017.03.00084

Cited by 7 publications

(2 citation statements)

References 33 publications

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“…The efficacy of silica nanoparticles (SiO 2 -NPs) applications in agriculture is increasing rapidly, which can help mitigate both biotic and abiotic stresses, providing new solutions to problems in plants and crop science to enhance the quality of plant products more efficiently [9]. Many agricultural wastes, such as rice husk, barley grass waste, and sugarcane bagasse, can be processed and used as a raw material for green synthesis of SiO 2 -NPs, conserving environment quality and lowering the agriculture sector's carbon footprint [10,11]. The small size, greater surface area, higher solubility, and surface reactivity of SiO 2 -NPs are unique physico-chemical features that result in greater and easier nutrient absorption by plants [12].…”

Section: Introductionmentioning

confidence: 99%

Suppression of Bacterial Leaf Spot by Green Synthesized Silica Nanoparticles and Antagonistic Yeast Improves Growth, Productivity and Quality of Sweet Pepper

Awad-Allah

Shams

Helaly

2021

Plants

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Plants are challenged with many kinds of biotic stresses caused by different living organisms, which result in various types of diseases, infections, and damage to crop plants and ultimately affect crop productivity. Plant disease management strategies based on current approaches are necessary for sustainable agriculture. A pot experiment was carried out under greenhouse conditions to evaluate the potential of green synthesized silica nanoparticles (SiO2-NPs) and antagonistic yeast (Saccharomyces cerevisiae) against pepper bacterial leaf spot disease, caused by Xanthomonas vesicatoria. In addition, to assess their efficacy and suppressive effects in reducing disease severity and improving sweet pepper growth, productivity, and quality. Results revealed that the combination of BCA (5%) and SiO2-NPs (150 ppm) was the most effective treatment for reducing disease severity and improving vegetative growth characters, mineral contents (N, P, K, Ca, Mg, and Si in leaves), as well as stimulating polyphenol oxidase (PPO) activity of sweet pepper leaves at 90 days from transplanting, while also at harvesting time enhancing sweet pepper fruit yield quality parameters significantly. In conclusion, green synthesized silica nanoparticles combined with antagonistic yeast have the potential to suppress a bacterial leaf spot disease with ecologically-sound management, while also boosting sweet pepper growth, productivity, and quality.

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Section: Introductionmentioning

confidence: 99%

Suppression of Bacterial Leaf Spot by Green Synthesized Silica Nanoparticles and Antagonistic Yeast Improves Growth, Productivity and Quality of Sweet Pepper

Awad-Allah

Shams

Helaly

2021

Plants

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“…The application of nanosensors to agriculture and the related fields of food and environmental monitoring have been reported in a number of review articles. [13,[129][130][131][132][133] Nanosensors have been proposed as a method for the rapid and effective analysis of a range of biological, chemical and physical factors in food [134] and agricultural [135] and environmental [136] samples, for the analysis of agrowastes [137] and for the control of irrigation systems [138].…”

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confidence: 99%

Machine Learning Techniques for Improving Nanosensors in Agroenvironmental Applications

Arellano Vidal,

Govan

2024

Agronomy

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Nanotechnology, nanosensors in particular, has increasingly drawn researchers’ attention in recent years since it has been shown to be a powerful tool for several fields like mining, robotics, medicine and agriculture amongst others. Challenges ahead, such as food availability, climate change and sustainability, have promoted such attention and pushed forward the use of nanosensors in agroindustry and environmental applications. However, issues with noise and confounding signals make the use of these tools a non-trivial technical challenge. Great advances in artificial intelligence, and more particularly machine learning, have provided new tools that have allowed researchers to improve the quality and functionality of nanosensor systems. This short review presents the latest work in the analysis of data from nanosensors using machine learning for agroenvironmental applications. It consists of an introduction to the topics of nanosensors and machine learning and the application of machine learning to the field of nanosensors. The rest of the paper consists of examples of the application of machine learning techniques to the utilisation of electrochemical, luminescent, SERS and colourimetric nanosensor classes. The final section consists of a short discussion and conclusion concerning the relevance of the material discussed in the review to the future of the agroenvironmental sector.

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Sustainable Recycling and Valorization of Organic Solid Wastes for Fuels and Fertilizers

Wang

Salehi

Zhang

2022

Production of Biofuels and Chemicals From Sustainable Recycling of Organic Solid Waste

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Recycling and Elimination of Wastes obtained from Agriculture by using Nanotechnology: Nanosensors

Cited by 7 publications

References 33 publications

Suppression of Bacterial Leaf Spot by Green Synthesized Silica Nanoparticles and Antagonistic Yeast Improves Growth, Productivity and Quality of Sweet Pepper

Suppression of Bacterial Leaf Spot by Green Synthesized Silica Nanoparticles and Antagonistic Yeast Improves Growth, Productivity and Quality of Sweet Pepper

Machine Learning Techniques for Improving Nanosensors in Agroenvironmental Applications

Sustainable Recycling and Valorization of Organic Solid Wastes for Fuels and Fertilizers

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