Carbon nanotubes in plant dynamics: Unravelling multifaceted roles and phytotoxic implications.

Carbon nanotubes (CNTs) have emerged as a promising frontier in plant science owing to their unique physicochemical properties and versatile applications. CNTs enhance stress tolerance by improving water dynamics and nutrient uptake and activating defence mechanisms against abiotic and biotic stresses. They can be taken up by roots and translocated within the plant, impacting water retention, nutrient assimilation, and photosynthesis. CNTs have shown promise in modulating plant-microbe interactions, influencing symbiotic relationships and mitigating the detrimental effects of phytopathogens. CNTs have demonstrated the ability to modulate gene expression in plants, offering a powerful tool for targeted genetic modifications. The integration of CNTs as sensing elements in plants has opened new avenues for real-time monitoring of environmental conditions and early detection of stress-induced changes. In the realm of agrochemicals, CNTs have been explored for their potential as carriers for targeted delivery of nutrients, pesticides, and other bioactive compounds. CNTs have the potential to demonstrate phytotoxic effects, detrimentally influencing both the growth and developmental processes of plants. Phytotoxicity is characterized by induction of oxidative stress, impairment of cellular integrity, disruption of photosynthetic processes, perturbation of nutrient homeostasis, and alterations in gene expression. This review aims to provide a comprehensive overview of the current state of knowledge regarding the multifaceted roles of CNTs in plant physiology, emphasizing their potential applications and addressing the existing challenges in translating this knowledge into sustainable agricultural practices.

Environmental resilience through artificial intelligence: innovations in monitoring and management.

The rapid rise of artificial intelligence (AI) technology has revolutionized numerous fields, with its applications spanning finance, engineering, healthcare, and more. In recent years, AI's potential in addressing environmental concerns has garnered significant attention. This review paper provides a comprehensive exploration of the impact that AI has on addressing and mitigating critical environmental concerns. In the backdrop of AI's remarkable advancement across diverse disciplines, this study is dedicated to uncovering its transformative potential in the realm of environmental monitoring. The paper initiates by tracing the evolutionary trajectory of AI technologies and delving into the underlying design principles that have catalysed its rapid progression. Subsequently, it delves deeply into the nuanced realm of AI applications in the analysis of remote sensing imagery. This includes an intricate breakdown of challenges and solutions in per-pixel analysis, object detection, shape interpretation, texture evaluation, and semantic understanding. The crux of the review revolves around AI's pivotal role in environmental control, examining its specific implementations in wastewater treatment and solid waste management. Moreover, the study accentuates the significance of AI-driven early-warning systems, empowering proactive responses to environmental threats. Through a meticulous analysis, the review underscores AI's unparalleled capacity to enhance accuracy, adaptability, and real-time decision-making, effectively positioning it as a cornerstone in shaping a sustainable and resilient future for environmental monitoring and preservation.

Formulation of Vermicelli Mixed Corn and Rice Flour with Additional Carrageenan and Its Economic Value.

The study was aimed at obtaining a vermicelli formulation on a mixture of corn and rice flour, adding carrageenan and its economic analysis. The experiment applied a 2-factorial randomized block design, where factor 1 was a mixture of corn and rice flour (5 levels) and factor 2 was carrageenan concentration (5 levels), repeated three times. The data were analyzed using ANOVA provided in SPSS. When there were significant differences, the analysis proceeded with DMRT at a level of 5% to see differences among treatments. The results show that the higher the corn flour and carrageenan concentration, the higher the vermicelli's ash and fat content. The formulation produces wet vermicelli with a good appearance. The production of vermicelli uses an extruder method. The selected vermicelli formulation was a mixture of 25% corn flour with 75% rice flour and the addition of 0.6% carrageenan. The characteristics of the wet vermicelli are moisture content of 42.84%, ash content of 0.21% on a wet basis (wb), and fat content of 0.43% wb. The organoleptic test of vermicelli was color 3.9 (liked), aroma 3.6 (liked), texture 2.6 (quite soft), taste 3.7 (liked), and general appearance 3.5 (liked). Economically, making vermicelli made of corn and rice flour is profitable because the R/C ratio value is greater than one, which is 2.27. The resulting wet vermicelli resembles wet noodles, large in size and yellow in color, so it can be recommended as gluten-free noodles, suitable for consumption by people with gluten allergies.