Desert locusts ( Schistocerca gregaria) pause a significant threat on food security. However, they also serve as a nutrient-rich delicacy in many African and Arab communities where they are traditionally harvested for food and feed during outbreaks. Traditional harvesting methods are inefficient, laborious and time-consuming hence, the need to explore more convenient and efficient techniques. This study assessed preferential selection and feeding behavior of desert locusts to identify trap plants that could attract and aggregate them for easy harvesting. Four trap plants (cowpea, finger millet, sorghum, and amaranth) and four repellent plants (neem, pencil cactus, garlic, and cayenne red pepper) were evaluated through multiple-choice experiments. A complete randomized design (CRD), mature adult, immature adult and hopper stages of desert locust replicated thrice were involved . One-way analysis of variance (ANOVA) was used to determine whether treatment effects was significant or not, and mean differences between treatments at p<0.05 were separated using post-hoc Tukey HSD. Cowpea was the most preferred trap plant by the three locust stages, while neem exhibited the most potent repellent effect. Neem as a push plant repelled locusts thereby reducing infestation and damage of cowpeas as a pull plant when both plants were grown in the same pot in a “push-pull” system. However, cowpea attracted large numbers of locusts repelled by neem for harvesting when both plants were grown in separate pots. These findings provide valuable insights on the potential of exploiting trap and repellents to enhance aggregation and harvesting of desert locusts for use as food and feed.
Food touches every human and every other species in the world throughout daily life. Food is therefore the subject of extensive regulation nationally, internationally across trade agreements, and under some religious law as well. Nanotechnology has been applied to food since the late 20 th century with attendant implications for food quality, quantity, and distribution. Applications of nanotechnology impacting food “from field to fork” include: more effective formulation of fertilizers, pesticides, and herbicides; nanosilver as an antibacterial in food handling and refrigeration; carbon nanotubes for secure and durable packaging Titanium dioxide to make food white, fluffy, and attractive to consumers; and nano-biosensors to detect temperature changes that might cause spoilage, thereby helping to prevent food loss. One nanoscale material in particular, Titanium Dioxide, has been subject to litigation and banned in Europe. By contrast, it is generally recognized as safe under USA laws, and has no specific federal limit if it consists of one percent or less of the total food involved. But, California’s assembly has also introduced legislation to ban this substance, and therefore the role of nanotechnology applied to food, shaping new laws and spawning litigation, is a hot new legal issue.
Plasmonic gratings provide an advantageous platform for fluorescence sensing due to their compatibility with functionalization techniques, imaging detection, and the potential for signal enhancement. Among traditional fluorescence detection methods, microscopes are commonly used tools. The interaction between dye fluorescence processes and the plasmonic modes of the grating strongly depends on the measurement configuration and is influenced by the dispersion and spectral characteristics of the plasmonic modes. In our study, we investigated the angular behavior of the fluorescence emission from ATTO700 dye by varying the collection angle using a standard optical microscope coupled with a spectrometer. Our results show a clear dependence of fluorescence emission in terms of spectral shape on the collection angle that can be attributed to plasmonic mode dispersion.
Photocatalytic coatings have the potential to contribute to the purification of water via an advanced oxidation process (AOP) . A commonly used method for analyzing the mechanism of the photocatalytic performance of a given reactor type is to document the degradation behavior in a solution containing methylene blue. However, since methylene blue is rather unstable, the degradation results should be viewed critically. In this work, the degradation behavior of a test solution with methylene blue on quartz glass surfaces coated with photocatalytic titanium dioxide (TiO 2) of the anatase modification was investigated through a variety of different light sources. The coating was deposited by the reactive pulsed DC magnetron sputtering (MSIP-PVD) method described in , while the quartz glasses were coated with a 100 nm thick TiO 2 coating. The same glasses were used for all experiments with TiO 2. In the determination of the degradation rate, additional experiments were performed using pure quartz glass without any coating, which made it possible to examine the influence of different light sources on the degradation rate of methylene blue in general. Three different light sources, namely UV-A, UV-C, and simple fluorescent lamps were used in this study. The concentration of methylene blue was recorded by photo spectrometer in 10-minute increments throughout the experiment and the experiments were performed for 24 hours in all cases.
This work elucidates the control of integrating non-minimum phase system via series cascade scheme with fractional-order P.I. (Proportional–Integral) plus D (Derivative) controller. The traditional Internal Model Control (IMC) is adopted for inner loop controller design. The feedback D controller is synthesized with the outer loop process model, which shows the work’s universality. The outer loop controller is suggested in the IMC framework after accountability of fractional-filter and inverse response compensator. This combination is revealed to enhance performance without compromising the robustness. The Riemann sheet principle is explored to compute the stability of the suggested controller. The sensitivity analysis has asserted the robustness. More importantly, the optimal value of controller settings is achieved via the Teaching Learning Based Optimization (TLBO) algorithm. This TLBO algorithm uses an objective function that minimizes Integral Square Error (ISE). Two illustrative problems are utilized to examine the recommended control structure’s virtue.