Decreasing the use of pesticides is one of the main goals of current agriculture, which requires fast, precise and continuous assessments of crop pests. Citrus pests cause a lot of damage worldwide and the techniques to evaluate them are mainly based on manual, time-consuming readings of insects stuck on traps spread over the crops. This is the case of red scale insects, whose control is notably challenging due to their small size and high reproduction rate. Hence, in this work, we carry out a spectral characterization of this insect in the visible range through spectrometric devices, microscopy and hyperspectral imaging technology to analyze the feasibility of using this information as a means of automatically identifying specimens belonging to this species in this era of precision agriculture. The results obtained show that spectral reflectance differences between red scales and other insects can be recorded at long (red) wavelengths and that red scales are morphologically different, i.e., smaller and more rounded. A reflectance ratio computed from spectral images taken at 774 nm and 410 nm is proposed as a new approach for automated discrimination of red scales from other insects.
The present-day substantial growth in the demand and utilization of plastics provokes severe economic and environmental consequences. Around 4 – 6 % of global oil and gas production is used directly or indirectly as feedstock in the production of plastics. A further 2 – 3 % is employed as energy during the manufacturing process. This study highlights recycling (chemical) against other sustainable waste management approaches, like mitigation of waste generation through the concept of reusing and energy recovery from plastics. As an example, the African context regarding the quality of the disposed waste and the waste characteristics in the Kumasi region, Ghana is taken into consideration. To process valuable and economically viable recycling products, pure polymers are required. Certain technologies, such as infrared (IR) spectroscopy, have limitations for accurately identifying different polymer types, particularly when the sample mix is contaminated with organic waste or is physically wet. There are promising technologies that are under development, like Raman spectroscopy and laser-aided spectroscopy combined with tracers (fluorescent markers). Nonetheless, these are essentially more expensive technologies and are currently in the development phase. Multiplexed near-infrared (NIR) spectroscopy is a fitting technology for polymer identification. It is a fast and nondestructive technique that does not influence the physical state nor chemical property of the sample polymers. Hence, it can be integrated in a continuous sorting system. Here, a prototype sorting system equipped with a multiplexed NIR spectrometer was utilized and used to test the sorting efficiency of the system as well as the purity of identified and sorted samples. Samples of PE (with subgroups of HDPE, LDPE and LLDPE), PS, PET, PP and PVC and unknown polymers were employed in several conditions. The measurements were carried out in real time, based on the speed of the conveyor belt. In this study, a novel setup is introduced and investigated, and its data analyzed to determine the reliability of the sorting method for plastics to be used for pyrolysis.