Microplastics are a global ubiquitous problem, which is becoming a major issue of concern at scientific and political levels around the world. This study presents physical and chemical characterizations of microplastic debris and a comparison between the spatial distribution and anthropogenic activities in 4 Panamanian beaches located in both sides of the Isthmus. Two of them (Juan Diaz and San Carlos beaches) are located toward the Pacific Ocean, Panamá Province, whereas the others (Palenque and Punta Galeta beaches) are located at the Caribbean Sea, Colón Province. They were chosen to show different landscape management and environmental impacts: touristic and protected areas; coastal areas that receive pollutants and marine litter from urban rivers or are used for local fishing activities. Plastic debris samples were collected and visually analyzed following the protocol proposed by the Joint Group of Experts on the Scientific Aspects of Marine Environmental Protection (GESAMP). The physical characterization of the samples consisted in the determination of variables associated with the number of plastic particles, shape, color, and size. The characterization of the polymers was performed by the attenuated total reflectance-Fourier transform infrared spectroscopy technique. A high concentration of microplastics (353 items/m ² ) were found at the studied sites at the Caribbean coast, whereas a lesser concentration with a greater diversity of shapes and polymer categories were found at the Pacific Coast (187 items/m ² ). The results indicate that, in addition to anthropogenic activities, the proximity to Panama Canal installations, as well as seasonality, natural phenomena, winds, and ocean currents may be influencing the increase in microplastic contents and the types of polymers observed.

Coastal areas are attractive for human settlements because they allow easy access to benefits like food, security, and fishing. These aquatic ecosystems are supported by photosynthetic organisms that constitute the base of the food web. The term “Harmful Algal Bloom” (HAB) refers to the excessive proliferation of some taxa of these microorganisms reaching harmful levels to humans and other organisms. Biotoxins produced by these HABs could be transferred to the food chain and are the best-documented impact that HABs have on humans. The location and abundance of the HAB species producing the toxin is a good indicator of a possible human health hazard. The aim of this study was to monitor potentially harmful benthic/epibenthic microalgae in Punta Galeta, Panama over a 15-month period. The 3 main microalgae found were 2 dinoflagellates from the genera Prorocentrum and Ostreopsis and 1 diatom from the genus Coscinodiscus. Sampling made with both natural and artificial substrates yielded similar overall abundance patterns; however, for the macroalgae samples, there appeared to be significant host preferences for Ostreopsis and Coscinodiscus. Physicochemical measures taken at the site were found to fall within previously reported growth parameters for the microalgae found in the study.

This article is about the design, development and validation of a new monitoring architecture for individual cells and stacks to facilitate the study of proton exchange fuel cells. The system consists of four main elements: input signals, signal processing boards, analogue-to-digital converters (ADCs) and a master terminal unit (MTU). The latter integrates a high-level graphic user interface (GUI) software developed by National Instruments LABVIEW, while the ADCs are based on three digital acquisition units (DAQs). Graphs showing the temperature, currents and voltages in individual cells as well as stacks are integrated for ease of reference. The system validation was carried out both in static and dynamic modes of operation using a Ballard Nexa 1.2 kW fuel cell fed by a hydrogen cylinder, with a Prodigit 32612 electronic load at the output. The system was able to measure the voltage distributions of individual cells, and temperatures at different equidistant points of the stack both with and without an external load, validating its use as an indispensable tool for the study and characterization of these systems.

This work presents a remote sensing application to estimate the leaf area index (LAI) in two rice (Oryza sativa L.) varieties (IDIAP 52-05 and IDIAP FL 137-11), as a proxy for crop performance. In-field, homogeneous spectroradiometric measurements (350–1050 nm) were carried in two campaigns (June–November 2017 and January–March 2018), on a private farm, TESKO, located in Juan Hombrón, Coclé Province, Panama. The spectral fingerprint of IDIAP 52-05 plants was collected in four dates (47, 67, 82 and 116 days after sowing), according to known phenological stages of rice plant growth. Moreover, true LAI or green leaf area was measured from representative plants and compared to LAI calculated from normalized PlanetScope multi-spectral satellite images (selected according to dates close to the in-field collection). Two distinct estimation models were used to establish the relationships of measured LAI and two vegetational spectral indices (NDVI and MTVI2). The results show that the MTVI2 based model has a slightly higher predictive ability of true LAI ($R^2$ = 0.92, RMSE = 2.20), than the NDVI model. Furthermore, the satellite images collected were corrected and satellite LAI was contrasted with true LAI, achieving in average 18% for Model 2 for MTVI2, with the NDVI (Model 1) corrected model having a smaller error around 13%. This work provides an important advance in precision agriculture, specifically in the monitoring of total crop growth via LAI for rice crops in the Republic of Panama.