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Low-cost air pollution wireless sensors are emerging in densely distributed networks that provide more spatial resolution than typical traditional systems for monitoring ambient air quality. This paper presents an air quality measurement system that is composed of a distributed sensor network connected to a cloud system forming a wireless sensor network (WSN). Sensor nodes are based on low-power ZigBee motes, and transmit field measurement data to the cloud through a gateway. An optimized cloud computing system has been implemented to store, monitor, process, and visualize the data received from the sensor network. Data processing and analysis is performed in the cloud by applying artificial intelligence techniques to optimize the detection of compounds and contaminants. This proposed system is a low-cost, low-size, and low-power consumption method that can greatly enhance the efficiency of air quality measurements, since a great number of nodes could be deployed and provide relevant information for air quality distribution in different areas. Finally, a laboratory case study demonstrates the applicability of the proposed system for the detection of some common volatile organic compounds, including: benzene, toluene, ethylbenzene, and xylene. Principal component analysis, a multilayer perceptron with backpropagation learning algorithm, and support vector machine have been applied for data processing. The results obtained suggest good performance in discriminating and quantifying the concentration of the volatile organic compounds.

This paper presents a portable device for outdoor air quality measurement that provides concentration values for the main pollutants: NO2, NO, CO, O3, PM2.5 and PM10, and other values such as temperature, humidity, location, and date. The device is based on the use of commercial electrochemical gas and optical particle matter sensors with a careful design of the electronics for reducing the electrical noise and increasing the accuracy of the measurements. The result is a low-cost system with IoT technology that connects to the Internet through a GSM module and sends all real-time data to a cloud platform with storage and computational potential. Two identical devices were fabricated and installed on a mobile reference measurement unit and deployed in Badajoz, Spain. The results of a two-month field campaign are presented and published. Data obtained from these measurements were calibrated using linear regression and neural network techniques. Good performance has been achieved for both gaseous pollutants (with a Pearson correlation coefficient of up to 0.97) and PM sensors.

This paper introduces a miniaturized personal electronic nose (39 mm × 33 mm), which is managed through an app developed on a smartphone. The electronic nose (e-nose) incorporates four new generation digital gas sensors. These MOx-type sensors incorporate a microcontroller in the same package, being also smaller than the previous generation. This makes it easier to integrate them into the electronics and improves their performance. In this research, the application of the device is focused on the detection of atmospheric pollutants in order to complement the information provided by the reference stations. To validate the system, it has been tested with different concentrations of NOx including some tests specifically developed to study the behavior of the device in different humidity conditions. Finally, a mobile application has been developed to provide classification services. In this regard, a neural network has been developed, trained, and integrated into a smartphone to process the information retrieved from e-nose devices.

Insect metamorphosis is regulated by ecdysteroids, which induce molts and juvenile hormone (JH), which inhibits metamorphic changes. The molecular action of ecdysteroids has been thoroughly studied, but that of JH is poorly understood, with data currently only being available for holometabolous species, like Drosophila melanogaster and Tribolium castaneum . We studied the function of Krüppel homolog 1 (Kr-h1) in Blattella germanica , a hemimetabolous model. Kr-h1 is a Zn finger transcription factor whose function as transductor of the antimetamorphic action of JH has recently been demonstrated in D. melanogaster and T. castaneum . The RNAi experiments reported herein indicated that Kr-h1 transduces the antimetamorphic action of JH also in B. germanica , thereby suggesting that this role is an ancestral condition that has been conserved in insect evolution from hemimetabolous to holometabolous species.

Nowadays, the electronic nose (e-nose) has gained a huge amount of attention due to its ability to detect and differentiate mixtures of various gases and odors using a limited number of sensors. Its applications in the environmental fields include analysis of the parameters for environmental control, process control, and confirming the efficiency of the odor-control systems. The e-nose has been developed by mimicking the olfactory system of mammals. This paper investigates e-noses and their sensors for the detection of environmental contaminants. Among different types of gas chemical sensors, metal oxide semiconductor sensors (MOXs) can be used for the detection of volatile compounds in air at ppm and sub-ppm levels. In this regard, the advantages and disadvantages of MOX sensors and the solutions to solve the problems arising upon these sensors’ applications are addressed, and the research works in the field of environmental contamination monitoring are overviewed. These studies have revealed the suitability of e-noses for most of the reported applications, especially when the tools were specifically developed for that application, e.g., in the facilities of water and wastewater management systems. As a general rule, the literature review discusses the aspects related to various applications as well as the development of effective solutions. However, the main limitation in the expansion of the use of e-noses as an environmental monitoring tool is their complexity and lack of specific standards, which can be corrected through appropriate data processing methods applications.

Food fraud, particularly in the olive oil sector, represents a pressing concern within the agri-food industry, with implications for consumer trust and product authenticity. Certified products like Protected Designation of Origin (PDO) Extra Virgin Olive Oil (EVOO) are premium products that undergo strict quality controls, must comply with specific production regulations, and generally have a higher market price. These characteristics make them particularly vulnerable to economically motivated adulteration. In this study, the adulteration of PDO EVOO with Olive Pomace Oil (POO) and Olive Oil (OO) was investigated through a combined analytical approach. A traditional technique, gas chromatography–mass spectrometry (GC-MS) combined with solid-phase microextraction (SPME), was employed alongside an innovative method based on an electronic nose equipped with metal oxide semiconductor (MOX) sensors. GC-MS analysis enabled the identification of characteristic volatile compounds, providing a detailed chemical fingerprint of the different oil samples. Concurrently, the MOX sensor array successfully detected variations in the volatile profiles released by the adulterated oils, demonstrating its potential as a rapid and cost-effective screening tool. The complementary use of both techniques highlighted the reliability of MOX sensors in differentiating authentic PDO EVOO from adulterated samples and underscored their applicability in routine quality control and fraud prevention strategies.

In 2009 we reported that depletion of Dicer-1, the enzyme that catalyzes the final step of miRNA biosynthesis, prevents metamorphosis in Blattella germanica . However, the precise regulatory roles of miRNAs in the process have remained elusive. In the present work, we have observed that Dicer-1 depletion results in an increase of mRNA levels of Krúñíóüüüppel homolog 1 (Kr-h1), a juvenile hormone-dependent transcription factor that represses metamorphosis, and that depletion of Kr-h1 expression in Dicer-1 knockdown individuals rescues metamorphosis. We have also found that the 3′UTR of Kr-h1 mRNA contains a functional binding site for miR-2 family miRNAs (for miR-2, miR-13a, and miR-13b). These data suggest that metamorphosis impairment caused by Dicer-1 and miRNA depletion is due to a deregulation of Kr-h1 expression and that this deregulation is derived from a deficiency of miR-2 miRNAs. We corroborated this by treating the last nymphal instar of B. germanica with an miR-2 inhibitor, which impaired metamorphosis, and by treating Dicer-1-depleted individuals with an miR-2 mimic to allow nymphal-to-adult metamorphosis to proceed. Taken together, the data indicate that miR-2 miRNAs scavenge Kr-h1 transcripts when the transition from nymph to adult should be taking place, thus crucially contributing to the correct culmination of metamorphosis. Significance MicroRNAs are short, single-stranded RNAs that bind to target mRNAs and block their translation. Five years ago we observed in the cockroach Blattella germanica that general depletion of microRNAs prevents metamorphosis. This observation led to two key questions: Which microRNAs are involved in this action, and which target do they act on? The results reported herein show that the microRNAs involved are those of an miR-2 family (miR-2, miR-13a, and miR-13b), and the target is the transcription factor Krúñíóüppel homolog 1, a master repressor of insect metamorphosis. The data presented indicate that miR-2 microRNAs rapidly clear Krúñíóüüppel homolog 1 transcripts in the last nymphal instar, a process that is crucial for proper metamorphosis. This reveals the elegant mechanism of an miRNA family leading metamorphosis to its correct conclusion.

Juvenile Hormone (JH) represses metamorphosis of young instars in insects. One of the main players in hormonal signalling is Methoprene-tolerant (Met), which plays the role of JH receptor. Using the Polyneopteran insect Blattella germanica as the model and RNAi for transcript depletion, we have confirmed that Met transduces the antimetamorphic signal of JH in young nymphs and plays a role in the last nymphal instar moult in this species. Previously, the function of Met as the JH receptor had been demonstrated in the Eumetabola clade, with experiments in Holometabola (in the beetle Tribolium castaneum) and in their sister group Paraneoptera (in the bug Pyrrhocoris apterus). Our result shows that the function of Met as JH receptor is also conserved in the more basal Polyneoptera. The function of Met as JH transducer might thus predate the evolutionary innovation of metamorphosis. Moreover, expression of Met was also found in last nymphal instar of B. germanica, when JH is absent. Depletion of Met in this stage provoked deficiencies in wing growth and ecdysis problems in the imaginal moult. Down-regulation of the ecdysone-inducible gene E75A and Insulin-Like-Peptide 1 in these Met-depleted specimens suggest that Met is involved in the ecdysone and insulin signalling pathways in last nymphal instar, when JH is virtually absent.

Current legislation in Spain indicates that table olives must be free of off‐odors and off-flavors and without symptoms of ongoing alteration or abnormal fermentations. In this regard, the International Olive Council (IOC) has developed a protocol for the sensory classification of table olives according to the intensity of the predominantly perceived defect (PPD). An electronic nose (e‐nose) was used to assess the abnormal fermentation defects of Spanish‐style table olives that were previously classified by a tasting panel according to the IOC protocol, namely zapateria, butyric, putrid, and musty or humidity. When olives with different defects were mixed, the putrid defect had the greatest sensory impact on the others, while the butyric defect had the least sensory domi-nance. A total of 49 volatile compounds were identified by gas chromatography, and each defect was characterized by a specific profile. The e‐nose data were analyzed using principal component analysis (PCA) and partial least square discriminant analysis (PLS‐DA). The different defects were clearly separated from each other and from the control treatment, independently of PPD intensity. Moreover, the e‐nose differentiated control olives from table olives with combined sensory defects despite the dilution effect resulting from the combination. These results demonstrate that e‐nose can be used as an olfactory sensor for the organoleptic classification of table olives and can success-fully support the tasting panel

Spanish-style table olives are one of the most common processed foods in the Mediterranean countries. Lack of control during fermentation can lead to one of the main defects of the olive, called ‘Zapateria’, caused by the combination of volatile fatty acids reminiscent of rotten leather. In this study, table olives altered with ‘Zapateria’ defect were stuffed with a hydrocolloid flavoured with the aroma ‘Mojo picón’ to improve consumer acceptance. Sensory analysis, determination of volatile compounds and electronic nose (E-nose) were used to evaluate the quality of the olives. The control samples had a high concentration of the defect ‘Zapateria’ and were classified in the second commercial category, while higher ‘Mojo picón’ flavour concentrations resulted in these olives being classified as ‘extra category’ (a masking effect). The main volatile compounds in olives with ‘Zapateria’ defect were cyclohexanecarboxylic acid and pentanoic acid. E-nose allowed discrimination between stuffed olives without added flavouring and olives with ‘Mojo picón’ flavouring at different concentrations. Finally, PLS regression allowed a predictive linear model to be established between E-nose and sensory analysis values. The RP2 values were 0.74 for perceived defect and 0.86 for perceived aroma. The E-nose was successfully applied for the first time to classify Spanish-style table olives with ‘Zapateria’ defect intensity and with the addition of the ‘Mojo picón’ aroma masking the defect.