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The purpose of this study is to extract and characterize a novel natural dye from the leaves of Lannea coromandelica and the extraction with finding ways of dyeing cotton fabric using three mordants.

The colouring agents were extracted from the leaves of Lannea coromandelica using an aqueous extraction method. The extract was characterized using analysis methods of pH, gas chromatography-mass spectrometry (GC-MS), Fourier transform infrared (FTIR), ultraviolet-visible (UV-vis) and cyclic voltammetry measurement. The extract was applied to cotton fabric samples using a non-mordant and three mordants under the two mordanting methods. The dyeing performance of the extracted colouring agent was evaluated using colour fastness properties, colour strength (K/S) and colour space (CIE Lab).

The aqueous dye extract showed reddish-brown colour, and its pH was 5.94. The GC-MS analysis revealed that the dye extract from the leaves of Lannea coromandelica contained active chemical compounds. The UV-vis and FTIR analyses found that groups influenced the reddish-brown colour of the dye extraction. The cyclic voltammetry measurements discovered the electrochemical properties of the dye extraction. The mordanted fabric samples showed better colour fastness properties than the non-mordanted fabric sample. The K/S and CIE Lab results indicate that the cotton fabric samples dyed with mordants showed more significant dye affinities than non-mordanted fabric samples.

Researchers have never discovered that the Lannea coromandelica leaf extract is a natural dye for cotton fabric dyeing. The findings of this study showed that natural dyes extracted from Lannea coromandelica leaf could be an efficient colouring agent for use in cotton fabric.

The purpose of this study is to investigate starch mucor (SM) in potassium iodide (KI) as corrosion inhibitor of aluminium in hydrochloric acid (HCl) medium.

The SM in KI was characterized by gravimetric, scanning electron microscopy, electrochemical impedance spectroscopy measurements, potentiodynamic polarization and gas chromatography-mass spectrometer techniques. The inhibition efficiency was optimized using response surface methodology.

The result revealed that the inhibitor inhibited corrosion at a low concentration with the rate of inhibition increasing as the concentration of the inhibitor increased. The inhibition efficiency increases as the temperature was increased with slight incorporation of the inhibitor (SM in KI). This indicates that the corrosion control is both inhibitor (SM in KI) and temperature dependent.

The research results can provide the basis for using SM in KI as corrosion inhibitor of aluminium in HCL medium. Mixed-type inhibitor nature of SM was proved by cathodic and anodic nature of the polarization curves.

Artificial fruit ripening is hazardous to mankind. In the recent past, artificial fruit ripening is increasing gradually due to its commercial benefits. To discriminate the type of fruit ripening involved at the vendors’ side, there is a great demand for on-sight ethylene detection in a nondestructive manner. Therefore, this study aims to deal with a comparison of various laboratory and portable methods developed so far with high-performance metrics to identify the ethylene detection at fruit ripening site.

This paper focuses on various types of technologies proposed up to date in ethylene detection, fabrication methods and signal conditioning circuits for ethylene detection in parts per million and parts per billion levels. The authors have already developed an infrared (IR) sensor to detect ethylene and also developed a lab-based setup belonging to the electrochemical sensing methods to detect ethylene for the fruit ripening application.

The authors have developed an electrochemical sensor based on multi-walled carbon nanotubes whose performance is relatively higher than the sensors that were previously reported in terms of material, sensitivity and selectivity. For identifying the best sensing technology for optimization of ethylene detection for fruit ripening discrimination process, authors have developed an IR-based ethylene sensor and also semiconducting metal-oxide ethylene sensor which are all compared with literature-based comparable parameters. This review paper mainly focuses on the potential possibilities for developing portable ethylene sensing devices for investigation applications.

The authors have elaborately discussed the new chemical and physical methods of ethylene detection and quantification from their own developed methods and also the key findings of the methods proposed by fellow researchers working on this field. The authors would like to declare that the extensive analysis carried out in this technical survey could be used for developing a cost-effective and high-performance portable ethylene sensing device for fruit ripening and discrimination applications.

The main aim of this study is to characterise and identify specific chemo-sensory profiles of ciders from the Canary Islands (Spain).

Commercial samples of Canary ciders were compared to ciders from the Basque Country and Asturias. In total, 18 samples were studied, six for each region. The analysis comprised their sensory profiling and chemical characterisation of their polyphenolic profile, volatile composition, conventional chemical parameters and CIELAB colour coordinates. In parallel, the sensory profile of the samples from the Canary Islands was first compared with their Basque and Asturian counterparts by labelled sorting task. Then, their specific aroma profile was characterised by flash profile. Further quantification of sensory-active compounds was performed by GC–MS and GC-FID to identify the volatile compounds involved in their aroma profile.

Results show that Canary ciders present a specific chemical profile characterised by higher levels of ethanol, and hydroxycinnamic acids, mainly t-ferulic, t-coumaric and neochologenic acids, and lower levels of volatile and total acidity than their Asturian and Basque counterparts. They also present a specific aroma profile characterised by fruity aroma, mainly fruit in syrup and confectionary, and sweet flavours related to their highest levels of vinylphenols formed by transformation of hydroxycinnamic acids.

An integrated strategy to explore the typicity of the currently existing Canary ciders in the market was developed. The results are important in that they will help other regions to identify specific typical chemo-sensory profiles and to promote the creation of certifications supporting regional typicity.

Drug cryptomarkets increase information available to market actors, which should reduce information asymmetry and increase market efficiency. This study aims to determine whether cryptomarket listings accurately represent the advertised substance, weight or number and purity, and whether there are differences in products purchased from the same listing multiple times.

Law enforcement drug purchases – predominantly cocaine, methamphetamine, MDMA and heroin – from Australian cryptomarket vendors (n = 38 in 2016/2017) were chemically analysed and matched with cryptomarket listings (n = 23). Descriptive and comparative analyses were conducted.

Almost all samples contained the advertised substance. In most of these cases, drugs were either supplied as-advertised-weight or number, or overweight or number. All listings that quantified purity overestimated the actual purity. There was no consistent relationship between advertised purity terms and actual purity. Across the six listings purchased from multiple times, repeat purchases from the same listing varied in purity, sometimes drastically, with wide variation detected on listings purchased from only one month apart.

In this data set, cryptomarket listings were mostly accurate, but the system was far from perfect, with purity overestimated. A newer, larger, globally representative sample should be obtained to test the applicability of these findings to currently operating cryptomarkets.

This paper reports on the largest data set of forensic analysis of drug samples obtained from cryptomarkets, where data about advertised drug strength/dose were obtained.

The purpose of this study is to investigate how the different generations of consumers behave in the field of healthy and quality food consumption, considering their perceptions about healthy attributes and healthy eating style, what are the main trusted sources influencing consumption or the attention towards healthy and quality food, how do they behave towards healthy and quality foods and which benefits and barriers affect their consumption.

Data for this study were obtained from a questionnaire survey carried out over a six-month period in 2021. The questionnaire was administered online. The sampling procedure was based on a convenient non-random sampling method applied to the Italian population aged between 18 and 75 years old. The data collection process resulted in 1,646 completed questionnaires.

The results show that, in line with the theory of generational cohorts, each generation has its own specificities regarding food behaviour. The study reveals a highly sensitive approach towards healthy and quality food consumption from both Z-ers and the Baby Boomers, whilst X-ers are quite aligned with the other generations. Millennials show specific, sometimes contradictory, attitudes and habits.

The present results offer new insights into the analysis of healthy and quality food consumption, highlighting significant differences amongst generations, which can inspire public and private intervention aimed at encouraging the overall attention and consumption of healthy and quality food with related implications in terms of society's well-being and longevity improvements.

Bales of cotton run through the gins and textile mill instruments, stick to them and make it cumbersome for the ginning mill workers. This is so because more time and money have to be invested in cleaning these instruments. The stickiness of cotton causes health hazards to the workers, decreases the yarn quality and economic loss to the textile industry. The effect of cotton stickiness on textile ginning, various methods for cotton stickiness detection and the steps for reduction are discussed.

The different methods that are available for detecting and measuring cotton stickiness are described. The sugars that cause stickiness are either of plant origin (physiological sugars) or from the feeding insects (entomological origin). The methods for stickiness detection and reduction are discussed under physical, chemical and biological categories.

This review suggests possible ways to mitigate cotton stickiness.

One of the major issues of the textile industry is honeydew-contaminated cotton stickiness. However, there are few papers on detection methods for analyzing honeydew cotton stickiness along with the approaches to reduce stickiness. This paper summarizes different methods along with a study for detection as well as reduction of cotton stickiness.

In the wine industry, maintaining superior quality standards is crucial to meet the expectations of both producers and consumers. Traditional approaches to assessing wine quality involve labor-intensive processes and rely on the expertise of connoisseurs proficient in identifying taste profiles and key quality factors. In this research, we introduce an innovative and efficient approach centered on the analysis of volatile organic compounds (VOCs) signals using an electronic nose, thereby empowering nonexperts to accurately assess wine quality.

To devise an optimal algorithm for this purpose, we conducted four computational experiments, culminating in the development of a specialized deep learning network. This network seamlessly integrates 1D-convolutional and long-short-term memory layers, tailor-made for the intricate task at hand. Rigorous validation ensued, employing a leave-one-out cross-validation methodology to scrutinize the efficacy of our design.

The outcomes of these e-demonstrates were subjected to meticulous evaluation and analysis, which unequivocally demonstrate that our proposed architecture consistently attains promising recognition accuracies, ranging impressively from 87.8% to an astonishing 99.41%. All this is achieved within a remarkably brief timeframe of a mere 4 seconds. These compelling findings have far-reaching implications, promising to revolutionize the assessment and tracking of wine quality, ultimately affording substantial benefits to the wine industry and all its stakeholders, with a particular focus on the critical aspect of VOCs signal analysis.

This research has not been published anywhere else.