Search Results (809)

The extensive use of conventional pesticides has been a fundamental strategy in modern agriculture for controlling pests and increasing crop productivity; however, their improper application poses significant risks to human health and environmental sustainability. This review compiles scientific evidence linking pesticide exposure to oxidative stress and genotoxic damage, particularly affecting rural populations and commonly consumed foods, even at levels exceeding the maximum permissible limits in fruits, vegetables, and animal products. Additionally, excessive pesticide use has been shown to alter soil microbiota, negatively compromising long-term agricultural fertility. In response to these challenges, recent advances in nanotechnology offer promising alternatives. This review highlights the development of nanopesticides designed for controlled release, improved stability, and targeted delivery of active ingredients, thereby reducing environmental contamination and increasing efficacy. Moreover, emerging nanobiosensor technologies, such as e-nose and e-tongue systems, have shown potential for real-time monitoring of pesticide residues and soil health. Although pesticides are still necessary, it is crucial to implement stricter laws and promote sustainable solutions that ensure safe and responsible agricultural practices. The need for evidence-based public policy is emphasized to regulate pesticide use and protect both human health and agricultural resources. Full article

A chili pepper variety and origin detection system that integrates a field-programmable gate array (FPGA) with an electronic nose (e-nose) is proposed in this paper to address the issues of variety confusion and origin ambiguity in the chili pepper market. The system uses the AIRSENSE PEN3 e-nose from Germany to collect gas data from thirteen different varieties of chili peppers and two specific varieties of chili peppers originating from seven different regions. Model training is conducted via the proposed lightweight convolutional neural network ChiliPCNN. By combining the strengths of a convolutional neural network (CNN) and a multilayer perceptron (MLP), the ChiliPCNN model achieves an efficient and accurate classification process, requiring only 268 parameters for chili pepper variety identification and 244 parameters for origin tracing, with 364 floating-point operations (FLOPs) and 340 FLOPs, respectively. The experimental results demonstrate that, compared with other advanced deep learning methods, the ChiliPCNN has superior classification performance and good stability. Specifically, ChiliPCNN achieves accuracy rates of 94.62% in chili pepper variety identification and 93.41% in origin tracing tasks involving Jiaoyang No. 6, with accuracy rates reaching as high as 99.07% for Xianjiao No. 301. These results fully validate the effectiveness of the model. To further increase the detection speed of the ChiliPCNN, its acceleration circuit is designed on the Xilinx Zynq7020 FPGA from the United States and optimized via fixed-point arithmetic and loop unrolling strategies. The optimized circuit reduces the latency to 5600 ns and consumes only 1.755 W of power, significantly improving the resource utilization rate and processing speed of the model. This system not only achieves rapid and accurate chili pepper variety and origin detection but also provides an efficient and reliable intelligent agricultural management solution, which is highly important for promoting the development of agricultural automation and intelligence. Full article

Donepezil (DPZ) is an Alzheimer’s disease (AD) drug that promotes cholinergic neurotransmission and exhibits excellent acetylcholinesterase (AChE) selectivity. The current oral formulations of DPZ demonstrate decreased bioavailability, attributed to limited drug permeability across the blood–brain barrier (BBB). In order to overcome these limitations, various dosage forms aimed at delivering DPZ have been explored. This discussion will focus on the nose-to-brain (N2B) delivery system, which represents the most promising approach for brain drug delivery. Intranasal (IN) drug delivery is a suitable system for directly delivering drugs to the brain, as it bypasses the BBB and avoids the first-pass effect, thereby targeting the central nervous system (CNS). Currently developed formulations include lipid-based, solid particle-based, solution-based, gel-based, and film-based types, and a systematic review of the N2B research related to these formulations has been conducted. According to the in vivo results, the brain drug concentration 15 min after IN administration was more than twice as high those from other routes of administration, and the direct delivery ratio of the N2B system improved to 80.32%. The research findings collectively suggest low toxicity and high therapeutic efficacy for AD. This review examines drug formulations and delivery methods optimized for the N2B delivery of DPZ, focusing on technologies that enhance mucosal residence time and bioavailability while discussing recent advancements in the field. Full article

Sensor operations in the food industry are faced with several major challenges, including in sensitivity, selectivity, accuracy and rapid detection. Among emerging technologies, e-nose and e-tongue systems have attracted much attention from researchers. This review examines 112 studies published from 2004 to 2025, and examines the functionalities and performance in detecting various food product-associated analytes. The sensitivity of e-nose and e-tongue systems was analyzed using various data processing techniques. Recent research and development in leading countries (i.e., China, United Kingdom, Columbia, India, Portugal, Spain, Hungary, Ireland) was examined. The findings indicate that principal component analysis (PCA) was the most widely used technique, while more articles were published in 2021. Worldwide research contributions showed China at the forefront of e-nose studies (26.7%) and Spain leading in e-tongue research (30%). The highest sensitivity values were 99.0% for the e-nose in 2015 and 100% for the e-tongue in 2012. In specific applications, the e-nose achieved a maximum average sensitivity of 15% in apple analysis, while the e-tongue achieved a maximum average sensitivity of 40.5% in water samples. Furthermore, the review presents an in-depth discussion of key parameters, including food sample types, citation rates, analysis techniques, accuracy, and sensitivity, with graphical representations for enhanced clarity. Full article

With the development of various new types of instrumental aroma sensing technologies, there is a need for methodologies that help developers and users evaluate the performance of the different devices. This study introduces a simple method that uses standard coffee beverages, reproducible worldwide, thus allowing users to compare aroma sensing devices and technologies globally. Eight different variations of commercial coffee capsules were used to brew espresso coffees (40 mL), consisting of either Arabica coffee or a blend of Robusta and Arabica coffee, covering a wide range of sensory attributes. The AlphaMOS Astree electronic tongue (equipped with sensors based on chemically modified field-effect transistor technology) and the AlphaMOS Heracles NEO and the Volatile Scout3 electronic noses (both using separation technology based on gas chromatography) were used to describe the taste and odor profiles of the freshly brewed coffee samples and also to compare them to the various sensory characteristics declared on the original packaging, such as intensity, roasting, acidity, bitterness, and body. Linear discriminant analysis (LDA) results showed that these technologies were able to classify the samples similarly to the pattern of the coffees based on the human sensory characteristics. In general, the arrangement of the different coffee types in the LDA results—i.e., the similarities and dissimilarities in the types based on their taste or smell—was the same in the case of the Astree electronic tongue and the Heracles electronic nose, while slightly different arrangements were found for the Scout3 electronic nose. The results of the Astree electronic tongue and those of the Heracles electronic nose showed the taste and smell profiles of the decaffeinated coffees to be different from their caffeinated counterparts. The Heracles and Scout3 electronic noses provided high accuracies in classifying the samples based on their odor into the sensory classes presented on the coffee capsules’ packaging. Despite the technological differences in the investigated devices, the introduced coffee test could assess the similarities in the taste and odor profiling capacities of the aroma fingerprinting technologies. Since the coffee capsules used for the test can be purchased all over the world in the same quality, these coffees can be used as global standard samples during the comparison of different devices applying different measurement technologies. The test can be used to evaluate instrumentational and data analytical developments worldwide and to assess the potential of novel, cost-effective, accurate, and rapid solutions for quality assessments in the food and beverage industry. Full article

In this study, four lactic acid bacteria (LAB) strains, including Lactiplantibacillus plantarum CICC21790, Lacticaseibacillus casei CICC6117, Lacticaseibacillus rhamnosus ATCC7469, and Limosilactobacillus fermentum CICC22704, were used to ferment a plant-based milk composed of chestnut and soybean. The fermentative characteristics of the four LAB strains and the aroma characteristics of the resulting plant-based milks were systematically investigated. The results showed that all four LAB strains successfully fermented the plant-based milk. The viable cell counts ranged from 7.67 to 8.57 lg CFU mL⁻¹, and pH values were between 3.80 and 4.10. Comprehensive analyses performed using E-nose and HS-GC-IMS revealed distinct aroma characteristics in plant-based milks fermented by different LAB strains. Specifically, LAB fermentation, particularly by the CICC22704, significantly reduced the concentrations of aldehydes (e.g., hexanal, heptanal), thereby diminishing Green aroma characteristics. The increased concentrations of alcohols (e.g., 1-pentanol), ketones (e.g., 2, 3-butanedione) and furan compounds (e.g., 2-pentylfuran) in fermented plant-based milks enhanced Pungent, Creamy, and Fruity aroma characteristics, respectively. Fermentation by CICC21790, ATCC7469, and CICC6117 may result in stronger intensities of these three aroma characteristics compared to fermentation by the CICC22704. For the Fatty aroma characteristic, it was enhanced by CICC21790 fermentation but diminished by ATCC7469, CICC6117, and CICC22704 fermentations. Full article

The early detection of liver cirrhosis (LC) is crucial due to its high morbidity and mortality in advanced stages. Reliable, non-invasive diagnostic tools are essential for timely intervention. Exhaled human breath, reflecting metabolic changes, offers significant potential for disease diagnosis. This paper focuses on the emerging role of sensor array-based volatile organic compounds (VOCs) analysis of exhaled breath, particularly using electronic nose (e-nose) technology to differentiate LC patients from healthy controls (HCs). This study included 55 participants: 27 LC patients and 28 HCs. Sensor’s measurement data were analyzed using machine learning techniques, such as principal component analysis (PCA), discriminant function analysis (DFA), and support vector machines (SVMs) that were utilized to uncover meaningful patterns and facilitate accurate classification of sensor-derived information. The diagnostic accuracy was thoroughly assessed through receiver operating characteristic (ROC) curve analysis, with specific emphasis on assessing sensitivity and specificity metrics. The e-nose effectively distinguished LC from HC, with PCA explaining 92.50% variance and SVMs achieving 100% classification accuracy. This study demonstrates the significant potential of e-nose technology towards VOCs analysis in exhaled breath, as a valuable tool for LC diagnosis. It also explores feature extraction methods and suitable algorithms for effectively distinguishing between LC patients and controls. This research provides a foundation for advancing breath-based diagnostic technologies for early detection and monitoring of liver cirrhosis. Full article

Assessing the quality of fresh produce is essential to ensure a safe and satisfactory product. Methods to monitor the quality of fresh produce exist; however, they are often expensive, time-consuming, and sometimes require the destruction of the sample. Electronic Nose (E-Nose) technology has been established to track the ripeness, spoilage, and quality of fresh produce. Our study developed a freshness monitoring system for tomatoes, combining E-Nose technology with storage condition monitoring, color analysis, and weight-loss tracking. Different post-purchase scenarios were investigated, focusing on the influence of temperature and mechanical damage on shelf life. Support Vector Classifier (SVC) and k-Nearest Neighbor (kNN) were applied to classify storage scenarios and storage days, while Support Vector Regression (SVR) and kNN regression were used for predicting storage days. By using a data fusion approach with Linear Discriminant Analysis (LDA), the SVC achieved an accuracy of 72.91% in predicting storage days and an accuracy of 86.73% in distinguishing between storage scenarios. The kNN yielded the best regression results, with a Mean Absolute Error (MAE) of 0.841 days and a coefficient of determination of 0.867. The results highlight the method’s potential to predict storage scenarios and storage days, providing insight into the product’s remaining shelf life. Full article

Benzene, toluene, ethylbenzene, and xylene (BTEX) are widespread volatile organic compounds commonly present in fuels and various industrial materials. Their release into the atmosphere significantly contributes to air pollution, prompting strict regulatory concentration limits in ambient air. In this work, we introduce Multiphoton Electron Extraction Spectroscopy (MEES) as an innovative technique for the sensitive, selective, and online detection and quantitation of BTEX compounds under ambient conditions. MEES employs tunable UV laser pulses to induce the resonant ionization of target molecules under a high electrical field, with subsequent measurement of the generated photocurrent. We now demonstrate the method’s ability to detect BTEX in ambient air, at part-per-trillion (ppt) concentration range, providing distinct spectral signatures for each compound, including individual xylene isomers. The technique represents a significant advancement in BTEX monitoring, with potential applications in environmental sensing and industrial air quality control. Full article

Detecting volatile organic compounds (VOCs) is essential for health, environmental protection, and industrial safety. VOCs contribute to air pollution, pose health risks, and can indicate leaks or contamination in industries. Applications include air quality monitoring, disease diagnosis, and food safety. This paper focuses on polymer-based hybrid sensor arrays (HSAs) utilizing interdigitated electrode (IDE) geometries for VOC detection. Achieving high selectivity and sensitivity in gas sensing remains a challenge, particularly in complex environments. To address this, we propose HSAs as an innovative solution to enhance sensor performance. IDE-based sensors are designed and fabricated using the Polysilicon Multi-User MEMS process (PolyMUMPs). Experimental evaluations are performed by exposing sensors to VOCs under controlled conditions. Traditional multi-sensor arrays (MSAs) achieve 82% prediction accuracy, while virtual sensor arrays (VSAs) leveraging frequency dependence improve performance: PMMA-VSA and PVP-VSA predict compounds with 100% and 98% accuracy, respectively. The proposed HSA, integrating these VSAs, consistently achieves 100% accuracy in compound identification and concentration estimation, surpassing MSA and VSA performance. These findings demonstrate that proposed polymer-based HSAs and VSAs, particularly with advanced IDE geometries, significantly enhance selectivity and sensitivity, advancing e-Nose technology for more accurate and reliable VOC detection across diverse applications. Full article

Low-frequency alternating electromagnetic fields (LF-AEMF) represent an innovative processing technology with significant potential for extending the shelf life of fruits and vegetables by modulating key physiological processes. In this study, the impact of the LF-AEMF intensities (1300, 1800, and 2500 V) on the postharvest preservation of satsuma mandarins was evaluated. Compared to the control group, the LF-AEMF-treated samples exhibited reduced weight loss (0.62% vs. 2.11%), respiration rate (32.73 vs. 40.08 mg/kg·h), and malondialdehyde (MDA) content (40.80 vs. 34.87 nmol/g) after 40 days of storage. In addition, LF-AEMF treatment also effectively preserved titratable acidity (TA) (0.34% vs. 0.30%), vitamin C (Vc) content (7.77 vs. 7.05 g/100 g), and phenylalanine ammonia-lyase (PAL) activity (79.757 vs. 62.395 U/g). E-nose analysis and low-field NMR further revealed that the application of LF-AEMF effectively facilitated the superior preservation of the intrinsic flavor profile of the satsuma mandarins and mitigated the loss of free water within the fruit. Overall, this research provides valuable insights for the potential application of LF-AEMF in extending the storage life of citrus fruits, which may also be applicable to other seasonal fruits and vegetables that require long-term storage. Full article

The evaluation of aroma-active profiles in dry-cured hams is crucial for determining quality, flavor, consumer acceptance, and economic value. This study characterized the volatile compounds in five varieties of dry-cured hams using gas chromatography-mass spectrometry-olfactometry (GC-MS-O) and an electronic nose (E-Nose). In total, 78 volatile compounds were identified across five varieties of dry-cured hams. A total of 29 compounds were recognized as aroma-active compounds. Odor description, intensity, and hedonic assessment were employed to evaluate these compounds. Black Hoof Cured Ham and Special-grade Xuan-Zi Ham contained higher levels of favorable compounds such as nonanal, 5-butyldihydro-2(3H)-furanone, and 2,6-dimethylpyrazine, contributing to sweet and popcorn-like notes. In contrast, Fei-Zhong-Wang Ham and Liang-Tou-Wu Ham exhibited higher proportions of off-odor compounds with lower hedonic scores. A principal component analysis clearly separated the five hams based on their aroma-active profiles, and a correlation analysis between E-Nose sensor responses and GC-MS-O data demonstrated a strong discriminatory ability for specific samples. These findings offer valuable insights into the chemical and sensory differentiation of dry-cured hams and provide a scientific basis for quality control, product development, and future improvements in E-Nose sensor design and intelligent aroma assessment. Full article

This study investigated aroma changes in Hui Li red Sichuan pepper across five different harvesting times within their typical optimum period based on 24 traditional solar terms, employing sensory evaluation, electronic nose (E-nose), gas chromatography-ion mobility spectrometry (GC-IMS) combined with relative odour activity value (ROAV) and partial least squares discriminant analysis (PLS-DA). Sensory analysis indicated that peppers were characterised by green, citrus, minty, sweet, woody, and peppery numbing aroma attributes. E-nose revealed the greatest aroma difference in peppers occurred between the early and late optimum harvest stages. GC-IMS identified 71 volatile compounds, with esters being the most abundant. Six key compounds identified were crucial for distinguishing peppers harvested at different times. Findings provided a valuable contribution to decide the optimal harvest window for Hui Li red Sichuan peppers, maximising their applications in the seasoning industry. Full article

To enhance the nutritional and functional properties of triticale noodles, this study assessed their proximate composition, sensory attributes, and antioxidant activity, along with protein and starch digestibilities when supplemented with varying concentrations (0%, 5%, 10%, 15%) of silkworm (Antheraea pernyi and Bombyx mori) pupa powder (SP). Incorporating SP into triticale noodles led to significant enhancements in protein, fat, and ash contents (p < 0.05). The addition of SP may also lead to noticeable color and texture differences by decreasing the lightness (L*) and increasing hardness and springiness in noodles, as well as the flavor difference revealed by E-nose and E-tongue analysis. Furthermore, the total phenolic content and abilities to scavenge DPPH and ABTS radicals improved as the SP level increased. Compared to the control, the SP-fortified noodles had a significantly high in vitro protein digestibility but a low estimated glycemic index. Overall, due to their enhanced nutritional value and bioactivities, SP triticale noodles could be regarded as a healthier alternative to traditional noodles. Full article

Cyprinus carpio, Parabramis pekinensis, Aristichthys nobilis, and Lateolabrax maculatus were systematically evaluated as crucial components of Chinese aquaculture with substantial market demand. Texture profile analysis (TPA) showed C. carpio had maximal hardness, while L. maculatus displayed optimal elasticity. Nutrient composition analysis revealed that the highest crude protein content was identified in L. maculatus, while a higher crude lipid level was recorded in C. carpio. Fatty acid profiling established L. maculatus as a superior source of monounsaturated fatty acids (MUFAs), whereas P. pekinensis was distinguished by its polyunsaturated fatty acid (PUFA) content. Volatile compounds were comprehensively analyzed using an electronic nose (e-nose) coupled with HS-SPME-GC-MS, resulting in the identification of 59 flavor compounds. Molecular docking demonstrated that hydrogen bonding and π–π stacking were identified as critical mechanisms governing flavor perception. These findings offer valuable information that can support improvements in aquaculture management practices and help inform consumer choices regarding fish quality. Full article