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Effectiveness of camera traps for quantifying daytime and nighttime visitation by vertebrate pollinators
摘要： Identification of pollen vectors is a fundamental objective of pollination biology. The foraging and social behavior of these pollinators has profound effects on plant mating, making quantification of their behavior critical for understanding the ecological and evolutionary consequences of different pollinators for the plants they visit. However, accurate quantification of visitation may be problematic, especially for shy animals and/or when the temporal and spatial scale of observation desired is large. Sophisticated heat- and movement-triggered motion-sensor cameras (“camera trapping”) provide new, underutilized tools to address these challenges. However, to date, there has been no rigorous evaluation of the sampling considerations needed for using camera trapping in pollination research. We measured the effectiveness of camera trapping for identifying vertebrate visitors and quantifying their visitation rates and foraging behavior on Banksia menziesii (Proteaceae). Multiple still cameras (Reconyx HC 500) and a video camera (Little Acorn LTL5210A) were deployed. From 2,753 recorded visits by vertebrates, we identified five species of nectarivorous honeyeater (Meliphagidae) and the honey possum (Tarsipedidae), with significant variation in the species composition of visitors among inflorescences. Species of floral visitor showed significant variation in their time of peak activity, duration of visits, and numbers of flowers probed per visit. Where multiple cameras were deployed on individual inflorescences, effectiveness of individual still cameras varied from 15% to 86% of all recorded visits. Methodological issues and solutions, and the future uses of camera traps in pollination biology, are discussed. Conclusions and wider implications: Motion-triggered cameras are promising tools for the quantification of vertebrate visitation and some aspects of behavior on flowers. However, researchers need to be mindful of the variation in effectiveness of individual camera traps in detecting animals. Pollinator studies using camera traps are in their infancy, and the full potential of this developing technology is yet to be realized.
关键词： camera trapping,honeyeaters,pollination,plant mating,vertebrates,pollination syndrome,remote sensing,honey possum,Banksia
更新于2025-09-23 15:21:01
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Novel honey mediated green synthesis of Graphene@Ag Nanocomposite and its two-dimensional application in photovoltaic and anti-microbial activity
摘要： The green and facile method were successfully employed for the fabrication of Graphene/Ag nanocomposite (Gr@AgNCs) with graphite oxide (GO) as graphene precursor and AgNO3 as precursor for Ag nanoparticles. Honey was used as a reducing and stabilizing agentwhich is known to be environment-friendly in nature. The characterization of synthesized Gr@AgNCs was done using x-ray diffraction (XRD),scanning electron microscopy (SEM),Transmission electron microscopy (TEM), Fourier transform infrared spectroscopy (FT-IR), Raman spectra (RS),Thermogravimetric analysis (TGA), and UV analysis. The results showed that Honey effectively reduced GO to graphene and silver ions to silver nanoparticles (AgNPs) which makes present synthesis more suitable for synthesizing other metals like gold (Au) on graphene sheets. This active synthesis perhaps can have wide applications in medical, technological and industrial ?eld. In addition to this, enhanced antimicrobial activity of silver nanoparticles (AgNPs) was retained in the Gr@AgNCs along with the photovoltaic activity signifyingtheir potential use as a graphene-based nanomaterial.
关键词： antimicrobial activity,honey,graphene,nano materials,graphene oxide,photovoltaic activity
更新于2025-09-23 15:19:57
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Fast Quantification of Honey Adulteration with Laser-Induced Breakdown Spectroscopy and Chemometric Methods
摘要： Honey adulteration is a major issue in food production, which may reduce the effective components in honey and have a detrimental effect on human health. Herein, laser-induced breakdown spectroscopy (LIBS) combined with chemometric methods was used to fast quantify the adulterant content. Two common types of adulteration, including mixing acacia honey with high fructose corn syrup (HFCS) and rape honey, were quantified with univariate analysis and partial least squares regression (PLSR). In addition, the variable importance was tested with univariable analysis and feature selection methods (genetic algorithm (GA), variable importance in projection (VIP), selectivity ratio (SR)). The results indicated that emissions from Mg II 279.58, 280.30 nm, Mg I 285.25 nm, Ca II 393.37, 396.89 nm, Ca I 422.70 nm, Na I 589.03, 589.64 nm, and K I 766.57, 769.97 nm had compact relationship with adulterant content. Best models for detecting the adulteration ratio of HFCS 55, HFCS 90, and rape honey were achieved by SR-PLSR, VIP-PLSR, and VIP-PLSR, with root-mean-square error (RMSE) of 8.9%, 8.2%, and 4.8%, respectively. This study provided a fast and simple approach for detecting honey adulteration.
关键词： partial least square regression,laser-induced breakdown spectroscopy,adulteration,feature variable,honey
更新于2025-09-23 15:19:57
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Fast Classification of Geographical Origins of Honey Based on Laser-Induced Breakdown Spectroscopy and Multivariate Analysis
摘要： Traceability of honey is highly required by consumers and food administration with the consideration of food safety and quality. In this study, a technique named laser-induced breakdown spectroscopy (LIBS) was used to fast trace geographical origins of acacia honey and multi-floral honey. LIBS emissions from elements of Mg, Ca, Na, and K had significant differences among different geographical origins. The clusters of honey from different geographical origins were visualized with principal component analysis. In addition, support vector machine (SVM) and linear discrimination analysis (LDA) were used to quantitively classify the origins. The results indicated that SVM performed better than LDA, and the discriminant results of multi-floral honey were better than acacia honey. The accuracy and mean average precision for multi-floral honey were 99.7% and 99.7%, respectively. This study provided a fast approach for geographical origin classification, and might be helpful for food traceability.
关键词： geographical origin,classification,honey,laser-induced breakdown spectroscopy,multivariate analysis
更新于2025-09-23 15:19:57
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3-3 Piezoelectric Metamaterial with Negative and Zero Poisson’s Ratio for Hydrophones Applications
摘要： This study presents the electromechanical properties of the 3-3 piezoelectric metamaterial based on variants of honeycomb (HC) structure. Three kinds of three-dimensional (3D) elastically anisotropic and piezoelectrically active HC structures were introduced, namely, conventional HC (3D-CHC), a re-entrant HC (3D-RE) and a semi-re-entrant HC (3D-SRE). Highly porous 3D finite element models of the mentioned three kinds of metamaterials were developed and the role of ligament orientation on their effective elastic, piezoelectric and dielectric properties was completely characterized. The intrinsic symmetry of HC structure was utilized and simplified mixed boundary conditions equivalent to periodic boundary conditions were recognized. In comparison to their bulk constituent, all the 3-3 type piezoelectric HC networks exhibited an enhanced response, especially for the longitudinal poling. The normalized figures of merit show a mild dependence on the angle θ and the underlying deformation mechanisms associated with the zero, positive and negative Poisson’s ratios. Figures of merit such as hydrostatic strain coefficient (hd), the hydrostatic figure of merit (ghhd) and the acoustic impedance (Z) reached their best values at small angles, i.e., θ=30°. Longitudinally poled networks exhibited four order of magnitude increase in their hydrostatic figure of merit (foam to solid ratio >10,000) and one order of magnitude decrease in the acoustic impedance indicating their applicability for the design of hydrophones.
关键词： piezoelectric materials,auxetic smart structures,metamaterials,electromechanical properties,cellular materials,honey comb structures,unit cell method
更新于2025-09-23 15:19:57
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Multivariate and machine learning approaches for honey botanical origin authentication using near infrared spectroscopy
摘要： In this work the feasibility of near infrared spectroscopy was evaluated combined with chemometric approaches, as a tool for the botanical origin prediction of 119 honey samples. Four varieties related to polyfloral, acacia, chestnut, and linden were first characterized by their physical–chemical parameters and then analyzed in triplicate using a near infrared spectrophotometer equipped with an optical path gold reflector. Three different classifiers were built on distinct multivariate and machine learning approaches for honey botanical classification. A partial least squares discriminant analysis was used as a first approach to build a predictive model for honey classification. Spectra pretreatments named autoscale, standard normal variate, detrending, first derivative, and smoothing were applied for the reduction of scattering related to the presence of particle size, like glucose crystals. The values of the descriptive statistics of the partial least squares discriminant analysis model allowed a sufficient floral group prediction for the acacia and polyfloral honeys but not in the cases of chestnut and linden. The second classifier, based on a support vector machine, allowed a better classification of acacia and polyfloral and also achieved the classification of chestnut. The linden samples instead remained unclassified. A further investigation, aimed to improve the botanical discrimination, exploited a feature selection algorithm named Boruta, which assigned a pool of 39 informative averaged near infrared spectral variables on which a canonical discriminant analysis was assessed. The canonical discriminant analysis accounted a better separation of samples according to the botanical origin than the partial least squares discriminant analysis. The approach used has permitted to achieve a complete authentication of the acacia honeys but not a precise segregation of polyfloral ones. The comparison between the variables important in projection and the Boruta pool showed that the informative wavelengths are partially shared especially in the middle and far band of the near infrared spectral range.
关键词： botanical origin,Honey,near infrared spectroscopy,support vector machine,variable importance in projection,canonical discriminant analysis
更新于2025-09-19 17:15:36
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Honey exposed to laser-induced breakdown spectroscopy for chaos-based botanical classification and fraud assessment
摘要： Given that honey is among the top ten foods with the highest adulteration rate in the European Union, in this research, a tool has been developed to tackle this malpractice. The combination of laser-induced breakdown spectroscopy (LIBS) and chaotic parameters has been employed to classify six European honeys of different botanical origins as well as detect samples containing the usually elusive rice syrup adulteration in weight concentrations as low as 2 %. The profiles of the LIBS emission spectra can be used to faithfully classify honey in terms of botanical origin by combining information extracted directly from the spectra with simple linear modeling. In contrast, the detection of low amounts of rice syrup in honey is not as straightforward, which is why algorithms based on chaotic parameters such as shifted (lag-k) autocorrelation coefficients were employed to extract underlying information representative of adulterated samples. Since these algorithms are capable of detecting slight changes in the composition of honeys, it has been possible to identify these adulterations with a success rate greater than 90 % when samples from honeys of different botanical origins are combined into the same model, and over 95 % when individual honey types are analyzed.
关键词： Chaotic Parameters,Classification,LIBS,Adulteration,Botanical Origin,Honey
更新于2025-09-16 10:30:52
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Recent Advances and Applications of Near Infrared Spectroscopy for Honey Quality Assessment
摘要： Currently, most of the technologies used to identify honey quality are inefficient and costly. There is a necessity to develop a more effective one for honey quality assessment. Near Infrared Spectroscopy (NIRS) has the potential to be such a technique for its unique characteristics. This study reviews recent advances and applications of NIR spectroscopy in honey authentication domain including constituents, adulteration, brand, botanical origin and geographical origin. It presents a comprehensive using of this technology, with advantages and limitations, in honey quality detection, which offers insights on selecting the most appropriate NIR spectroscopic method for samples presentation, spectral acquisition, spectral pretreatment and modeling. Future research is to be focused on increasing model robustness, developing overall NIR spectroscopic database and a NIR-based integrated technology system on honey quality assessment.
关键词： honey,near infrared spectroscopy,Advances,detection,applications
更新于2025-09-04 15:30:14