Search Results (5)

Citrus is one of the most important economic crops and is widely distributed across the monsoon region. Citrus fruits are deeply loved by consumers because of their special color, fragrance and high nutritional value. However, their health benefits have not been fully understood, especially the pericarps of citrus fruits which have barely been utilized due to their unknown chemical composition. In the present study, the pericarp and juices of four typical varieties of citrus fruits (lemon, dekopon, sweet orange and pomelo) were analyzed by NMR spectroscopy combined with pattern recognition. A total of 62 components from the citrus juices and 87 components from the citrus pericarps were identified and quantified, respectively. The different varieties of the citrus fruits could be distinguished from the others, and the chemical markers in each citrus juice and pericarp were identified by a combination of univariate and multivariate statistical analyses. The nutritional analysis of citrus juices offers favorable diet recommendations for human consumption and data guidance for their potential medical use, and the nutritional analysis of citrus pericarps provides a data reference for the subsequent comprehensive utilization of citrus fruits. Our results not only provide an important reference for the potential nutritional and medical values of citrus fruits but also provide a feasible platform for the traceability analysis, adulteration identification and chemical composition analysis of other fruits. Full article

Floral fragrance is one of the most important characteristics of ornamental plants and plays a pivotal role in plant lifespan such as pollinator attraction, pest repelling, and protection against abiotic and biotic stresses. However, the precise determination of floral fragrance is limited. In the present study, the floral volatile compounds of six Hedychium accessions exhibiting from faint to highly fragrant were comparatively analyzed via gas chromatography–mass spectrometry (GC–MS) and Electronic nose (E-nose). A total of 42 volatile compounds were identified through GC–MS analysis, including monoterpenoids (18 compounds), sesquiterpenoids (12), benzenoids/phenylpropanoids (8), fatty acid derivatives (2), and others (2). In Hedychium coronarium ‘ZS’, H. forrestii ‘Gaoling’, H. ‘Jin’, H. ‘Caixia’, and H. ‘Zhaoxia’, monoterpenoids were abundant, while sesquiterpenoids were found in large quantities in H. coccineum ‘KMH’. Hierarchical clustering analysis (HCA) divided the 42 volatile compounds into four different groups (I, II, III, IV), and Spearman correlation analysis showed these compounds to have different degrees of correlation. The E-nose was able to group the different accessions in the principal component analysis (PCA) corresponding to scent intensity. Furthermore, the pattern-recognition findings confirmed that the E-nose data validated the GC–MS results. The partial least squares (PLS) analysis between floral volatile compounds and sensors suggested that specific sensors were highly sensitive to terpenoids. In short, the E-nose is proficient in discriminating Hedychium accessions of different volatile profiles in both quantitative and qualitative aspects, offering an accurate and rapid reference technique for future applications. Full article

There is an interest in sensors for the detection of odorant molecules in the gaseous phase, especially those related to the fragrance of fruits, because odorant sensing is useful for on-site quality control of agricultural products. Previously, gas-chromatographic methods requiring bench-top devices were used for odorant-molecule detection. Herein, we report an odorant sensor based on cyclodextrins (CDs) as a stable odorant receptor, using a highly mass-sensitive and quantitative 27-MHz quartz crystal microbalance (QCM) device, which has the advantage of possible incorporation into portable devices. When ethyl butyrate (a model odorant molecule for fruit fragrances) was flowed onto a QCM plate modified with α-, β-, or γ-CD network films, a decrease in frequency was observed (corresponding to an increase in mass), owing to the capture of odorant molecules by CD molecules. The CD films were capable of capturing and releasing odorant molecules, depending on the type of CD (α-, β-, or γ-CD). Thus, these sensors are reusable for odorant-molecule sensing, and are applicable to pattern recognition of odorant molecules. Thus, sensors based on CD films combined with a QCM handheld device could be applied to monitoring the condition of fruits. Full article

Fast gas chromatography-surface acoustic wave sensor (GC/SAW) has been applied for the detection of the pharmacological volatiles emanated from Houttuynia cordata Thunb which is from South Korea. H. cordata Thunb with unpleasant and fishy odors shows a variety of pharmacological activities such as anti-microbial, anti-inflammatory, anti-cancer, and insect repellent. The aim of this study is to show a novel quality control by GC/SAW methodology for the discrimination of the three different parts of the plant such as leaves, aerial stems, and underground stems for H. cordata Thunb. Sixteen compounds were identified. β-Myrcene, cis-ocimene and decanal are the dominant volatiles for leaves (71.0%) and aerial stems (50.1%). While, monoterpenes (74.6%) are the dominant volatiles for underground stems. 2-Undecanone (1.3%) and lauraldehyde (3.5%) were found to be the characteristic components for leaves. Each part of the plant has its own characteristic fragrance pattern owing to its individual chemical compositions. Moreover, its individual characteristic fragrance patterns are conducive to discrimination of the three different parts of the plant. Consequently, fast GC/SAW can be a useful analytical method for quality control of the different parts of the plant with pharmacological volatiles as it provides second unit analysis, a simple and fragrant pattern recognition. Full article

Monitoring indoor air quality (IAQ) is deemed important nowadays. A sophisticated IAQ monitoring system which could classify the source influencing the IAQ is definitely going to be very helpful to the users. Therefore, in this paper, an IAQ monitoring system has been proposed with a newly added feature which enables the system to identify the sources influencing the level of IAQ. In order to achieve this, the data collected has been trained with artificial neural network or ANN—a proven method for pattern recognition. Basically, the proposed system consists of sensor module cloud (SMC), base station and service-oriented client. The SMC contain collections of sensor modules that measure the air quality data and transmit the captured data to base station through wireless network. The IAQ monitoring system is also equipped with IAQ Index and thermal comfort index which could tell the users about the room’s conditions. The results showed that the system is able to measure the level of air quality and successfully classify the sources influencing IAQ in various environments like ambient air, chemical presence, fragrance presence, foods and beverages and human activity. Full article