Development of Fast E-nose System for Early-Stage Diagnosis of Aphid-Stressed Tomato Plants.

An electronic nose (E-nose) system equipped with a sensitive sensor array was developed for fast diagnosis of aphid infestation on greenhouse tomato plants at early stages. Volatile organic compounds (VOCs) emitted by tomato plants with and without aphid attacks were detected using both the developed E-nose system and gas chromatography mass spectrometry (GC-MS), respectively. Sensor performance, with fast sensor responses and high sensitivity, were observed using the E-nose system. A principle component analysis (PCA) indicated accurate diagnosis of aphid-stressed plants compared to healthy ones, with the first two PCs accounting for 86.7% of the classification. The changes in VOCs profiles of the healthy and infested tomato plants were quantitatively determined by GC-MS. Results indicated that a group of new VOCs biomarkers (linalool, carveol, and nonane (2,2,4,4,6,8,8-heptamethyl-)) played a role in providing information on the infestation on the tomato plants. More importantly, the variation in the concentration of sesquiterpene VOCs (e.g., caryophyllene) and new terpene alcohol compounds was closely associated with the sensor responses during E-nose testing, which verified the reliability and accuracy of the developed E-nose system. Tomato plants growing in spring had similar VOCs profiles as those of winter plants, except several terpenes released from spring plants that had a slightly higher intensity.

Plant Pest Detection Using an Artificial Nose System: A Review.

This paper reviews artificial intelligent noses (or electronic noses) as a fast and noninvasive approach for the diagnosis of insects and diseases that attack vegetables and fruit trees. The particular focus is on bacterial, fungal, and viral infections, and insect damage. Volatile organic compounds (VOCs) emitted from plants, which provide functional information about the plant's growth, defense, and health status, allow for the possibility of using noninvasive detection to monitor plants status. Electronic noses are comprised of a sensor array, signal conditioning circuit, and pattern recognition algorithms. Compared with traditional gas chromatography-mass spectrometry (GC-MS) techniques, electronic noses are noninvasive and can be a rapid, cost-effective option for several applications. However, using electronic noses for plant pest diagnosis is still in its early stages, and there are challenges regarding sensor performance, sampling and detection in open areas, and scaling up measurements. This review paper introduces each element of electronic nose systems, especially commonly used sensors and pattern recognition methods, along with their advantages and limitations. It includes a comprehensive comparison and summary of applications, possible challenges, and potential improvements of electronic nose systems for different plant pest diagnoses.

Discrimination of American ginseng and Asian ginseng using electronic nose and gas chromatography-mass spectrometry coupled with chemometrics.

BACKGROUND: American ginseng (Panax quinquefolius L.) and Asian ginseng (Panax ginseng Meyer) products, such as slices, have a similar appearance, but they have significantly different prices, leading to widespread adulteration in the commercial market. Their aroma characteristics are attracting increasing attention and are supposed to be effective and nondestructive markers to determine adulteration. METHODS: The aroma characteristics of American and Asian ginseng were investigated using gas chromatography-mass spectrometry(GC-MS) and an electronic nose (E-nose). Their volatile organic compounds were separated, classified, compared, and analyzed with different pattern recognition. RESULTS: The E-nose showed a good performance in grouping with a principle component analysis explaining 94.45% of variance. A total of 69 aroma components were identified by GC-MS, with 35.6% common components and 64.6% special ingredients between the two ginsengs. It was observed that the components and the number of terpenes and alcohols were markedly different, indicating possible reasons for their difference. The results of pattern recognition confirmed that the E-nose processing result is similar to that of GC-MS. The interrelation between aroma constituents and sensors indicated that special sensors were highly related to some terpenes and alcohols. Accordingly, the contents of selected constituents were accurately predicted by corresponding sensors with most R2 reaching 90%. CONCLUSION: Combined with advanced chemometrics, the E-nose is capable of discriminating between American and Asian ginseng in both qualitative and quantitative angles, presenting an accurate, rapid, and nondestructive reference approach.

Value-added processing of crude glycerol into chemicals and polymers.

Crude glycerol is a low-value byproduct which is primarily obtained from the biodiesel production process. Its composition is significantly different from that of pure glycerol. Crude glycerol usually contains various impurities, such as water, methanol, soap, fatty acids, and fatty acid methyl esters. Considerable efforts have been devoted to finding applications for converting crude glycerol into high-value products, such as biofuels, chemicals, polymers, and animal feed, to improve the economic viability of the biodiesel industry and overcome environmental challenges associated with crude glycerol disposal. This article reviews recent advances of biological and chemical technologies for value-added processing of crude glycerol into chemicals and polymers, and provides strategies for addressing production challenges.

Qualitative and quantitative analysis on aroma characteristics of ginseng at different ages using E-nose and GC-MS combined with chemometrics.

Aroma profiles of ginseng samples at different ages were investigated using electronic nose (E-nose) and GC-MS techniques combined with chemometrics analysis. The bioactive ginsenoside and volatile oil content increased with age. E-nose performed well in the qualitative analyses. Both Principal Component Analysis (PCA) and Discriminant Functions Analysis (DFA) performed well when used to analyze ginseng samples, with the first two principal components (PCs) explaining 85.51% and the first two factors explaining 95.51% of the variations. Hierarchical Cluster Analysis (HCA) successfully clustered the different types of ginsengs into four groups. A total of 91 volatile constituents were identified. 50 of them were calculated and compared using GC-MS. The main fragrance ingredients were terpenes and alcohols, followed by aromatics and ester. The changes in terpenes, alcohols, aromatics, esters, and acids during the growth year once again confirmed the dominant role of terpenes. The Partial Least Squares (PLS) loading plot of gas sensors and aroma ingredients indicated that particular sensors were closely related to terpenes. The scores plot indicated that terpenes and its corresponding sensors contributed the most in grouping. As regards to quantitative analyze, 7 constituent of terpenes could be accurately explained and predicted by using gas sensors in PLS models. In predicting ginseng age using Back Propagation-Artificial Neural Networks (BP-ANN), E-nose data was found to predict more accurately than GC-MS data. E-nose measurement may be a potential method for determining ginseng age. The combination of GC-MS can help explain the hidden correlation between sensors and fragrance ingredients from two different viewpoints.

Taste characteristics based quantitative and qualitative evaluation of ginseng adulteration.

BACKGROUND: Adulteration of American ginseng with Asian ginseng is common and has caused much damage to customers. Panel evaluation is commonly used to determine their differences, but it is subjective. Chemical instruments are used to identify critical compounds but they are time-consuming and expensive. Therefore, a fast, accurate and convenient method is required. A taste sensing system, combining both advantages of the above two technologies, provides a novel potential technology for determining ginseng adulteration. The aim is to build appropriate models to distinguish and predict ginseng adulteration by using taste characteristics. RESULTS: It was found that ginsenoside contents decreased linearly (R(2) = 0.92) with mixed ratios. A bioplot of principal component analysis showed a good performance in classing samples with the first two principal components reaching 89.7%, and it was noted that it was the bitterness, astringency, aftertaste of bitterness and astringency, and saltiness leading the successful determination. After factor screening, bitterness, astringency, aftertaste of bitterness and saltiness were employed to build latent models. Tastes of bitterness, astringency and aftertaste bitterness were demonstrated to be most effective in predicting adulteration ratio, mean while, bitterness and aftertaste bitterness turned out to be most effective in ginsenoside content prediction. CONCLUSION: Taste characteristics of adulterated ginsengs, considered as taste fingerprint, can provide novel guidance for determining the adulteration of American and Asian ginseng.