Volatile biomarkers for early-stage detection of insect-infested brown rice: Isopentenols and polysulfides

Comprehensive Analysis on Physicochemical Properties and Characteristic Compounds of Insect-Infested Ziziphi Spinosae Semen

Objectives: Ziziphi spinosae semen (ZSS), an edible and medicinal substance, was easily infested by Plodia interpunctella (P. interpunctella) during storage. However, there was no identification method for insect-infested ZSS based on its chemical composition. Therefore, the characteristic compounds in ZSS before and after being infested by P. interpunctella were discovered based on the comparison of volatile organic compounds (VOCs), untargeted metabolomics, and other quality characters. Methods: Color, total flavonoid content (TFC), and main active compound content were measured to explore the change of physicochemical properties in ZSS after being infested by P. interpunctella. Non-targeted metabolomic techniques, including ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) and headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) were used to assess molecular-level alterations. Results: The color changed significantly. The TFC and main active compounds of spinosin, jujuboside A, jujuboside B, and betulinic acid were decreased significantly. A total of nine VOCs and twenty-one metabolites were screened out that could be used to identify whether ZSS was infested. And some metabolites, such as uric acid, gluconic acid, hypoxanthine, and xanthine, were discovered as characteristic compounds in ZSS after being infested by P. interpunctella. Conclusions: The study provided the basis and reference for the identification of insect-infested ZSS and offered an example for the identification of other insect-infested edible and medicinal materials.

Volatile Byproducts of Carotenoid Degradation as Biomarkers of Maize Infestation by the Maize Weevil (Sitophilus zeamais) (Motsch.)

Maize (Zea mays) is a major global food crop and a source of industrial raw materials. Effective postharvest storage is important for national food security programs, international trade, and global agriculture economics. The maize weevil (Sitophilus zeamais) is a primary postharvest insect pest that infests maize during storage and leads to significant losses. Using multivariate discriminant analysis of volatile profiles collected from intact and infested maize, we identified two volatile apocarotenoids, 6-methyl-5-hepten-2-one and 6-methyl-5-hepten-2-ol, as indicators of maize weevil infestation in stored maize. Emission of these biomarker compounds rapidly signaled maize weevil infestation and showed a significant correlation with oviposition damage to the stored kernels. The pattern of elevated biomarker emission after weevil exposure was consistent across all seven maize lines examined. These volatile biomarkers can be used for early detection and removal of infested maize and can aid in the control of this pest.

Novel pyrazole and imidazolone compounds: synthesis, X-ray crystal structure with theoretical investigation of new pyrazole and imidazolone compounds anticipated insecticide's activities against targeting Plodia interpunctella and nilaparvata lugens

In this study, we synthesized (2-propoxyphenyl)(3-(p-tolyl)oxiran-2-yl)methanone through oxidizing the double bond of the respective chalcone via the Weitz-Scheffer epoxidation reaction. Additionally, the chalcone with an oxirane ring served as a fundamental building block for the synthesis of various pyrazole and imidazole derivatives, employing diverse nitrogen nucleophiles. All synthesized compounds were confirmed via analytical and spectroscopic analysis, such as FT-IR, 1H NMR, 13C NMR, and mass spectroscopy. Furthermore, all these nitrogen heterocycles were optimized via the DFT/B3LYP/6-31G(d,p) basis set and their physical descriptors were identified. Compound 11 was further confirmed using single-crystal X-ray diffraction with Hirshfeld analysis, and the results were correlated with the optimized structure by comparing their bond length and bond angle, which provided excellent correlation. Additionally, the insecticidal activities of the newly synthesized compounds were tested against P. interpunctella and Nilaparvata lugens. The heterocyclic compounds exhibited remarkable activity compared to the standard reference thiamethoxam. These findings were further confirmed through docking simulation with different proteins, namely PDBID 3aqy and 3wyw. The compounds interacted effectively within the protein pockets, displaying a higher binding energy with amino acids.

Detection of Specific Volatile Organic Compounds in Tribolium castaneum (Herbst) by Solid-Phase Microextraction and Gas Chromatography-Mass Spectrometry

The red flour beetle, Tribolium castaneum (Herbst) (Coleoptera: Tenebrionidae), is a major storage pest that could lead to a wide range of damage. Its secretions have a significant impact on the quality of stored grain and food, leading to serious food safety problems such as grain spoilage and food carcinogenesis. This study investigates new detection techniques for grain storage pests to improve grain insect detection in China. The primary volatile organic chemicals (VOCs) in these secretions are identified using headspace solid-phase microextraction (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS). The specific VOCs that are unique to T. castaneum are selected as criteria for determining the presence of T. castaneum in the granary. To obtain more specific VOCs, experiments were designed for the analysis of T. castaneum samples under different extraction times, two types of SPME fibers and two GC-MS devices of different manufacturers. The experimental results showed that 12 VOCs were detected at relatively high levels, seven of which were common and which were not detected in other grains and grain insects. The seven compounds are 1-pentadecene, 2-methyl-p-benzoquinone, 2-ethyl-p-benzoquinone, 1-hexadecene, cis-9-tetradecen-1-ol, m-cresol and paeonol. These seven compounds can be used as volatile markers to identify the presence of T. castaneum, which could serve as a research foundation for the creation of new techniques for T. castaneum monitoring.

The Effects of Insect Infestation on Stored Agricultural Products and the Quality of Food

In this review article, we focus on the effects of insect pests on the quality of stored cereals and legume grains. The changes in the amino-acid content, the quality of proteins, carbohydrates, and lipids, and the technological characteristics of the raw materials when infested by specific insects are presented. The differences reported concerning the rate and kind of infestation effects are related to the trophic habits of the infesting insect species, the variation of the component distribution in the different species of grains, and the length of the storage period. For example, wheat germ and brans feeders such as Trogoderma granarium may cause a higher reduction in proteins than endosperm feeders such as Rhyzopertha dominica, since the germ and brans contain higher concentrations of proteins. Trogoderma granarium may also cause higher reduction in lipids than R. dominica in wheat, maize and sorghum, in which most of the lipids exist in the germ. Furthermore, infestation with insects such as Tribolium castaneum may downgrade the overall quality of wheat flour, by increasing the moisture content, the number of insect fragments, the color change, the concentration of uric acid, the microbial growth, and the prevalence of aflatoxins. Whenever possible, the significance of the insect infestation and the concomitant compositional alterations on human health are presented. It should be highlighted that understanding the impact of insect infestation on stored agricultural products and the quality of food will be crucial for the required food security in the future.

Early infestation volatile biomarkers of fruit fly Bactrocera dorsalis (Hendel) ovipositional activity in mango (Mangifera indica L.)

Infestation of agricultural commodities by insect pests results in significant economic, import and export, food safety, and invasive insect introduction issues for growers, consumers, and inspectors. The Oriental fruit fly (Bactrocera dorsalis) is considered a highly invasive insect pest with populations reported in more than 60 countries, with prevalent distributions in Asia and Africa. B. dorsalis is phytophagous with a host range encompassing hundreds of fruits and vegetables. Damage to the fruit or vegetable is inflicted through oviposition and subsequent larval feeding resulting in spoilage. Early detection of insect pest infestations is a critical component for ensuring food safety as well as controlling introduction and spread of invasive insects. However, detection of ovipositional activity and early larval development is visually difficult, thus rapid and non-destructive detection often relies on odors associated with infestation. We investigated the odors of mangoes (Mangifera indica L.) infested with B. dorsalis and compared the volatile profiles of infested mangoes to non-infested and mechanically damaged mangoes 24 h post-infestation. GC-MS and multivariate analyses provided the identification of eleven compounds unique to infested mangoes compared to mechanically damaged or non-infested fruit. Results indicated compositional and quantitative differentiation of volatile profiles among treatments for detection of infested fruit at quality checks or points of commerce.

Non-Destructive Detection of Soybean Pest Based on Hyperspectral Image and Attention-ResNet Meta-Learning Model

Soybean plays an important role in food, medicine, and industry. The quality inspection of soybean is essential for soybean yield and the agricultural economy. However, soybean pest is an important factor that seriously affects soybean yield, among which leguminivora glycinivorella matsumura is the most frequent pest. Aiming at the problem that the traditional detection methods have low accuracy and need a large number of samples to train the model, this paper proposed a detection method for leguminivora glycinivorella matsumura based on an A-ResNet (Attention-ResNet) meta-learning model. In this model, the ResNet network was combined with Attention to obtain the feature vectors that can better express the samples, so as to improve the performance of the model. As well, the classifier was designed as a multi-class support vector machine (SVM) to reduce over-fitting. Furthermore, in order to improve the training stability of the model and the prediction performance on the testing set, the traditional Batch Normalization was replaced by the Layer Normalization, and the Label Smooth method was used to punish the original loss. The experimental results showed that the accuracy of the A-ResNet meta-learning model reached 94.57 ± 0.19%, which can realize rapid and accurate nondestructive detection, and provides theoretical support for the intelligent detection of soybean pests.

Potential volatile markers of brown rice infested by the rice weevil, Sitophilus oryzae (L.) (Coleoptera: Curculionidae)

The rice weevil, Sitophilus oryzae (L.) (Coleoptera: Curculionidae) could cause significant grain loss by feeding internally on seeds. In this study, we tried to analyze the volatile compounds in non-infested and S. oryzae-infested brown rice during different storage periods to identify potential markers in S. oryzae-infested brown rice and facilitate pest monitoring during brown rice storage. Headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC-MS) and headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) were used to identify the volatile compounds. On the basis of GC-MS and GC-IMS data, a reliable method to distinguish between non-infested and S. oryzae-infested brown rice was discovered using partial least squares-discriminant analysis (PLS-DA). 1-Octen-3-ol, 1-hexanol and 3-octanone were co-selected as potential markers because their variable importance in projection (VIP) was greater than 1 in both models. The current study's findings lay a foundation for further research on the brown rice infestation mechanism and safe storage monitoring.

Correlation between Irradiation Treatment and Metabolite Changes in Bactrocera dorsalis (Diptera: Tephritidae) Larvae Using Solid-Phase Microextraction (SPME) Coupled with Gas Chromatography-Mass Spectrometry (GC-MS)

The metabolites produced by the larvae of Bactrocera dorsalis (Diptera: Tephritidae) exposed to different doses of irradiation were analyzed using solid phase microextraction (SPME) and gas chromatography-mass spectrometry (GC-MS), and a metabonomic analysis method of irradiated insects based on GC-MS was established. The analysis revealed 67 peaks, of which 23 peaks were identified. The metabolites produced by larvae treated with different irradiation doses were compared by multivariate statistical analysis, and eight differential metabolites were selected. Irradiation seriously influenced the fatty acid metabolic pathway in larvae. Using the R platform combined with the method of multivariate statistical analysis, changes to metabolite production under four irradiation doses given to B. dorsalis larvae were described. Differential metabolites of B. dorsalis larvae carried chemical signatures that indicated irradiation dose, and this method is expected to provide a reference for the detection of irradiated insects.

Research advance in gas detection of volatile organic compounds released in rice quality deterioration process

Rice quality deterioration will cause grievous waste of stored grain and various food safety problems. Gas detection of volatile organic compounds (VOCs) produced by deterioration is a nondestructive detection method to judge rice quality and alleviate rice spoilage. This review discussed the research advance of VOCs detection in terms of nondestructive detection methods of rice quality deterioration, applications of VOCs in grain detection, inspection of characteristic gas produced during rice spoilage, rice deterioration prevention and control, and detection of VOCs released by rice mildew and insect attack. According to the main causes of rice quality deterioration and major sources of VOCs with off-odor generated during rice storage, deterioration can be divided into mold and insect infection. The results of literature manifested that researches mainly focused on the infection of Aspergillus in the mildew process and the attack of certain pests in recent years, thus the research scope was limited. In this paper, the gas detection methods combined with the chemometrics to qualitatively analyze the VOCs, as well as the correlation with the number of colonies and insects were further studied based on the common dominant strains during rice mildew, that is, Aspergillus and Penicillium fungi, and the common pests during storage, that is, Sitophilus oryzae and Rhyzopertha dominica. Furthermore, this paper pointed out that the quantitative determination of characteristic VOCs, the numeration relationship between VOCs and the degree of mildew and insect infestation, the further expansion of detection range, and the application of degraded rice should be the spotlight of future research.