Mechanochemical effects on the structural properties of wheat starch during vibration ball milling of wheat endosperm.

Pure wheat endosperm was fully ground in a vibratory ball mill and structural changes in wheat starch were measured to assess the effect of mechanochemical action during the grinding process. Vibratory ball milling changed the endosperm granule size to ~30 µm (D50). There was a significant increase in damaged starch content, and this was positively correlated with the grinding time. The relative crystallinity of starch decreased by 5% after milling 105 min, and the short-range order decreased. The damaged structure of amylopectin starch decreased with milling time, as detected macroscopically by the peak viscosity and final viscosity of milling samples. Overall, the in vitro digestion results showed that mechanical modification caused irregular defects inside wheat starch crystals, increased the sensitivity of wheat starch to enzymes, enhanced the hydrolysis rate three-fold, and increased the maximum starch hydrolysis by 50%. Mechanochemistry effects was used to analyze the quality changes in wheat milling.

Sourdough improves the quality of whole-wheat flour products: Mechanisms and challenges-A review.

Increasing the intake of whole-wheat flour (WWF) products is one of the methods to promote health. Sourdough fermentation is increasingly being used in improving the quality of WWF products. This review aims to analyze the effect of sourdough fermentation on WWF products. The effects of sourdough on bran particles, starch, and gluten, as well as the rheology, antinutritional factors, and flavor components in WWF dough/products are comprehensively reviewed. Meanwhile, sourdough fermentation technology has a promising future in reducing anti-nutritional factors and toxic and harmful substances in WFF products. Finally, researchers are encouraged to focus on the efficient strain screening and metabolic pathway control of sourdough for WWF products, as well as the use of bran pre-fermentation and integrated biotechnology to improve the quality of whole-wheat products. This review provides a comprehensive understanding of the effect of sourdough fermentation technology on wholemeal products to promote WWF production.

Effects of thermal properties and behavior of wheat starch and gluten on their interaction: A review.

Starch and gluten, the most important macromolecules in wheat flour, vary in thermal properties. The thermal behavior of starch, gluten and their complexes during the manufacture and quality control of flour products need to be accurately understood. However, the high complexity of starch-gluten systems impedes the accurate description of their interactions. When heated within varying temperature ranges and when water molecules are involved, the behaviors of amylose and amylopectin change, and the properties of the starch are modified. Moreover, important indicators of starch granules such as gelatinization temperature, peak viscosity, and so on, which are encapsulated by the gluten matrix, are altered. Meanwhile, the high-temperature environment induces the opening of the intrachain disulfide bonds of gliadin, leading to an increase in the probability of interchain disulfide bond formation in the gluten network system. These behaviors are notable and may provide insights into this complex interaction. In this review, the relationship between the thermal behavior of wheat starch and gluten and the quality of flour products is analyzed. Several methods used to investigate the thermal characteristics of wheat and its flour products are summarized, and some thermal interaction models of starch and gluten are proposed.

Detection Method of Citrus Psyllids With Field High-Definition Camera Based on Improved Cascade Region-Based Convolution Neural Networks.

Citrus psyllid is the only insect vector of citrus Huanglongbing (HLB), which is the most destructive disease in the citrus industry. There is no effective treatment for HLB, so detecting citrus psyllids as soon as possible is the key prevention measure for citrus HLB. It is time-consuming and laborious to search for citrus psyllids through artificial patrol, which is inconvenient for the management of citrus orchards. With the development of artificial intelligence technology, a computer vision method instead of the artificial patrol can be adopted for orchard management to reduce the cost and time. The citrus psyllid is small in shape and gray in color, similar to the stem, stump, and withered part of the leaves, leading to difficulty for the traditional target detection algorithm to achieve a good recognition effect. In this work, in order to make the model have good generalization ability under outdoor light condition, a high-definition camera to collect data set of citrus psyllids and citrus fruit flies under natural light condition was used, a method to increase the number of small target pests in citrus based on semantic segmentation algorithm was proposed, and the cascade region-based convolution neural networks (R-CNN) (convolutional neural network) algorithm was improved to enhance the recognition effect of small target pests using multiscale training, combining CBAM attention mechanism with high-resolution feature retention network high-resoultion network (HRNet) as feature extraction network, adding sawtooth atrous spatial pyramid pooling (ASPP) structure to fully extract high-resolution features from different scales, and adding feature pyramid networks (FPN) structure for feature fusion at different scales. To mine difficult samples more deeply, an online hard sample mining strategy was adopted in the process of model sampling. The results show that the improved cascade R-CNN algorithm after training has an average recognition accuracy of 88.78% for citrus psyllids. Compared with VGG16, ResNet50, and other common networks, the improved small target recognition algorithm obtains the highest recognition performance. Experimental results also show that the improved cascade R-CNN algorithm not only performs well in citrus psylla identification but also in other small targets such as citrus fruit flies, which makes it possible and feasible to detect small target pests with a field high-definition camera.

Citrus Huanglongbing Detection Based on Multi-Modal Feature Fusion Learning.

Citrus Huanglongbing (HLB), also named citrus greening disease, occurs worldwide and is known as a citrus cancer without an effective treatment. The symptoms of HLB are similar to those of nutritional deficiency or other disease. The methods based on single-source information, such as RGB images or hyperspectral data, are not able to achieve great detection performance. In this study, a multi-modal feature fusion network, combining a RGB image network and hyperspectral band extraction network, was proposed to recognize HLB from four categories (HLB, suspected HLB, Zn-deficient, and healthy). Three contributions including a dimension-reduction scheme for hyperspectral data based on a soft attention mechanism, a feature fusion proposal based on a bilinear fusion method, and auxiliary classifiers to extract more useful information are introduced in this manuscript. The multi-modal feature fusion network can effectively classify the above four types of citrus leaves and is better than single-modal classifiers. In experiments, the highest accuracy of multi-modal network recognition was 97.89% when the amount of data was not very abundant (1,325 images of the four aforementioned types and 1,325 pieces of hyperspectral data), while the single-modal network with RGB images only achieved 87.98% recognition and the single-modal network using hyperspectral information only 89%. Results show that the proposed multi-modal network implementing the concept of multi-source information fusion provides a better way to detect citrus HLB and citrus deficiency.

Characterization of an Ecdysteroid-Regulated 16 kDa Protein Gene in Chinese Oak Silkworm, Antheraea pernyi (Lepidoptera: Saturniidae).

A large number of ecdysteroid-regulated 16 kDa proteins (ESR16s) of insects have been isolated and annotated in GenBank; however, knowledge on insect ESR16s remain limited. In the present study, we characterized an ecdysteroid-regulated 16 kDa protein gene isolated in Chinese oak silkworm, Antheraea pernyi Guérin-Méneville ('ApESR16' in the following), an important silk-producing and edible insect. The obtained cDNA sequence of ApESR16 is 1,049 bp, harboring an open reading frame of 441 bp that encodes a polypeptide of 146 amino acids. CD-search revealed that ApESR16 contains the putative cholesterol/lipid binding sites on conserved domain Npc2_like (Niemann-Pick type C-2) belonging to the MD-2-related lipid-recognition superfamily. Sequence comparison revealed that ApESR16 exhibits 51-57% identity to ESR16s of lepidopteran insects, 36-41% identity to ESR16 or NPC2a of nonlepidopteran insects, and 28-32% identity to NPC2a of vertebrates, indicating a high sequence divergence during the evolution of animals. Phylogenetic analysis found that the used sequences were divided into two groups corresponding to vertebrates and invertebrates, and the used insect sequences were also well clustered according to their families. The A. pernyi ESR16 mRNA is expressed during all four developmental stages and in all tested tissues. Injection of 20-hydroxyecdysone (20-E) into A. pernyi diapausing pupae triggering diapause termination induced upregulation of ESR16 mRNA compared to the diapausing pupae, with the highest expression level at day 2 in the ovaries but day 12 in the fat body. Our results suggested that ApESR16 might be a diapause-related gene and plays a vital role in the pupal diapause of A. pernyi.

Transcriptome Analysis of the Midgut of the Chinese Oak Silkworm Antheraea pernyi Infected with Antheraea pernyi Nucleopolyhedrovirus.

The Antheraea pernyi nucleopolyhedrovirus (ApNPV) is an exclusive pathogen of A. pernyi. The intense interactions between ApNPV and A. pernyi cause a series of physiological and pathological changes to A. pernyi. However, no detailed report exists regarding the molecular mechanisms underlying the interactions between ApNPV and A. pernyi. In this study, four cDNA libraries of the A. pernyi midgut, including two ApNPV-infected groups and two control groups, were constructed for transcriptomic analysis to provide new clues regarding the molecular mechanisms that underlie these interactions. The transcriptome of the A. pernyi midgut was de novo assembled using the Trinity platform because of the lack of a genome resource for A. pernyi. Compared with the controls, a total of 5,172 differentially expressed genes (DEGs) were identified, including 2,183 up-regulated and 2,989 down-regulated candidates, of which 2,965 and 911 DEGs were classified into different GO categories and KEGG pathways, respectively. The DEGs involved in A. pernyi innate immunity were classified into several categories, including heat-shock proteins, apoptosis-related proteins, serpins, serine proteases and cytochrome P450s. Our results suggested that these genes were related to the immune response of the A. pernyi midgut to ApNPV infection via their essential roles in regulating a variety of physiological processes. Our results may serve as a basis for future research not only on the molecular mechanisms of ApNPV invasion but also on the anti-ApNPV mechanism of A. pernyi.

Preparation and characterization of molecularly imprinted microspheres for dibutyl phthalate recognition in aqueous environment.

Molecularly imprinted microspheres (MIMs) were prepared by suspension polymerization for the binding and recognition of dibutyl phthalate (DBP). DBP was used as the template molecule, methacrylic acid as the functional monomer, ethylene dimethacrylate (EDMA) as the linking agent, PVA as the dispersing agent, and Span 60 as the surfactant. The MIMs were characterized with electron microscope scanning and rebinding experiments. The Scatchard plot revealed that the template-polymer system has a two-site binding behavior with dissociation constants of 4.05 and 0.515 mmol/L. The MIMs exhibited the highest selective rebinding to DBP at 736.85 µg/g. The recoveries of the MIM-SPE column for DBP extraction was 94.75-101.9% with the RSD of 1.5-7.3%, indicating the feasibility of the prepared MIMs for DBP extraction. Finally, the method developed was used to analyze the trace levels of phthalate in aqueous environment samples.

Preparation and evaluation of molecularly imprinted solid-phase micro-extraction fibers for selective extraction of phthalates in an aqueous sample.

A novel molecularly imprinted polymer (MIP) that was applied to a solid-phase micro-extraction (SPME) device, which could be coupled directly to gas chromatograph and mass spectrometer (GC/MS), was prepared using dibutyl phthalate (DBP) as the template molecule. The characteristics and application of this fiber were investigated. Electron microscope images indicated that the MIP-coated solid-phase micro-extraction (MI-SPME) fibers were homogeneous and porous. The extraction yield of DBP with the MI-SPME fibers was higher than that of the non-imprinted polymer (NIP)-coated SPME (NI-SPME) fibers. The MI-SPME fibers had a higher selectivity to other phthalates that had similar structures as DBP. A method was developed for the determination of phthalates using MI-SPME fibers coupled with GC/MS. The extraction conditions were optimized. Detection limits for the phthalate samples were within the range of 2.17-20.84 ng L(-1). The method was applied to five kinds of phthalates dissolved in spiked aqueous samples and resulted in recoveries of up to 94.54-105.34%, respectively. Thus, the MI-SPME fibers are suitable for the extraction of trace phthalates in complicated samples.