Research on Classification of Grassland Degeneration Indicator Objects Based on UAV Hyperspectral Remote Sensing and 3D_RNet-O Model.

Real-time and high-precision land cover classification is the foundation for efficient and quantitative research on grassland degradation using remote sensing techniques. In view of the shortcomings of manual surveying and satellite remote sensing, this study focuses on the identification and classification of grass species indicating grassland degradation. We constructed a UAV-based hyperspectral remote sensing system and collected field data in grassland areas. By applying artificial intelligence technology, we developed a 3D_RNet-O model based on convolutional neural networks, effectively addressing technical challenges in hyperspectral remote sensing identification and classification of grassland degradation indicators, such as low reflectance of vegetation, flat spectral curves, and sparse distribution. The results showed that the model achieved a classification accuracy of 99.05% by optimizing hyperparameter combinations based on improving residual block structures. The establishment of the UAV-based hyperspectral remote sensing system and the proposed 3D_RNet-O classification model provide possibilities for further research on low-altitude hyperspectral remote sensing in grassland ecology.

Quantification of hetero-cyclic amines from different categories of braised beef by optimized UPLC-TQ-XS/ESI method.

This research work has developed and optimized a sensitive analytical method for separation and quantification of heterocyclic amines (HCAs) mainly including PhIP, Harman, Norharman, IQ, MeIQ, AαC, MeAαC and Trp-P-2 by optimizing UPLC-TQ-XS using electrospray ionization source (ESI+) on ACQUITY UPLC® BEH C18 column in <7 min, from braised beef sample matrix. Meanwhile, modified HCAs extraction by modifying QuEChERS (quick, easy, cheap, efficient, rugged and safe) technique and revisited with solid phase extraction (SPE) for HCAs purification, instead using traditional QuEChERS salts. Moreover, optimized pH conditions of HCA extracts before purification, for better extraction recoveries. Furthermore, this method was validated in terms of method validation parameters. Lastly, simulation of real braised beef model provided the minimum formation of HCAs by optimizing cooking parameters and precursors in a cooking system. Therefore, this method could be applied simultaneously on braised beef matrix either marketed or home cooked for HCAs analysis.

Identification and Classification of Small Sample Desert Grassland Vegetation Communities Based on Dynamic Graph Convolution and UAV Hyperspectral Imagery.

Desert steppes are the last barrier to protecting the steppe ecosystem. However, existing grassland monitoring methods still mainly use traditional monitoring methods, which have certain limitations in the monitoring process. Additionally, the existing deep learning classification models of desert and grassland still use traditional convolutional neural networks for classification, which cannot adapt to the classification task of irregular ground objects, which limits the classification performance of the model. To address the above problems, this paper uses a UAV hyperspectral remote sensing platform for data acquisition and proposes a spatial neighborhood dynamic graph convolution network (SN_DGCN) for degraded grassland vegetation community classification. The results show that the proposed classification model had the highest classification accuracy compared to the seven classification models of MLP, 1DCNN, 2DCNN, 3DCNN, Resnet18, Densenet121, and SN_GCN; its OA, AA, and kappa were 97.13%, 96.50%, and 96.05% in the case of only 10 samples per class of features, respectively; The classification performance was stable under different numbers of training samples, had better generalization ability in the classification task of small samples, and was more effective for the classification task of irregular features. Meanwhile, the latest desert grassland classification models were also compared, which fully demonstrated the superior classification performance of the proposed model in this paper. The proposed model provides a new method for the classification of vegetation communities in desert grasslands, which is helpful for the management and restoration of desert steppes.

Effects of emulsifiers on heterocyclic amine formation and water distribution in roasted chicken patties.

The present study aimed to investigate the effects of five emulsifiers, including DATEM, DMG, PL, SDS, and SPP, on HA formation in chemical models and roasted chicken patties. UPLC-MS analysis showed that DMG and SPP were the most promising among them. In particular, at 0.15-0.9% (w/w) in roasted chicken patties, they effectively reduced the contents of PhIP (21-43%), MeIQx (26-50%) and 4,8-DiMeIQx (16-43%) relative to the control, whereas DATEM, PL and SDS promoted their formation. Low-Field Nuclear Magnetic Resonance and Magnetic Resonance Imaging analysis revealed that the inhibitory effect of SPP and DMG was partly mediated through their capability to help retain water in the macromolecular structures of the muscle tissue. This favorable effect was also supported by the significantly improved adhesiveness of the SPP and DMG samples relative to other samples. These findings suggest that SPP and DMG are effective additives for attenuation of HA contents in meat-based products.

Using green alga Haematococcus pluvialis for astaxanthin and lipid co-production: Advances and outlook.

Astaxanthin is one of the secondary carotenoids involved in mediating abiotic stress of microalgae. As an important antioxidant and nutraceutical compound, astaxanthin is widely applied in dietary supplements and cosmetic ingredients. However, most astaxanthin in the market is chemically synthesized, which are structurally heterogeneous and inefficient for biological uptake. Astaxanthin refinery from Haematococcus pluvialis is now a growing industrial sector. H. pluvialis can accumulate astaxanthin to ∼5% of dry weight. As productivity is a key metric to evaluate the production feasibility, understanding the biological mechanisms of astaxanthin accumulation is beneficial for further production optimization. In this review, the biosynthesis mechanism of astaxanthin and production strategies are summarized. The current research on enhancing astaxanthin accumulation and the potential joint-production of astaxanthin with lipids was also discussed. It is conceivable that with further improvement on the productivity of astaxanthin and by-products, the algal-derived astaxanthin would be more accessible to low-profit applications.

Chinese chive and Mongolian leek suppress heterocyclic amine formation and enhance nutritional profile of roasted cod.

Heterocyclic amines (HAs) are potent mutagens, which can form DNA adducts in various human tissues. There is increasing evidence that mutagenic HA formation and nutrition loss can occur concurrently in fish during vigorous heat treatment. Our study investigated the effects of five Allium spp. (garlic, onion, welsh onion, Chinese chive, and Mongolian leek) on reducing HA formation and improving nutritional quality of roasted cod (Gadus morhua). The results showed that cod patties pretreated with powders of the selected Allium spp. had significantly (P < 0.05) lower levels of HAs (82-92%, except garlic, 49%) than the control. The contents of 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) in the patties exhibited strong negative correlations with total antioxidant activity (-0.937), phenolic (-0.948), and lipophilic flavonoid (-0.933) contents, whereas the 2-amino-3,8 dimethylimidazo [4,5-f] quinoxaline (MeIQx) (made up only ∼0.7-3% of total HAs) contents exhibited significant positive correlations with these antioxidant parameters. In terms of nutrient composition change, Chinese chive and Mongolian leek were the most effective in preventing oxidative degradation of proteins and unsaturated fatty acids in roasted cod patties, which was translated into significantly higher contents of soluble proteins, essential amino acids, and polyunsaturated fatty acids. This has been the first report on the strong HA-formation inhibitory effect of Chinese chive and Mongolian leek. The dual beneficial functionality of these two Allium spp. may be utilized to reduce the intake of hazardous by-products while enhancing the nutritional and antioxidant properties of roasted cod and probably other protein-rich heat-processed foods.

Application of high pressure processing to improve digestibility, reduce allergenicity, and avoid protein oxidation in cod (Gadus morhua).

In this study, comprehensive analysis was performed to evaluate the impact of high hydrostatic pressure (HHP) and traditional thermal processing methods (baking and steaming) on cod proteins. Results showed that HHP, but not baking or steaming, was able to increase the content of soluble protein nitrogen (1.42-fold), compared with control. Total peptide contents of HHP-treated samples were also significantly higher than baked and steamed ones. In addition, protein oxidation was greatly increased after baking (1.56-fold) and steaming (1.97-fold), whereas HHP did not exhibit any appreciable effect. Furthermore, the allergenicity of cod was significantly reduced after HHP as reflected by the attenuated IgE and IgG-binding capacities (67-84% relative to control), while baking and steaming resulted in higher allergenicity. This study strongly supports the potential of HHP for reducing allergenicity, avoiding protein oxidation, and improving digestibility of cod and other protein-rich foods susceptible to quality deterioration during thermal processing.