Comparative anti-inflammatory effect of extract from novel Korean strawberry cultivars (Fragaria × ananassa) on lipopolysaccharide-induced RAW264.7 macrophages and mouse model.

BACKGROUND: Dietary interventions are crucial in modulating inflammation in humans. Strawberries are enjoyed by people of different ages as a result of their attractive phenotype and taste. In addition, the active compounds in strawberries may contribute to the reduction of inflammation. When developing new strawberry cultivars to address agricultural and environmental threats, the bioactivity of strawberries must be improved to maintain their health benefits. RESULTS: We determined the phytochemical contents of extracts from a new Korean strawberry cultivar, with the CN7 cultivar extract possessing the highest total polyphenol and flavonoid contents compared to the CN5 and Seolhyang cultivar extracts. The new Korean strawberry cultivars reduced the expression of inflammatory-related genes in lipopolysaccharide (LPS)-induced RAW264.7 cells via the nuclear factor-kappa B signaling pathway, indicating an anti-inflammatory effect. The CN7 cultivar showed greater bioactivity potential and the highest ellagic acid content; hence, we assessed the effect of the CN7 cultivar in an LPS-stimulated mouse model. The CN7 cultivar treatment demonstrated its effectiveness in reducing inflammation via the downregulation of inflammatory cytokines secretion and gene expression. CONCLUSION: The results obtained in the present study have revealed the observable differences of the newly developed strawberry cultivars with Seolhyang in mitigating inflammation induced by LPS. The enhanced phytochemical content of the CN7 cultivar extract may contribute to its improved anti-inflammatory effect. Therefore, it is crucial to maintain the nutritive benefits of strawberry during the development of new cultivation. © 2023 Society of Chemical Industry.

An automatic identification system for citrus greening disease (Huanglongbing) using a YOLO convolutional neural network.

Huanglongbing (HLB), or citrus greening disease, has complex and variable symptoms, making its diagnosis almost entirely reliant on subjective experience, which results in a low diagnosis efficiency. To overcome this problem, we constructed and validated a deep learning (DL)-based method for detecting citrus HLB using YOLOv5l from digital images. Three models (Yolov5l-HLB1, Yolov5l-HLB2, and Yolov5l-HLB3) were developed using images of healthy and symptomatic citrus leaves acquired under a range of imaging conditions. The micro F1-scores of the Yolov5l-HLB2 model (85.19%) recognising five HLB symptoms (blotchy mottling, "red-nose" fruits, zinc-deficiency, vein yellowing, and uniform yellowing) in the images were higher than those of the other two models. The generalisation performance of Yolov5l-HLB2 was tested using test set images acquired under two photographic conditions (conditions B and C) that were different from that of the model training set condition (condition A). The results suggested that this model performed well at recognising the five HLB symptom images acquired under both conditions B and C, and yielded a micro F1-score of 84.64% and 85.84%, respectively. In addition, the detection performance of the Yolov5l-HLB2 model was better for experienced users than for inexperienced users. The PCR-positive rate of Candidatus Liberibacter asiaticus (CLas) detection (the causative pathogen for HLB) in the samples with five HLB symptoms as classified using the Yolov5l-HLB2 model was also compared with manual classification by experts. This indicated that the model can be employed as a preliminary screening tool before the collection of field samples for subsequent PCR testing. We also developed the 'HLBdetector' app using the Yolov5l-HLB2 model, which allows farmers to complete HLB detection in seconds with only a mobile phone terminal and without expert guidance. Overall, we successfully constructed a reliable automatic HLB identification model and developed the user-friendly 'HLBdetector' app, facilitating the prevention and timely control of HLB transmission in citrus orchards.

[Development of indel markers for molecular authentication of Panax ginseng and P. quinquefolius].

Panax ginseng and P. quinquefolius are two kinds of important medicinal herbs. They are morphologically similar but have different pharmacological effects. Therefore, botanical origin authentication of these two ginsengs is of great importance for ensuring pharmaceutical efficacy and food safety. Based on the fact that intron position in orthologous genes is highly conserved across plant species, intron length polymorphisms were exploited from unigenes of ginseng. Specific primers were respectively designed for these two species based on their insertion/deletion sequences of cytochrome P450 and glyceraldehyde 3-phosphate dehydrogenase, and multiplex PCR was conducted for molecular authentication of P.ginseng and P. quinquefolius. The results showed that the developed multiplex PCR assay was effective for molecular authentication of P.ginseng and P. quinquefolius without strict PCR condition and the optimization of reaction system.This study provides a preferred ideal marker system for molecular authentication of ginseng,and the presented method can be employed in origin authentication of other herbal preparations.