Comparative study of the endophytic and rhizospheric bacterial diversity of Angelica sinensis in three main producing areas in Gansu, China

Ling, Lijun; Ma, Wenxia; Li, Zibin; Jiao, Zhenglong; Xu, Xiaoyan; Lu, Lu; Zhang, Xi; Feng, Juanjuan; Zhang, Ji

doi:10.1016/j.sajb.2019.12.029

Cited by 8 publications

(4 citation statements)

References 26 publications

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“…Various factors, including soil type, structure, moisture content, nutrient distribution, oxygen levels, environmental pressure, and adaptation mechanisms, impacted the shape of AS [37,38]. And soil mineral content, pH levels, and microbial activity played a role in determining its color [39]. The combination of these factors contributed to the diversity of AS grades.…”

Section: Determination Of the Optimal Featurementioning

confidence: 99%

Automated Grading of Angelica sinensis Using Computer Vision and Machine Learning Techniques

Zhang,

Xiao,

Wang

et al. 2024

Agriculture

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Angelica sinensis (Oliv.) Diels, a member of the Umbelliferae family, is commonly known as Danggui (Angelica sinensis, AS). AS has the functions of blood tonic, menstrual pain relief, and laxatives. Accurate classification of AS grades is crucial for efficient market management and consumer health. The commonly used method to classify AS grades depends on the evaluator’s observation and experience. However, this method has issues such as unquantifiable parameters and inconsistent identification results among different evaluators, resulting in a relatively chaotic classification of AS in the market. To address these issues, this study introduced a computer vision-based approach to intelligently grade AS. Images of AS at five grades were acquired, denoised, and segmented, followed by extraction of shape, color, and texture features. Thirteen feature parameters were selected based on difference and correlation analysis, including tail area, whole body area, head diameter, G average, B average, R variances, G variances, B variances, R skewness, G skewness, B skewness, S average, and V average, which exhibited significant differences and correlated with grades. These parameters were then used to train and test both the traditional back propagation neural network (BPNN) and the BPNN model improved with a growing optimizer (GOBPNN). Results showed that the GOBPNN model achieved significantly higher average testing precision, recall, F-score, and accuracy (97.1%, 95.9%, 96.5%, and 95.0%, respectively) compared to the BPNN model. The method combining machine vision technology with GOBPNN enabled efficient, objective, rapid, non-destructive, and cost effective AS grading.

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Section: Determination Of the Optimal Featurementioning

confidence: 99%

Automated Grading of Angelica sinensis Using Computer Vision and Machine Learning Techniques

Zhang,

Xiao,

Wang

et al. 2024

Agriculture

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“…The root tissues were immersed in 75% ethanol for 2 minutes followed by 5% (v/v) sodium hypochlorite for 5 min. After each treatment, the samples were washed ve times using sterile water (Ling et al 2020). Finally, sterile water from the last treatment was placed on Luria-Bertani agar (LB) medium and cultured at 28°C for 72 hours.…”

Section: Sample Collection and Processingmentioning

confidence: 99%

The characters of root-derived fungi from Gentiana scabra Bunge and the relations with their habitats

Wang

et al. 2023

Plant Soil

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Gentiana scabra Bunge (GTSB) root-derived fungi including endophytic fungi (EF) and rhizospheric fungi (RF) are key factors which in uence the quality and tness of this important herb. MethodsWe determined the population, diversity, and the dominant type of EF and RF in GTSB obtained from Liaoning, Yunnan and Jilin province, China by using ITS rRNA cloning and sequencing methods.Meanwhile, we investigated the potential in uence of different habitats on fungi communities, and analyzed the correlation between fungi communities, the main active metabolites of Gentian polysaccharide and gentiopicroside in GTSB and soil physicochemical properities. Results5,419 fungal isolates, belonging to 1 domain, 1 kingdom, 8 phyla, 32 classes, 104 orders, 280 families, 630 genera, 1,238 species were obtained. The population and diversity of EF and RF varied in both habitats and months, showing a signi cant difference. Among them, the predominant genera of EF were Lecidella and unclassi ed_p_Ascomycota, while the predominant genera of RF were complicated. Compared to EF, the diversity of rhizosphere fungi is more affected by soil physicochemical properties, including pH, water content, alkali-hydrolyzable nitrogen, available phosphorus, etc. Additionally, we found that the accumulation of gentiopicroside was positively correlated with EF of Epicoccum and RF of Mortierella, Solicoccozyma, Talaromyces and Trichoderma. The accumulation of Gentian polysaccharide was negatively correlated with EF of Lenzites, Mucor, Myrothecium and Saccharomycopsis and rhizosphere fungi, such as Botrytis, Cadophora, Cladophora, Didymela, Fusarium, etc. ConclusionsThis work will guide the development strategies to cultivate high-quality Gentiana scabra Bunge in the future and provide new ideas for the study of other medicinal plants.

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“…Soil attached to the roots was collected using sterile spatulas and passed through a 0.5-mm sieve. In order to analyze endophytes in surface-sterilized roots, root tissue was immersed in 2% (v/v) sodium hypochlorite for three min and was washed five times in sterile water, according to the method of Ling et al [21] with some modifications. DNA extraction of soil and root (non-sterilized and surface-sterilized) was carried out using the DNA extraction kit for soil (MP Bio-medicals™ FastDNA™ SPIN Kit, USA) and plant (Qiagen, DNeasy® Plant Pro Kit, Germany), respectively, following the manufacturer's protocols.…”

Section: Sampling and Dna Extractionmentioning

confidence: 99%

Shifts in the Rhizosphere and Endosphere Colonizing Bacterial Communities Under Drought and Salinity Stress as Affected by a Biofertilizer Consortium

2021

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The present research asks how plant growth-promoting bacterial (PGPB) inoculants and chemical fertilizers change rhizosphere and root endophytic bacterial communities in durum wheat, and its dependence on environmental stress. A greenhouse experiment was carried out under drought (at 40% field capacity), or salinity (150 mM NaCl) conditions to investigate the effects of a chemical fertilizer (containing nitrogen, phosphorus, potassium and zinc) or a biofertilizer (a bacterial consortium of four PGPBs). High-throughput amplicon sequencing of the 16S rRNA of the rhizosphere, non-sterilized, or surfacesterilized roots, showed shifts in bacterial communities in response to stress treatments, which were greater for salinity than for drought and tended to show increased oligotrophs relative abundances compared to non-stress controls. The results also showed that Proteobacteria, Acidobacteria, Bacteroidetes, Gemmatimonadetes, Thaumarchaeota, Firmicutes, and Verrucomicrobia had a higher relative abundance in the rhizosphere, while Actinobacteria were more abundant on roots, while Candidatus_Saccharibacteria and Planctomycetes inside roots. The results indicated that the root endophytic bacterial communities were more affected by (bio-) fertilization treatments than those in the rhizosphere, particularly as affected by PGPB inoculation. This greater susceptibility of endophytes to (bio-) fertilizers was associated with increased abundance of the 16S rRNA and acdS genes in plant roots, especially under stress conditions. These changes in root endophytes, which coincided with an improvement in grain yield and photosynthetic capacity of plants, may be considered as one of the mechanisms by which PGPB affect plants.

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Comparative study of the endophytic and rhizospheric bacterial diversity of Angelica sinensis in three main producing areas in Gansu, China

Cited by 8 publications

References 26 publications

Automated Grading of Angelica sinensis Using Computer Vision and Machine Learning Techniques

Automated Grading of Angelica sinensis Using Computer Vision and Machine Learning Techniques

The characters of root-derived fungi from Gentiana scabra Bunge and the relations with their habitats

Shifts in the Rhizosphere and Endosphere Colonizing Bacterial Communities Under Drought and Salinity Stress as Affected by a Biofertilizer Consortium

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