Determination of sodium alginate in algae by near-infrared spectroscopy

Pang, Xu; Na, Na; Gao, Shouwu; Geng, Cunzhen

doi:10.5004/dwt.2019.24652

Cited by 12 publications

(3 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…erefore, in the present study, multiple features are exploited to establish a remote sensing recognition model for black and odorous water bodies. In previous studies, the Rrs (NIR) was utilized as the analysis feature, but because algal bloom and duckweed can cause regular water bodies to exhibit optical properties comparable to those of black and odorous water bodies, in the present study, it was not considered in the selection of features to prevent the introduction of additional errors [19][20][21][22].…”

Section: Methodsmentioning

confidence: 99%

Classification and Regression Tree Models for Remote Recognition of Black and Odorous Water Bodies Based on Sensor Networks

Zhao

Dong

et al. 2022

Scientific Programming

View full text Add to dashboard Cite

Black and odorous water bodies represent a topic of significant interest in the field of water pollution prevention and control. Remote sensing technology is increasingly exploited for the monitoring of black and odorous water bodies because of its high efficiency and large-scale monitoring potential. In the present study, the Sentinel-2A imagery data were combined with data obtained by measuring spectral properties of black and odorous water bodies to produce a classification and regression tree (CART) model-based improved remote sensing recognition method for such water bodies. This method transforms the traditional single-feature empirical threshold segmentation algorithm to a multi-feature fuzzy decision-tree classification algorithm. The results reveal overall accuracy values of 84.78%, 92.85%, and 72.23% for the CART decision-tree algorithm, the confidence zone classification, and the fuzzy zone node classification, respectively. The method proposed in the present study enables the highly precise extraction of features representing black and odorous water bodies from satellite imagery. The characterization of confidence and fuzzy zones minimizes the need for field inspections, and it enhances the efficiency of diverse applications including engineering.

show abstract

Section: Methodsmentioning

confidence: 99%

Classification and Regression Tree Models for Remote Recognition of Black and Odorous Water Bodies Based on Sensor Networks

Zhao

Dong

et al. 2022

Scientific Programming

View full text Add to dashboard Cite

show abstract

“…The strength of cement in the mixed materials should not be less than 42.5 grade, and the storage and use of cement should be distinguished according to the standards of brand, grade and production date, and the phenomenon of cement mixing should not occur. According to the industrial standard "General Portland Cement" GB175 [26,27], P.042.5 ordinary Portland cement is selected for the pavement project, and its related indexes are tested by the GB1345-2005 negative pressure screen method and Reich method. The basic performance indexes of P.042.5 ordinary Portland cement are shown in Table 1.…”

Section: Selection Of Raw Materials For Rubber Permeable Concretementioning

confidence: 99%

The Application of Rubber Aggregate-Combined Permeable Concrete Mixture in Sponge City Construction

Gao

Pang

2023

Coatings

View full text Add to dashboard Cite

Permeable concrete is a new type of pavement material, which can effectively improve the urban flood discharge system, and is of great significance to the construction of sponge city. In order to optimize the use effect of permeable concrete and improve the application value of permeable concrete in permeable road engineering, the combination of rubber aggregate and permeable concrete is proposed, and the mix ratio of rubber permeable concrete mixture material is designed, which is applied to the engineering of pavement in Hunan Province, and its comprehensive pavement performance is analyzed and evaluated. The results show that the rubber permeable concrete has the best performance when the water cement ratio is 0.3, the designed porosity is 15%, the rubber particle size is 16 mesh, the rubber content is 15% and the coarse aggregate ratio is 4:6. The removal rates of suspended solids and metal pollutants are 0.65 and 0.72, respectively, which are increased by 0.23 and 0.19, respectively, compared with ordinary permeable concrete. This shows that rubber permeable concrete improves the ecological benefits of permeable concrete pavement, gives full play to the economic benefits of waste rubber products, reduces the construction cost of permeable concrete pavement, and provides assistance for promoting the construction of sponge city.

show abstract

“…Due to its unique structure and healthful effects [ 6 ], it has been widely used in pharmaceutical, food and textile applications [ 2 , 7 , 8 ]. The alginate content of various algae purchased on the market varies widely, so in the alginate industry, an accurate knowledge of the composition and structure of alginate is required [ 9 ], and purity is examined as an important quality indicator [ 10 ], and the analysis of the M and G content of alginate allows the examination of the quality of the product [ 11 ]. However, there are no uniform standards and specifications for its content analysis methods [ 12 ], and fewer reports on the optimization of alginate hydrolysis conditions and quality studies have been reported, which directly affects the assessment of its quality and limits its potential applications to a certain extent [ 13 ].…”

Section: Introductionmentioning

confidence: 99%

Optimization of hydrolysis conditions of alginate based on high performance liquid chromatography

Wang,

Fu,

et al. 2024

Heliyon

View full text Add to dashboard Cite

Determination of sodium alginate in algae by near-infrared spectroscopy

Cited by 12 publications

References 14 publications

Classification and Regression Tree Models for Remote Recognition of Black and Odorous Water Bodies Based on Sensor Networks

Classification and Regression Tree Models for Remote Recognition of Black and Odorous Water Bodies Based on Sensor Networks

The Application of Rubber Aggregate-Combined Permeable Concrete Mixture in Sponge City Construction

Optimization of hydrolysis conditions of alginate based on high performance liquid chromatography

Contact Info

Product

Resources

About