Does Long-Term Industrial Pollution Affect the Fine and Coarse Root Mass in Forests? Preliminary Investigation of Two Copper Smelter Contaminated Areas

Smorkalov, I. A.; Воробейчик, Е. Л.

doi:10.1007/s11270-022-05512-0

Cited by 9 publications

(2 citation statements)

References 82 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The calculated results show that the hybrid algorithm can significantly improve the computational efficiency and the ability to search the global optimal solution [17]. Smorkalov and Vorobeichik proposed to use GA in the optimization design of steel structures, discussed in detail the principle and implementation steps of GA, and put forward useful improvement suggestions for the advantages and disadvantages of GA, providing guidance for the application of GA in practical engineering [18]. Lotta et al developed a clothing style-aided design system by using genetic programming technology, which encodes a series of relevant dimensions of styles into chromosomes, and the system evolves styles according to the user's choice.…”

Section: Related Workmentioning

confidence: 99%

Application of GA in Furniture Modeling Style Design

Liu

2022

Journal of Function Spaces

View full text Add to dashboard Cite

With the rapid development of the national economy, the construction industry is unprecedentedly active and has made great achievements. However, most traditional structural design is based on the personal experience of designers. In order to improve the production efficiency of furniture, it is necessary to optimize it. Since the evaluation criteria mainly depend on people’s subjective thoughts, it is difficult to describe the individual’s adaptive function. In this paper, an interactive innovation evolution system based on evolutionary algorithm is proposed. Taking full advantage of the evolution function of genetic algorithm and the modeling advantages of ACIS platform, a prototype innovation evolution system is developed based on ACIS/hoops platform with the genetic algorithm based on tree structure as the innovation support, which can help designers complete the innovation modeling design. The results show that the total processing time of the sorting scheme obtained by this algorithm is reduced by 2475.2 s, the production efficiency is increased by 20.6%, and the job waiting time is reduced by 15079.2 s. The results show that the algorithm is feasible and effective in solving the furniture production scheduling problem. The furniture production scheduling scheme solved by genetic algorithm can provide certain reference value for production personnel to formulate production scheduling scheme and improve production efficiency.

show abstract

Section: Related Workmentioning

confidence: 99%

Application of GA in Furniture Modeling Style Design

Liu

2022

Journal of Function Spaces

View full text Add to dashboard Cite

show abstract

“…Bacillus-based biofertilizers increase plant-available nutrients in rhizospheres, reduce pathogenic microbe development, and activate pest defense mechanisms 26 . Further, the microbial communities in these contaminated soils are disrupted, which affects their important roles in recycling organic matter, controlling plant diseases, boosting plant growth, and getting clear of harmful chemicals in the soil 27,28 . The inoculation of Bacillus spp.…”

mentioning

confidence: 99%

Influence of biofertilizer on heavy metal bioremediation and enzyme activities in the soil to revealing the potential for sustainable soil restoration

Haroun,

Xie,

Awadelkareem

et al. 2023

Sci Rep

View full text Add to dashboard Cite

Overuse of chemical fertilizer and pesticides in agricultural activity is frequently damaging to soil health and can accumulate heavy metals in the soil environment, causing harm to plants, humans, and the ecosystem. This study was done to evaluate the effectiveness of biofertilizers in reducing heavy metal levels in contaminated soil and enhancing the activity of soil enzymes that are crucial to plant growth and development. Two bacteria strains, Pseudomonas aeruginosa. and Bacillus firmus, were chosen to develop biofertilizers based on molasses. The pot experiment was setup using a completely randomized design with four treatments and five levels; Bacillus firmus and Pseudomonas aeruginosa were used separately, and they were combined for the biofertilizer dose (20, 40, 60, 80, and 100 mL). Utilizing contaminated soils taken from a greenhouse farm the effect of biofertilizer on heavy metal bioremediation and soil enzyme activity was examined. Methods of soil agrochemical analysis were used to determine the soil physiochemical properties and the concentrations of heavy metals Cu, Fe, Zn, Cd, Mo, Mn, were determined by inductively coupled plasma–mass spectrometry ICP-MS, following DTPA extraction methods. In results, soil pH decreased from 8.28 to 7.39, Ec increased from 0.91 to 1.12, organic matter increased from 18.88 to 20.63 g/kg, N increased gradually from 16.7 to 24.4 mg/kg, and K increased from 145.25 to 201.4 mg/kg. The effect of biofertilizer treatment on soil physiochemical characteristics was significantly positive. Application of biofertilizer significantly increased the heavy metal bioavailability and the activities of soil enzymes. Soil pH were positively correlated with soil Zn (0.99819*), APK (0.95869*) activity and negatively correlated with Fe (0.96759*) also statistically significant at (p < 0.05). The soil Cu positively correlated with Fe (0.99645*), Cd (0.97866*), β.D.GLU (0.99769*) and negatively correlated with PAK (− 0.9624*). Soil ARY had positive correlation with soil Mn (0.99683*), Cd (0.95695*), and negative correlation with PAK (− 0.99424*) at (p < 0.05). Soil enzyme activities were negatively correlated to heavy metals at a significant level. Collectively, the study highlights the potential of biofertilizers as a sustainable and effective approach to enhance soil health and remediate heavy metal-contaminated soils in greenhouses.

show abstract