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The purpose of this paper is to study bio‐safe technology – impact of rhizospheric bacteria Azotobacter and Bacillus within the composition of environmentally clean complex microbiological biofertilizer “BioWais” prepared on the basis of nitrogen‐, phospho‐ and silicon‐bacterin on physiological parameters of plants: growth, productivity, the role of rhizobacteria in plants resistance to biotic and abiotic factors.

The following contemporary methods of investigation of physiological parameters of biological objects: immunoenzyme analysis of phytohormones, method of combinatory light dissemination, determination of amino acid composition of grain proteins by ion‐exchange chromatography, spectrophotometric methods were used.

The positive impact of biofertilizer “BioWais” on plant growth and development, enhancement of resistance of bacterized plants to hypothermia and pathogenic infection, increase of carotid content were demonstrated.

The bacteria under study biopreparation were shown to act as plant growth‐promoting rhizobacteria foster increase of plant anti‐oxidant protection, adaptation of seedlings to hypothermia, synthesize cytokinins and indolyl acetic acid.

Bacterial preparation increases quality and amount of agricultures yield, it may be recommended to treat seeds prior to planting with the view to stimulate germination, to enhance plants resistance to hypothermia and fungus‐induced diseases, for improvement of plant growth and development.

New, innovative, environmentally pure bacterial preparation BioWais showed significant efficiency for a number of agrocultures and may be used for acquisition of safe plant products of high quality (with high content of protein, essential amino acids and carotin, potential source of vitamin A, low content of nitrates).

In India, agriculture is considered as the major source of income for a major sector of people. Our country's GDP (Gross Domestic Product) can increase only if we focus on agriculture and its growth toward global economy. There have been several attempts to improve the agricultural sector since decades.

This work describes about the design of a device which continuously monitors the plant growth and sends the data to a centralized database, where data is dynamically analyzed based on base references using various machine learning algorithms like regression, gradient descent, clustering etc.

This paper aims at analyzing the plant growth in of our country and focuses on the improvement of plant growth based on factors such as temperature, air moisture, radiant energy, carbon dioxide levels, soil pH& temperature through the design of a device.

It is anticipated to provide a solution by analyzing the plant growth percentage in different regions over a period of time. Based on the inferences, we will be able to suggest an optimum environment for the plant species to grow best. Various sensors like temperature and humidity sensors, light sensors and pH electrodes can be used in collecting data from the plant environment.

The study aimed at developing the bioremediation model of Lapindo mud through multisymbiotic organism.

The research was conducted using completely randomized design. The model plants chosen in this research were soybean. The interaction pattern during the treatment was used to develop the bioremediation model based on the parameters.

The results showed that there was an effect of the type of organism on the parameters, namely: the growth of plant (biomass, height, length of root, and number of leaves), the biomass of root nodules, the percentage of mycorrhizal infection, the content of water, nitrogen, phosphorus, and total petroleum hydrocarbons (TPHs). There was a pattern of multisymbiotic interaction between each organism and roles of each symbiont in that interaction. Therefore, the plants were capable of surviving in the environment of Sidoarjo Lapindo mud. This pattern can be named as the bioremediation model proposed, which is the analogy of tripartite symbiosis between plants, mycorrhizae, and Rhizobium but also adding plant growth bacteria such as phosphate-solubilizing bacteria and hydrocarbon degradation bacteria. The implementation of this model can be used to treat oil-contaminated soil in order to be used as a plant growth medium.

Phytoremediation is a new and promising approach to remove contaminants in the environment but using plants alone for remediation confronts many limitations. Therefore, the application of plant-growth-promoting rhizobia (PGPR) has been extended to remediate contaminated soils in association with plants (Zhuang et al., 2007). The development of the model will use the analogy of tripartite symbiosis between plants, mycorrhizae, and Rhizobium. The developed model will be based on the interaction pattern on each parameters obtained. Bioremediation is chosen because it is considered an effective technique to transform toxic components into less toxic products without disrupting the surrounding environment. Besides, bioremediation is cheaper and environment-friendly because it utilizes microorganisms to clean pollutants from the environment (Nugroho, 2006).

The purpose of this study is to examine the effects of nitrogen (N) deposition on clonal growth in a rhizome clonal plant, Leymus chinensis (Trin.) Tzvel.

The study established seven N concentration gradients (0, 2, 4, 8, 16, 32 and 64 g N m⁻²) to simulate the continuous increase in N deposition for the cultivation of L. chinensis seedlings and assess the response mechanism of the cloned L. chinensis plant at different N levels by analyzing the aboveground and belowground plant appearance traits, parent ramets and daughter ramets of resource allocation and biomass allocation.

The results of this study showed that the different N treatment levels could promote clonal growth and had certain regularity under the seven treatments. The addition of N could significantly increase the ramet number, rhizome length, rhizome spacer length, biomass of mother ramets, daughter ramets and belowground L. chinensis population when the N addition was greater than 4 g m⁻²; however, the clonal growth ability of L. chinensis decreased and the rhizome length, ramet number, stem and leaf biomass of daughter ramets and stem biomass of mother ramets significantly decreased when the N addition was greater than 32 g N m⁻².

With global warming, atmospheric N deposition is increasing and it is of great significance to explore the response mechanism of different N levels for the growth of clone plants. This study provides basic data and a theoretical basis for the survival prediction of cloned plants under the background of a global climate change strategy and has important theoretical and practical significance for the scientific management of grasslands in the future.

Does the long-term growth rate of a firm increase by exporting? If yes, how large is that increase in a developing economy? The paper aims to discuss this issue.

The authors incorporate data from the manufacturing plants in Iran as a developing economy for 2003–2011 to address this question. Using fixed effect panel and propensity score matching method, the authors examine whether exportation can affect a firm’s growth rate to test for the learning to grow hypothesis.

The findings document that: not only the exporters are larger and more productive than non-exporters, but they also grow faster in size and productivity measures as well. Additionally, the authors find that the rise in the growth rate is a short-term phenomenon and it disappears in the second year; meaning that exportation does not have a permanent growth effect. The findings are consistent with a spot effect of learning, compared to a permanent growth engine. Results are robust to different analysis tests.

The authors investigate the learning effect of exporting within recently released firm-level data of a developing country.

The purpose of this article is to provide information about interactions between pink-pigmented facultative methylotroph (PPFM) organisms and plants, their molecular mechanisms of methylotrophic metabolism, application of PPFMs in agriculture, biotechnology and bioremediation and also to explore lacuna in PPFMs research and direction for future research.

Research findings on PPFM organisms as potent plant growth promoting organisms are discussed in the light of reports published by various workers. Unexplored field of PPFM research are detected and their application as a new group of biofertilizer that also help host plants to overcome draught stress in poorly irrigated crop field is suggested.

PPFMs are used as plant growth promoters for improved crop yield, seed germination capacity, resistance against pathogens and tolerance against drought stress. Anti-oxidant and UV resistant properties of PPFM pigments protect the host plants from strong sunshine. PPFMs have excellent draught ameliorating capacity.

To meet the ever increasing world population, more and more barren, less irrigated land has to be utilized for agriculture and horticulture purpose and use of PPFM group of organisms due to their draught ameliorating properties in addition to their plant growth promoting characters will be extremely useful. PPFMs are also promising candidates for the production of various industrially and medicinally important enzymes and other value-added products. Wider application of this ecofriendly group of bacteria will reduce crop production cost thus improving economy of the farmers and will be a greener alternative of hazardous chemical fertilizers and fungicides.

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The purpose of this paper is to propose a new hybrid algorithm, named improved plant growth simulation algorithm and genetic hybrid algorithm (PGSA-GA), for solving structural optimization problems.

PGSA-GA is based on PGSA and three improved strategies, namely, elitist strategy of morphactin concentration calculation, strategy of intelligent variable step size and strategy of initial growth point selection based on GA. After a detailed formulation and explanation of its implementation, PGSA-GA is verified using the examples of typical truss and single-layer lattice shell.

Improved PGSA-GA was implemented and optimization was carried out for two typical optimization problems; then, a comparison was made between the PGSA-GA and other methods. The results show that the method proposed in the paper has the advantages of high efficiency and rapid convergence, which enable it to be used for the optimization of various types of steel structures.

Through the examples of typical truss and single-layer lattice shell, it shows that the optimization efficiency and effect of PGSA-GA are better than those of other algorithms and methods, such as GA, secondary optimization method, etc. The results show that PGSA-GA is quite suitable for structural optimization.

The purpose of this paper is to examine the effect of the application of microorganisms of phosphate providers and organic matters for the growth of Arabica coffee seedlings in Bener Meriah Regency.

The experiments were performed inside the screen house using a random design of factorial group with six repetitions. The experimental treatments consisted of two factors. Factor I is the application of microorganisms of phosphate providers. Factor II is the application of organic matters (T. diversifolia and the coffee bean skins). The parameters observed were as follows: enhancement of plant height was observed every 30 days for 270 days, and a number of primary branch and dry weight of roots were observed 270 days after planting (DAP). The data obtained were analyzed by analyzing the variance at 5 per cent level; if the treatment had an effect, then the treatment was continued to Duncan’s multiple range test at 5 per cent.

The application of microorganisms of phosphate provider increases the height improvement, the number of primary branches and the dry weight of roots of Arabica coffee seedlings. The application of Listeria sp. microorganisms of phosphate provider gives the highest yield on the height increase, the number of primary branches and the dry weight of roots of Arabica coffee seedlings. The application of organic matters of coffee beans skin gives higher yield than Tithonia diversifolia in height and dry weight of roots of Arabica coffee seedlings. The interaction between the application of microorganisms of phosphate provider and organic matters increases the dry weight of roots of Arabica coffee seedlings. The interaction of Listeria sp.-skin of coffee beans gives the highest yield on dry weight of roots of Arabica coffee seedlings.

Several other studies have demonstrated that the application of microorganisms of phosphate providers using phosphate solubilizing bacteria (Fitriatin et al., 2014; Sembiring et al., 2017) and mycorrhizal use (Hart and Trevors, 2005; Rouphael et al., 2015) increased the growth and yield plant. No previous study comprehensively studied the application of microorganisms of phosphate providers and organic matters to improve the growth of Arabica coffee seedlings in Andisol in Bener Meriah Regency.

The purpose of this paper is to deal with utilization of marine trash fish (MTF) in the production of organic liquid fertilizer for effective solid waste management in urban locations.

Chopped MTF was treated with molasses and allowed to bacterial degradation. Spectroscopic tools – FT-IR and GC-MS were employed to characterize the biomolecules were employed to characterize the biomolecules. Nutrient content in final organic liquid fertilizer was estimated by physico-chemical analysis. The liquid fertilizer was treated to soil and applied as a foliar spray on leaves of Tomato plants and growth parameters such as height of plants (cm), number of leaves and diameter of leaves (cm) were monitored.

MTF was converted to organic liquid fertilizer using Bacillus subtilis. GC-MS analysis of the final product detected presence of fatty acids that could enrich organic carbon (OC) upon soil application. The final product possesses various organic nutrients to assist plant growth. Tomato plants treated with 5 and 10 per cent organic fertilizer showed highest height than plants treated with chemical fertilizer.

Urban solid waste management is essentially required in developing countries to reduce its impact on the environment and this approach would be helpful for effective utilization of MTF in organic agriculture.

This paper aims to study the changes in productivity for 25 state‐owned coal‐fired power plants (CFPPs) over a period of seven years (2003‐2010).

The methodology that is utilized in the study follows a non‐parametric approach of data envelopment analysis (DEA) and uses the Malmquist index to estimate the change in productivity of panel samples. In the calculations, the study considers installed capacity, fuel, labour, electricity used, and average operational time as inputs and considers net electricity produced as output.

The results indicate that the average total factor productivity regressed during the investigation period at an annual rate of 2 percent. The decrease in productivity is equally attributed to the technical efficiency change and technological change components, with an average decline in productivity of 1 percent per year. A plant‐wise analysis demonstrates that the Parichha plant recorded an average increase in productivity of 3.9 percent per year that was mainly driven by the technical efficiency change component (4.2 percent).There is little variation in the productivity of small‐size plants when compared with medium and large‐size plants. The productivity of multivaried plants is comparatively lower than BHEL (Bharat Heavy Electricals Limited) make plants.

The impact of size, make and region on change in productivity is examined. This study recommends specific policies that can be implemented to increase the productivity of power plants. The study also provides a contemporary overview of Indian CFPPs that can aid energy planners and plant operators in the monitoring and detection of changes in productivity.