5 resultados para statistical application

em Cochin University of Science


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This work envisages the fermentation of prawn shell waste into a more nutritious product with simpler components for application as a feed ingredient in aquaculture. This product would be a rich source of protein along with chitin, minerals, vitamins and N-acetyl glucosamine. A brief description of the various processing (chemical and bioprocess) methods employed for chitin, chitosan and single sell protein preparations from shell waste. It deals with the isolation of micro flora associated with prawn shell degradation. It describes the methods adopted for fermentation of prawn shell degradation and fermentation of prawn shell waste with the selected highly chitinoclastic strains. The comparison of SSF and SmF for each selected strain in terms of enrichment of protein, lipid and carbohydrate in the fermented product was done. Detailed analysis of product quality is discussed. The feed for mulation and feeding experiment explained in detail. Statistical analysis of various biogrowth parameters was done with Duncan’s multiple range test. Very briefly explains 28 days of feeding experiment. A method for the complete utilization of shell waste explains with the help of experiments.

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Marine fungi remain totally unexplored as a source of industrial enzyme and prospective applications. Further tannase production by a marine organism has so far not been established. The primary objective of this study included the evaluation of the potential of Aspergillus awamori isolated from sea water as part of an earlier study and available in the culture collection of the Microbial technology laboratory for tannase production through different fermentation methods, optimization of bioprocess variables by statistical methods, purification and characterization of the enzyme, genetic study, and assessment of its potential applications.

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The present study aimed at the utlisation of microbial organisms for the production of good quality chitin and chitosan. The three strains used for the study were Lactobacillus plantarum, Lactobacililus brevis and Bacillus subtilis. These strains were selected on the basis of their acid producing ability to reduce the pH of the fermenting substrates to prevent spoilage and thus caused demineralisation of the shell. Besides, the proteolytic enzymes in these strains acted on proteinaceous covering of shrimp and thus caused deprotenisation of shrimp shell waste. Thus the two processes involved in chitin production can be affected to certain extent using bacterial fermentation of shrimp shell.Optimization parameters like fermentation period, quantity of inoculum, type of sugar, concentration of sugar etc. for fermentation with three different strains were studied. For these, parameters like pH, Total titrable acidity (TTA), changes in sugar concentration, changes in microbial count, sensory changes etc. were studied.Fermentation study with Lactobacillus plantarum was continued with 20% w/v jaggery broth for 15 days. The inoculum prepared yislded a cell concentration of approximately 108 CFU/ml. In the present study, lactic acid and dilute hydrochloric acid were used for initial pH adjustment because; without adjusting the initial pH, it took more than 5 hours for the lactic acid bacteria to convert glucose to lactic acid and during this delay spoilage occurred due to putrefying enzymes active at neutral or higher pH. During the fermentation study, pH first decreased in correspondence with increase in TTA values. This showed a clear indication of acid production by the strain. This trend continued till their proteolytic activity showed an increasing trend. When the available sugar source started depleting, proteolytic activity also decreased and pH increased. This was clearly reflected in the sensory evaluation results. Lactic acid treated samples showed greater extent of demineralization and deprotenisation at the end of fermentation study than hydrochloric acid treated samples. It can be due to the effect of strong hydrochloric acid on the initial microbial count, which directly affects the fermentation process. At the end of fermentation, about 76.5% of ash was removed in lactic acid treated samples and 71.8% in hydrochloric acid treated samples; 72.8% of proteins in lactic acid treated samples and 70.6% in hydrochloric acid treated samples.The residual protein and ash in the fermented residue were reduced to permissible limit by treatment with 0.8N HCI and 1M NaOH. Characteristics of chitin like chitin content, ash content, protein content, % of N- acetylation etc. were studied. Quality characteristics like viscosity, degree of deacetylation and molecular weight of chitosan prepared were also compared. The chitosan samples prepared from lactic acid treated showed high viscosity than HCI treated samples. But degree of deacetylation is more in HCI treated samples than lactic acid treated ones. Characteristics of protein liquor obtained like its biogenic composition, amino acid composition, total volatile base nitrogen, alpha amino nitrogen etc. also were studied to find out its suitability as animal feed supplement.Optimization of fermentation parameters for Lactobacillus brevis fermentation study was also conducted and parameters were standardized. Then detailed fermentation study was done in 20%wlv jaggery broth for 17 days. Also the effect of two different acid treatments (mild HCI and lactic acid) used for initial pH adjustment on chitin production were also studied. In this study also trend of changes in pH. changes in sugar concentration ,microbial count changes were similar to Lactobacillus plantarum studies. At the end of fermentation, residual protein in the samples were only 32.48% in HCI treated samples and 31.85% in lactic acid treated samples. The residual ash content was about 33.68% in HCI treated ones and 32.52% in lactic acid treated ones. The fermented residue was converted to chitin with good characteristics by treatment with 1.2MNaOH and 1NHCI.Characteristics of chitin samples prepared were studied and extent of Nacetylation was about 84% in HCI treated chitin and 85%in lactic acid treated ones assessed from FTIR spectrum. Chitosan was prepared from these samples by usual chemical method and its extent of solubility, degree of deacetylation, viscosity and molecular weight etc were studied. The values of viscosity and molecular weight of the samples prepared were comparatively less than the chitosan prepared by Lactobacillus plantarum fermentation. Characteristics of protein liquor obtained were analyzed to determine its quality and is suitability as animal feed supplement.Another strain used for the study was Bacillus subtilis and fermentation was carried out in 20%w/v jaggery broth for 15 days. It was found that Bacillus subtilis was more efficient than other Lactobacillus species for deprotenisation and demineralization. This was mainly due to the difference in the proteolytic nature of the strains. About 84% of protein and 72% of ash were removed at the end of fermentation. Considering the statistical significance (P

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Marine fungus BTMFW032, isolated from seawater and identified as Aspergillus awamori, was observed to produce an extracellular lipase, which could reduce 92% fat and oil content in the effluent laden with oil. In this study, medium for lipase production under submerged fermentation was optimized statistically employing response surface method toward maximal enzyme production. Medium with soyabean meal- 0.77% (w/v); (NH4)2SO4-0.1 M; KH2PO4-0.05 M; rice bran oil-2% (v/v); CaCl2-0.05 M; PEG 6000-0.05% (w/v); NaCl-1% (w/v); inoculum-1% (v/v); pH 3.0; incubation temperature 35 8C and incubation period-five days were identified as optimal conditions for maximal lipase production. The time course experiment under optimized condition, after statistical modeling, indicated that enzyme production commenced after 36 hours of incubation and reached a maximum after 96 hours (495.0 U/ml), whereas maximal specific activity of enzyme was recorded at 108 hours (1164.63 U/mg protein). After optimization an overall 4.6- fold increase in lipase production was achieved. Partial purification by (NH4)2SO4 precipitation and ion exchange chromatography resulted in 33.7% final yield. The lipase was noted to have a molecular mass of 90 kDa and optimal activity at pH 7 and 40 8C. Results indicated the scope for potential application of this marine fungal lipase in bioremediation.

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Study on variable stars is an important topic of modern astrophysics. After the invention of powerful telescopes and high resolving powered CCD’s, the variable star data is accumulating in the order of peta-bytes. The huge amount of data need lot of automated methods as well as human experts. This thesis is devoted to the data analysis on variable star’s astronomical time series data and hence belong to the inter-disciplinary topic, Astrostatistics. For an observer on earth, stars that have a change in apparent brightness over time are called variable stars. The variation in brightness may be regular (periodic), quasi periodic (semi-periodic) or irregular manner (aperiodic) and are caused by various reasons. In some cases, the variation is due to some internal thermo-nuclear processes, which are generally known as intrinsic vari- ables and in some other cases, it is due to some external processes, like eclipse or rotation, which are known as extrinsic variables. Intrinsic variables can be further grouped into pulsating variables, eruptive variables and flare stars. Extrinsic variables are grouped into eclipsing binary stars and chromospheri- cal stars. Pulsating variables can again classified into Cepheid, RR Lyrae, RV Tauri, Delta Scuti, Mira etc. The eruptive or cataclysmic variables are novae, supernovae, etc., which rarely occurs and are not periodic phenomena. Most of the other variations are periodic in nature. Variable stars can be observed through many ways such as photometry, spectrophotometry and spectroscopy. The sequence of photometric observa- xiv tions on variable stars produces time series data, which contains time, magni- tude and error. The plot between variable star’s apparent magnitude and time are known as light curve. If the time series data is folded on a period, the plot between apparent magnitude and phase is known as phased light curve. The unique shape of phased light curve is a characteristic of each type of variable star. One way to identify the type of variable star and to classify them is by visually looking at the phased light curve by an expert. For last several years, automated algorithms are used to classify a group of variable stars, with the help of computers. Research on variable stars can be divided into different stages like observa- tion, data reduction, data analysis, modeling and classification. The modeling on variable stars helps to determine the short-term and long-term behaviour and to construct theoretical models (for eg:- Wilson-Devinney model for eclips- ing binaries) and to derive stellar properties like mass, radius, luminosity, tem- perature, internal and external structure, chemical composition and evolution. The classification requires the determination of the basic parameters like pe- riod, amplitude and phase and also some other derived parameters. Out of these, period is the most important parameter since the wrong periods can lead to sparse light curves and misleading information. Time series analysis is a method of applying mathematical and statistical tests to data, to quantify the variation, understand the nature of time-varying phenomena, to gain physical understanding of the system and to predict future behavior of the system. Astronomical time series usually suffer from unevenly spaced time instants, varying error conditions and possibility of big gaps. This is due to daily varying daylight and the weather conditions for ground based observations and observations from space may suffer from the impact of cosmic ray particles. Many large scale astronomical surveys such as MACHO, OGLE, EROS, xv ROTSE, PLANET, Hipparcos, MISAO, NSVS, ASAS, Pan-STARRS, Ke- pler,ESA, Gaia, LSST, CRTS provide variable star’s time series data, even though their primary intention is not variable star observation. Center for Astrostatistics, Pennsylvania State University is established to help the astro- nomical community with the aid of statistical tools for harvesting and analysing archival data. Most of these surveys releases the data to the public for further analysis. There exist many period search algorithms through astronomical time se- ries analysis, which can be classified into parametric (assume some underlying distribution for data) and non-parametric (do not assume any statistical model like Gaussian etc.,) methods. Many of the parametric methods are based on variations of discrete Fourier transforms like Generalised Lomb-Scargle peri- odogram (GLSP) by Zechmeister(2009), Significant Spectrum (SigSpec) by Reegen(2007) etc. Non-parametric methods include Phase Dispersion Minimi- sation (PDM) by Stellingwerf(1978) and Cubic spline method by Akerlof(1994) etc. Even though most of the methods can be brought under automation, any of the method stated above could not fully recover the true periods. The wrong detection of period can be due to several reasons such as power leakage to other frequencies which is due to finite total interval, finite sampling interval and finite amount of data. Another problem is aliasing, which is due to the influence of regular sampling. Also spurious periods appear due to long gaps and power flow to harmonic frequencies is an inherent problem of Fourier methods. Hence obtaining the exact period of variable star from it’s time series data is still a difficult problem, in case of huge databases, when subjected to automation. As Matthew Templeton, AAVSO, states “Variable star data analysis is not always straightforward; large-scale, automated analysis design is non-trivial”. Derekas et al. 2007, Deb et.al. 2010 states “The processing of xvi huge amount of data in these databases is quite challenging, even when looking at seemingly small issues such as period determination and classification”. It will be beneficial for the variable star astronomical community, if basic parameters, such as period, amplitude and phase are obtained more accurately, when huge time series databases are subjected to automation. In the present thesis work, the theories of four popular period search methods are studied, the strength and weakness of these methods are evaluated by applying it on two survey databases and finally a modified form of cubic spline method is intro- duced to confirm the exact period of variable star. For the classification of new variable stars discovered and entering them in the “General Catalogue of Vari- able Stars” or other databases like “Variable Star Index“, the characteristics of the variability has to be quantified in term of variable star parameters.