Application of Biofloc Technology (BFT) in the nursery rearing and farming of giant freshwater prawn, Macrobrachium rosenbergii (deMan)

In India a study conducted by CIFE and CIBA (1997), concluded that shrimp farming does more good than harm and it is not eco-unfriendly (Krishnan and Birthal, 2002). Upsurge in coastal aquaculture activity induced by high profitability is reported to have caused adverse impacts on coastal ecosystems and social environments (Parthasarathy and Nirmala, 2000). The crustacean farming sector has received criticism for excessive use of formulated feed containing high protein, of which around 50% gets accumulated at the pond bottom as unconsumed (Avnimelech, 1999; Hari et al., 2004, 2006). The wasted feeds undergo the process of degradation and results in the release of toxic metabolites to the culture system. Reduction of protein in the feed, manipulation and utilisation of natural food in the culture system are the remedy for the above problems. But before reducing the feed protein, it should be confirmed that the feed with reduced protein is not affecting the growth and health of the cultured animal. In the present study, biofloc technology is identified as one of the innovative technologies for ensuring the ecological and environmental Sustainability and examines the compatibility of BFT for the sustainable aquaculture of giant prawn, M. rosenbergii. This thesis starts with a general introduction (Chapter-1), a brief review of the most relevant literature (Chapter-2), results of various experiments (Chapter-3-6), summary (Chapter-7) and recommendations and future research perspectives in the field of biofloc based aquaculture (Chapter – 8). The major objectives of this thesis are, to improve the ecological and economical sustainability of prawn farming by the applicationof BFT and to improve the nutrient utilisation in aquaculture systems.

Design, Development and Realization of Quadratic Volterra Filters for Selected Applications

The basic concepts of digital signal processing are taught to the students in engineering and science. The focus of the course is on linear, time invariant systems. The question as to what happens when the system is governed by a quadratic or cubic equation remains unanswered in the vast majority of literature on signal processing. Light has been shed on this problem when John V Mathews and Giovanni L Sicuranza published the book Polynomial Signal Processing. This book opened up an unseen vista of polynomial systems for signal and image processing. The book presented the theory and implementations of both adaptive and non-adaptive FIR and IIR quadratic systems which offer improved performance than conventional linear systems. The theory of quadratic systems presents a pristine and virgin area of research that offers computationally intensive work. Once the area of research is selected, the next issue is the choice of the software tool to carry out the work. Conventional languages like C and C++ are easily eliminated as they are not interpreted and lack good quality plotting libraries. MATLAB is proved to be very slow and so do SCILAB and Octave. The search for a language for scientific computing that was as fast as C, but with a good quality plotting library, ended up in Python, a distant relative of LISP. It proved to be ideal for scientific computing. An account of the use of Python, its scientific computing package scipy and the plotting library pylab is given in the appendix Initially, work is focused on designing predictors that exploit the polynomial nonlinearities inherent in speech generation mechanisms. Soon, the work got diverted into medical image processing which offered more potential to exploit by the use of quadratic methods. The major focus in this area is on quadratic edge detection methods for retinal images and fingerprints as well as de-noising raw MRI signals