Studies on relationships among physio-chemical and biotic variables in integrated semi-intensive fish culture ponds

Two earthen ponds of dimensions 15m x 8m x 2m (length x width x depth) were used to conduct this research. Ponds were prepared according to Javed (1988). Both the ponds were filled initially with unchlorinated tube well water upto the level of 1.5 m and this level was maintained throughout the experimental period so as to have a pond volume of 180 m-3. Both the ponds were stocked with three fish species viz. Catla catla, Labeo rohita and Cirrhina mrigala (68 in each pond) with 35, 50 and 15 percent respectively. On the next day of stocking, fertilization of ponds was started (based on nitrogen content of broiler dropping) at the rate of 0.17 g nitrogen per 100 g of wet fish weight daily for six months. However, treated pond was supplemented with feed of 28 percent crude protein at the rate of 2 g feed per 100 g wet fish weight daily from 28-07-2000 to 23-11- 2000. The cultured fish stock was captured randomly at fortnightly basis by using the nylon drag net from each of the ponds to monitor increase in fish yield. After obtaining the data, fish were released back into their respective ponds. Water samples were collected fortnightly and analyzed for physico- chemical characteristics and the dry weights of the planktonic biomass to see the influence of supplementary feed at a constant rate of fertilization, with broiler droppings, on these variables and on increase in fish yield. The variables under study were water temperature, light penetration, pH, electrical conductivity, dissolved oxygen, total alkalinity, total hardness, calcium, magnesium, planktonic biomass, chlorides and increase in fish yields. The data on all the variables, under study, were subjected to statistical analysis through MSTATC and MICROSTAT packages of computer software. The comparison of mean values for various parameters were computed by using analysis of variance and Duncan's Multiple- Range (DMR) tests. Regression analyses were also performed to find-out relationships among various physico-chemical and biotic factors influencing the fish yield. Under the above experimental conditions the following conclusions were drawn. The differences between treatments for their response towards all the physico- chemical variables were statistically non-significant except light penetration, pH, calcium and chlorides. All the physico- chemical variables fluctuated significantly during various fortnights of the study period except for light penetration, total alkalinity, total hardness, magnesium and planktonic biomass. In control pond, calcium, dissolved oxygen, light penetration, electrical conductivity and chlorides were the variables, which contributed 93.89 percent variations in the planktonic biomass production. The partial regression coefficient, for regression model, was observed positive and highly significant for calcium and electrical conductivity while the same was negative but highly significant for light penetration. The regression co- efficient for chlorides was negatively non-significant while positively, significant for dissolved oxygen. In treated pond, the regression of temperature on planktonic biomass was highly significant while it was observed negatively non-significant, for total hardness. Temperature and total hardness variables were responsible for 91.94 and 94.46 percent variations in planktonic biomass respectively. In control pond, magnesium was single variable, which was responsible for 63.28 percent variations in fish yield. Increase in fish yield was negative but non-significantly correlated with the dry weights of the planktonic biomass in control pond while the same for treated pond was positively non-significant. The correlation between increase in fish yield and temperature was positively non-significant for both control and treated ponds. The regression of increase in fish yield on nitrogen added was negative but non-significant in both control and treated ponds. The regression model computed for control pond reveals 88.60 percent variations in planktonic productivity due to added nitrogen while the Contribution of added nitrogen, in the form of broiler droppings and feed, towards planktonic biomass was 24.20 percent.