000 | 02016nam a2200181Ia 4500 | ||
---|---|---|---|
999 |
_c25595 _d25595 |
||
003 | OSt | ||
005 | 20220817142441.0 | ||
008 | 151218b xxu||||| |||| 00| 0 eng d | ||
082 |
_a640 _bSEE/CO |
||
100 | _aSeena C | ||
245 | _aComparisin of Alternative Methods for the Control of Experimental Error in Perrenial Crops | ||
260 |
_aVellanikkara _bDepartment of Agricultural Statistics, College of Horticulture _c1994 |
||
502 | _bMSc | ||
520 | 3 | _aThe feasibility of using certain novel devices for the control of error in experiments on perennial crops was examined on the basis of actual experimental data and the resulting efficiency gain evaluated. A considerable amount of reduction in error variance was achieved by the application of analysis of covariance with suitable functions of pre-experimental yield as concomitant variable. Application of quadratic covariance resulted a substantial gain of precision in the analysis of data on coconut. Nearest neighbourhood analysis (NNA) resulted in a significant improvement of precision in the analysis of data in most of the experiments. Double covariance analysis involving suitable functions of pre-experimental yield and NN variable as covariates resulted in further reduction of experimental error. Pearce’s iterative NN procedure was found to be the best alternative method for reduction of error over the coventional method of stratification. A plot of eight trees was found to be optimum for conducting yield trails on coconut and cashew. The percentage of genetic variability to the total phenotypic variability in the yields of cashew, coconut and cocoa was estimated to be 77.7, 83.4 and 45.4 respectively. The result called for the use of calibration of the plots and choice of appropriate concomitant variables for the reduction of experimental error in designing experiments on perennial crops. | |
700 | _aPrabhakaran P V (Guide) | ||
856 | _uhttp://krishikosh.egranth.ac.in/handle/1/5810096500 | ||
942 |
_2ddc _cTH |