Young Plant Testing for Important Characters in Tea Breeding (Part 2)

Abstract

In the present paper, it was shown that the prediction of yield was carried out by means of multiple regression analysis between yield and characters of shoot using 21 clones for black tea.In this analysis, dependent variable was yield (Y), and independent variables were number of flush shoots per unit area (X1), weight of 100 plucked shoots (X2), average length of flush shoot at plucking time (X3), leaf number of flush shoot at plucking time (X4), average length of plucked shoot (X5), and width of row (X6).Fifteen multiple regression equations of yield were calculated in 1st, 2nd and 3rd plucking seasons, respectively. These equations included three to six independent variables. Both X1 and X6 were common to all equations, and the other variables were combined in all combinations.Processing of the data was accomplished by a TOSBAC 3400 computer of the Computing Centre for Research in Agriculture, Forestry and Fishery.The multiple regression equations including six characters were given as follows:1st plucking season;Y =-1792.5+2.36X1+3.02X2+19.79X3+17.08X4-20.27X5+1.32X6 R=0.902 2nd plucking season;Y =-1239.6+0.75X1-0.02X2+21.96X3+35.74X4-7.87X5+0.77X6 R=0.946 3rd plucking season;Y=-387.4+1.48X1+3.48X2+22.80X3-39.40X4-24.10X5+0.49X6 R=0.855Squaring these correlation coefficients gives 81%, 89% and 73% as the percentage of the variability in yield accounted for by its association with the six characters.It became clear that these multiple correlation coefficients were so high that the yield of each plucking season could be predicted accurately by these equations.As the number of concerned independent variables in a equation diminished, the values of multiple correlation coefficients gradually diminished, but all multiple regression coefficients exceeded the 1% or 5% level of significance.The multiple correlation coefficients including X1, X3 and X6 were 0.868, 0.921 and 0.780 in each plucking season, respectively. There were only a little differences between the multiple correlation coefficient including three characters and that including six characters in each plucking season. Therefor, the multiple regression equation including X1, X3 and X6 is also considered to be practically useful in predicting the yield.From the values of standard partial regression coefficients, it may be concluded that the important characters to predict the yield in mature tea garden are number of flush shoots per unit area, average length of flush shoot at plucking time, and width of row. It seems to be necessary to find the young plant's characters which are closely related with these three characters for young plant testing on yield.