Correlation and Regression Analysis of Growth and Yield Parameters in Jasmine (Jasminum sambac L.) during the Off-season

The present investigation was attempted to highlight the correlation and regression Analysis of Growth and Yield Parameters in Jasmine (Jasminum sambac L.) During the Off-Season. Jasmine (Jasminum sambac L.) stands first among the fragrant loose flowers. India is one of the centre of origin of jasmine. In the present investigation, staggered pruning has been carried out to enhance the flower yield during off-season period (December to March). Data on various growth and yield component variables (X1–X­12) were subjected to correlation coefficient with flower yield (Y) and concrete content (Y). The results showed that the number of flowers per plant had the highest and positive association with flower yield (r=0.828**). The positive and significant “b” coefficient was also observed with (b=0.367**) growth and yield attributes. Hence, the regression equation to predict the flower yield would be Y= a + 0.367**. The leaf area was found to be highly correlated with concrete content (r=0.856**); whereas the regression coefficient is 0.895**. with one per cent significant. Therefore, the regression equation would be Y= a + 0.895x. Hence, it could be concluded from the present investigation that leaf area and number of flowers per plant are the important parameters to increase the flower yield and concrete content respectively. sambac L.) during the Off-season R. Kumaravel S. Ganesh

The present investigation was attempted to highlight the correlation and regression Analysis of Growth and Yield Parameters in Jasmine (Jasminum sambac L.) During the Off-Season. Jasmine (Jasminum sambac L.) stands first among the fragrant loose flowers. India is one of the centre of origin of jasmine. In the present investigation, staggered pruning has been carried out to enhance the flower yield during off-season period (December to March). Data on various growth and yield component variables (X1–X­12) were subjected to correlation coefficient with flower yield (Y) and concrete content (Y). The results showed that the number of flowers per plant had the highest and positive association with flower yield (r=0.828**). The positive and significant “b” coefficient was also observed with (b=0.367**) growth and yield attributes. Hence, the regression equation to predict the flower yield would be Y= a + 0.367**. The leaf area was found to be highly correlated with concrete content (r=0.856**); whereas the regression coefficient is 0.895**. with one per cent significant. Therefore, the regression equation would be Y= a + 0.895x. Hence, it could be concluded from the present investigation that leaf area and number of flowers per plant are the important parameters to increase the flower yield and concrete content respectively.
02 18 2025 473 478 10.9734/jabb/2025/v28i22007 https://journaljabb.com/index.php/JABB/article/view/2007 https://journaljabb.com/index.php/JABB/article/download/2007/4831 https://journaljabb.com/index.php/JABB/article/download/2007/4831 https://journaljabb.com/index.php/JABB/article/download/2007/4832 https://journaljabb.com/index.php/JABB/article/download/2007/4833