Non-destructive estimation of chlorophyll and nitrogen content in leaf of Rosa damascena (Mill)
2012
Pal, Probir Kumar | Singh, Rakesh Devsharan | Prasad, Ramdeen
Chlorophyll (Chl) and nitrogen (N) status of leaves provide valuable information about the physiological condition of plants. The conventional methods for measuring Chl and N contents in leaves are destructive, costly, time-consuming, and do not allow repetitive measurement of the same sample. The Damask Rose (Rosa damascena Mill) is an important aromatic crop in the western Himalaya region in India. Generally, flower yield and oil yield of the Damask rose are correlated with nitrogen, phosphorus, and potassium (NPK) levels in the leaf at the bud development stage. The dynamics of N within the rose plant have not been reported clearly. Thus, there is a pressing need for non-destructive techniques to estimate Chl and N content in the leaf of the Damask rose. Our objective was to establish an appropriate mathematical relationship between the Chl content index (CCI) value and the total Chl/N contents for non-destructive estimation of total Chl and N in the leaf of the Damask rose. The regression models were developed with destructively measured parameters (total Chl and N) as the dependent variable and a parameter derived from CCM-200 as the independent variable (CCI). We found that polynomial regression models are suitable for non-destructive estimation of total Chl, and the model predicted values were very close to traditionally measured values with a root mean square prediction error (RMSE p) less than 0.20 mg g ⁻¹ of Chl. In the case of N estimation, a power regression model was appropriate with lowest Akaike's information criteria (AIC) and root mean square validated error (RMSE v) value. Significant correlations (P ≤ 0.001) were observed between traditionally measured values and our model predicted values in both cases.
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