Nondestructive Detection of Nitrogen in Chinese Cabbage Leaves Using VIS–NIR Spectroscopy

Proper nutrient management is essential to increase yield, quality and profit. This study was conducted to estimate the N concentrations of chinese cabbage ( Brassica campestris L. ssp. pekinensis `Norangbom') plug seedlings using visible and near infrared spectroscopy for nondestructive N detection. Chinese cabbage seeds were sown and raised in three 200-cell plug trays filled with growing mixture in a plant growth chamber with three different levels (40%, 80%, and 100%) of required N. Reflectance for leaves of chinese cabbage seedlings was measured with a spectrophotometer 15 days after the experiment started. Reflectance was measured in the 400 to 2500 nm wavelength range at 1.1-nm increments. The leaves were dried afterwards to measure their water content and were analyzed for their actual N contents. The experiment was repeated twice (group I and II). Correlation coefficient spectrum, standard deviation spectrum, stepwise multiple linear regression (SMLR), and partial least squares (PLS) regression were used to determine wavelengths for N prediction models. Performances of SMLR and PLS were similar. For the validation data set (group II), SMLR produced an r 2 of 0.846 and PLS yielded r 2 of 0.840. The most significant wavelength 710 nm, which was identified by all methods, was correlated to chlorophyll. Water content positively correlated with N concentration ( r = 0.76). Wavelengths of 1467, 1910, and 1938 nm selected by SMLR from both groups also showed that water had a strong effect on N prediction. Wavelengths near 2136 nm indicated that protein had potential use in N prediction. Wavelengths near 550 and 840 nm could also contribute to N prediction.