Understanding physiology and developing tools for management of bioenergy crops are prerequisite as these crops become a reality in the southern US landscapes in the near future. Nitrogen is an important element in plant growth and detection of plant N status can help farm managers make appropriate N management decisions. Two experiments were conducted under outdoor pot-culture conditions to determine the effects of nitrogen deficiency on leaf hyperspectral reflectance properties in castor, cv. Hale, and switchgrass, cv. Alamo. Plants were seeded in 12-L pots filled with fine sand and three treatments were imposed after initially supplied with Hoagland's nutrient solution: (1) control (100% N) continued receiving the control solution; (2) reduced N to 20% of the control (20% N); and (3) withheld N from the solution (0% N). Photosynthetic pigments, N concentrations, and hyperspectral reflectance of the uppermost, fully expanded leaves were determined at 3 to 4-day interval from 34 to 64 DAS in castor and from 45 to 90 DAS in switchgrass. N deficiency stress increased leaf reflectance at 555 and 715 nm in castor and at 550 and 750 nm in switchgrass. In castor, reflectance ratios enhanced prediction of photosynthetic pigments at 635 and 705 nm wavelengths. Wavebands of 505, 605 nm and 455 and 605 nm predicted leaf N on area and weight-based estimations, respectively. For switchgrass, first derivative of reflectance at 775 nm provided best estimation of leaf N (%). For leaf N expressed on area basis (g/m-2), ratios of first derivatives of reflectance at 765 nm and 615 nm wavelengths improved the prediction. Chlorophyll content was best estimated with first derivatives of reflectance at 765 nm. The analysis indicates the need to find crop-specific waveband combinations to accurately predict leaf N and pigments by remote sensing methods.