Reflectance Spectra Of Plants Research Articles

Estimating leaf nitrogen concentration in heterogeneous crop plants from hyperspectral reflectance

The estimation of leaf nitrogen concentration (LNC) in crop plants is an effective way to optimize nitrogen fertilizer management and to improve crop yield. The objectives of this study were to (1) analyse the spectral features, (2) explore the spectral indices, and (3) investigate a suitable modelling strategy for estimating the LNC of five species of crop plants (rice (Oryza sativa L.), corn (Zea mays L.), tea (Camellia sinensis), gingili (Sesamum indicum), and soybean (Glycine max)) with laboratory-based visible and near-infrared reflectance spectra (300–2500 nm). A total of 61 leaf samples were collected from five species of crop plant, and their LNC and reflectance spectra were measured in laboratories. The reflectance spectra of plants were reduced to 400–2400 and smoothed using the Savitzky–Golay (SG) smoothing method. The normalized band depth (NBD) values of all bands were calculated from SG-smoothed reflectance spectra, and a successive projections algorithm-based multiple linear regression (SPA-MLR) method was then employed to select the spectral features for five species. The SG-smoothed reflectance spectra were resampled using a spacing interval of 10 nm, and normalized difference spectral index (NDSI) and three-band spectral index (TBSI) were calculated for all wavelength combinations between 400 and 2400 nm. The NDSI and TBSI values were employed to calibrate univariate regression models for each crop species. The leave-one-out cross-validation procedure was used to validate the calibrated regression models. Study results showed that the spectral features for LNC estimation varied among different crop species. TBSI performed better than NDSI in estimating LNC in crop plants. The study results indicated that there was no common optimal TBSI and NDSI for different crop species. Therefore, we suggest that, when monitoring LNC in heterogeneous crop plants with hyperspectral reflectance, it might be appropriate to first classify the data set considering different crop species and then calibrate the model for each species. The method proposed in this study requires further testing with the canopy reflectance and hyperspectral images of heterogeneous crop plants.

Effects of heavy metals on the absorbance and reflectance spectra of plants

Abstract. Published work on the reflectance of vegetation growing over soil mineralizations is reviewed. Experimental work was carried out on several species grown in a glasshouse and was extended to a pilot field study. In the laboratory studies, the most general effects of Cd, Cu, Pb or Zn were growth inhibition. A detailed study of the leaf pigments of pea plants showed that the chl a/chl b ratio (chl=chlorophyll) decreased under conditions of Cd or Cu stress but showed little effect with Pb or Zn. However, the absorption spectra of chloroplast pigments were not found to show any wavelength shifts with metal treatments, indicating that new spectral forms of chlorophyll were not produced as a stress response. A decrease in the total chlorophyll content of leaf tissue (fresh weight basis) was correlated with an increase in visible-wavelength leaf reflectance (R) of pea plants. R at infrared wavelengths of 0.85 μm, 1.65 μm and 2.20 μm decreased in metal-treated plants, compared with controls. Although experiments with other species, and a review of published literature, indicate that reflectance effects are dependent on species, phase of growth cycle and environment, the existence of correlations between R at certain wavelengths and the metal concentrations to which roots are exposed was confirmed using oak trees growing naturally in the area of a copper-arsenic mineralization in south-west England. Metal (Cu or As) concentrations in the soil were strongly negatively correlated (p > 99 per cent) with R at 1.65 μm and 2.20 μm, and positively correlated (p > 95 per cent) with R at 0.660 μm, in close agreement with the experiments on pea plants. The inclusion of the relevant infrared bands on Earth resource survey instruments is likely to enhance their usefulness for detecting heavy metal stress in plants.

Effects of heavy metals on the absorbance and reflectance spectra of plants

The spectral responses of plants to various concentrations of heavy metals in their rooting media are investigated in relation to the application of remote sensing methods to the detection of vegetation under stress. Absorption photometry of chloroplasts, measurements of metal and chlorophyll concentrations and reflectance spectrometry were performed on leaves of pea, sunflower and soybean plants grown under greenhouse conditions with the addition of various concentrations of Cd, Cu, Pb and Zn to their rooting media and on leaves of oak trees growing naturally in an area of a copper-arsenic mineralization. Under laboratory conditions, the most general effect observed was growth inhibition and ultimately death, with pea plants also exhibiting changes of chlorophyll a/ chlorophyll b ratios with Cd and Cu and reflectance increases in the visible and decreases in the infrared. Although results for other species indicate that reflectance effects are dependent on species, correlations between reflectance and metal exposure is confirmed by the field investigations. It is concluded that a remote sensing system would be improved by the inclusion of bands around 1.65 and 2.20 microns to detect soil mineralization from plant spectra.