We present SOAR/OSIRIS cross-dispersed near-infrared (NIR) integrated spectra of 12 Galactic globular clusters that are employed to test Maraston NIR evolutionary population synthesis models, and to provide spectral observational constraints to calibrate future models. We measured equivalent widths (W_λ) of the most prominent NIR absorption features: λ 1.49 μm, Mg iλ 1.58 μm, Fe i/Mg i, λ 1.59 μm, Si i, λ 1.71 μm, Mg i, λ 2.21 μm, Na i and λ 2.26 μm, Ca i as well as the λ 1.62 μm, λ 2.29 μm, CO and λ 2.05 μm, CN molecular bands. Optical W_λ of G band (4300 Å), Hβ, Mg₂, Fe i (4531, 527 and 5335 Å) and Na i (5897 Å) were also measured. The globular clusters W_λ were compared with model predictions with ages within 4–15 Gyr, and metallicities between 0.005 and 2 Z_⊙. Observed integrated colours (B−V, V−I and V−K_s) were also compared with models. The NIR integrated spectra among our sample appear qualitatively similar in most of the absorption features. The Maraston models can properly predict the optical W_λ observed in globular clusters. Regarding the NIR, they do underestimate the strength of Mg i 1.49 μm, but they can reproduce the observed W_λ of Fe i 1.58 μm, Si i 1.59 μm and CO 2.29 μm, in about half of our sample. The remaining objects require the inclusion of intermediate-age populations. Thus, we suggest that the presence of C- and O-rich stars in models is important to reproduce the observed strengths of metallic lines. Another possibility is the lack of α-enhancement in the models. In the case of the optical and NIR Fe i lines, standard models and those that include blue horizontal branch stars produce similar results. A similar trend is observed for Na i 5895 Å, while in the case of the G band, the models with blue horizontal branch do describe better the observations. For most of the sample, the optical to NIR colours are well described by the Maraston models. In general, Maraston models can provide reliable information on the NIR stellar population of galaxies, but only when W_λ and colours are taken together; in other words, W_λ and continuum fluxes should be simultaneously fitted. However, the results should be taken with caution, since the models tend to predict results biased towards young ages.

Soybean yield is modelled from data gathered from crops in Rio Grande do Sul State, Brazil. The model comprises an agrometeorological term, obtained by adjusting the multiplicative model of Jensen, modified by Berlato, and a spectral term, obtained from National Oceanic and Atmospheric Administration (NOAA) satellite images of the maximum Normalized Difference Vegetation Index (NDVI). The weather data used to calculate the relative evapotranspiration (ET _r /ET ₀) cover the period from 1975 to 2000, and the NDVI/NOAA images were obtained from 1982 to 2000. Application of the agrometeorological–spectral model produced better yield estimates (of about 5%) than Jensen's model, allowing the further generation of yield maps for the most significant soybean production regions within the Rio Grande do Sul State.

Estimations of crop area were made based on the temporal profiles of the Enhanced Vegetation Index (EVI) obtained from moderate resolution imaging spectroradiometer (MODIS) images. Evaluation of the ability of the MODIS crop detection algorithm (MCDA) to estimate soybean crop areas was performed for fields in the Mato Grosso state, Brazil. Using the MCDA approach, soybean crop area estimations can be provided for December (first forecast) using images from the sowing period and for February (second forecast) using images from the sowing period and the maximum crop development period. The area estimates were compared to official agricultural statistics from the Brazilian Institute of Geography and Statistics (IBGE) and from the National Company of Food Supply (CONAB) at different crop levels from 2000/2001 to 2010/2011. At the municipality level, the estimates were highly correlated, withR2=0.97and RMSD = 13,142 ha. The MCDA was validated using field campaign data from the 2006/2007 crop year. The overall map accuracy was 88.25%, and the Kappa Index of Agreement was 0.765. By using pre-defined parameters, MCDA is able to provide the evolution of annual soybean maps, forecast of soybean cropping areas, and the crop area expansion in the Mato Grosso state.

Phytopathogenic diseases impact the development and yield of grapevines, resulting in economic, social and environmental losses. Sick plants have their metabolism changed, leading to alterations in their reflectance spectra. Little is known on these alterations, and a better knowledge could be used in the development of sensors able to detect diseases through fast, non-destructive techniques. This study was aimed at detecting spectral changes of grape leaves (Vitis vinifera cv. Cabernet Sauvignon), with early symptoms of downy mildew (Plasmopara viticola), powdery mildew (Uncinula necator), black-foot (Dactylonectria macrodidyma) and Petri disease (Phaeoacremonium spp.). Plants grown in pots and kept in a greenhouse were inoculated with the pathogens. In early stages of disease development, reflectance measurements were performed using a FieldSpec 3 spectroradiometer with leaf-clip attachment. The investigation began with discriminant analysis, which revealed that symptomatic plants are separated from the control ones. Reflectance spectra were, therefore, further investigated, looking for alterations on the shape of the spectra, characteristic of each disease. The disease descriptors were based on ratios between spectral features internal to a spectrum, a procedure which allowed the derivation of parameters intrinsic to each disease. A set of thresholds, defined as the ratios of reflectance at selected wavelengths, were derived for the studied diseases. For these ratios, the selected wavelengths (nm) were R443/R496, R443/R573, R443/R695, R443/R1900, R496/R573, R496/R695, R516/R1900 and R1900/R2435. The spectra from symptomatic plants present shape changes of as much as 20% with respect to healthy plants. The observed spectral changes are larger for black-foot and powdery mildew, but some wavelength ratios are also indicators of downy mildew and Petri disease. Data from wavelengths shorter than 700 nm in general carry more information than measurements at near infrared. These results are potentially useful to the development of low-cost devices to field use, providing real-time disease detection to early assessment of vineyard health status.