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Estimation of chlorophyll content with portable meters is an easy way to quantify crop nitrogen status in sugar beet leaves. In this work, an alternative for chlorophyll content estimation using RGB-only vegetation indices has been explored. In a first step, pictures of spring-sown ‘Fernanda KWS’ variety sugar beet leaves taken with a commercial camera were used to calculate 25 RGB indices reported in the literature and to obtain 9 new indices through principal component analysis (PCA) and stepwise linear regression (SLR) techniques. The performance of the 34 indices was examined in order to evaluate their ability to estimate chlorophyll content and chlorophyll degradation in the leaves under different natural light conditions along 4 days of the canopy senescence period. Two of the new proposed RGB indices were found to improve the already good performance of the indices reported in the literature, particularly for leaves featuring low chlorophyll contents. The 4 best indices were finally tested in field conditions, using unmanned aerial vehicle (UAV)-taken photographs of a sugar beet plot, finding a reasonably good agreement with chlorophyll-meter data for all indices, in particular for I2 and (R−B)/(R+G+B). Consequently, the suggested RGB indices may hold promise for inexpensive chlorophyll estimation in sugar beet leaves during the harvest time, although a direct relationship with nitrogen status still needs to be validated.

Unmanned Aerial Vehicles (UAVs) offer excellent survey capabilities at low cost to provide farmers with information about the type and distribution of weeds in their fields. In this study, the problem of detecting the infestation of a typical weed (charlock mustard) in an alfalfa crop has been addressed using conventional digital cameras installed on a lightweight UAV to compare RGB-based indices with the widely used Normalized Difference Vegetation Index (NDVI) index. The simple (R−B)/(R+B) and (R−B)/(R+B+G) vegetation indices allowed one to easily discern the yellow weed from the green crop. Moreover, they avoided the potential confusion of weeds with soil observed for the NDVI index. The small overestimation detected in the weed identification when the RGB indices were used could be easily reduced by using them in conjunction with NDVI. The proposed methodology may be used in the generation of weed cover maps for alfalfa, which may then be translated into site-specific herbicide treatment maps.

An analysis of the similarities in the ATR-FTIR spectra from Argania spinosa, Rosa rubiginosa and Elaeis guineensis oils AbstractThe attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR) spectra of the essential oil from Rosa rubiginosa L. seeds and the vegetable oils from Argania spinosa L. kernel and Elaeis guineensis Jacq. pulp show important similitudes that hamper their identification by vibrational spectroscopy techniques if they are not complemented with wellestablished methods such as gas chromatography. Nevertheless, the observed similarities in structure-composition-traditional uses between Argania spinosa and Rosa rubiginosa oils suggest that they could be interchangeable when skin physicians, dermatologic-surgeons or cosmetologists perceive in their practice that one of the oils produces an allergic reaction or other side effects, although further activity studies are needed. Keywords: argan; ATR-FTIR; African oil palm; oils; sweet briar.of FTIR spectroscopy has been deemed suitable for verifying the presence of functional groups or for structure elucidation. Moreover, when coupled with an ATR accessory, this technique shortens the time of sample preparation and eases spectral reproducibility, thus making sample analysis even faster. ATR-FTIR is used in vegetal oil chemistry as a rapid quantitative tool to determine the main components (i.e., saturated, trans, mono-and polyunsaturated fatty acids)

Changes in environmental conditions resulting from Climate Change are expected to have a major impact on crops. In order to foresee adaptation measures and to minimize yield decline, it is necessary to estimate the effect of those changes on the evapotranspiration and on the associated irrigation needs of crops. In the study presented herein, future conditions extracted from RCP4.5 scenario of IPCC, particularized for Castilla-y-León (Spain), were used as inputs for FAO crop simulation model (AquaCrop) to estimate sugar beet agronomic performance in the medium-term (2050 and 2070). A regional analysis of future trends in terms of yield, biomass and CO2 sequestration was carried out. An annual ET0 increase of up to 200 mm was estimated in 2050 and 2070 scenarios, with ETc increases of up to 40 mm/month. At current irrigation levels, temperature rise would be accompanied by a 9% decrease in yield and a ca. 6% decrease in assimilated CO2 in the 2050 and 2070 scenarios. However, it is also shown that the implementation of adequate adaptation measures, in combination with a more efficient irrigation management, may result in up to 17% higher yields and in the storage of between 9% and 13% higher amounts of CO2.