Crambe is an oleaginous plant mainly cultivated in Brazil due to its oil characteristics that provide stability to oxidation, qualifying it for the use in a variety of products. Understanding the spectral-temporal pattern of the crambe crop is important to identify and quantify already cultivated areas via remote sensing. This study spectrally characterised the plant, seeking to relate the spectral pattern to the phenological stages of the crop throughout its development. The spectral information was obtained by passive terrestrial sensors in two harvests, thus generating a spectral-temporal pattern and the crambe temporal profile through the vegetation indices NDVI and SAVI. During the phenological stages of the seedling and the beginning of the vegetative growth, the red spectral band showed higher values of reflectance; this occurred because the crop had not yet completely covered the soil. Stages at the end of the vegetative growth and the beginning of the flowering, there was a higher reflectance in the near infrared and a lower reflectance in the mid-infrared. For the granulation and maturation stages, the reflectance in the mean and near infrared reduced due to leaf senescence and loss of cellular water content. The NDVI and SAVI temporal profiles demonstrate linear growth up to the vegetative peak, which occurs between the end of the phenological stage of the vegetative growth and the beginning of the flowering and highest amount of green biomass. At the beginning of grain formation and filling, yellowing of leaves and senescence, granulation and maturation stages, the values reduced.
Crambe (Crambe abyssinica Hoschst) is a winter oilseed crop with yield potential of 1500 kg ha -1 . It is indicated for crop rotation systems and tolerates moderate frost. However, crambe presents thermal and water limitations that influence sowing dates since it needs water at blooming and at least 200 mm rainfall until it reaches the flowering stage. This study aimed to assess the performance of a crambe crop in different sowing dates. The experiment was conducted on the experimental farm of Assis Gurgacz College (Faculdade Assis Gurgacz -FAG) Cascavel -Paraná, at an altitude of 700 m, within latitudes 24°56'25.39" S and 24°56'45.39" S and longitudes 53°30'9.89" W and 53°31'17.01" W. The experimental design consisted of randomized blocks with three sowing dates (April, June and July) and five replications. Phenometric parameters such as plant height, dry mass, plants per meter, grain yield and mass of 1000 grains were assessed and data were subjected to Tukey's test at 5% probability. Phenometric variables were influenced by sowing dates. Degree days and rainfall influenced the results. April has proven to be the best month for sowing.
The purpose of this study was to describe and compare the spectral response of common beans desiccated with diquat and glufosinate-ammonium (GLA) using a hyperspectral terrestrial sensor and report how the desiccants influence dry bean visual appearance. Bean plants were desiccated with two different types of diquat and GLA desiccants. After the measurements of the spectral curves were carried out, from these values the indices of vegetation and derivatives were calculated, the chlorophyll content of the leaves on the days of the campaign was also measured. After harvesting the grains, some qualitative variables of the grains, such as cooking time and color, were evaluated Vegetation indices (VIs) in the near-infrared and mid-infrared regions of the spectrum (wavelength locations of 705, 750, 860, and 1240 nm) were significantly different between desiccant treatments (p≤0.05) two days after application (DAA). Desiccant application caused chlorophyll degradation as detected at the wavelength of 650 and 800 nm at DAA 1. The red edge and first derivatives showed that crop injury was higher in the diquat treatment because peak magnitude for this treatment became smaller over time. The desiccant application negatively affected seed quality, resulting in smaller Hue values and longer cooking time (CT). Hue angle correlated negatively with plant water content variation and CT Our results suggest that hyperespectral terrestrial sensing can differentiate the effects caused by the desiccants, showing that ammonium glufosinate causes less damage to seed quality and the water loss is like the control group
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