Search results for "chlorophyll content"
showing 9 items of 19 documents
Retrieval of Crop Variables from Proximal Multispectral UAV Image Data Using PROSAIL in Maize Canopy
2022
Mapping crop variables at different growth stages is crucial to inform farmers and plant breeders about the crop status. For mapping purposes, inversion of canopy radiative transfer models (RTMs) is a viable alternative to parametric and non-parametric regression models, which often lack transferability in time and space. Due to the physical nature of RTMs, inversion outputs can be delivered in sound physical units that reflect the underlying processes in the canopy. In this study, we explored the capabilities of the coupled leaf–canopy RTM PROSAIL applied to high-spatial-resolution (0.015 m) multispectral unmanned aerial vehicle (UAV) data to retrieve the leaf chlorophyll content (LC…
Seasonal Mapping of Irrigated Winter Wheat Traits in Argentina with a Hybrid Retrieval Workflow Using Sentinel-2 Imagery
2022
Earth observation offers an unprecedented opportunity to monitor intensively cultivated areas providing key support to assess fertilizer needs and crop water uptake. Routinely, vegetation traits mapping can help farmers to monitor plant development along the crop’s phenological cycle, which is particularly relevant for irrigated agricultural areas. The high spatial and temporal resolution of the Sentinel-2 (S2) multispectral instrument leverages the possibility to estimate leaf area index (LAI), canopy chlorophyll content (CCC), and vegetation water content (VWC) from space. Therefore, our study presents a hybrid retrieval workflow combining a physically-based strategy with a machine learni…
Hybrid retrieval of crop traits from multi-temporal PRISMA hyperspectral imagery
2022
The recently launched and upcoming hyperspectral satellite missions, featuring contiguous visible-to-shortwave infrared spectral information, are opening unprecedented opportunities for the retrieval of a broad set of vegetation traits with enhanced accuracy through novel retrieval schemes. In this framework, we exploited hyperspectral data cubes collected by the new-generation PRecursore IperSpettrale della Missione Applicativa (PRISMA) satellite of the Italian Space Agency to develop and test a hybrid retrieval workflow for crop trait mapping. Crop traits were mapped over an agricultural area in north-east Italy (Jolanda di Savoia, FE) using PRISMA images collected during the 2020 and 202…
The influence of brassinosteroid on growth and parameters of photosynthesis of wheat and mustard plants.
1984
The growth response of wheat (Triticum aest. L.) and mustard seedlings (Sinapis alba L.) treated with 10(-6) mol · l(-1) brassinosteroid (BR) foliar spray was measured. BR-treatment resulted in a general promotion of plant growth. We found the accumulation of photosynthates to be stimulated in the treated plants, as indicated by enhanced fresh and dry weights of leaves and shoots. BR also promoted the synthesis of soluble proteins and soluble reducing sugars, whereas the chlorophyll content was hardly affected. CO(2)-fixation in vivo as well as the (in vitro) RubPC-ase activity of BR-treated leaves were enhanced. In the developing wheat leaves we detected no difference in the ratio fraction…
Is Your Moss Alive during Active Biomonitoring Study?
2021
Biomonitoring was proposed to assess the condition of living organisms or entire ecosystems with the use of bioindicators—species sensitive to specific pollutants. It is important that the bioindicator species remains alive for as long as possible while retaining the ability to react to the negative effects of pollution (elimination/neutralization of hazardous contaminants). The purpose of the study was to assess the survival of Pleurozium schreberi moss during exposure (moss-bag technique) based on the measurement of the concentration of elements (Ni, Cu, Zn, Cd, and Pb), chlorophyll content, and its fluorescence. The study was carried out using a CCM-300 portable chlorophyll content meter…
On the semi-automatic retrieval of biophysical parameters based on spectral index optimization
2014
Abstract: Regression models based on spectral indices are typically empirical formulae enabling the mapping of biophysical parameters derived from Earth Observation (EO) data. Due to its empirical nature, it remains nevertheless uncertain to what extent a selected regression model is the most appropriate one, until all band combinations and curve fitting functions are assessed. This paper describes the application of a Spectral Index (SI) assessment toolbox in the Automated Radiative Transfer Models Operator (ARTMO) package. ARTMO enables semi-automatic retrieval and mapping of biophysical parameters from optical remote sensing observations. The SI toolbox facilitates the assessment of biop…
Effect of salinity on Puccinellia distans (L.) Parl. treated with NaCl and foliarly applied glycinebetaine
2009
Turfgrasses general appearance is much affected by environmental stresses because the species used for this purpose are particularly exigent in terms of technical inputs and water need. In the Mediterranean area, sometimes irrigation is provided by using waste water which may contain high concentrations of dissolved salts which can cause salt stress injury and poor turf quality. Puccinellia distans (L.) Parl. is a halophyte cool season grass that seems to have a high salinity tolerance when cultivated in sodic soils or in NaCl-rich hydroponic cultures. We investigated the response of P. distans to salinity in a soil culture in a controlled growth environment. The effect of different concent…
Deep Gaussian processes for biogeophysical parameter retrieval and model inversion
2020
Parameter retrieval and model inversion are key problems in remote sensing and Earth observation. Currently, different approximations exist: a direct, yet costly, inversion of radiative transfer models (RTMs); the statistical inversion with in situ data that often results in problems with extrapolation outside the study area; and the most widely adopted hybrid modeling by which statistical models, mostly nonlinear and non-parametric machine learning algorithms, are applied to invert RTM simulations. We will focus on the latter. Among the different existing algorithms, in the last decade kernel based methods, and Gaussian Processes (GPs) in particular, have provided useful and informative so…
Evaluation of Hybrid Models to Estimate Chlorophyll and Nitrogen Content of Maize Crops in the Framework of the Future CHIME Mission
2022
In the next few years, the new Copernicus Hyperspectral Imaging Mission (CHIME) is foreseen to be launched by the European Space Agency (ESA). This mission will provide an unprecedented amount of hyperspectral data, enabling new research possibilities within several fields of natural resources, including the “agriculture and food security” domain. In order to efficiently exploit this upcoming hyperspectral data stream, new processing methods and techniques need to be studied and implemented. In this work, the hybrid approach (HYB) and its variant, featuring sampling dimensionality reduction through active learning heuristics (HAL), were applied to CHIME-like data to evaluate the…