Search results for "leaf"

How Universal Is the Relationship between Remotely Sensed Vegetation Indices and Crop Leaf Area Index? A Global Assessment

2016

This study aims to assess the relationship between Leaf Area Index (LAI) and remotely sensed Vegetation Indices (VIs) for major crops, based on a globally explicit dataset of in situ LAI measurements over a significant set of locations. We used a total of 1394 LAI measurements from 29 sites spanning 4 continents and covering 15 crop types with corresponding Landsat satellite images. Best-fit functions for the LAI-VI relationships were generated and assessed in terms of crop type, vegetation index, level of radiometric/atmospheric processing, method of LAI measurement, as well as the time difference between LAI measurements and satellite overpass. These global LAI-VI relationships were evalu…

Allium makrianum (Alliaceae), a new autumnal species from Greece

2010

Allium makrianum is described as a new species growing on the limestone of the Chios, north-eastern Aegean island (Greece). It is a very rare autumnal geophyte, showing some relationship with A. archeotrichon from Rhodos. Its iconography, morphology, chromosome number (2n=16), leaf anatomy, ecology and taxonomy are examined.

Considerazioni tassonomiche e cariologiche sulle popolazioni siciliane di Sternbergia colchiciflora Waldst. & Kit. (Amaryllidaceae)

2004

A citotaxonomic study on two Sicilian populations of Sternbergia colchiciflora from Madonie and Mt. Etna was carried out. They show marked differences in their morphology and caryology.This suggests to treat them as two distinct taxa, but their correct taxonomic position needs further investigation on other populations of Sternbergia colchiciflora from Mediterranean area

Micromorfologia fogliare comparata ed anatomia generale di Epipactis microphylla (Ehrh.) SW. ed E. helleborine (L.) Crantz (Orchidaceae) in Sicilia

2009

Solvent-free microwave-assisted extraction of polyphenols from olive tree leaves: Antioxidant and antimicrobial properties

2017

International audience; Response surface methodology (RSM) and artificial neural networks (ANN) were evaluated and compared in order to decide which method was the most appropriate to predict and optimize total phenolic content (TPC) and oleuropein yields in olive tree leaf (Olea europaea) extracts, obtained after solvent-free microwave- assisted extraction (SFMAE). The SFMAE processing conditions were: microwave irradiation power 250-350 W, extraction time 2-3 min, and the amount of sample 5-10 g. Furthermore, the antioxidant and antimicrobial activities of the olive leaf extracts, obtained under optimal extraction conditions, were assessed by several in vitro assays. ANN had better predic…

The possibilities of using low-cost fibrous natural materials as sorbents for removing aliphatic hydrocarbons (C6-C15) from an aqueous solution

2020

Sorption of oil-related products (including mainly the propellants) is the basic process that coun-teracts spreading these types of pollution into the environment. Plenty of synthetic substances (including multi-component petroleum products) must be removed both from the fresh and ground-water. The aim of this study was to compare the possibilities of using natural fibrous materials (also weed or waste materials): broadleaf cattail (Typha latifolia L.) seeds, peat and coconut fiber as sorbents of aliphatic hydrocarbons from an aqueous solution. In order to increase sorptive capacity, tested materials were mercerized in hot (80°C) NaOH for sorption properties improvement. The removal of alip…

Discriminating irrigated and rainfed olive orchards with thermal ASTER imagery and DART 3D simulation

2009

Article in Press

A prediction model for field drying of hay using a heat balance method

1993

Abstract A hay drying model with a multi-layer representation has been developed. This model, based on a heat balance method, was designed to compute hay drying dynamics in the field. It was implemented for hay spread over a field or in windrows. The necessary inputs are: (1) meteorological data (temperature, humidity, wind speed, solar and atmospheric radiation); (2) biological characteristics of the plant; (3) hay physical parameters (depth, leaf area index). The output provides time-dependent cumulative water losses and changes in water content and temperature in the different layers. The model was tested against data measured under experimental conditions with different kinds of grass (…

Characterization and intercomparison of global moderate resolution leaf area index (LAI) products: Analysis of climatologies and theoretical uncertai…

2013

products (R 2 >0.74), with typical deviations of<0.5 for nonforest and<1.0 for forest biomes. JRC-TIP, the only effective LAI product, is about half the values of the other LAI products. The average uncertainties and relative uncertainties are in the following order: MODIS (0.17, 11.5%)<GEOV1 (0.24, 26.6%)<Land-SAF (0.36, 37.8%) <JRC-TIP (0.43, 114.3%). The highest relative uncertainties usually appear in ecological transition zones. More than 75% of MODIS, GEOV1, JRC-TIP, and Land-SAF pixels are within the absolute uncertainty requirements (� 0.5) set by the Global Climate Observing System (GCOS), whereas more than 78.5% of MODIS and 44.6% of GEOV1 pixels are within the threshold for relat…

Obtaining the three-dimensional structure of tree orchards from remote 2D terrestrial LIDAR scanning

2009

In recent years, LIDAR (light detection and ranging) sensors have been widely used to measure environmental parameters such as the structural characteristics of trees, crops and forests. Knowledge of the structural characteristics of plants has a high scientific value due to their influence in many biophysical processes including, photosynthesis, growth, CO2-sequestration and evapotranspiration, playing a key role in the exchange of matter and energy between plants and the atmosphere, and affecting terrestrial, above-ground, carbon storage. In this work, we report the use of a 2D LIDAR scanner in agriculture to obtain three-dimensional (3D) structural characteristics of plants. LIDAR allows…