Search results: Found 6

Listing 1 - 6 of 6
Sort by
Abiotic Stress Effects on Performance of Horticultural Crops

Authors: ---
ISBN: 9783039217502 / 9783039217519 Year: Volume: 1 Pages: 126 DOI: 10.3390/books978-3-03921-751-9 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Biology --- Agriculture (General)
Added to DOAB on : 2019-11-05 10:43:33
License:

Loading...
Export citation

Choose an application

Abstract

Horticultural crop yield and quality depend on genotype, environmental conditions, and production management. In particular, adverse environmental conditions may greatly affect crop performance, reducing crop yield by 50%–70%. Abiotic stresses such as cold, heat, drought, flooding, salinity, nutrient deficiency, and ultraviolet radiation affect multiple physiological and biochemical mechanisms in plants as they attempt to cope with the stress conditions. However, different crop species can have different sensitivities or tolerances to specific abiotic stresses. Tolerant plants may activate different strategies to adapt to or avoid the negative effect of abiotic stresses. At the physiological level, photosynthetic activity and light-use efficiency of plants may be modulated to enhance tolerance against the stress. At the biochemical level, several antioxidant systems may be activated, and many enzymes may produce stress-related metabolites to help avoid cellular damage, including compounds such as proline, glycine betaine, and amino acids. Within each crop species there is a wide variability of tolerance to abiotic stresses, and some wild relatives may carry useful traits for enhancing the tolerance to abiotic stresses in their progeny through either traditional or biotechnological breeding. The research papers and reviews presented in this book provide an update of the scientific knowledge of crop interactions with abiotic stresses.

Salinity Tolerance in Plants

Author:
ISBN: 9783039210268 / 9783039210275 Year: Pages: 422 DOI: 10.3390/books978-3-03921-027-5 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Biology --- Biochemistry
Added to DOAB on : 2019-06-26 10:09:00
License:

Loading...
Export citation

Choose an application

Abstract

Salt stress is one of the most damaging abiotic stresses because most crop plants are susceptible to salinity to different degrees. According to the FAO, about 800 million Has of land are affected by salinity worldwide. Unfortunately, this situation will worsen in the context of climate change, where there will be an overall increase in temperature and a decrease in average annual rainfall worldwide. This Special Issue presents different research works and reviews on the response of plants to salinity, focused from different points of view: physiological, biochemical, and molecular levels. Although an important part of the studies on the response to salinity have been carried out with Arabidopsis plants, the use of other species with agronomic interest is also notable, including woody plants. Most of the conducted studies in this Special Issue were focused on the identification and characterization of candidate genes for salt tolerance in higher plants. This identification would provide valuable information about the molecular and genetic mechanisms involved in the salt tolerance response, and it also supplies important resources to breeding programs for salt tolerance in plants.

Keywords

Arabidopsis --- Brassica napus --- ion homeostasis --- melatonin --- NaCl stress --- nitric oxide --- redox homeostasis --- Chlamydomonas reinhardtii --- bZIP transcription factors --- salt stress --- transcriptional regulation --- photosynthesis --- lipid accumulation --- Apocyni Veneti Folium --- salt stress --- multiple bioactive constituents --- physiological changes --- multivariate statistical analysis --- banana (Musa acuminata L.) --- ROP --- genome-wide identification --- abiotic stress --- salt stress --- MaROP5g --- rice --- genome-wide association study --- salt stress --- germination --- natural variation --- Chlamydomonas reinhardtii --- salt stress --- transcriptome analysis --- impairment of photosynthesis --- underpinnings of salt stress responses --- chlorophyll fluorescence --- J8-1 plum line --- mandelonitrile --- Prunus domestica --- redox signalling --- salicylic acid --- salt-stress --- soluble nutrients --- Arabidopsis thaliana --- VOZ --- transcription factor --- salt stress --- transcriptional activator --- chlorophyll fluorescence --- lipid peroxidation --- Na+ --- photosynthesis --- photosystem --- RNA binding protein --- nucleolin --- salt stress --- photosynthesis --- light saturation point --- booting stage --- transcriptome --- grapevine --- salt stress --- ROS detoxification --- phytohormone --- transcription factors --- Arabidopsis --- CDPK --- ion homeostasis --- NMT --- ROS --- salt stress --- antioxidant enzymes --- Arabidopsis thaliana --- ascorbate cycle --- hydrogen peroxide --- reactive oxygen species --- salinity --- SnRK2 --- RNA-seq --- DEUs --- flax --- NaCl stress --- EST-SSR --- Salt stress --- Oryza sativa --- proteomics --- iTRAQ quantification --- cell membrane injury --- root activity --- antioxidant systems --- ion homeostasis --- melatonin --- salt stress --- signal pathway --- SsMAX2 --- Sapium sebiferum --- drought, osmotic stress --- salt stress --- redox homeostasis --- strigolactones --- ABA --- TGase --- photosynthesis --- salt stress --- polyamines --- cucumber --- abiotic stresses --- high salinity --- HKT1 --- halophytes --- glycophytes --- poplars (Populus) --- salt tolerance --- molecular mechanisms --- SOS --- ROS --- Capsicum annuum L. --- CaDHN5 --- salt stress --- osmotic stress --- dehydrin --- Gossypium arboretum --- salt tolerance --- single nucleotide polymorphisms --- association mapping. --- n/a

Afforestation and Reforestation: Drivers, Dynamics, and Impacts

Authors: --- --- --- --- et al.
ISBN: 9783039214471 / 9783039214488 Year: Pages: 194 DOI: 10.3390/books978-3-03921-448-8 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Biology --- Forestry
Added to DOAB on : 2019-12-09 11:49:15
License:

Loading...
Export citation

Choose an application

Abstract

Afforestation/reforestation (or forestation) has been implemented worldwide as an effective measure towards sustainable ecosystem services and addresses global environmental problems such as climate change. The conversion of grasslands, croplands, shrublands, or bare lands to forests can dramatically alter forest water, energy, and carbon cycles and, thus, ecosystem services (e.g., carbon sequestration, soil erosion control, and water quality improvement). Large-scale afforestation/reforestation is typically driven by policies and, in turn, can also have substantial socioeconomic impacts. To enable success, forestation endeavors require novel approaches that involve a series of complex processes and interdisciplinary sciences. For example, exotic or fast-growing tree species are often used to improve soil conditions of degraded lands or maximize productivity, and it often takes a long time to understand and quantify the consequences of such practices at watershed or regional scales. Maintaining the sustainability of man-made forests is becoming increasingly challenging under a changing environment and disturbance regime changes such as wildland fires, urbanization, drought, air pollution, climate change, and socioeconomic change. Therefore, this Special Issue focuses on case studies of the drivers, dynamics, and impacts of afforestation/reforestation at regional, national, or global scales. These new studies provide an update on the scientific advances related to forestation. This information is urgently needed by land managers and policy makers to better manage forest resources in today’s rapidly changing environments.

Remote Sensing of Leaf Area Index (LAI) and Other Vegetation Parameters

Authors: --- ---
ISBN: 9783039212392 / 9783039212408 Year: Pages: 334 DOI: 10.3390/books978-3-03921-240-8 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General)
Added to DOAB on : 2019-12-09 11:49:15
License:

Loading...
Export citation

Choose an application

Abstract

Monitoring of vegetation structure and functioning is critical to modeling terrestrial ecosystems and energy cycles. In particular, leaf area index (LAI) is an important structural property of vegetation used in many land surface vegetation, climate, and crop production models. Canopy structure (LAI, fCover, plant height, and biomass) and biochemical parameters (leaf pigmentation and water content) directly influence the radiative transfer process of sunlight in vegetation, determining the amount of radiation measured by passive sensors in the visible and infrared portions of the electromagnetic spectrum. Optical remote sensing (RS) methods build relationships exploiting in situ measurements and/or as outputs of physical canopy radiative transfer models. The increased availability of passive (radar and LiDAR) RS data has fostered their use in many applications for the analysis of land surface properties and processes, thanks also to their insensitivity to weather conditions and the capability to exploit rich structural and textural information. Data fusion and multi-sensor integration techniques are pressing topics to fully exploit the information conveyed by both optical and microwave bands.

Keywords

conifer forest --- leaf area index --- smartphone-based method --- canopy gap fraction --- terrestrial laser scanning --- forest inventory --- density-based clustering --- forest aboveground biomass --- root biomass --- tree heights --- GLAS --- artificial neural network --- allometric scaling and resource limitation --- structure from motion (SfM) --- 3D point cloud --- remote sensing --- local maxima --- fixed tree window size --- managed temperate coniferous forests --- point cloud --- spectral information --- structure from motion (SfM) --- unmanned aerial vehicle (UAV) --- chlorophyll fluorescence (ChlF) --- drought --- Mediterranean --- photochemical reflectance index (PRI) --- photosynthesis --- R690/R630 --- recovery --- BAAPA --- remote sensing --- household survey --- forest --- farm types --- automated classification --- sampling design --- adaptive threshold --- over and understory cover --- LAI --- leaf area index --- EPIC --- simulation --- satellite --- MODIS --- biomass --- evaluation --- southern U.S. forests --- VIIRS --- leaf area index (LAI) --- Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR) --- MODIS --- consistency --- uncertainty --- evaluation --- downscaling --- Pléiades imagery --- unmanned aerial vehicle --- stem volume estimation --- remote sensing --- clumping index --- leaf area index --- trunk --- terrestrial LiDAR --- HemiView --- forest above ground biomass (AGB) --- polarization coherence tomography (PCT) --- P-band PolInSAR --- tomographic profiles --- canopy closure --- global positioning system --- hemispherical sky-oriented photo --- signal attenuation --- geographic information system --- digital aerial photograph --- aboveground biomass --- leaf area index --- photogrammetric point cloud --- recursive feature elimination --- machine-learning --- forest degradation --- multisource remote sensing --- modelling aboveground biomass --- random forest --- Brazilian Amazon --- validation --- phenology --- NDVI --- LAI --- spectral analyses --- European beech --- altitude --- forests biomass --- remote sensing --- REDD+ --- random forest --- Tanzania --- RapidEye

Advances in Quantitative Remote Sensing in China – In Memory of Prof. Xiaowen Li

Authors: --- ---
ISBN: 9783038972709 Year: Volume: 1 Pages: 404 DOI: 10.3390/books978-3-03897-271-6 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Geography
Added to DOAB on : 2019-03-08 11:42:05
License:

Loading...
Export citation

Choose an application

Abstract

Quantitative land remote sensing has recently advanced dramatically, particularly in China. It has been largely driven by vast governmental investment, the availability of a huge amount of Chinese satellite data, geospatial information requirements for addressing pressing environmental issues and other societal benefits. Many individuals have also fostered and made great contributions to its development, and Prof. Xiaowen Li was one of these leading figures. This book is published in memory of Prof. Li. The papers collected in this book cover topics from surface reflectance simulation, inversion algorithm and estimation of variables, to applications in optical, thermal, Lidar and microwave remote sensing. The wide range of variables include directional reflectance, chlorophyll fluorescence, aerosol optical depth, incident solar radiation, albedo, surface temperature, upward longwave radiation, leaf area index, fractional vegetation cover, forest biomass, precipitation, evapotranspiration, freeze/thaw snow cover, vegetation productivity, phenology and biodiversity indicators. They clearly reflect the current level of research in this area. This book constitutes an excellent reference suitable for upper-level undergraduate students, graduate students and professionals in remote sensing.

Keywords

evapotranspiration --- Northeast China --- MS–PT algorithm --- spatial-temporal variations --- controlling factors --- potential evapotranspiration --- vegetation remote sensing --- reflectance model --- spectra --- leaf --- copper --- PROSPECT --- leaf area density --- terrestrial LiDAR --- tree canopy --- vertical structure --- voxel --- spatial representativeness --- heterogeneity --- validation --- land-surface temperature products (LSTs) --- observations --- HiWATER --- remote sensing --- spatiotemporal representative --- cost-efficient, sampling design --- heterogeneity --- validation --- FY-3C/MERSI --- GLASS --- Land surface temperature --- Land surface emissivity --- GPP --- SIF --- MuSyQ-GPP algorithm --- BEPS --- vegetation phenology --- Tibetan Plateau --- MODIS --- NDVI --- start of growing season (SOS) --- end of growing season (EOS) --- GLASS LAI time series --- forest disturbance --- disturbance index --- latent heat --- machine learning algorithms --- plant functional type --- high-resolution freeze/thaw --- AMSR2 --- MODIS --- LAI --- ZY-3 MUX --- GF-1 WFV --- HJ-1 CCD --- maize --- PROSPECT-5B+SAILH (PROSAIL) model --- spatial heterogeneity --- variability --- evapotranspiration --- land surface variables --- probability density function --- HiWATER --- spectral --- albedometer --- interference filter --- photoelectric detector --- validation --- land surface albedo --- multi-scale validation --- rugged terrain --- MRT-based model --- MCD43A3 C6 --- precipitation --- statistics methods --- China --- Tibetan Plateau --- South China’s --- drought --- SPI --- TMI data --- crop-growing regions --- downward shortwave radiation --- machine learning --- gradient boosting regression tree --- AVHRR --- CMA --- BRDF --- aerosol --- MODIS --- sunphotometer --- arid/semiarid --- solar-induced chlorophyll fluorescence --- fluorescence quantum efficiency in dark-adapted conditions (FQE) --- SCOPE --- Fraunhofer Line Discrimination (FLD) --- gross primary productivity (GPP) --- longwave upwelling radiation (LWUP) --- Visible Infrared Imaging Radiometer Suite (VIIRS) --- surface radiation budget --- hybrid method --- remote sensing --- leaf age --- leaf spectral properties --- leaf area index --- Cunninghamia --- Chinese fir --- canopy reflectance --- NIR --- EVI2 --- geometric optical radiative transfer (GORT) model --- land surface albedo --- snow-free albedo --- rugged terrain --- topographic effects --- black-sky albedo (BSA) --- GPP --- NPP --- MODIS --- validation --- phenology --- RADARSAT-2 --- rice --- Synthetic Aperture Radar (SAR) --- decision tree --- forest canopy height --- aboveground biomass --- ICESat GLAS --- Landsat --- random forest model --- anisotropic reflectance --- BRDF --- rugged terrain --- solo slope --- composite slope --- surface solar irradiance --- geostationary satellite --- polar orbiting satellite --- LUT method --- SURFRAD --- downward shortwave radiation --- daily average value --- Antarctica --- sinusoidal method --- cloud fraction --- interpolation --- boreal forest --- GPP --- spatiotemporal distribution and variation --- meteorological factors --- phenological parameters --- multisource data fusion --- aerosol retrieval --- urban scale --- vegetation dust-retention --- multiple ecological factors --- geographical detector model --- snow cover --- passive microwave --- FY-3C/MWRI --- algorithmic assessment --- China --- land surface temperature --- satellite observations --- flux measurements --- latitudinal pattern --- land cover change --- fractional vegetation cover (FVC) --- multi-data set --- northern China --- spatio-temporal --- inter-annual variation --- uncertainty --- standard error of the mean --- downscaling --- GPP --- spatial heterogeneity --- remote sensing --- subpixel information --- LiDAR --- point cloud --- leaf --- gap fraction --- 3D reconstruction --- biodiversity --- remote sensing --- species richness --- metric comparison --- metric integration --- leaf area index --- MODIS products --- Landsat --- high resolution --- homogeneous and pure pixel filter --- pixel unmixing --- vertical vegetation stratification --- gross primary production (GPP) --- light use efficiency --- dense forest --- MODIS --- VPM --- temperature profiles --- humidity profiles --- n/a --- geometric-optical model --- thermal radiation directionality --- quantitative remote sensing inversion --- scale effects --- comprehensive field experiment

Advances in Quantitative Remote Sensing in China – In Memory of Prof. Xiaowen Li

Authors: --- ---
ISBN: 9783038972761 Year: Volume: 2 Pages: 404 DOI: 10.3390/books978-3-03897-277-8 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Geography
Added to DOAB on : 2019-03-08 11:42:05
License:

Loading...
Export citation

Choose an application

Abstract

Quantitative land remote sensing has recently advanced dramatically, particularly in China. It has been largely driven by vast governmental investment, the availability of a huge amount of Chinese satellite data, geospatial information requirements for addressing pressing environmental issues and other societal benefits. Many individuals have also fostered and made great contributions to its development, and Prof. Xiaowen Li was one of these leading figures. This book is published in memory of Prof. Li. The papers collected in this book cover topics from surface reflectance simulation, inversion algorithm and estimation of variables, to applications in optical, thermal, Lidar and microwave remote sensing. The wide range of variables include directional reflectance, chlorophyll fluorescence, aerosol optical depth, incident solar radiation, albedo, surface temperature, upward longwave radiation, leaf area index, fractional vegetation cover, forest biomass, precipitation, evapotranspiration, freeze/thaw snow cover, vegetation productivity, phenology and biodiversity indicators. They clearly reflect the current level of research in this area. This book constitutes an excellent reference suitable for upper-level undergraduate students, graduate students and professionals in remote sensing.

Keywords

evapotranspiration --- Northeast China --- MS–PT algorithm --- spatial-temporal variations --- controlling factors --- potential evapotranspiration --- vegetation remote sensing --- reflectance model --- spectra --- leaf --- copper --- PROSPECT --- leaf area density --- terrestrial LiDAR --- tree canopy --- vertical structure --- voxel --- spatial representativeness --- heterogeneity --- validation --- land-surface temperature products (LSTs) --- observations --- HiWATER --- remote sensing --- spatiotemporal representative --- cost-efficient, sampling design --- heterogeneity --- validation --- FY-3C/MERSI --- GLASS --- Land surface temperature --- Land surface emissivity --- GPP --- SIF --- MuSyQ-GPP algorithm --- BEPS --- vegetation phenology --- Tibetan Plateau --- MODIS --- NDVI --- start of growing season (SOS) --- end of growing season (EOS) --- GLASS LAI time series --- forest disturbance --- disturbance index --- latent heat --- machine learning algorithms --- plant functional type --- high-resolution freeze/thaw --- AMSR2 --- MODIS --- LAI --- ZY-3 MUX --- GF-1 WFV --- HJ-1 CCD --- maize --- PROSPECT-5B+SAILH (PROSAIL) model --- spatial heterogeneity --- variability --- evapotranspiration --- land surface variables --- probability density function --- HiWATER --- spectral --- albedometer --- interference filter --- photoelectric detector --- validation --- land surface albedo --- multi-scale validation --- rugged terrain --- MRT-based model --- MCD43A3 C6 --- precipitation --- statistics methods --- China --- Tibetan Plateau --- South China’s --- drought --- SPI --- TMI data --- crop-growing regions --- downward shortwave radiation --- machine learning --- gradient boosting regression tree --- AVHRR --- CMA --- BRDF --- aerosol --- MODIS --- sunphotometer --- arid/semiarid --- solar-induced chlorophyll fluorescence --- fluorescence quantum efficiency in dark-adapted conditions (FQE) --- SCOPE --- Fraunhofer Line Discrimination (FLD) --- gross primary productivity (GPP) --- longwave upwelling radiation (LWUP) --- Visible Infrared Imaging Radiometer Suite (VIIRS) --- surface radiation budget --- hybrid method --- remote sensing --- leaf age --- leaf spectral properties --- leaf area index --- Cunninghamia --- Chinese fir --- canopy reflectance --- NIR --- EVI2 --- geometric optical radiative transfer (GORT) model --- land surface albedo --- snow-free albedo --- rugged terrain --- topographic effects --- black-sky albedo (BSA) --- GPP --- NPP --- MODIS --- validation --- phenology --- RADARSAT-2 --- rice --- Synthetic Aperture Radar (SAR) --- decision tree --- forest canopy height --- aboveground biomass --- ICESat GLAS --- Landsat --- random forest model --- anisotropic reflectance --- BRDF --- rugged terrain --- solo slope --- composite slope --- surface solar irradiance --- geostationary satellite --- polar orbiting satellite --- LUT method --- SURFRAD --- downward shortwave radiation --- daily average value --- Antarctica --- sinusoidal method --- cloud fraction --- interpolation --- boreal forest --- GPP --- spatiotemporal distribution and variation --- meteorological factors --- phenological parameters --- multisource data fusion --- aerosol retrieval --- urban scale --- vegetation dust-retention --- multiple ecological factors --- geographical detector model --- snow cover --- passive microwave --- FY-3C/MWRI --- algorithmic assessment --- China --- land surface temperature --- satellite observations --- flux measurements --- latitudinal pattern --- land cover change --- fractional vegetation cover (FVC) --- multi-data set --- northern China --- spatio-temporal --- inter-annual variation --- uncertainty --- standard error of the mean --- downscaling --- GPP --- spatial heterogeneity --- remote sensing --- subpixel information --- LiDAR --- point cloud --- leaf --- gap fraction --- 3D reconstruction --- biodiversity --- remote sensing --- species richness --- metric comparison --- metric integration --- leaf area index --- MODIS products --- Landsat --- high resolution --- homogeneous and pure pixel filter --- pixel unmixing --- vertical vegetation stratification --- gross primary production (GPP) --- light use efficiency --- dense forest --- MODIS --- VPM --- temperature profiles --- humidity profiles --- n/a --- geometric-optical model --- thermal radiation directionality --- quantitative remote sensing inversion --- scale effects --- comprehensive field experiment

Listing 1 - 6 of 6
Sort by
Narrow your search

Publisher

MDPI - Multidisciplinary Digital Publishing Institute (6)


License

CC by-nc-nd (6)


Language

eng (6)


Year
From To Submit

2019 (6)