Soil-Terrain Modeling for Site-Specific Agricultural Management

Bioenergy potentials from recently abandoned cropland under the land-energy-water nexus

10.5194/egusphere-egu21-16111 ◽

2021 ◽

Author(s):

Jan Sandstad Næss ◽

Otavio Cavalett ◽

Francesco Cherubini

Keyword(s):

Nature Conservation ◽

Water Use ◽

Soil Characteristics ◽

Agricultural Management ◽

Site Specific ◽

Bioenergy Production ◽

Trade Offs ◽

Irrigation Water Use ◽

Land Availability ◽

Abandoned Cropland

Bioenergy plays a key role in scenarios limiting global warming below 2&#176;C in 2100 relative to pre-industrial times. Land availability for bioenergy production is constrained due to competition with agriculture, nature conservation and other land uses. Utilizing recently abandoned cropland to produce bioenergy is a promising option for gradual bioenergy deployment with lower risks of potential trade-offs on food security and the environment. Up until now, the global extent of abandoned cropland has been unclear. Furthermore, there is a need to better map bioenergy potentials, taking into account site-specific conditions such as local climate, soil characteristics, agricultural management and water use.Our study spatially quantify global bioenergy potentials from recently abandoned cropland under the land-energy-water nexus. We integrate a recently developed high-resolution satellite-derived land cover product (European Space Agency Climate Change Initiative Land Cover) with an agro-ecological crop yield model (Global Agro-Ecological Zones 3.0). Abandoned cropland is mapped as pixels transitioning from cropland to non-urban classes. We further identify candidate areas for nature conservation and areas with increased pressure on water resources. Based on climatic conditions, soil characteristics and agricultural management levels, we spatially model bioenergy yields and irrigation water use on abandoned cropland for three perennial grasses. We compute and analyze bioenergy potentials for 296 different variants of management factors and land and water use constraints. By assessing key energy, water and land indicators, we identify optimal bioenergy production strategies and site-specific trade-offs.We found 83 million hectares of abandoned cropland between 1992 and 2015, equivalent of 5% of today&#8217;s cropland area. Bioenergy potentials range between 6-39 exajoules per year (EJ yr-1) (11-68% of today&#8217;s bioenergy demand), depending on agricultural management, land availability and irrigation water use. We further show and extensively discuss site-specific trade-offs between increased bioenergy production, land-use and water-use. Our high-end estimate (39 EJ yr-1) relies on complete irrigation and land availability. When acknowledging site-specific trade-offs on water resources and nature conservation, a potential of 20 EJ yr-1 is achievable without production in biodiversity hotspots or irrigation in water scarce areas. This is equal to 8-23% of median projected bioenergy demand in 2050 for 1.5&#176;C scenarios across different Shared Socio-economic Pathways. The associated land and water requirements are equal to 3% of current global cropland extent and 8% of today&#8217;s global agricultural water use, respectively.

Download Full-text

Site Specific Nitrogen Management in Citrus Orchard to Minimize Nitrogen Pollution

10.5194/egusphere-egu2020-10572 ◽

2020 ◽

Author(s):

Tarin Paz-Kagan ◽

Dolev Termin ◽

Raphael Linker ◽

Eran Raveh ◽

Noa Ohana ◽

...

Keyword(s):

Spatial Variability ◽

Spectral Index ◽

Spatial Representation ◽

Agricultural Management ◽

Support Vector ◽

Crop Water Stress Index ◽

Citrus Orchard ◽

Model Composite ◽

Site Specific ◽

Clustering Model

Site-specific agricultural management relies on identifying within-field spatial variability and is being used for variable rate input of resources. Precision agricultural management commonly attempts to integrate multiple datasets to determine management zones (MZs), homogenous units within the field, based on spatial characteristics of environmental and crop properties (i.e., terrain, soil, vegetation conditions). This study aims to develop a novel statistical multivariate spatial clustering approach to determine MZs for precision nitrogen fertilization in a citrus orchard along the growing season. Five variables were used to characterize spatial variability (i.e., N spectral index, crop water stress index (CWSI), tree height, elevation, and slope) within four plots based on a monthly thermal and multispectral high-resolution imagery acquired from an unmanned aerial vehicle (UAV). The UAV data was tested against leaf N samplings based on samples taken from 48 trees within the four craters plots, which were selected based on a stratified random design (SRD) model. A Support Vector Machines-Regression (SVM-R) model was applied to develop a prediction N spectral index for canopy N levels. The clustering model included the following components &#8212; spatial representation of the data based on Getis Ord Gi*. Then variable weights were assigned based on their relative contribution to principal component analysis. Fuzzy C-means algorithm was applied to the weighted spatial representation and was found to generate spatially continuous and homogeneous MZs with similar numbers of trees. In addition, we analyzed the temporal dynamics in the MZs and clustering patterns throughout the year, using information based on the monthly UAV imagery. Management of the sub-units, or plots, using spatial representation rather than the measured values, is suggested as a more suitable platform for agricultural practices. Future development of fertilization applications for individual trees will require adjusting the statistical approach to support tree-specific management. The proposed model composite is flexible and may be composed of different models and/or variables for developing optimal MZ delineation for specific plots.

Download Full-text

Large-cluster and combined fluorescent and gold immunoprobes

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100166920 ◽

1996 ◽

Vol 54 ◽

pp. 892-893

Author(s):

Richard D. Powell ◽

James F. Hainfeld ◽

Carol M. R. Halsey ◽

David L. Spector ◽

Shelley Kaurin ◽

...

Keyword(s):

Metal Cluster ◽

Sulfonyl Chloride ◽

Gel Filtration ◽

Cross Linking ◽

Site Specific ◽

Fab Fragments ◽

Cluster Label ◽

Covalently Linked ◽

Texas Red ◽

Fold Excess

Two new types of covalently linked, site-specific immunoprobes have been prepared using metal cluster labels, and used to stain components of cells. Combined fluorescein and 1.4 nm “Nanogold” labels were prepared by using the fluorescein-conjugated tris (aryl) phosphine ligand and the amino-substituted ligand in the synthesis of the Nanogold cluster. This cluster label was activated by reaction with a 60-fold excess of (sulfo-Succinimidyl-4-N-maleiniido-cyclohexane-l-carboxylate (sulfo-SMCC) at pH 7.5, separated from excess cross-linking reagent by gel filtration, and mixed in ten-fold excess with Goat Fab’ fragments against mouse IgG (obtained by reduction of F(ab’)2 fragments with 50 mM mercaptoethylamine hydrochloride). Labeled Fab’ fragments were isolated by gel filtration HPLC (Superose-12, Pharmacia). A combined Nanogold and Texas Red label was also prepared, using a Nanogold cluster derivatized with both and its protected analog: the cluster was reacted with an eight-fold excess of Texas Red sulfonyl chloride at pH 9.0, separated from excess Texas Red by gel filtration, then deprotected with HC1 in methanol to yield the amino-substituted label.

Download Full-text

The challenge of detecting modifications on proteins

Essays in Biochemistry ◽

10.1042/ebc20190055 ◽

2020 ◽

Vol 64 (1) ◽

pp. 135-153 ◽

Cited By ~ 1

Author(s):

Lauren Elizabeth Smith ◽

Adelina Rogowska-Wrzesinska

Keyword(s):

Mass Spectrometry ◽

Protein Function ◽

Chemical Properties ◽

Lysine Acetylation ◽

Mass Determination ◽

Post Translational Modifications ◽

Site Specific ◽

The Common

Abstract Post-translational modifications (PTMs) are integral to the regulation of protein function, characterising their role in this process is vital to understanding how cells work in both healthy and diseased states. Mass spectrometry (MS) facilitates the mass determination and sequencing of peptides, and thereby also the detection of site-specific PTMs. However, numerous challenges in this field continue to persist. The diverse chemical properties, low abundance, labile nature and instability of many PTMs, in combination with the more practical issues of compatibility with MS and bioinformatics challenges, contribute to the arduous nature of their analysis. In this review, we present an overview of the established MS-based approaches for analysing PTMs and the common complications associated with their investigation, including examples of specific challenges focusing on phosphorylation, lysine acetylation and redox modifications.

Download Full-text