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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,387 records · Page 77

Evolution of A-Type Macrosegregation in Large Size Steel Ingot After Multistep Forging and Heat Treatment

A-type macrosegregation refers to the channel chemical heterogeneities that can be formed during solidification in large size steel ingots. In this research, a combination of experiment and simulation was used to study the influence of open die forging parameters on the evolution of A-type macrosegregation patterns during a multistep forging of a 40 metric ton (MT) cast, high-strength steel ingot. Macrosegregation patterns were determined experimentally by macroetch along the longitudinal axis of the forged and heat-treated ingot. Mass spectroscopy, on more than 900 samples, was used to determine the chemical composition map of the entire longitudinal sectioned surface. FORGE NxT 1.1 finite element modeling code was used to predict the effect of forging sequences on the morphology evolution of A-type macrosegregation patterns. For this purpose, grain flow variables were defined and implemented in a large scale finite element modeling code to describe oriented grains and A-type segregation patterns. Examination of the A-type macrosegregation showed four to five parallel continuous channels located nearly symmetrical to the axis of the forged ingot. In some regions, the A-type patterns became curved or obtained a wavy form in contrast to their straight shape in the as-cast state. Mass spectrometry analysis of the main alloying elements (C, Mn, Ni, Cr, Mo, Cu, P, and S) revealed that carbon, manganese, and chromium were the most segregated alloying elements in A-type macrosegregation patterns. The observed differences were analyzed using thermodynamic calculations, which indicated that changes in the chemical composition of the liquid metal can affect the primary solidification mode and the segregation intensity of the alloying elements. Finite element modeling simulation results showed very good agreement with the experimental observations, thereby allowing for the quantification of the influence of temperature and deformation on the evolution of the shape of the macrosegregation channels during the open die forging process.

36 MATERIALS SCIENCE↗

Parallel Guanine Duplex and Cytosine Duplex DNA with Uninterrupted Spines of Ag I -Mediated Base Pairs

Here, hydrogen bonding between nucleobases produces diverse DNA structural motifs, including canonical duplexes, guanine (G) quadruplexes, and cytosine (C) i-motifs. Incorporating metal-mediated base pairs into nucleic acid structures can introduce new functionalities and enhanced stabilities. Here we demonstrate, using mass spectrometry (MS), ion mobility spectrometry (IMS), and fluorescence resonance energy transfer (FRET), that parallel-stranded structures consisting of up to 20 G–Ag I –G contiguous base pairs are formed when natural DNA sequences are mixed with silver cations in aqueous solution. FRET indicates that duplexes formed by poly(cytosine) strands with 20 contiguous C–Ag I –C base pairs are also parallel. Silver-mediated G-duplexes form preferentially over G-quadruplexes, and the ability of Ag + to convert G-quadruplexes into silver-paired duplexes may provide a new route to manipulating these biologically relevant structures. IMS indicates that G-duplexes are linear and more rigid than B-DNA. DFT calculations were used to propose structures compatible with the IMS experiments. Such inexpensive, defect-free, and soluble DNA-based nanowires open new directions in the design of novel metal-mediated DNA nanotechnology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Plant Diversity and Fertilizer Management Shape the Belowground Microbiome of Native Grass Bioenergy Feedstocks

Plants may actively cultivate microorganisms in their roots and rhizosphere that enhance their nutrition. To develop cropping strategies that substitute mineral fertilizers for beneficial root symbioses, we must first understand how microbial communities associated with plant roots differ among plant taxa and how they respond to fertilization. Arbuscular mycorrhizal (AM) fungi and rhizobacteria are of particular interest because they enhance nutrient availability to plants and perform a suite of nutrient cycling functions. The purpose of this experiment is to examine the root and soil microbiome in a longterm switchgrass ( Panicum virgatum ) biofuel feedstock experiment and determine how AM fungi and rhizobacteria respond to plant diversity and soil fertility. We hypothesize that intra- and interspecific plant diversity, nitrogen fertilization (+N), and their interaction will influence the biomass and community composition of AM fungi and rhizobacteria. We further hypothesize that +N will reduce the abundance of nitrogenase-encoding nifH genes on the rhizoplane. Roots and soils were sampled from three switchgrass cultivars (Cave-in-Rock, Kanlow, Southlow) grown in monoculture, intraspecific mixture, and interspecific planting mixtures with either Andropogon gerardii or diverse native tallgrass prairie species. Molecular sequencing was performed on root and soil samples, fatty acid extractions were assessed to determine microbial biomass, and quantitative polymerase chain reaction (qPCR) was performed on nifH genes from the rhizoplane. Sequence data determined core AM fungal and bacterial microbiomes and indicator taxa for plant diversity and +N treatments. We found that plant diversity and +N influenced AM fungal biomass and community structure. Across all plant diversity treatments, +N reduced the biomass of AM fungi and nifH gene abundance by more than 40%. The AM fungal genus Scutellospora was an indicator for +N, with relative abundance significantly greater under +N and in monoculture treatments. Community composition of rhizobacteria was influenced by plant diversity but not by +N. Verrucomicrobia and Proteobacteria were the dominant bacterial phyla in both roots and soils. Our findings provide evidence that soil fertility and plant diversity structure the root and soil microbiome. Optimization of soil communities for switchgrass production must take into account differences among cultivars and their unique responses to shifts in soil fertility.

59 BASIC BIOLOGICAL SCIENCES↗

Uranus occults SAO158687

Experience gained in obtaining atmospheric parameters, oblatenesses, and diameters of Jupiter and Mars from recent stellar occultations by these planets is used to predict what can be learned from the March 1977 occultation of the star SAO158687 by Uranus. The spectra of this star and Uranus are compared to indicate the relative instrument intensities of the two objects, the four passbands where the relative intensities are most nearly equal are listed, and expected photon fluxes from the star are computed on the assumption that it has UBVRI colors appropriate for a K5 main-sequence object. It is shown that low photon noise errors can be achieved by choosing appropriate passbands for observation, and the rms error expected for the Uranus temperature profiles obtained from the occultation light curves is calculated. It is suggested that observers of this occultation should record their data digitally for optimum time resolution.

Elliot, J. L.↗

Long Duration Exposure Facility (LDEF) low temperature Heat Pipe Experiment Package (HEPP) flight results

The Low Temperature Heat Pipe Flight Experiment (HEPP) is a fairly complicated thermal control experiment that was designed to evaluate the performance of two different low temperature ethane heat pipes and a low-temperature (182 K) phase change material. A total of 390 days of continuous operation with an axially grooved aluminum fixed conductance heat pipe and an axially grooved stainless steel heat pipe diode was demonstrated before the data acquisition system's batteries lost power. Each heat pipe had approximately 1 watt applied throughout this period. The HEPP was not able to cool below 188.6 K during the mission. As a result, the preprogrammed transport test sequence which initiates when the PCM temperature drops below 180 K was never exercised, and transport tests with both pipes and the diode reverse mode test could not be run in flight. Also, because the melt temperature of the n-heptane PCM is 182 K, its freeze/thaw behavior could not be tested. Post-flight thermal vacuum tests and thermal analyses have indicated that there was an apparent error in the original thermal analyses that led to this unfortunate result. Post-flight tests have demonstrated that the performance of both heat pipes and the PCM has not changed since being fabricated more than 14 years ago. A summary of HEPP's flight data and post-flight test results are presented.

Mcintosh, Roy↗

An application of miniscale experiments on Earth to refine microgravity analysis of adiabatic multiphase flow in space

Adiabatic two-phase flow is of interest to the design of multiphase fluid and thermal management systems for spacecraft. This paper presents original data and unifies existing data for capillary tubes as a step toward assessing existing multiphase flow analysis and engineering software. Comparisons of theory with these data once again confirm the broad accuracy of the theory. Due to the simplicity and low cost of the capillary tube experiments, which were performed on earth, we were able to closely examine for the first time a flow situation that had not previously been examined appreciably by aircraft tests. This is the situation of a slug flow at high quality, near transition to annular flow. Our comparison of software calculations with these data revealed overprediction of pipeline pressure drop by up to a factor of three. In turn, this finding motivated a reexamination of the existing theory, and then development of a new analytical and is in far better agreement with the data. This sequence of discovery illustrates the role of inexpensive miniscale modeling on earth to anticipate microgravity behavior in space and to complete and help define needs for aircraft tests.

Rothe, Paul H.↗

Computational Modeling of Cephalad Fluid Shift for Application to Microgravity-Induced Visual Impairment

An improved understanding of spaceflight-induced ocular pathology, including the loss of visual acuity, globe flattening, optic disk edema and distension of the optic nerve and optic nerve sheath, is of keen interest to space medicine. Cephalad fluid shift causes a profoundly altered distribution of fluid within the compartments of the head and body, and may indirectly generate phenomena that are biomechanically relevant to visual function, such as choroidal engorgement, compromised drainage of blood and cerebrospinal fluid (CSF), and altered translaminar pressure gradient posterior to the eye. The experimental body of evidence with respect to the consequences of fluid shift has not yet been able to provide a definitive picture of the sequence of events. On earth, elevated intracranial pressure (ICP) is associated with idiopathic intracranial hypertension (IIH), which can produce ocular pathologies that look similar to those seen in some astronauts returning from long-duration flight. However, the clinically observable features of the Visual Impairment and Intracranial Pressure (VIIP) syndrome in space and IIH on earth are not entirely consistent. Moreover, there are at present no experimental measurements of ICP in microgravity. By its very nature, physiological measurements in spaceflight are sparse, and the space environment does not lend itself to well-controlled experiments. In the absence of such data, numerical modeling can play a role in the investigation of biomechanical causal pathways that are suspected of involvement in VIIP. In this work, we describe the conceptual framework for modeling the altered compartmental fluid distribution that represents an equilibrium fluid distribution resulting from the loss of hydrostatic pressure gradient.

Nelson, Emily S.↗

Single-Molecule Electron Transport in Peptoids

Peptoids are structural analogs of peptides in which side chains are appended to the backbone nitrogen rather than the α-carbon. The sequence-defined modularity of peptoids enables precise control over structure−function relationships, enabling applications in energy storage and biomedical materials. Despite recent progress, the role of sequence and conformation on electron transport in peptoid molecules is not fully understood. Here, we synthesize a library of peptoid oligomers and characterize their molecular electronic properties using the scanning tunneling microscope-break junction (STM-BJ) technique. Our results show well-defined electron transport behavior for peptoid sequences containing aromatic side groups lacking hydrogen bonds (H-bonds) and without chemical substitutions at the N−C α position. This behavior fundamentally differs from electron transport in peptides, where H-bond interactions give rise to higher conductance states. All-atom molecular dynamics (MD) simulations are used to understand the conformational heterogeneity of peptoids, and molecular conformations obtained from MD simulations are used in quantum mechanical calculations based on the nonequilibrium Green’s function−density functional theory (NEGF-DFT) formalism. In all cases, computational results are in reasonable qualitative agreement with experiments. Our work demonstrates that the conductance behavior of peptoids depends on monomer identity, including side-chain aromaticity and substitution at the N−C α position. Overall, this work provides new insights into the structure−function relationships governing electron transport in peptoid-based materials and establishes design rules for peptoid-based molecular junctions.

Charge transport↗

Compact Peptoid Molecular Brushes for Nanoparticle Stabilization

Controlling the interfaces and interactions of colloidal nanoparticles (NPs) via tethered molecular moieties is crucial for NP applications in engineered nanomaterials, optics, catalysis, and nanomedicine. Despite a broad range of molecular types explored, there is a need for a flexible approach to rationally vary the chemistry and structure of these interfacial molecules for controlling NP stability in diverse environments, while maintaining a small size of the NP molecular shell. Here, we demonstrate that low-molecular-weight, bifunctional comb-shaped, and sequence-defined peptoids can effectively stabilize gold NPs (AuNPs). The generality of this robust functionalization strategy was also demonstrated by coating of silver, platinum, and iron oxide NPs with designed peptoids. Each peptoid (PE) is designed with varied arrangements of a multivalent AuNP-binding domain and a solvation domain consisting of oligo-ethylene glycol (EG) branches. Among designs, a peptoid (PE5) with a diblock structure is demonstrated to provide a superior nanocolloidal stability in diverse aqueous solutions while forming a compact shell (similar to 1.5 nm) on the AuNP surface. We demonstrate by experiments and molecular dynamics simulations that PE5-coated AuNPs (PE5/AuNPs) are stable in select organic solvents owing to the strong PE5 (amine)-Au binding and solubility of the oligo-EG motifs. At the vapor-aqueous interface, we show that PE5/AuNPs remain stable and can self-assemble into ordered 2D lattices. The NP films exhibit strong near-field plasmonic coupling when transferred to solid substrates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Exploring Water System Vulnerabilities in California's Central Valley Under the Late Renaissance Megadrought and Climate Change

Abstract California faces cycles of drought and flooding that are projected to intensify, but these extremes may impact water users across the state differently due to the region's natural hydroclimate variability and complex institutional framework governing water deliveries. To assess these risks, this study introduces a novel exploratory modeling framework informed by paleo and climate‐change based scenarios to better understand how impacts propagate through the Central Valley's complex water system. A stochastic weather generator, conditioned on tree‐ring data, produces a large ensemble of daily weather sequences conditioned on drought and flood conditions under the Late Renaissance Megadrought period (1550–1580 CE). Regional climate changes are applied to this weather data and drive hydrologic projections for the Sacramento, San Joaquin, and Tulare Basins. The resulting streamflow ensembles are used in an exploratory stress test using the California Food‐Energy‐Water System model, a highly resolved, daily model of water storage and conveyance throughout California's Central Valley. Results show that megadrought conditions lead to unprecedented reductions in inflows and storage at major California reservoirs. Both junior and senior water rights holders experience multi‐year periods of curtailed water deliveries and complete drawdowns of groundwater assets. When megadrought dynamics are combined with climate change, risks for unprecedented depletion of reservoir storage and sustained curtailment of water deliveries across multiple years increase. Asymmetries in risk emerge depending on water source, rights, and access to groundwater banks.

Gupta, Rohini S. [School of Civil and Environmenta↗

Molecular mechanisms and environmental adaptations of flagellar loss and biofilm growth of Rhodanobacter under environmental stress

Biofilms aid bacterial adhesion to surfaces via direct and indirect mechanisms, and formation of biofilms is considered as an important strategy for adaptation and survival in suboptimal environmental conditions. However, the molecular underpinnings of biofilm formation in subsurface sediment/groundwater ecosystems where microorganisms often experience fluctuations in nutrient input, pH, and nitrate or metal concentrations are underexplored. Here, we examined biofilm formation under different nutrient, pH, metal, and nitrate regimens of 16 Rhodanobacter strains isolated from subsurface groundwater wells spanning diverse levels of pH (3.5 to 5) and nitrates (13.7 to 146 mM). Eight Rhodanobacter strains demonstrated significant biofilm growth under low pH, suggesting adaptations for survival and growth at low pH. Biofilms were intensified under aluminum stress, particularly in strains possessing fewer genetic traits associated with biofilm formation, findings warranting further investigation. Through random barcode transposon-site sequencing (RB-TnSeq), proteomics, use of specific mutants, and transmission electron microscopy analysis, we discovered flagellar loss under aluminum stress, indicating a potential relationship between motility, metal tolerance, and biofilm growth. Comparative genomic analyses revealed the absence of flagella and chemotaxis genes and the presence of a putative type VI secretion system in the highly biofilm-forming strain FW021-MT20. In this study we identified genetic determinants associated with biofilm growth under metal stress in a predominant environmental genus, Rhodanobacter, and identified traits aiding survival and adaptation to contaminated subsurface environments.

59 BASIC BIOLOGICAL SCIENCES↗

Structural synthesis: Precursor and catalyst

More than twenty five years have elapsed since it was recognized that a rather general class of structural design optimization tasks could be properly posed as an inequality constrained minimization problem. It is suggested that, independent of primary discipline area, it will be useful to think about: (1) posing design problems in terms of an objective function and inequality constraints; (2) generating design oriented approximate analysis methods (giving special attention to behavior sensitivity analysis); (3) distinguishing between decisions that lead to an analysis model and those that lead to a design model; (4) finding ways to generate a sequence of approximate design optimization problems that capture the essential characteristics of the primary problem, while still having an explicit algebraic form that is matched to one or more of the established optimization algorithms; (5) examining the potential of optimum design sensitivity analysis to facilitate quantitative trade-off studies as well as participation in multilevel design activities. It should be kept in mind that multilevel methods are inherently well suited to a parallel mode of operation in computer terms or to a division of labor between task groups in organizational terms. Based on structural experience with multilevel methods general guidelines are suggested.

Schmit, L. A.↗

Creating Benchmark Data for Artificial Intelligence and Machine Learning Space Biology Research

To identify an appropriate AI/ML approach for a specific problem, the best practice is to measure algorithm performance through the benchmarking process. A scientific benchmark consists of an AI-ready dataset and a reference implementation on a specific scientific question. The NASA Science Mission Directorate (SMD) has started the “Benchmark Initiative for AI/ML to create scientific benchmark datasets in three applications: 1) scientific benchmarking, which finds the best algorithm for a specific problem; 2) application benchmarking, which measures algorithm performance against a set of parameters; and 3) system benchmarking, which evaluates performance of hardware and software architecture. Currently, there are no standardized datasets available to benchmark AI/ML algorithms in the domain of space biology. In this work, we constructed two AI/ML-ready biological datasets from experiments in space-flown mice: cellular imaging and RNA-seq. First, radiation-exposed immune cells harbor DNA damage foci that can be fluorescently marked to visualize the amount of damage following exposure to ionizing radiation. However, such large datasets are difficult to analyze visually, due to imaging inconsistencies and human bias, and classical image processing approaches can fail on imaging artifacts. AI/ML are therefore exciting alternative, providing the speed of machines and the accuracy of humans. We have made this dataset available at https://registry.opendata.aws/bps_microscopy/. Second, high-throughput nucleic acid sequencing (DNA-seq, RNA-seq) has become widespread in biomedical research due to the growing availability and affordability of these assays. However, most sequencing datasets suffer from high dimensionality and low sample count. In this work, we used a generative adversarial network to synthesize a standardized, AI-ready, publicly available benchmark dataset for space biology RNA-seq data with sufficient space-flown and ground control mouse liver samples from NASA GeneLab. This dataset is available at https://registry.opendata.aws/bps_rnaseq/. These datasets are now fully open the Space Biology community to test their favorite AI/ML approaches.

James Casaletto↗

System Deterioration Detection and Root Cause Learning on Time Series Graphs

System deterioration detection and root cause analysis is crucial for today's industrial society. However, the design and operation of mechanic system is getting more and more complex, which makes it hard at identifying deterioration with noisy data. Our research focus on solving such problem on time-evolving sensor graphs in a streaming setting. Given a sequence of graphs, the ability to identify 1) any gradual and stable structured change and 2) the root cause components is of importance for early warning and system diagnosis. Existing methods either raise too many false alerts on instant changes or are too sensitive to noise. To address these problems, we propose Robust Failure Detection and Diagnosis (RoFaD). RoFaD can capture failure propagation given a time series of graph. By optimizing a matrix based Taylor expansion, RoFaD can identify system deterioration in the presence of noise and immediate changes, and diagnose the root cause components. Experiments on both synthetic and real world datasets demonstrate that RoFaD is more effective than the popular baselines.

97 MATHEMATICS AND COMPUTING↗

Correlated High-Pressure Phase Sequence of VO 2 under Strong Compression

Understanding how the structures of a crystal behave under compression is a fundamental issue both for condensed matter physics and for geoscience. Traditional description of a crystal as the stacking of a unit cell with special symmetry has gained much success on the analysis of physical properties. Unfortunately, it is hard to reveal the relationship between the compressed phases. Taking the family of metal dioxides (MO 2 ) as an example, the structural evolution, subject to fixed chemical formula and highly confined space, often appears as a set of random and uncorrelated events. In this work, we provide an alternative way to treat the crystal as the stacking of the coordination polyhedron and then discover a unified structure transition pattern, in our case VO 2 . X-ray diffraction (XRD) experiments and first-principles calculations show that the coordination increase happens only at one apex of the V-centered octahedron in an orderly fashion, leaving the base plane and the other apex topologically intact. The polyhedron evolves toward increasing their sharing, indicating a general rule for the chemical bonds of MO 2 to give away the ionicity in exchange for covalency under pressure.

36 MATERIALS SCIENCE↗

Long-Term Warming in Alaska Enlarges the Diazotrophic Community in Deep Soils

Tundra ecosystems are typically carbon (C) rich but nitrogen (N) limited. Since biological N 2 fixation is the major source of biologically available N, the soil N 2 -fixing (i.e., diazotrophic) community serves as an essential N supplier to the tundra ecosystem. Recent climate warming has induced deeper permafrost thaw and adversely affected C sequestration, which is modulated by N availability. Therefore, it is crucial to examine the responses of diazotrophic communities to warming across the depths of tundra soils. Herein, we carried out one of the deepest sequencing efforts of nitrogenase gene ( nifH ) to investigate how 5 years of experimental winter warming affects Alaskan soil diazotrophic community composition and abundance spanning both the organic and mineral layers. Although soil depth had a stronger influence on diazotrophic community composition than warming, warming significantly ( P < 0.05) enhanced diazotrophic abundance by 86.3% and aboveground plant biomass by 25.2%. Diazotrophic composition in the middle and lower organic layers, detected by nifH sequencing and a microarray-based tool (GeoChip), was markedly altered, with an increase of α-diversity. Changes in diazotrophic abundance and composition significantly correlated with soil moisture, soil thaw duration, and plant biomass, as shown by structural equation modeling analyses. Therefore, more abundant diazotrophic communities induced by warming may potentially serve as an important mechanism for supplementing biologically available N in this tundra ecosystem. IMPORTANCE With the likelihood that changes in global climate will adversely affect the soil C reservoir in the northern circumpolar permafrost zone, an understanding of the potential role of diazotrophic communities in enhancing biological N 2 fixation, which constrains both plant production and microbial decomposition in tundra soils, is important in elucidating the responses of soil microbial communities to global climate change. A recent study showed that the composition of the diazotrophic community in a tundra soil exhibited no change under a short-term (1.5-year) winter warming experiment. However, it remains crucial to examine whether the lack of diazotrophic community responses to warming is persistent over a longer time period as a possibly important mechanism in stabilizing tundra soil C. Through a detailed characterization of the effects of winter warming on diazotrophic communities, we showed that a long-term (5-year) winter warming substantially enhanced diazotrophic abundance and altered community composition, though soil depth had a stronger influence on diazotrophic community composition than warming. These changes were best explained by changes in soil moisture, soil thaw duration, and plant biomass. These results provide crucial insights into the potential factors that may impact future C and N availability in tundra regions.

59 BASIC BIOLOGICAL SCIENCES↗

Machine Learning Reveals Missing Edges and Putative Interaction Mechanisms in Microbial Ecosystem Networks

Different organisms in a microbial community may drastically affect each other’s growth phenotypes, significantly affecting the community dynamics, with important implications for human and environmental health. Novel culturing methods and the decreasing costs of sequencing will gradually enable high-throughput measurements of pairwise interactions in systematic coculturing studies. However, a thorough characterization of all interactions that occur within a microbial community is greatly limited both by the combinatorial complexity of possible assortments and by the limited biological insight that interaction measurements typically provide without laborious specific follow-ups. Here, we show how a simple and flexible formal representation of microbial pairs can be used for the classification of interactions via machine learning. The approach we propose predicts with high accuracy the outcome of yet-to-be performed experiments and generates testable hypotheses about the mechanisms of specific interactions.

59 BASIC BIOLOGICAL SCIENCES↗

Kansas environmental and resource study: A Great Plains model

The author has identified the following significant results. Improvement in the land use classification accuracy of ERTS-1 MSS multi-images over Kansas can be made using two distances between neighboring grey tone N-tuples instead of one distance. Much more information is contained texturally than spectrally on the Kansas image. Ground truth measurements indicate that reflectance ratios of the 545 and 655 nm wavebands provide an index of plant development and possibly physiological stress. Preliminary analysis of MSS 4 and 5 channels substantiate the ground truth interpretation. Results of the land use mapping experiment indicate that ERTS-1 imagery has major potential in regionalization. The ways in which land is utilized within these regions may then be studied more effectively than if no adequate regionalization is available. A model for estimating wheat yield per acre has been applied to acreage estimates derived from ERTS-1 imagery to project the 1973 wheat yields for a ten county area in southwest Kansas. The results are within 3% of the preharvest estimates for the same area prepared by the USDA. Visual identification of winter wheat is readily achieved by using a temporal sequence of images. Identification can be improve by stratifying the project area into subregions having more or less homogeneous agricultural practices and crop mixes.

Haralick, R. M.↗