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NASA NTRS1979

Ancillary data acquisition for LACIE

The design, implementation, and operational functions of the three phases of LACIE supported the data needs of all other elements of the project and required several types of data in addition to LANDSAT multispectral digital data. The nonelectronic data base consisted of statistical data, printed reports, periodicals, ground observed data received from intensive test sites and operational segments, and full-frame multispectral scanner CIR photographs. The following data were collected for the test sites in the United States and Canada: land use inventories, periodic crop observations, solar radiometer measurements, rainfall, and wheat yield for selected fields.

Spiers, B. E.↗

NASA NTRS1994

Optimization of lamp spectrum for vegetable growth

An increase in the demand for and production of vegetables in the winter, mainly in northern and Siberian regions, inevitably leads to mass building of structures for growing plants under completely artificial conditions. An industrial lighting technology is required whose main parameters (spectrum, irradiance, photoperiod) should be assigned carefully and should uniquely determine, along with other important characteristics of the artificial climate, the productivity of the plant-production facility. The most widespread crops grown in our country under indoor conditions are cucumber and tomato plants, which account for more than 98% of the area in greenhouses. These plants are good prospects for growing completely under intense artificial lighting conditions (photocultures). Optimization of the main parameters of optical radiation when growing these plants is the most important task of achieving their profitable production. At present, considerable experience has been gained in studying the dependence of productivity of cucumber and tomato communities on irradiation conditions. Fundamental studies of the Agrophysical Research Institute of the Russian Academy of Sciences, Timiryazev Institute of Plant Physiology of the Russian Academy of Sciences, Timiryazev Agricultural Academy, and other institutes create a good basis for a detailed study of the given problem. Commercial sources of radiation substantially differing in spectral characteristics in the region of photosynthetically active radiation (PAR) were used in the studies.

Prikupets, L. B.↗

NASA NTRS1980

Use of Landsat data in soil and agricultural land use studies

This paper describes how the synoptic, multispectral, and temporal characteristics of Landsat can be used to locate Soil Association boundaries. Then, using these techniques we describe how a low intensity soil survey was conducted and how some interpretive maps were developed from this. Finally, we describe how soil suitability and land use interpretations were made to aid in defining Agrophysical units used in crop inventories.

Westin, F. C.↗

NASA NTRSDate not supplied

Demonstration of A Long Duration Crop in the Advanced Plant Habitat Engineering Demonstration Unit: Key Factors to Consider Prior to Testing and Lessons Learned

The Advanced Plant Habitat (APH) is a fully enclosed, closed-loop, plant growth facility currently deployed on the International Space Station (ISS). It is equipped with complete environmental control (i.e.spectral qualityandlight intensity, temperature, relative humidity, and CO2),root module which containsa growth substrate(typically arcillite) and a porous tube based automated water delivery system. Two APH units, one ground unitidentical to the on-orbit versionand an Engineering Development Unit (EDU; a high fidelity test version), currently reside at Kennedy Space Center. Prior to conducting tests on-orbit, these APH ground units areutilized to conductbothScience Verification Tests(SVT; primarilyinthe EDU) and Experiment Verification Tests (EVT; primarily in the Ground Unit). In February 2020, a 122 day experiment was concluded in the APH EDU where four 'Numex Española Improved' pepper plants (Capsicum annuum) were successfully grown from seed to harvestyieldingover 50 fruit, demonstrating the capabilityand versatilityof this APH EDU system to support plant growth for long life cycle flowering/fruiting plants.

L. E. Spencer↗

NASA NTRS2016

A Satellite Data-Driven, Client-Server Decision Support Application for Agricultural Water Resources Management

Water cycle extremes such as droughts and floods present a challenge for water managers and for policy makers responsible for the administration of water supplies in agricultural regions. In addition to the inherent uncertainties associated with forecasting extreme weather events, water planners need to anticipate water demands and water user behavior in a typical circumstances. This requires the use decision support systems capable of simulating agricultural water demand with the latest available data. Unfortunately, managers from local and regional agencies often use different datasets of variable quality, which complicates coordinated action. In previous work we have demonstrated novel methodologies to use satellite-based observational technologies, in conjunction with hydro-economic models and state of the art data assimilation methods, to enable robust regional assessment and prediction of drought impacts on agricultural production, water resources, and land allocation. These methods create an opportunity for new, cost-effective analysis tools to support policy and decision-making over large spatial extents. The methods can be driven with information from existing satellite-derived operational products, such as the Satellite Irrigation Management Support system (SIMS) operational over California, the Cropland Data Layer (CDL), and using a modified light-use efficiency algorithm to retrieve crop yield from the synergistic use of MODIS and Landsat imagery. Here we present an integration of this modeling framework in a client-server architecture based on the Hydra platform. Assimilation and processing of resource intensive remote sensing data, as well as hydrologic and other ancillary information occur on the server side. This information is processed and summarized as attributes in water demand nodes that are part of a vector description of the water distribution network. With this architecture, our decision support system becomes a light weight 'app' that connects to the server to retrieve the latest information regarding water demands, land use, yields and hydrologic information required to run different management scenarios. Furthermore, this architecture ensures all agencies and teams involved in water management use the same, up-to-date information in their simulations.

Agricultural↗

NASA NTRS2024

Plasma-Based Elemental Analyzer for Crewed Transit and Planetary Habitation

As NASA continues to perform research on the ISS and move towards the Moon and Mars, it is important for astronauts to have a technology capable of determining the composition of solid, liquid, and gas samples. Currently, samples are transported back to Earth for analysis, which may impact results due to the time delay of samples waiting to be returned to Earth as well as potential sample contamination from re-entry, change in environment, and various personnel handling. Therefore, researchers at the Applied Chemistry Lab at KSC have developed a proof-of-concept “Plasma-Based Elemental Analyzer,” which has the capability of testing solid, liquid, and gas samples for identification. Currently, the analysis is only qualitative, with quantitative identification left for future work. This technology is similar to ICP-OES, but differs in instrument size and sample preparation. Both technologies use plasma to ionize samples for light emission. The plasma elemental analyzer aims to be portable and lightweight, require only electrical power, and analyze solid, liquid, and gas samples. It does not use acid digestion or a nebulizer, requires less power than ICP-OES, and is able to operate with minimal to no usage of argon gas. Furthermore, the plasma elemental analyzer operates within low power constraints, which makes it feasible for usage on future missions with higher power constraints. The technology was tested at atmospheric pressure using mostly room air as the carrier gas for plasma production in the proof-of-concept study. The results showed the peak signals of the elements with an associated arbitrary signal intensity that allowed for qualitative identification. Solid samples that were tested included inedible biomass from the Golden Heirloom Cherry Tomato plant and Lunar Highlands Simulants (LHS-1). The liquid samples included elements of interest for the space crop production community. This work showed that a system smaller than the traditional ICP-OES equipment is able to be designed and implemented in future use cases, although it requires further development.

Kenneth Engeling↗

NASA NTRS1983

Early season spring small grains direct proportion estimation - Development and evaluation of a Landsat based methodology

The Inventory Technology Development (ITD) project of the Agriculture and Resources Inventory Surveys Through Aerospace Remote Sensing (AgRISTARS) program has developed an accurate, automated technology for early season estimation of spring small grains areal proportion from Landsat MSS data. The design criteria for an early season procedure included estimates available within the first 30 days of the growing season, low data processing/preprocessing requirements and no need for scene-to-scene registration. The prototype estimator which meets the design goals is based on a constrained linear model in which the observed spectral response of an entire scene is modeled as a linear combination of the major constituent elements in the scene. The procedure was evaluated over 100 sample segments collected for crop years 1976 through 1979 in the U.S. Northern Great Plains. Analysis of the test results indicated accuracy that compare favorably with both the automated at-harvest technologies tested during the FY81-82 AgRISTARS Spring Small Grains Pilot experiments and earlier analyst-intensive at-harvest technologies.

Phinney, D. E.↗

NASA NTRS1999

Growing wheat in Biosphere 2 under elevated CO2: observations and modeling

Spring wheat (Triticum aestivum L., cv. Yecora Rojo) was grown in the intensive agricultural biome (IAB) of Biosphere 2 during the l995-l996 winter/spring season. Environmental conditions were characterized by a day/night temperature regime of 27/17 degrees C, relative humidity (RH) levels around 45%, mean atmospheric CO2 concentration of 450 ppmv, and natural light conditions with mean intensities about half of outside levels. Weekly samples of above-ground plant matter were collected throughout the growing season and phenological events recorded. A computer model, CERES-Wheat, previously tested under both field and controlled conditions, was used to simulate the observed crop growth and to help in data analysis. We found that CERES-Wheat simulated the data collected at Biosphere 2 to within 10% of observed, thus suggesting that wheat growth inside the IAB was comparable to that documented in other environments. The model predicts phenological stages and final dry matter (DM) production within l0% of the observed data. Measured DM production rates, normalized for light absorbed by the crop. suggested photosynthetic efficiencies intermediate between those observed under optimal field conditions and those recorded in NASA-Controlled Ecological Life-Support Systems (CELSS). We suggest that such a difference can be explained primarily in terms of low light levels inside the IAB, with additional effects due to elevated CO2 concentrations and diffuse light fractions.

Non-NASA Center↗

NASA NTRS1974

The economic value of remote sensing of earth resources from space: An ERTS overview and the value of continuity of service. Volume 3: Intensive use of living resources: Agriculture. Part 1: Overview

Potential economic benefits obtainable from a state-of-the-art ERS system in the resource area of intensive use of living resources, agriculture, are studied. A spectrum of equal capability (cost saving), increased capability, and new capability benefits are quantified. These benefits are estimated via ECON developed models of the agricultural marketplace and include benefits of improved production and distribution of agricultural crops. It is shown that increased capability benefits and new capability benefits result from a reduction of losses due to disease and insect infestation given ERS's capability to distinguish crop vigor and from the improvement in world trade negotiations given ERS's worldwide surveying capability.

Kornhauser, A. L.↗

NASA NTRS1976

Precision processing of earth image data

Precise corrections of Landsat data are useful for generating land-use maps, detecting various crops and determining their acreage, and detecting changes. The paper discusses computer processing and visualization techniques for Landsat data so that users can get more information from the imagery. The elementary unit of data in each band of each scene is the integrated value of intensity of reflected light detected in the field of view by each sensor. To develop the basic mathematical approach for precision correction of the data, differences between positions of ground control points on the reference map and the observed control points in the scene are used to evaluate the coefficients of cubic time functions of roll, pitch, and yaw, and a linear time function of altitude deviation from normal height above local earth's surface. The resultant equation, termed a mapping function, corrects the warped data image into one that approximates the reference map. Applications are discussed relative to shade prints, extraction of road features, and atlas of cities.

Bernstein, R.↗

NASA NTRS2007

Remote Sensing of Parasitic Nematodes in Plants

A method and apparatus for remote sensing of parasitic nematodes in plants, now undergoing development, is based on measurement of visible and infrared spectral reflectances of fields where the plants are growing. Initial development efforts have been concentrated on detecting reniform nematodes (Rotylenchulus reniformis) in cotton plants, because of the economic importance of cotton crops. The apparatus includes a hand-held spectroradiometer. The readings taken by the radiometer are processed to extract spectral reflectances at sixteen wavelengths between 451 and 949 nm that, taken together, have been found to be indicative of the presence of Rotylenchulus reniformis. The intensities of the spectral reflectances are used to estimate the population density of the nematodes in an area from which readings were taken.

Lawrence, Gary W.↗

NASA NTRS2009

Monitoring Phenology as Indicator for Timing of Nutrient Inputs in Northern Gulf Watersheds

Nutrient over-enrichment defined by the U.S. Environmental Protection Agency as the anthropogenic addition of nutrients, in addition to any natural processes, causing adverse effects or impairments to the beneficial uses of a water body has been identified as one of the most significant environmental problems facing sensitive estuaries and coastal waters. Understanding the timing of nutrient inputs into those waters through remote sensing observables helps define monitoring and mitigation strategies. Remotely sensed data products can trace both forcings and effects of the nutrient system from landscape to estuary. This project is focused on extracting nutrient information from the landscape. The timing of nutrients entering coastal waters from the land boundary is greatly influenced by hydrologic processes, but can also be affected by the timing of nutrient additions across the landscape through natural or anthropogenic means. Non-point source nutrient additions to watersheds are often associated with specific seasonal cycles, such as decomposition of organic materials in fall and winter or addition of fertilizers to crop lands in the spring. These seasonal cycles or phenology may in turn be observed through the use of satellite sensors. Characterization of the phenology of various land cover types may be of particular interest in Gulf of Mexico estuarine systems with relatively short pathways between intensively managed systems and the land/estuarine boundary. The objective of this study is to demonstrate the capability of monitoring phenology of specific classes of land, such as agriculture and managed timberlands, at a refined watershed level. The extraction of phenological information from the Moderate Resolution Imaging Spectroradiometer (MODIS) data record is accomplished using analytical tools developed for NASA at Stennis Space Center: the Time Series Product Tool and the Phenological Parameters Estimation Tool. MODIS reflectance data (product MOD09) were used to compute the Normalized Difference Vegetation Index, which is sensitive to changes in vegetation canopies. The project team is working directly with the Mississippi Department of Environmental Quality to understand end-user requirements for this type of information product. Initial focus areas are identification of time frames for pre-plant fertilizer applications (prior to start of season), side-dress fertilizer applications (during rapid green-up), and periods of plant decomposition (during and after senescence). Prototypical maps of phenological stages related to these time frames have been generated for watersheds in the northern Gulf of Mexico. Where feasible, these maps have been compared to existing in situ nutrient monitoring data, but the in situ data is temporally sparse (monthly frequency or less), which makes interpretation challenging. Future work will include integrating effects of rainfall and seeking couplings with estuarine remote sensing.

Ross, Kenton W.↗

NASA NTRS2015

Introduction The Role of the Agricultural Model Intercomparison and Improvement Project

Climate impacts on agriculture are of increasing concern in both the scientific and policy communities because of the need to ensure food security for a growing population. A special challenge is posed by the changes in the frequency and intensity of heat-waves, droughts, and episodic rainstorms already underway in many parts of the world. Changes in production are directly linked to such variations in temperature and precipitation during the growing season, and often to offseason changes in weather affecting soil-water storage and availability to crops. This is not an isolated problem but one of both global and regional importance, because of impacts on the livelihoods of smallholder farmers as well as consequences for the world food trade system. This two-part set the Agricultural Model Intercomparison and Improvement Project (AgMIP): Integrated Crop and Economic Assessments is the first to be entirely devoted to AgMIP (www.agmip.org). AgMIP is a major international research program focused on climate change and agriculture. The goal of the two parts is to advance the field by providing detailed information on new simulation techniques and assessments being conducted by this program. It presents information about new methods of global and regional integrated assessment, results from agricultural regions, and adaptation strategies for maintaining food security under changing climate conditions.

security↗

NASA NTRS1990

Ground and aircraft infrared observations over a partially-vegetated area

Consideration is given to the feasibility of estimated a reliable composite surface temperature over a partially-vegetated and furrowed cotton field with an intensive ground sampling routing using hand-held radiometers. The ground-based data are compared with surface temperatures taken from an aircraft at an altitude of about 150 m. A simple model is presented for computing the composite surface temperature using component temperatures of the soil and vegetation and row crop dimensions and orientations. The results of the modeling are compared with the ground-based and airborne radiometric measurements. It is found that estimates of the composite surface temperature comparable to low-flying aircraft observations over row crops with sparse cover may be obtained using ground-based estimates of average canopy temperature.

Kustas, W. P.↗

NASA NTRS2018

Identifying the Community Structure of the Food-Trade International Multi-Network

Achieving international food security requires improved understanding of how international trade networks connect countries around the world through the import-export flows of food commodities. The properties of international food trade networks are still poorly documented, especially from a multi-network perspective. In particular, nothing is known about the multi-network's community structure. Here we find that the individual crop-specific layers of the multi-network have densely connected trading groups, a consistent characteristic over the period 2001-2011. Further, the multi-network is characterized by low variability over this period but with substantial heterogeneity across layers in each year. In particular, the layers are mostly assortative: more-intensively connected countries tend to import from and export to countries that are themselves more connected. We also fit econometric models to identify social, economic and geographic factors explaining the probability that any two countries are co-present in the same community. Our estimates indicate that the probability of country pairs belonging to the same food trade community depends more on geopolitical and economic factors-such as geographical proximity and trade-agreement co-membership-than on country economic size and/or income. These community-structure findings of the multi-network are especially valuable for efforts to understand past and emerging dynamics in the global food system, especially those that examine potential 'shocks' to global food trade.

complex networks↗

NASA NTRS2013

The Effect of Agricultural Growing Season Change on Market Prices in Africa

Local agricultural production is a key element of food security in many agricultural countries in Africa. Climate change and variability is likely to adversely affect these countries, particularly as they affect the ability of smallholder farmers to raise enough food to feed themselves. Seasonality influences farmers' decisions about when to sow and harvest, and ultimately the success or failure of their crops. At a 2009 conference in the United Kingdom hosted by the Institute of Development Studies, Jennings and Magrath (2009) described farmer reports from East Asia, South Asia, Southern Africa, East Africa and Latin America. Farmers indicate significant changes in the timing of rainy seasons and the pattern of rains within seasons, including: More erratic rainfall, coming at unexpected times in and out of season; Extreme storms and unusually intense rainfall are punctuated by longer dry spells within the rainy season; Increasing uncertainty as to the start of rainy seasons in many areas; Short or transitional second rainy seasons are becoming stronger than normal or are disappearing altogether. These farmer perceptions of change are striking in that they are geographically widespread and are remarkably consistent across diverse regions (Jennings and Magrath, 2009). The impact of these changes on farmers with small plots and few resources is large. Farming is becoming riskier because of heat stress, lack of water, pests and diseases that interact with ongoing pressures on natural resources. Lack of predictability in the start and length of the growing season affects the ability of farmers to invest in appropriate fertilizer levels or improved, high yielding varieties. These changes occur at the same time as the demand for food is rising and is projected to continue to rise for the next fifty years (IAASTD, 2008). Long-term data records derived from satellite remote sensing can be used to verify these reports, providing necessary analysis and documentation required to plan effective adaptation strategies. Remote sensing data can also provide some understanding of the spatial extent of these changes and whether they are likely to continue. Given the agricultural nature of most economies on the African continent, agricultural production continues to be a critical determinant of both food security and economic growth (Funk and Brown, 2009). Crop phenological parameters, such as the start and end of the growing season, the total length of the growing season, and the rate of greening and senescence are important for planning crop management, crop diversification, and intensification. The World Food Summit of 1996 defined food security as: "when all people at all times have access to sufficient, safe, nutritious food to maintain a healthy and active life". Food security roughly depends on three factors: 1) availability of food; 2) access to food and 3) appropriate use of food, as well as adequate water and sanitation. The first factor is dependent on growing conditions and weather and climate. In a previous paper we have investigated this factor by evaluating the effect of large scale climate oscillation on land surface phenology (Brown et al., 2010). We found that all areas in Africa are significantly affected by at least one type of large scale climate oscillations and concluded that these somewhat predictable oscillations could perhaps be used to forecast agricultural production. In addition, we have evaluated changes in agricultural land surface phenology over time (Brown et al., 2012). We found that land surface phenology models, which link large-scale vegetation indices with accumulated humidity, could successfully predict agricultural productivity in several countries around the world. In this chapter we are interested in the effect of variability in peak timing of the growing season, or phenology, on the second factor of food security, food access. In this chapter we want to determine if there is a link between market prices and land surface phenology and to determine which markets are vulnerable to land surface phenology changes and variability and which market prices are not correlated.

Prices↗

NASA NTRS2019

Dwarf Tomato and Pepper Cultivars for Space Crops

Several dwarf tomato and pepper varieties were evaluated under ISS-simulated growth conditions (22ºC, 50% RH, 1500 ppm CO2, and 300 μmol m(exp -2) s(exp -1) of light for 16 h per day) with the goal of selecting those with the best growth, nutrition, and organoleptic potential for use in a pick and eat salad crop system on ISS and future exploration flights. Testing included six cultivars of tomato (Red Robin, Scarlet Sweet ’N’ Neat, Tiny Tim, Mohamed, Patio Princess, and Tumbler) and six cultivars of pepper (Red Skin, Fruit Basket, Cajun Belle, Chablis, Sweet Pickle, and Pompeii). Plants were grown to an age sufficient to produce fruit (70 to 106 days for tomato and 109 days for pepper). Tomato fruits were harvested when they showed full red color, beginning ca. 70-days age and then at weekly intervals thereafter, while peppers were grown until numerous fruits showed color and all fruits (green and colored) were harvested once at the end of the test. Plant sizes, yields, and nutritional attributes were measured and used to down-select to three cultivars for each species. In particular, we were interested in cultivars that were short (dwarf) but still produced high yields. Nutritional data included elemental (Ca, Mg, Fe, and K) composition, vitamin K, phenolics, lycopene, anthocyanin, lutein, and zeaxanthin. The three down-selected cultivars for each species were evaluated for sensory attributes, including overall acceptability, appearance, color intensity aroma, flavor and texture. The combined data were compared and given weighting factors to rank the cultivars as potential candidates for testing in space. For tomato, the ranking was 1) cv. Mohamed, 2) cv. Red Robin, and 3) cv. Sweet N’ Neat. For pepper, the ranking was 1) cv. Pompeii, 2) cv. Red Skin, and 3) cv. Fruit Basket. These rankings are somewhat subjective but provide a good starting point for conducting higher fidelity testing with these crops (e.g., testing with LED lighting similar to the Veggie plant unit), and ultimately conducting flight experiments.

Spencer, LaShelle E.↗

NASA NTRS2002

Solid state 31phosphorus nuclear magnetic resonance of iron-, manganese-, and copper-containing synthetic hydroxyapatites

The incorporation of micronutrients into synthetic hydroxyapatite (SHA) is proposed for slow release of these nutrients to crops in the National Aeronautics and Space Administration's (NASA's) Advanced Life Support (ALS) program for Lunar or Martian outposts. Solid state 31P nuclear magnetic resonance (NMR) was utilized to examine the paramagnetic effects of Fe3+, Mn2+, and Cu2+ to determine if they were incorporated into the SHA structure. Separate Fe3+, Mn2+, and Cu2+ containing SHA materials along with a transition metal free SHA (pure-SHA) were synthesized using a precipitation method. The proximity (<1 nm) of the transition metals to the 31P nuclei of SHA were apparent when comparing the integrated 31P signal intensities of the pure-SHA (87 arbitrary units g-1) with the Fe-, Mn-, and Cu-SHA materials (37-71 arbitrary units g-1). The lower integrated 31P signal intensities of the Fe-, Mn-, and Cu-SHA materials relative to the pure-SHA suggested that Fe3+, Mn2+, and Cu2+ were incorporated in the SHA structure. Further support for Fe3+, Mn2+, and Cu2+ incorporation was demonstrated by the reduced spin-lattice relaxation constants of the Fe-, Mn-, and Cu-SHA materials (T'=0.075-0.434s) relative to pure-SHA (T1=58.4s). Inversion recovery spectra indicated that Fe3+, Mn2+, and Cu2+ were not homogeneously distributed about the 31P nuclei in the SHA structure. Extraction with diethylene-triamine-penta-acetic acid (DTPA) suggested that between 50 and 80% of the total starting metal concentrations were incorporated in the SHA structure. Iron-, Mn-, and Cu-containing SHA are potential slow release sources of Fe, Mn, and Cu in the ALS cropping system.

NASA Discipline Life Support Systems↗