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NASA NTRS2010

Agricultural Productivity Forecasts for Improved Drought Monitoring

Water stresses on agricultural crops during critical phases of crop phenology (such as grain filling) has higher impact on the eventual yield than at other times of crop growth. Therefore farmers are more concerned about water stresses in the context of crop phenology than the meteorological droughts. However the drought estimates currently produced do not account for the crop phenology. US Department of Agriculture (USDA) and National Oceanic and Atmospheric Administration (NOAA) have developed a drought monitoring decision support tool: The U.S. Drought Monitor, which currently uses meteorological droughts to delineate and categorize drought severity. Output from the Drought Monitor is used by the States to make disaster declarations. More importantly, USDA uses the Drought Monitor to make estimates of crop yield to help the commodities market. Accurate estimation of corn yield is especially critical given the recent trend towards diversion of corn to produce ethanol. Ethanol is fast becoming a standard 10% ethanol additive to petroleum products, the largest traded commodity. Thus the impact of large-scale drought will have dramatic impact on the petroleum prices as well as on food prices. USDA's World Agricultural Outlook Board (WAOB) serves as a focal point for economic intelligence and the commodity outlook for U.S. WAOB depends on Drought Monitor and has emphatically stated that accurate and timely data are needed in operational agrometeorological services to generate reliable projections for agricultural decision makers. Thus, improvements in the prediction of drought will reflect in early and accurate assessment of crop yields, which in turn will improve commodity projections. We have developed a drought assessment tool, which accounts for the water stress in the context of crop phenology. The crop modeling component is done using various crop modules within Decision Support System for Agrotechnology Transfer (DSSAT). DSSAT is an agricultural crop simulation system, which integrates the effects of soil, crop phenotype, weather, and management options. It has been in use for more than 15 years by researchers, growers and has become a de-facto standard in crop modeling communities spanning over 100 countries. The meteorological forcings to DSSAT are provided by NASA s National Land Data Assimilation System (NLDAS) datasets. NLDAS is a framework that incorporates atmospheric forcing and land parameter values along with land surface models to diagnose and predict the state of the land surface.

Limaye, Ashutosh↗
NASA NTRS2026

LAI Assimilation Schedules to Constrain Uncertain Cultivars and Soils in CERES-Maize

In anticipation of large-domain crop model applications where precise local configuration and calibration is not possible, we describe benefits and potential drawbacks of employing a crop pest module to achieve leaf area index (LAI) assimilation into a high performing CERES-Maize crop model configuration at a field experiment site in Perry, Iowa. Simulation experiments explore the use of MODIS satellite-derived LAI to constrain and adjust LAI to counter imprecise cultivar and soil configurations often occurring in the absence of high-quality local information. Simulations using single-day, window, and continuous LAI replacement across 5 cultivars and 2 soil calibration approaches for nine corn rotation years from 2004 to 2020 led to different yield outcomes and reverberations throughout the field environment. Evaluating variance and mean bias, results indicate minimal interventions in early vegetative and grain-filling stages were more beneficial than use of continuous LAI adjustments, as they minimized disruptions to the internal resource balances governing plant stresses and grain production. LAI adjustment was particularly helpful in constraining growth related to uncertain thermal unit requirements and leaf tip appearance rates (P1 and PHINT cultivar parameters, respectively). Findings underscore the need to assimilate additional state variables to ensure internal biophysical coherence. This approach shows promise for applications spanning wider domains with prediction time pressure where detailed configuration, more complex assimilation methods, or recalibration of crop model parameters may not be practical.

Phenology↗
NASA NTRS2015

The 2010 Russian Drought Impact on Satellite Measurements of Solar-Induced Chlorophyll Fluorescence: Insights from Modeling and Comparisons with the Normalized Differential Vegetation Index (NDVI)

We examine satellite-based measurements of chlorophyll solar-induced fluorescence (SIF) over the region impacted by the Russian drought and heat wave of 2010. Like the popular Normalized Difference Vegetation Index (NDVI) that has been used for decades to measure photosynthetic capacity, SIF measurements are sensitive to the fraction of absorbed photosynthetically-active radiation (fPAR). However, in addition, SIF is sensitive to the fluorescence yield that is related to the photosynthetic yield. Both SIF and NDVI from satellite data show drought-related declines early in the growing season in 2010 as compared to other years between 2007 and 2013 for areas dominated by crops and grasslands. This suggests an early manifestation of the dry conditions on fPAR. We also simulated SIF using a global land surface model driven by observation-based meteorological fields. The model provides a reasonable simulation of the drought and heat impacts on SIF in terms of the timing and spatial extents of anomalies, but there are some differences between modeled and observed SIF. The model may potentially be improved through data assimilation or parameter estimation using satellite observations of SIF (as well as NDVI). The model simulations also offer the opportunity to examine separately the different components of the SIF signal and relationships with Gross Primary Productivity (GPP).

vegetation↗
NASA NTRSDate not supplied

Verification Testing and Veg-05 Tomato Crop Production on the International Space Station

Production of fresh, nutritious, and tasty produce for astronauts during spaceflight may provide health-promoting, bioavailable nutrients and enhance the dietary experience as we move into longer-duration missions. Growing and caring for plants may also reduce the psychological stresses associated with spaceflight and enhance connections to Earth. Requirements to consistently grow a diversity of crops under spaceflight environmental conditions remain poorly defined. The VEG-05 experiment is part of a series of experiments with pick-and-eat salad crops to better define best practices for crop production and handling in space. VEG-05 and predecessor experiments VEG-04A and VEG-04B, use the Veggie vegetable production facilities on the International Space Station to grow salad crops under different spectral compositions. In VEG-04A and B, mizuna mustard was cultivated with two different red: blue light treatments, and in VEG-05 we are cultivating ‘Red Robin’ dwarf cherry tomatoes under the same light spectra. Light can impact the growth habit, yield, nutritional composition, microbial levels, and even flavor attributes within crops, and our team will assess these characteristics for this crop during VEG-05. Prior to launch and installation on ISS in late 2022, both a science verification test (SVT), and an experiment verification test (EVT) were conducted at Kennedy Space Center in ISS Environment Simulator Chambers. Science verification testing, and a previous fertilizer test, grew plants in both plant pillows and PONDS (Passive Orbital Nutrient Delivery System) units and tested two different fertilizer treatments in both sets of hardware, with each test under only one of the light conditions. Because of challenges validating the PONDS hardware on ISS, and with good crop production in plant pillows, the EVT moved forward using only plant pillows with the highest fertilizer composition tested during SVT, and two Veggie units were utilized. One Veggie had light settings consisting of equal levels of red: blue light (150 µmol/m2/s for each color) plus green light (30 µmol/m2/s) while the second Veggie had a 90:10 ratio of red: blue light (270 µmol/m2/s red and 30 µmol/m2/s blue) plus green, so each unit provided 330 µmol/m2/s of photosynthetically active radiation to the tomato crops on average. Our original plan, based on prior ground testing, was to grow the crop for 104 days and harvest at 80, 90 and 104 days after initiation. For SVT, under the equal red: blue light treatment, fruit ripening in plant pillows was delayed and fruit were not ripe by day 80, so actual harvest days were days 90, 97, and 104. For EVT we saw fruit ripening earlier, especially in the high red treatment, and so we harvested at days 83, 90, and 99 days after initiation. In SVT we had mostly daily watering, and this led to excess water in plant pillows, which leaked out. This excess water also caused fungus to grow on one leaf and a couple of plant stems. To reduce this excess moisture, we throttled back the watering for EVT, and used the root mat reservoir more frequently. This led to watering only every other day, reducing crew time needed for plant care, however, two wilting events occurred during this EVT, at days 51 and 75. Plants recovered from these wilting events, but these events may have influenced the rate of fruit ripening and flower formation. Regardless, more than 10 fruit were produced from each plant on average, with the high red treatment producing slightly heavier fruit. Microbial testing from fruit during SVT indicated that fruit were safe for consumption with microbial levels below detection limits. VEG-05 flight and ground operations are expected to run between December 2022 and March 2023. This research was co-funded by the Human Research Program and Space Biology (MTL#1075) in the ILSRA 2015 NRA call.

Gioia D. Massa↗
NASA NTRS2019

Dwarf Tomato and Dwarf Pepper as Potential Space Crops

Crops for space life support systems and in particular, early supplemental food production systems must be able to fit into the confined volume of space craft or space habitats. For example, spaceflight plant chambers such as Svet, Lada, Astroculture, BPS, and Veggie provided approximately 15-40 cm of growing height for plant shoots. Six cultivars each of tomato and pepper were selected for initial study based on their advertised dwarf growth and high yields. Plants were grown in 10-cm pots with solid potting medium and controlled-release fertilizer to simulate the rooting constraints that might be faced in space environments. Lighting was provided by fluorescent lamps (~300 umol m(exp -1) s(exp -1) and a 16 h light / 8 h dark photoperiod. Cultivars were then down selected to three each for pepper (cvs. Red Skin, Pompeii, and Fruit Basket) and tomato (cvs. Red Robin, Mohamed, and Sweet n' Neat). In all cases (pepper and tomato), the plants grew to an approximate height of 20 cm and produced between 200 and 300 g fruit fresh mass per plant. In previous hydroponic studies with unrestricted root growth, Fruit Basket pepper and Red Robin tomato produced much larger plants with taller shoots. The findings suggest that high value, nutritious crops like tomato and pepper could be grown within small volumes of space habitats, but horticultural issues, such as rooting volume could be important in controlling plant size.

Life Support↗
NASA NTRS1973

A scheme for the uniform mapping and monitoring of earth resources and environmental complexes using ERTS-1 imagery

There are no author-identified significant results in this report. Progress on plans for the development and testing of a practical procedure and system for the uniform mapping and monitoring of natural ecosystems and environmental complexes from space-acquired imagery is discussed. With primary emphasis on ERTS-1 imagery, but supported by appropriate aircraft photography as necessary, the objectives are to accomplish the following: (1) Develop and test in a few selected sites and areas of the western United States a standard format for an ecological and land use legend for making natural resource inventories on a simulated global basis. (2) Based on these same limited geographic areas, identify the potentialities and limitations of the legend concept for the recognition and annotation of ecological analogs and environmental complexes. An additional objective is to determine the optimum combination of space photography, aerial photography, ground data, human data analysis, and automatic data analysis for estimating crop yield in the rice growing areas of California and Louisiana.

Poulton, C. E.↗
NASA NTRSDate not supplied

Regional and Model-Specific Response Types in A Global Gridded Crop Model Ensemble

Crop models are often employed to project crop yields under changing conditions such as global warming and associated management change for adaptation. Multi-model ensembles are promoted to enhance the robustness of projections, but questions remain on what causes often large differences between projections of individual models. Global Gridded Crop Models (GGCMs) are especially exposed to this question when applied for assessing climate change impacts, adaptation, environmental impacts of agricultural production, because their results are used in downstream analyses, such as in integrated assessment or economic modeling for projecting future land-use change. Even though global gridded crop models are often based on detailed field-scale models or have implemented similar modeling principles in other ecosystem models, global-scale models are subject to substantial uncertainties from both model structure and parametrization as well as from calibration and input data quality. AgMIP’s Global Gridded Crop Model Intercomparison (GGCMI) has thus set out to intercompare GGCMs in order to evaluate model performance, describe model uncertainties, identify inconsistencies within the ensemble and underlying reasons, and to ultimately improve models and modeling capacities. In phase 2 of the GGCMI activities, 12 modeling groups followed a modeling protocol that asked for up to 1404 31-year global simulations at 0.5 arc-degree spatial resolution to assess models’ sensitivities to changes in carbon dioxide (C; 4 different levels) temperature (T; 7 different offset levels), water supply (W; 9 levels), and nitrogen (N; 3 levels), the so-called CTWN experiment (Franke et al. 2020; http://dx.doi.org/10.5194/gmd-13-2315-2020). We here present analyses of model response types using impact response surfaces along the C, T, W, and N dimensions, respectively and collectively. Doing so, we can understand differences in simulated responses per driver rather than aggregated changes in yields. We find that models’ sensitivities to the individual driver dimensions are substantially different and often more different across models than across regions. A cluster analysis finds regional and model-specific patterns. There is some agreement across models with respect to the spatial patterns of response types but strong differences in the distribution of response type clusters across models suggests that models need to undergo further scrutiny. We suggest establishing standards in model process evaluation not only against historical dynamics but also against dedicated experiments across the CTWN dimensions.

crop models↗
NASA NTRS1980

AgRISTARS: Foreign commodity production forecasting. Minutes of the annual formal project manager's review, including preliminary technical review reports of FY80 experiments

The U.S./Canada wheat/barley exploratory experiment is discussed with emphasis on labeling, machine processing using P1A, and the crop calendar. Classification and the simulated aggregation test used in the U.S. corn/soybean exploratory experiment are also considered. Topics covered regarding the foreign commodity production forecasting project include: (1) the acquisition, handling, and processing of both U.S. and foreign agricultural data, as well as meteorological data. The accuracy assessment methodology, multicrop sampling and aggregation technology development, frame development, the yield project interface, and classification for area estimation are also examined.

Source record↗
NASA NTRS2021

Sustainable Use of Groundwater May Dramatically Reduce Irrigated Production of Maize, Soybean, and Wheat

Groundwater extraction in the United States (US) is unsustainable, making it essential to understand the impacts of limited water use on irrigated agriculture. To improve this understanding, we integrated a gridded crop model with satellite observations, recharge estimates, and water survey data to assess the effects of sustainable groundwater withdrawals on US irrigated agricultural production. The gridded crop model agrees with satellite-based estimates of evapotranspiration (R2 = 0.68), as well as survey data from the United States Department of Agriculture (R2 = 0.82–0.94 for county-level production and 0.37–0.54 for county-level yield). Using the optimistic assumption that groundwater extraction equals effective aquifer recharge rate, we find that sustainable groundwater use decreases US irrigated production of maize, soybean, and winter wheat by 20%, 6%, and 25%, respectively. Using a more conservative assumption of groundwater availability, US irrigated production of maize, soybean, and winter wheat decreases by 45%, 37%, and 36%, respectively. The wide range of simulated losses is driven by considerable uncertainty in surface water and groundwater interactions, as well as accounting for the many aspects of sustainability. Our results demonstrate the vulnerability of US irrigated agriculture to unsustainable groundwater pumping, highlighting the difficulty of expanding or even maintaining irrigated food production in the face of climate change, population growth, and shifting dietary demands. These findings are based on reducing pumping by fallowing irrigated farmland; however, alternate pumping reduction strategies or technological advances in crop genetics and irrigation could produce different results.

sustainability↗
NASA NTRS1979

Landsat-simulating radiometer for agricultural remote sensing

The reliability of a Landsat-simulating ground-based spectral radiometer for use in agricultural remote sensing was investigated. Significant correlation coefficients in all wavebands except Band 7 were found to exist between Landsat computer compatible tape (CCT) and ground-based radiometric data from several corn fields. No significant correlations were found within data from small grain fields. Combined data from several common agricultural crops yielded significant correlation coefficients in the wavebands most commonly employed in agricultural remote sensing. It was also found that sun angle within certain limits of a given day had minimal effect on ground-based radiometric measurements taken from a fallow and barley field.

Lemme, G. D.↗
NASA NTRS2013

Projected Climate Impacts to South African Maize and Wheat Production in 2055: A Comparison of Empirical and Mechanistic Modeling Approaches

Crop model-specific biases are a key uncertainty affecting our understanding of climate change impacts to agriculture. There is increasing research focus on intermodel variation, but comparisons between mechanistic (MMs) and empirical models (EMs) are rare despite both being used widely in this field. We combined MMs and EMs to project future (2055) changes in the potential distribution (suitability) and productivity of maize and spring wheat in South Africa under 18 downscaled climate scenarios (9 models run under 2 emissions scenarios). EMs projected larger yield losses or smaller gains than MMs. The EMs' median-projected maize and wheat yield changes were 3.6% and 6.2%, respectively, compared to 6.5% and 15.2% for the MM. The EM projected a 10% reduction in the potential maize growing area, where the MM projected a 9% gain. Both models showed increases in the potential spring wheat production region (EM = 48%, MM = 20%), but these results were more equivocal because both models (particularly the EM) substantially overestimated the extent of current suitability. The substantial water-use efficiency gains simulated by the MMs under elevated CO2 accounted for much of the EMMM difference, but EMs may have more accurately represented crop temperature sensitivities. Our results align with earlier studies showing that EMs may show larger climate change losses than MMs. Crop forecasting efforts should expand to include EMMM comparisons to provide a fuller picture of crop-climate response uncertainties.

DSSAT↗
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 NTRSDate not supplied

Evaluating Microgreens Crop Readiness for Space Production.

Microgreens are small-size, nutrient-rich, and fast-grown crops, which are considered as candidates for future space exploration missions. In particular, the ISS, the Lunar Gateway, and Mars and Lunar missions could benefit from growing microgreens to supplement astronaut diets in the near future. Research at NASA’s Kennedy Space Center has focused on (1) the selection of microgreens compatible species, (2) the evaluation of microgreens food safety, (3) the use of passive wicking, on-demand watering, and hydroponics cultivation, (4) simulated microgravity growth, (5) microgreen canopy gas exchange, and (6) harvesting techniques in microgravity. This presentation summarizes this research. Microgreen species will be evaluated for their yield in relationship to the quantity of inputs – water, seeds, substrate, light intensity, photoperiod, crew time – required for their growth; for their organoleptic and sensory factors in order to down select species that are highly acceptable for humans; and for their microbial loads as detected in their growth environment and the food safety metrics of their edible tissue. Passive wicking, on-demand watering, and hydroponic systems are being studied as an efficient way to deliver essential nutrients and water to microgreens, included in a microgravity environment. Growth studies in simulated microgravity (using 3-dimensional clinostats) will assess microgreens growth relative to that in 1g. Gas exchange studies on microgreens canopies in various airflows will assess their photosynthesis and transpiration. Finally, a series of parabolic flights has enabled the evaluation of different harvesting and bagging techniques in microgravity. Indeed, traditional plant harvesting methods (scissors) in microgravity could generate significant microgreen debris in the space station cabin. Two innovative techniques, coupled to a dedicated bagging method, were designed and evaluated against the control, traditional, harvesting technique. This research was supported by grants from NASA KSC’s Independent Research and Technology Development Program, NASA’s Flight Opportunity Program, NASA Postdoctoral Program Fellowships (L.P. & C.J.) supported by NASA’s Space Biology program, and support from NASA’s Human Research Program.

crop↗
NASA NTRSDate not supplied

Evaluating Microgreens Crop Readiness for Space Production

Microgreens are small-size, nutrient-rich, and fast-grown crops, which are considered as candidates for future space exploration missions. In particular, the ISS, the Lunar Gateway, and Mars and Lunar missions could benefit from growing microgreens to supplement astronaut diets in the near future. Research at NASA’s Kennedy Space Center has focused on (1) the selection of microgreens compatible species, (2) the evaluation of microgreens food safety, (3) the use of passive wicking, on-demand watering, and hydroponics cultivation, (4) simulated microgravity growth, (5) microgreen canopy gas exchange, and (6) harvesting techniques in microgravity. This interactive presentation summarizes this research. Microgreen species will be evaluated for their yield in relationship to the quantity of inputs – water, seeds, substrate, light intensity, photoperiod, crew time – required for their growth; for their organoleptic and sensory factors in order to down select species that are highly acceptable for humans; and for their microbial loads as detected in their growth environment and the food safety metrics of their edible tissue. Passive wicking, on-demand watering, and hydroponic systems are being studied as an efficient way to deliver essential nutrients and water to microgreens, included in a microgravity environment. Growth studies in simulated microgravity (using 3-dimensional clinostats) will assess microgreens growth relative to that in 1g. Gas exchange studies on microgreens canopies in various airflows will assess their photosynthesis and transpiration. Finally, a series of parabolic flights has enabled the evaluation of different harvesting and bagging techniques in microgravity. Indeed, traditional plant harvesting methods (scissors) in microgravity could generate significant microgreen debris in the space station cabin. Two innovative techniques, coupled to a dedicated bagging method, were designed and evaluated against the control, traditional, harvesting technique. This research was supported by grants from NASA KSC’s Independent Research and Technology Development Program, NASA’s Flight Opportunity Program, NASA Postdoctoral Program Fellowships (L.P. & C.J.) supported by NASA’s Space Biology program, and support from NASA’s Human Research Program.

Space Crop Production↗
NASA NTRS2020

Land management and climate change determine second‐generation bioenergy potential of the US Northern Great Plains

Bioenergy with carbon capture and storage (BECCS) has been proposed as a potential climate mitigation strategy raising concerns over trade‐offs with existing ecosystem services. We evaluate the feasibility of BECCS in the Upper Missouri River Basin (UMRB), a landscape with diverse land use, ownership, and bioenergy potential. We develop land‐use change scenarios and a switchgrass (Panicum virgatum L.) crop functional type to use in a land‐surface model to simulate second‐generation bioenergy production. By the end of this century, average annual switchgrass production over the UMRB ranges from 60 to 210 Tg dry mass/year and is dependent on the Representative Concentration Pathway for greenhouse gas emissions and on land‐use change assumptions. Under our simple phase‐in assumptions this results in a cumulative total production of 2,000–6,000 Tg C over the study period with the upper estimates only possible in the absence of climate change. Switchgrass yields decreased as average CO2 concentrations and temperatures increased, suggesting the effect of elevated atmospheric CO2 was small because of its C4 photosynthetic pathway. By the end of the 21st century, the potential energy stored annually in harvested switchgrass averaged between 1 and 4 EJ/year assuming perfect conversion efficiency, or an annual electrical generation capacity of 7,000–28,000 MW assuming current bioenergy efficiency rates. Trade‐offs between bioenergy and ecosystem services were identified, including cumulative direct losses of 1,000–2,600 Tg C stored in natural ecosystems from land‐use change by 2090. Total cumulative losses of ecosystem carbon stocks were higher than the potential ~300 Tg C in fossil fuel emissions from the single largest power plant in the region over the same time period, and equivalent to potential carbon removal from the atmosphere from using biofuels grown in the same region. Numerous trade‐offs from BECCS expansion in the UMRB must be balanced against the potential benefits of a carbon‐negative energy system.

climate change↗
NASA NTRS1992

The dynamics of hydroponic crops for simulation studies of the CELSS initial reference configurations

The goal of this research is to develop a progressive series of mathematical models for the CELSS hydroponic crops. These models will systematize the experimental findings from the crop researchers in the CELSS Program into a form useful to investigate system-level considerations, for example, dynamic studies of the CELSS Initial Reference Configurations. The crop models will organize data from different crops into a common modeling framework. This is the fifth semiannual report for this project. The following topics are discussed: (1) use of field crop models to explore phasic control of CELSS crops for optimizing yield; (2) seminar presented at Purdue CELSS NSCORT; and (3) paper submitted on analysis of bioprocessing of inedible plant materials.

Volk, Tyler↗
NASA NTRS1983

A simulation study of the effects of land cover and crop type on sensing soil moisture with an orbital C-band radar

Simulated C-band radar imagery for a 124-km by 108-km test site in eastern Kansas is used to classify soil moisture. Simulated radar resolutions are 100 m by 100 m, 1 km by 1 km, and 3 km by 3 km, and each is processed using more than 23 independent samples. Moisture classification errors are examined as a function of land-cover distribution, field-size distribution, and local topographic relief for the full test site and also for subregions of cropland, urban areas, woodland, and pasture/rangeland. Results show that a radar resolution of 100 m by 100 m yields the most robust classification accuracies.

Dobson, M. C.↗
NASA NTRS2019

How Does Water Delivery System Design Impact the Microbial Load of Salad Crops?

In a microgravity setting, such as the environment aboard the International Space Station (ISS), an ideal plant water delivery system is one that can grow edible crops with minimal resource consumption and minimal risk to crew members. There are also concerns associated with the ability to control fluid escape and biofilm formation resulting in potential dangers to systems, crops, or crewmembers. To identify an appropriate system, candidate systems were assembled and operated under simulated ISS environmental conditions (T,CO2,and RH) with red romaine lettuce (Lactuca sativa cultivar 'Outredgeous') as a model crop. Fluid reservoirs and randomly selected planting sites were sampled every seven days until maturity at which point edible plant biomass and root samples were also taken. Heterotrophic bacteria and fungi growth patterns throughout each planting cycle were determined by plate counts on appropriate agar media. The candidate systems were compared to a classic hydroponics system as a control and harvested crops were compared to controls as well as Veggie-grown and market produce. Plants harvested from candidate systems yielded lower average heterotrophic bacteria and fungi per gram of plant mass levels when compared to market and Veggie samples as well as those from the control system. Additional studies to evaluate the system sanitation regimen as well as testing additional crops should be considered to aid in the selection of an ideal system.

Curry, Aaron B.↗