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At least 109 records · Page 6

Yield Model Development (YMD) implementation plan for fiscal years 1981 and 1982

A plan is described for supporting USDA crop production forecasting and estimation by (1) testing, evaluating, and selecting crop yield models for application testing; (2) identifying areas of feasible research for improvement of models; and (3) conducting research to modify existing models and to develop new crop yield assessment methods. Tasks to be performed for each of these efforts are described as well as for project management and support. The responsibilities of USDA, USDC, USDI, and NASA are delineated as well as problem areas to be addressed.

Ambroziak, R. A.↗

Wheat Crop Traits Conferring High Yield Potential May Also Improve Yield Stability Under Climate Change

Increasing genetic wheat yield potential is considered by many as critical to increasing global wheat yields and production, baring major changes in consumption patterns. Climate change challenges breeding by making target environments less predictable, altering regional productivity and potentially increasing yield variability. Here we used a crop simulation model solution in the SIMPLACE framework to explore yield sensitivity to select trait characteristics (radiation use efficiency [RUE], fruiting efficiency and light extinction coefficient) across 34 locations representing the world’s wheat-producing environments, determining their relationship to increasing yields, yield variability and cultivar performance. The magnitude of the yield increase was trait-dependent and differed between irrigated and rainfed environments. RUE had the most prominent marginal effect on yield, which increased by about 45 % and 33 % in irrigated and rainfed sites, respectively, between the minimum and maximum value of the trait. Altered values of light extinction coefficient had the least effect on yield levels. Higher yields from improved traits were generally associated with increased inter-annual yield variability (measured by standard deviation), but the relative yield variability (as coefficient of variation) remained largely unchanged between base and improved genotypes. This was true under both current and future climate scenarios. In this context, our study suggests higher wheat yields from these traits would not increase climate risk for farmers and the adoption of cultivars with these traits would not be associated with increased yield variability.

Climate change↗

Accuracy assessment in the Large Area Crop Inventory Experiment

The Accuracy Assessment System (AAS) of the Large Area Crop Inventory Experiment (LACIE) was responsible for determining the accuracy and reliability of LACIE estimates of wheat production, area, and yield, made at regular intervals throughout the crop season, and for investigating the various LACIE error sources, quantifying these errors, and relating them to their causes. Some results of using the AAS during the three years of LACIE are reviewed. As the program culminated, AAS was able not only to meet the goal of obtaining accurate statistical estimates of sampling and classification accuracy, but also the goal of evaluating component labeling errors. Furthermore, the ground-truth data processing matured from collecting data for one crop (small grains) to collecting, quality-checking, and archiving data for all crops in a LACIE small segment.

Houston, A. G.↗

The Economics of Farming Expansion in the Brazilian Cerrado Under Possible Effects of Climate Change

This analysis assesses the financial viability of legally investing in native Cerrado vegetation deforestation for crop production, considering climate change. The study uses data from twelve different crop models based on three different climate models to predict potential future crop yields in cleared land for growing soy and maize. The outcomes show that in many micro-regions, investments in clearing land for crop production would destroy economic value, that is, generate a negative net present value because of low/negative and volatile cashflows driven primarily by future yields as affected by climate. Our analysis was carried out based on present agricultural practices and technology. As climate changes, farmers may adapt their practices, which can lead to more resilient and productive crops, or grow different crops, which could provide better returns on investment in clearing land than the ones resulting from our analysis. Despite various uncertainties, farmers, policy makers and financial institutions should be aware of the climatic and financial risks associated with land clearing in Brazil, mainly in micro-regions in which all scenarios resulted in negative outcomes in the investment analysis.

agricultural expansion↗

Review: The Next Steps in Crop Improvement: Adoption of Emerging Strategies to Identify Bottlenecks in Sugar Flux

We report sugar allocation in plants is the fundamental process that transports sugar from source to sink tissues and has a dramatic impact on crop yields. Controlling sugar allocation is required to increase crop yields, as well as biomass for biofuel production. Successful examples have demonstrated that genetic engineering of sugar partitioning offers a promising strategy to achieve this goal. However, improvement has thus far been limited by gaps in understanding of the underlying mechanisms controlling the allocation of sugars. The dynamics of sugar partitioning are minimally predictable under different conditions, between species, or in response to abiotic stresses. Here, we discuss four methodologies that have not been sufficiently exploited for the identification of bottlenecks in sugar flux. Furthermore, we suggest how these strategies can be used and combined to provide the insight needed to maximize crop yields or biomass, especially under conditions of environmental stress.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Earth benefits of interdisciplinary CELSS-related research by the NSCORT in Bioregenerative Life Support

Earth benefits of research from the NSCORT in Bioregenerative Life Support will include the following: development of active control mechanisms for light, CO2, and temperature to maximize photosynthesis of crop plants during important phases of crop development; automation of crop culture systems; creation of novel culture systems for optimum productivity; creation of value-added crops with superior nutritional, yield, and waste-process characteristics; environmental control of food and toxicant composition of crops; new process technologies and novel food products for safe, nutritious, palatable vegetarian diets; creation of menus for healthful vegetarian diets with psychological acceptability; enzymatic procedures to degrade recalcitrant crop residues occurring in municipal waste; control-system strategies to ensure sustainabilty of a CELSS that will enable management of diverse complex systems on Earth.

NASA Discipline Number 93-10↗

Uncertainties in Predicting Rice Yield by Current Crop Models Under a Wide Range of Climatic Conditions

Predicting rice (Oryza sativa) productivity under future climates is important for global food security. Ecophysiological crop models in combination with climate model outputs are commonly used in yield prediction, but uncertainties associated with crop models remain largely unquantified. We evaluated 13 rice models against multi-year experimental yield data at four sites with diverse climatic conditions in Asia and examined whether different modeling approaches on major physiological processes attribute to the uncertainties of prediction to field measured yields and to the uncertainties of sensitivity to changes in temperature and CO2 concentration [CO2]. We also examined whether a use of an ensemble of crop models can reduce the uncertainties. Individual models did not consistently reproduce both experimental and regional yields well, and uncertainty was larger at the warmest and coolest sites. The variation in yield projections was larger among crop models than variation resulting from 16 global climate model-based scenarios. However, the mean of predictions of all crop models reproduced experimental data, with an uncertainty of less than 10 percent of measured yields. Using an ensemble of eight models calibrated only for phenology or five models calibrated in detail resulted in the uncertainty equivalent to that of the measured yield in well-controlled agronomic field experiments. Sensitivity analysis indicates the necessity to improve the accuracy in predicting both biomass and harvest index in response to increasing [CO2] and temperature.

crop-model ensembles↗

The crop assessment subsystem: System implementation and approaches used for the generation of crop production reports

The primary responsibility of the crop assessment subsystem (CAS) during the three phases of LACIE was to produce crop reports that included estimates of wheat area, yield, and production, as well as a specified set of associated statistical descriptors. The operations of CAS are described with emphasis on sampling strategy, input/output data, evolution of aggregation/reporting system capabilities, and CAS aggregation procedures.

Mcallum, W. E.↗

Metabolic engineering of energycane to hyperaccumulate lipids in vegetative biomass

Abstract Background The metabolic engineering of high-biomass crops for lipid production in their vegetative biomass has recently been proposed as a strategy to elevate energy density and lipid yields for biodiesel production. Energycane and sugarcane are highly polyploid, interspecific hybrids between Saccharum officinarum and Saccharum spontaneum that differ in the amount of ancestral contribution to their genomes. This results in greater biomass yield and persistence in energycane, which makes it the preferred target crop for biofuel production. Results Here, we report on the hyperaccumulation of triacylglycerol (TAG) in energycane following the overexpression of the lipogenic factors Diacylglycerol acyltransferase 1-2 ( DGAT 1-2) and Oleosin 1 ( OLE 1) in combination with RNAi suppression of SUGAR-DEPENDENT 1 ( SDP 1) and Trigalactosyl diacylglycerol 1 ( TGD 1). TAG accumulated up to 1.52% of leaf dry weight (DW,) a rate that was 30-fold that of non-modified energycane, in addition to almost doubling the total fatty acid content in leaves to 4.42% of its DW. Pearson’s correlation analysis showed that the accumulation of TAG had the highest correlation with the expression level of ZmDGAT 1-2, followed by the level of RNAi suppression for SDP 1. Conclusions This is the first report on the metabolic engineering of energycane and demonstrates that this resilient, high-biomass crop is an excellent target for the further optimization of the production of lipids from vegetative tissues.

1-2↗

Global irrigation contribution to wheat and maize yield

Irrigation is the largest sector of human water use and an important option for increasing crop production and reducing drought impacts. However, the potential for irrigation to contribute to global crop yields remains uncertain. Here, we quantify this contribution for wheat and maize at global scale by developing a Bayesian framework integrating empirical estimates and gridded global crop models on new maps of the relative difference between attainable rainfed and irrigated yield (ΔY). At global scale, ΔY is 34 ± 9% for wheat and 22 ± 13% for maize, with large spatial differences driven more by patterns of precipitation than that of evaporative demand. Comparing irrigation demands with renewable water supply, we find 30–47% of contemporary rainfed agriculture of wheat and maize cannot achieve yield gap closure utilizing current river discharge, unless more water diversion projects are set in place, putting into question the potential of irrigation to mitigate climate change impacts.

Irrigation↗

Marine Renewable Energy Applications for Restorative Ocean Farming: Kelp

Kelp farming and kelp forest restoration have both been proposed as a solution to locally decrease the impacts of ocean acidification and eutrophication, often with co-benefits to other forms of aquaculture and mariculture. Compared to global markets, the kelp industry in the United States is still in its early phases, with the first commercial kelp farm founded in Casco Bay, Maine in 2010. Since then, interest and effort in kelp production has been increasing, with farms now present in Maine, New Hampshire, Connecticut, Rhode Island, Massachusetts, New York, Washington, and Alaska. Many research projects are underway in the United States to explore benefits of 3D ocean farming, tackle logistical problems of working in the ocean, autonomous farming, and explore viable end uses for kelp products. In seaweed farming, to remove the stored carbon or excess nutrients from the system, the biomass needs to be harvested at the optimal time to avoid the release of CO 2 that comes with decomposition. Timing of the harvest is also important for maximum crop yield, which can vary based on the final product. Additional monitoring needs can include a variety of water quality metrics, growth measurements, and visuals to ensure the health of the farm, comply with permits, support operations and maintenance functions. The variables measured may vary by desired end use of the product, location of farm, and operational design. Monitoring all of these parameters requires specialized devices that can be costly and challenging to maintain. Monitoring devices often face power and logistical constraints that could prevent kelp farmers from adopting these technologies or receiving accurate, efficient monitoring to assess ecosystem benefits and valuation. Marine energy has been identified as a possible power source for these devices. This project investigates the power needs for conducting kelp farm environmental monitoring compared with the available marine energy resource to evaluate if locally generated ocean energy could provide a solution to these monitoring challenges and benefit kelp farmers. This process was structured as follows: 1. Define what data is needed for farmers and their communities through desk research and interviews with end users. 2. Identify sensors and power requirements currently in use or available for commercial purchase. 3. Analyze current kelp and other mariculture farm locations for the potential marine energy resource. 4. Analyze farm designs and associated structures to make recommendations for marine energy design. 5. Quantify value that investment in sensors could provide in terms of carbon credit possibilities.

09 BIOMASS FUELS↗

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

VEG-05 is an experiment to better define best practices for crop production and handling in space. Light can impact the growth habit, yield, nutritional composition, microbial levels, and flavor within crops and VEG-05 used the Veggie facilities on the International Space Station to grow ‘Red Robin’ dwarf tomatoes under different spectral compositions to assess these characteristics. Prior to launch, both a science verification test (SVT), and an experiment verification test (EVT) were conducted. SVT, and a previous fertilizer test, grew plants in both plant pillows and PONDS units and tested different fertilizer treatments, with each test under one of the light conditions. EVT used only plant pillows with the highest fertilizer composition tested, and two Veggie units were utilized. One Veggie had light settings consisting of equal levels of red: blue light while the second Veggie had a 90:10 ratio of red: blue light, both with the addition of ~10% green. For SVT, under the equal red: blue light treatment, fruit ripening in plant pillows was delayed. For EVT we saw fruit ripening earlier, especially in the red-rich treatment. In SVT we had mostly daily watering, and this led to excess water in plant pillows which leaked and caused fungus to grow. We reduced this excess in EVT, however, wilting events occurred. 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 indicated that fruit were safe for consumption. VEG-05 flight operations ran December 2022 and March 2023, with considerable challenges in watering and unexpectedly low humidity on ISS during critical periods. Only 12 ripe fruit formed, and all were returned. Fruit and other samples are currently being analyzed. This research was co-funded by NASA’s Human Research Program and Space Biology.

Gioia Donna Massa↗

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

VEG-05 is an experiment to better define best practices for crop production and handling in space. Light can impact the growth habit, yield, nutritional composition, microbial levels, and flavor within crops and VEG-05 used the Veggie facilities on the International Space Station to grow ‘Red Robin’ dwarf tomatoes under different spectral compositions to assess these characteristics. Prior to launch, both a science verification test (SVT), and an experiment verification test (EVT) were conducted. SVT, and a previous fertilizer test, grew plants in both plant pillows and PONDS units and tested different fertilizer treatments, with each test under one of the light conditions. EVT used only plant pillows with the highest fertilizer composition tested, and two Veggie units were utilized. One Veggie had light settings consisting of equal levels of red: blue light while the second Veggie had a 90:10 ratio of red: blue light, both with the addition of ~10% green. For SVT, under the equal red: blue light treatment, fruit ripening in plant pillows was delayed. For EVT we saw fruit ripening earlier, especially in the red-rich treatment. In SVT we had mostly daily watering, and this led to excess water in plant pillows which leaked and caused fungus to grow. We reduced this excess in EVT, however, wilting events occurred. 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 indicated that fruit were safe for consumption. VEG-05 flight operations ran December 2022 and March 2023, with considerable challenges in watering and unexpectedly low humidity on ISS during critical periods. Only 12 ripe fruit formed, and all were returned. Fruit and other samples are currently being analyzed. This research was co-funded by NASA’s Human Research Program and Space Biology.

Gioia D. Massa↗

Rising Temperatures Reduce Global Wheat Production

Crop models are essential tools for assessing the threat of climate change to local and global food production. Present models used to predict wheat grain yield are highly uncertain when simulating how crops respond to temperature. Here we systematically tested 30 different wheat crop models of the Agricultural Model Intercomparison and Improvement Project against field experiments in which growing season mean temperatures ranged from 15 degrees C to 32◦ degrees C, including experiments with artificial heating. Many models simulated yields well, but were less accurate at higher temperatures. The model ensemble median was consistently more accurate in simulating the crop temperature response than any single model, regardless of the input information used. Extrapolating the model ensemble temperature response indicates that warming is already slowing yield gains at a majority of wheat-growing locations. Global wheat production is estimated to fall by 6% for each degree C of further temperature increase and become more variable over space and time.

agriculture↗

Outdoor annual algae productivity improvements at the pre-pilot scale through crop rotation and pond operational management strategies

The Development of Integrated Screening, Cultivar Optimization, and Verification Research (DISCOVR) collaborative consortium operated pre-pilot scale outdoor ponds to deliver much-needed multi-year, long-term and consistent, algae cultivation data relevant to understanding the current state of technology in terms of expected seasonal algae biomass productivity. Over the course of four years from 2018 to 2021, twelve identical 4.2 m 2 mini-ponds were run in triplicate sets to test strains and operational strategies demonstrated in small-, indoor photobioreactors, in pursuit of increasing overall algae areal productivity and projected farm yield. Fourteen different cultivars derived from a strain screening pipeline were tested. Through deliberate seasonal crop rotation and improvements in operational strategies, annual biomass productivity increased from 11.6 to 17.6 g m -2 day -1 , a > 50% increase over the 2018 baseline. Both brackish and marine strains were included and four out of the fourteen strains consistently yielded high productivity across multiple years; brackish strains Monoraphidium minutum (26BAM) and Scenedesmus obliquus (UTEX393), and marine strains Tetraselmis striata (LANL1001) and Picochlorum celeri (TG2). These freely available datasets, which represent nearly complete annual daily coverage of cultivation metrics including weather, pond temperature and pH, nutrients, and productivity, are unique in the public domain and seek to fill agronomic and operational knowledge gaps to help in the eventual commercialization of algal biofuels and bioproducts.

09 BIOMASS FUELS↗

Rapid Composting of Crop Space Waste

This project processed multiple types of waste simulant feedstocks using commercial composting units and NASA Trash-to-Gas (TtG) technology processing units to see what solids, liquids, and gases could be recovered. The feedstock waste included inedible biomass, mission waste from the Johnson Space Center (JSC) Crew Health and Performance Exploration Analog (CHAPEA), Mars analog, and the long duration Orbital Syngas/Commodity Augmentation Reactor (OSCAR) Waste Simulant (OWS) and OSCAR Full Scale (FS) (also referred to as Mars 850-day mission waste simulant). The performance data was collected, and overall performance of the waste processing systems, as well as elemental analysis of the product yields for enabling Lunar and Martian regolith mixtures in a crop grow-out study, were performed. Germination took place in certain Lunar and Martian regolith studies, with promising preliminary results that TtG solid products can be used as plant nutrients to enable crop growth in off-world regolith simulants.

Anne Meier↗

Modeling Yield, Biogenic Emissions, and Carbon Sequestration in Southeastern Cropping Systems With Winter Carinata

Sustainable aviation fuel (SAF) production from lipids is a technologically mature approach for replacing conventional fossil fuel use in the aviation sector, and there is increasing demand for such feedstocks. The oilseed Brassica carinata (known as Ethiopian mustard or simply carinata) is a promising SAF feedstock that can be grown as a supplemental cash crop over the winter fallow season of various annual crop rotations in the Southeast US, avoiding land use changes and potentially achieving some of the soil carbon sequestration and ecosystem service benefits of winter cover crops. However, carinata may require more intensive management than traditional cover crops, potentially leading to additional soil greenhouse gas (GHG) emissions through increased carbon losses from soil tillage and nitrous oxide (N 2 O) emissions from nitrogen fertilizer application. In this work, the 2017 version of the process-based DayCent ecosystem model was used to establish initial expectations for the total regional SAF production potential and associated soil GHG emissions when carinata is integrated as a winter crop into the existing crop rotations across its current suitability range in southern Alabama, southern Georgia, and northern Florida. Using data from academic and industry carinata field trials in the region, DayCent was calibrated to reproduce carinata yield, nitrogen response, harvest index, and biomass carbon-to-nitrogen ratio. The resulting model was then used to simulate the integration of carinata every third winter across all 2.1 Mha of actively cultivated cropland in the study area. The model predicted regional average yields of 2.9–3.0 Mg carinata seed per hectare depending on crop management assumptions. That results in the production of more than two million Mg of carinata seed annually across the study area, enough to supply approximately one billion liters of SAF. Conventional management of carinata led to only modest increases in soil carbon storage that were largely offset by additional N2O emissions. Climate-smart management via adopting no-till carinata establishment or using poultry litter as a nitrogen source resulted in a substantial net soil GHG sink (0.23–0.31 Mg CO 2 e ha -1 y -1 , or 0.24–0.32 Mg CO2e per Mg of seed produced) at the farms where carinata is cultivated.

54 ENVIRONMENTAL SCIENCES↗