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At least 109 records · Page 6

Historical and Future Global Irrigation Energy Consumption by Fuel and Region

Irrigation energy use is a significant component of agricultural production costs, contributing directly to the energy and emissions intensity of crop production and ultimately to food prices. Understanding the existing structure of irrigation energy consumption help achieve food-energy-water security and environmental goals. We present a comprehensive global data set detailing country-level irrigation energy consumption, emphasizing the comparative use of electric, diesel, and emerging solar pumps. To our knowledge, no such data set exists. We draw from a literature review to develop a logistic transformed regression model to estimate the shares of fuel sources for irrigation across countries over historical years to construct a global data set of country-level irrigation energy consumption by multiple fuel sources. Additionally, we compare our estimates of irrigation energy use with agricultural energy use as reported by the International Energy Agency and other external sources. We then use this data to project future irrigation energy use with the Global Change Analysis Model, which is a multisector dynamics model, to showcase the usage of this data set. Projections under the reference scenario show a global shift in fuel types for irrigation pumping, while patterns vary across regions, with India and Pakistan leading in solar-powered irrigation growth and countries like the USA and China continuing to rely primarily on grid electricity. This data set provides a resource to understand the role of irrigation fuel choices within the broader energy sector, as well as the connected agricultural, land use, and water sectors under alternative future scenarios, enabling informed decision making toward efficient agricultural practices.

Global Change Analysis Model (GCAM)↗

Soil Biogeochemistry

Depending upon type and pedogenic stage, soils are subject to biotic and abiotic interactions of complex nature depending on type, nature and specific properties. Soil biogeochemistry involves the study of elemental cycling as mediated by complex and inseparable interactions between the biotic (living) and abiotic (non-living) components of soils. Human activities have substantially altered biogeochemical cycling of several key elements including carbon, nitrogen, phosphorus, potassium, and other secondary and minor nutrients over the past few decades, which, in turn, had serious environmental consequences. The present chapter outlines the soil biogeochemical investigations conducted within Indian subcontinent in both natural ecosystems and managed agricultural systems and addresses the state-of-the-art in order to understand the undergoing biogeochemical reactions. Here, we sought to clarify complex interactions generally occurred during biogeochemical transformations of an element (or compound) of interest within the type-specific soil. Further, we emphasized the importance of advancing our understanding of feedback loops in soil biogeochemical processes as altered by anthropogenic perturbations in tropical and sub-tropical soils of India. Overall, this chapter is broadly focused on the nutrient cycling, which is followed by more specific topics like “soil microbiology,” “soil biodiversity,” and “soil biotechnology.”

Sihi, Debjani↗

Green Era Anaerobic Digester

Green Era Educational NFP constructed and commissioned the Green Era Renewable Energy & Urban Farming Campus in Chicago’s Auburn Gresham neighborhood. The project transformed a long-vacant brownfield site into a commercial-scale anaerobic digestion facility that converts food waste into renewable natural gas and nutrient-rich material for agricultural use. The facility can process up to 80,000 wet tons of food waste annually and supports approximately 15 permanent jobs while advancing food waste diversion, renewable energy production, nutrient recovery and community revitalization.

03 NATURAL GAS↗

A survey of automated remote sensing for agriculture

The state-of-the-art of the technology available to make remote sensing crop production estimates is reviewed with reference to several past and present research projects. In particular, attention is given to Landsat data acquisition, registration and preprocessing, data transformation, data modeling, proportion estimation, and labeling. Development stage models and crop condition models are briefly characterized, and areas where further research is needed are identified.

Hall, F. G.↗

A multi-omics approach to lignocellulolytic enzyme discovery reveals a new ligninase activity from Parascedosporium putredinis NO1

Lignocellulose, the structural component of plant cells, is a major agricultural byproduct and the most abundant terrestrial source of biopolymers on Earth. The complex and insoluble nature of lignocellulose limits its conversion into value-added commodities, and currently, efficient transformation requires expensive pretreatments and high loadings of enzymes. In this work, we report on a fungus from the Parascedosporium genus, isolated from a wheat-straw composting community, that secretes a large and diverse array of carbohydrate-active enzymes (CAZymes) when grown on lignocellulosic substrates. We describe an oxidase activity that cleaves the major β-ether units in lignin, thereby releasing the flavonoid tricin from monocot lignin and enhancing the digestion of lignocellulose by polysaccharidase mixtures. We show that the enzyme, which holds potential for the biorefining industry, is widely distributed among lignocellulose-degrading fungi from the Sordariomycetes phylum.

59 BASIC BIOLOGICAL SCIENCES↗

Color enhancement of landsat agricultural imagery: JPL LACIE image processing support task

Color enhancement techniques were applied to LACIE LANDSAT segments to determine if such enhancement can assist analysis in crop identification. The procedure involved increasing the color range by removing correlation between components. First, a principal component transformation was performed, followed by contrast enhancement to equalize component variances, followed by an inverse transformation to restore familiar color relationships. Filtering was applied to lower order components to reduce color speckle in the enhanced products. Use of single acquisition and multiple acquisition statistics to control the enhancement were compared, and the effects of normalization investigated. Evaluation is left to LACIE personnel.

Madura, D. P.↗

Tracing Carbon Metabolism with Stable Isotope Metabolomics Reveals the Legacy of Diverse Carbon Sources in Soil

Tracking the metabolic activity of whole soil communities can improve our understanding of the transformation and fate of carbon in soils. For this work, we used stable isotope metabolomics to trace 13 C from nine labeled carbon sources into the water-soluble metabolite pool of an agricultural soil over time. Soil was amended with a mixture of all nine sources, with one source isotopically labeled in each treatment. We compared changes in the 13 C enrichment of metabolites with respect to carbon source and time over a 48-day incubation and contrasted differences between soluble sources (glucose, xylose, amino acids, etc.) and insoluble sources (cellulose and palmitic acid). Whole soil metabolite profiles varied singularly by time, while the composition of 13 C-labeled metabolites differed primarily by carbon source (R 2 = 0.68) rather than time (R 2 = 0.07), with source-specific differences persisting throughout incubations. The 13 C labeling of metabolites from insoluble carbon sources occurred slower than that from soluble sources but yielded a higher average atom percent (atom%) 13 C in metabolite markers of biomass (amino acids and nucleic acids). The 13 C enrichment of metabolite markers of biomass stabilized between 5 and 15 atom% 13 C by the end of incubations. Temporal patterns in the 13 C enrichment of tricarboxylic acid cycle intermediates, nucleobases (uracil and thymine), and by-products of DNA salvage (allantoin) closely tracked microbial activity. Our results demonstrate that metabolite production in soils is driven by the carbon source supplied to the community and that the fate of carbon in metabolites do not generally converge over time as a result of ongoing microbial processing and recycling.

59 BASIC BIOLOGICAL SCIENCES↗

SWAT model application for evaluating agricultural conservation practice effectiveness in reducing phosphorous loss from the Western Lake Erie Basin

Lake Erie is threatened by eutrophication and harmful algal blooms due to excess nutrient loading from agricultural sources. Agricultural conservation practices (ACPs) have been developed and implemented to reduce nutrient losses but estimating ACP effectiveness is challenging. The Soil and Water Assessment Tool (SWAT) has been used to investigate ACP effectiveness for water quality improvement. Many SWAT applications have been developed by different investigators to evaluate ACP effectiveness for reducing nutrient, particularly phosphorus (P), loading in the agriculturally-dominated Western Lake Erie Basin (WLEB). Our objective is to establish what has been achieved by past modeling research and make suggestions for future applications and improvements. We synthesized the findings of 28 SWAT modeling studies within the WLEB. Models generally performed satisfactorily against accepted criteria for streamflow and sediment, but performance for P loads, like soluble reactive P, was mostly “unsatisfactory”. The “unsatisfactory” performance maybe due to imperfections and idealizations in model formulations and/or parameterization. Thus, simulations of P transport and transformation processes need improvement. In addition, model parameter selection is the key part of model set-up. Most SWAT modeling studies used default values during initial set-up, then performed calibration and validation. It was found that the calibrated P related parameter values varied widely across different studies, even within the same watershed with some values unrealistic for the study areas. The phenomena of different combinations of model parameters producing similar outputs indicates equifinality. Equifinality in the baseline model may impact results when ACPs are incorporated. Furthermore, the unrealistic values used in ACP assessment undermine the credibility of ACP effectiveness. Future model applications should try to re-examine the calibrated P parameters and make sure they are realistic for the study area as well as reduce equifinality by constraining the model with characterization of watershed conditions, better understanding of hydrologic processes, and parameter values based on real-world observations. As a result, future model applications should focus on improving P transport and transformation processes, using measured watershed characteristics for parameterization, and improving reflections of climate change, which could result in more accurate assessments of ACP effectiveness to meet targeted goals.

54 ENVIRONMENTAL SCIENCES↗

Argument-Based Airworthiness Assurance of Small UAS

Presently, there are three avenues by which Unmanned Aircraft System (UAS) operations are authorized in the U.S. National Airspace System (NAS): obtaining either (i) a certificate of authorization (COA), or (ii) a special airworthiness certificate (SAC) in either the experimental, or the restricted category, or (iii) an exemption from an airworthiness certificate together with a civil COA. The first is meant primarily for public entities, such as NASA; the remaining two are the only available means for civil UAS operations. Recently, the Federal Aviation Administration (FAA) has also proposed a regulatory framework targeted for certain small UAS, specifically those weighing 55 pounds or less, although final rulemaking remains pending. We have previously shown how an assurance case can aggregate heterogeneous reasoning and safety evidence, with application to UAS safety. In this paper, we describe how assurance cases can serve as a common framework to justify overall system safety, unifying both operational aspects and airworthiness, in particular system design assurance. We also show how this approach can coexist with, and augment, existing safety analysis processes and best-practices, by transforming the artifacts they produce into structured assurance arguments. To illustrate the applicability and utility of our approach, we have been applying it for the design assurance of an unmanned rotorcraft system, intended for precision agriculture operations, as part of the NASA Unmanned Aircraft System (UAS) Integration in the National Airspace System (NAS) project.

Rotocraft↗

Hydrologic and Agricultural Earth Observations and Modeling for the Water-Food Nexus

In a globalizing and rapidly-developing world, reliable, sustainable access to water and food are inextricably linked to each other and basic human rights. Achieving security and sustainability in both requires recognition of these linkages, as well as continued innovations in both science and policy. We present case studies of how Earth observations are being used in applications at the nexus of water and food security: crop monitoring in support of G20 global market assessments, water stress early warning for USAID, soil moisture monitoring for USDA's Foreign Agricultural Service, and identifying food security vulnerabilities for climate change assessments for the UN and the UK international development agency. These case studies demonstrate that Earth observations are essential for providing the data and scalability to monitor relevant indicators across space and time, as well as understanding agriculture, the hydrological cycle, and the water-food nexus. The described projects follow the guidelines for co-developing useable knowledge for sustainable development policy. We show how working closely with stakeholders is essential for transforming NASA Earth observations into accurate, timely, and relevant information for water-food nexus decision support. We conclude with recommendations for continued efforts in using Earth observations for addressing the water-food nexus and the need to incorporate the role of energy for improved food and water security assessments

Food Security↗

Coronado Ecological Conservation: Assessing Vegetation Change Due to Border Wall Construction and Shifting Social Trails

Species monitoring is essential in mitigating the impacts of plant invasion, such as radical changes in an area’s ecosystem, degraded soil health, increased wildfire severity, landslides, and increased flooding. NASA DEVELOP partnered with the National Park Service (NPS) to investigate invasive species in disturbed lands: specifically, areas affected by off-trail walking and US-Mexico border construction activities. The team assessed how construction has impacted the distribution of Lehmann’s lovegrass and Russian thistle invasives throughout Coronado National Memorial, AZ from 1986 to 2022. Using data from Landsat 5 and 8, Sentinel-2, the National Agriculture Imagery Program, and PlanetScope, the team computed vegetation indices including the Normalized Difference Vegetation Index, Normalized Difference Moisture Index, Modified Soil Adjusted Vegetation Index 2, Enhanced Vegetation Index, and Tasseled Cap Wetness, Brightness, and Greenness transformations as vegetation health indicators to input into various machine learning algorithms. To minimize noise, the team conducted Principal Component Analysis on the vegetation indices and spectral bands before running k-means++ clustering and random forest classification algorithms. Between all datasets, we found the median area fully overtaken by invasive plants was 5.37% of the park’s total area in 2022. The NPS will use the end products to help increase restoration efforts in disturbed areas with high concentrations of invasive plants. The NPS’s collection of ground data for 2022–2023, in conjunction with future data collection, will notably improve the accuracy of classification models, leading to more precise monitoring of invasive spread over time.

Carson Schuetze↗

Transforming the Future of Marine Aquaculture: A Circular Economy Approach

By mid-century, society will need to significantly intensify the output of its food production system while simultaneously reducing that system’s detrimental impacts on climate, land use, freshwater resources, and biodiversity. This will require finding alternatives to carbon emissions-intensive agriculture, which provides the backbone of today’s global food production system. Here, we explore the hypothesis that marine algae-based aquaculture can help close the projected gap in society’s future nutritional demands while simultaneously improving environmental sustainability. Food production from marine algae-based aquaculture has the potential to contribute more than the total global protein demand projected for 2050, which ranges from 263.8 Mt/yr to 286.5 Mt/yr. It also offers important nutritional and environmental sustainability advantages relative to terrestrial agriculture. Marine algae can provide a better source of high-quality nutritional protein, essential amino acids, and other micronutrients relative to terrestrial plants. In addition, because marine algae do not require soil, irrigation, and the open application of fertilizer, their cultivation does not need to compete with agriculture for arable land and freshwater nor does it lead to fertilizer runoff and downstream eutrophication. Furthermore, by reducing agriculture’s demand for arable land and freshwater, marine algae-based aquaculture can reduce the pressure for deforestation, potentially leading to globally significant reductions in carbon emissions and biodiversity loss.

59 BASIC BIOLOGICAL SCIENCES↗

Feeding Ten Billion People Is Possible Within Four Terrestrial Planetary Boundaries

Global agriculture puts heavy pressure on planetary boundaries, posing the challenge to achieve future food security without compromising Earth system resilience. On the basis of process-detailed, spatially explicit representation of four interlinked planetary boundaries (biosphere integrity, land-system change, freshwater use, nitrogen flows) and agricultural systems in an internally consistent model framework, we here show that almost half of current global food production depends on planetary boundary transgressions. Hotspot regions, mainly in Asia, even face simultaneous transgression of multiple underlying local boundaries. If these boundaries were strictly respected, the present food system could provide a balanced diet (2,355 kcal per capita per day) for 3.4 billion people only. However, as we also demonstrate, transformation towards more sustainable production and consumption patterns could support 10.2 billion people within the planetary boundaries analysed. Key prerequisites are spatially redistributed cropland, improved water–nutrient management, food waste reduction and dietary changes. Adoption of the Sustainable Development Goals by all nations in 2015 is the first ever commitment to a world development path that safeguards the stability of the Earth system as a prerequisite for meeting universal human standards1. The longstanding challenge of achieving food security through sustainable agriculture is particularly acute in this context as world agriculture is a leading cause for the current transgressions of multiple planetary boundaries (PBs) globally and regionally2–5. The PB framework is a comprehensive scientific attempt to synoptically define our planet’s biogeophysical limits to anthropogenic interference. It suggests bounds to nine interacting processes that together delineate a Holocene-like Earth system state. The Holocene is chosen as the reference state as it is the only period known to provide a safe operating space for a world population of several billion people, and according to a precautionary principle, the PBs are set in sufficient distance from processes that may critically undermine Earth system resilience and global sustainability. A challenging question, thus, is whether human development goals such as food security can be met while maintaining multiple PBs along with their subglobal manifestations. Further PB transgressions could jeopardize the chances of providing sufficient food for a world population projected to be wealthier and reach >9 billion by 2050. This conundrum portrays a tradeoff between Earth’s biophysical carrying capacity and humankind’s rising food demand, calling in response for radical rethinking of food production and consumption patterns6–9. Yield gap closures, avoidance of excessive input use, shifts towards less resource-demanding diets, food waste reductions and efficient international trade are crucial options for sustainably increasing the food supply10–15. For example, enhancing water-use efficiency on irrigated and rain-fed farms can triple or quadruple crop yields in low-performing systems, suggesting possible global gains of >20% (ref. 16). Even higher gains appear feasible through globally optimized configurations of the land-use pattern17, and cutting food losses by half could generate food for another billion people18. Thus, collective large-scale implementation of such options could sustain food for a further growing world population19. Yet achieving this within a safe operating space as defined by PBs requires not only a halt to but actually a reversal of existing PB transgressions. Previous studies suggest that such a reconciliation might be possible, but these were based on aggregate representations of PBs (not accounting for the spatial patterns of limits, transgressions and interactions) or considered only one boundary in isolation17,20–23. Here, we systematically quantify to what extent current food production depends on local to global transgressions of the PBs for biosphere integrity, land-system change, freshwater use and nitrogen (N) flows, along with the potential of a range of solutions to avoid these transgressions and still increase food supply (Table 1). To this end, we configured an internally consistent process-based model of the terrestrial biosphere including agriculture (LPJmL) with multiple spatially distributed PBs and their interactions. LPJmL is among the longest-established and best-evaluated biosphere models, showing robust performance regarding simulation of, for example, carbon, water and crop yield dynamics (Supplementary Figs. 1 and 2 and Supplementary Table 1; see ref. 24 for a comprehensive benchmarking and Supplementary Methods for more detail on model evaluations). In principle following established definitions4, we refine the computation of some PBs with respect to their regional patterns and interactions (Methods), providing globally gridded precautionary limits to human interference with the Earth system at a level of great detail. In particular, we account for the evidence that many PBs need to be represented spatially explicitly4 to cover their

Gerten, Dieter↗

Enabling Technology - Reducing Greenhouse Gas Emissions and Energy Demands in the Meat Production Industry via Scaling Advanced 3D Culture Bioreactors

The project “Enabling Technology - Reducing Greenhouse Gas Emissions and Energy Demands in the Meat Production Industry via Scaling Advanced 3D Culture Bioreactors” focuses on developing transformational and disruptive food technologies, specifically in the area of alternative protein and meat production techniques. The impetus for developing alternative protein technologies include reducing intensive greenhouse gas emissions and energy/land/water usages associated with conventional meat production (animal agriculture). Additional rationales include providing alternatives to livestock rearing as a means of reducing antimicrobial resistance (most antibiotic and antimicrobial use occurs in food-producing animals), as well as the transmission of zoonotic diseases. The goal of this ARPA-E project was to research and develop novel and effective technologies to produce cell-cultured meat (also named in vitro meat, cultivated meat). Cell-cultured meat is an alternative protein or meat technology that involves directly growing muscle and fat tissues (which comprise meat) without using the full animal. This offers benefits in terms of animal welfare (elimination of animal slaughter), while also being projected to be more resource efficient in terms of metrics such as land use and greenhouse gas emissions, especially when compared to beef and lamb. Cell cultured meat additionally offers greater control over the cultivated cells, enabling more precise control over nutrition and taste. For example, cultured cells could be tuned to produce antioxidants such as carotenoids to improve human health. However, to date there are no scalable methods of producing cell-cultured meat cheaply at a large scale.

59 BASIC BIOLOGICAL SCIENCES↗

User Needs and Assessing the Impact of Low Latency NASA Earth Observation Data Availability on Societal Benefit

Since the advent of NASA's Earth Observing System, knowledge of the practical benefits of Earth science data has grown considerably. The community using NASA Earth science observations in applications has grown significantly, with increasing sophistication to serve national interests. Data latency, or how quickly communities receive science observations after acquisition, can have a direct impact on the applications and usability of the information. This study was conducted to determine how users are incorporating NASA data into applications and operational processes to benefit society beyond scientific research, as well as to determine the need for data latency of less than 12 h. The results of the analysis clearly show the significant benefit to society of serving the needs of the agricultural, emergency response, environmental monitoring and weather communities who use rapidly delivered, accurate Earth science data. The study also showed the potential of expanding the communities who use low latency NASA science data products to provide new ways of transforming data into information. These benefits can be achieved with a clear and consistent NASA policy on product latency.

NASA↗

Short‐Term Hourly Weather Forecasting Using PredRNN With Image Preprocessing

Global weather forecast models are vital tools with numerous applications, including public safety, agriculture, and transportation. Recent advancements in artificial intelligence (AI) and deep learning (DL) have shown the potential to enhance weather forecasting accuracy and speed. In this study, we developed a short-term hourly weather forecast framework with a wavelet transform function for data preprocessing and a spatiotemporal DL model, PredRNN, for predicting five surface atmospheric variables, including wind speed and direction, mean sea level pressure (MSLP), temperature, and precipitation. The framework demonstrated promising results. It produces global forecasts at 0.25° (∼25 km) with a 1-day lead time RMSE of 1.8 m/s for wind components, 180 Pa for MSLP, and 1.8 K for temperature. Although our model does not surpass state-of-the-art AI weather forecast models across all metrics, it outperforms these models in precipitation forecasting and wind prediction at short lead times and achieves comparable accuracy for MSLP. Its native hourly forecasting capability, together with training on widely accessible GPU hardware, contributes meaningfully to the advancement of accessible DL weather forecasting methods. Our work highlights the importance of integrating temporal components and data transformation techniques to improve the predictability and accuracy of weather forecasts.

Tran, Hoang [Pacific Northwest National Laboratory↗

Automatic registration of satellite imagery

Image registration is one of the basic image processing operations in remote sensing. With the increase in the number of images collected every day from different sensors, automated registration of multi-sensor/multi-spectral images has become an important issue. A wide range of registration techniques has been developed for many different types of applications and data. The objective of this paper is to present an automatic registration algorithm which uses a multiresolution analysis procedure based upon the wavelet transform. The procedure is completely automatic and relies on the grey level information content of the images and their local wavelet transform modulus maxima. The registration algorithm is very simple and easy to apply because it needs basically one parameter. We have obtained very encouraging results on test data sets from the TM and SPOT sensor images of forest, urban and agricultural areas.

Fonseca, Leila M. G.↗

Detection of Deforestation and Land Conversion in Rondonia, Brazil Using Change Detection Techniques

Fires associated with tropical deforestation, land conversion, and land use greatly contribute to emissions as well as the depletion of carbon and nutrient pools. The objective of this research was to compare change detection techniques for identifying deforestation and cattle pasture formation during a period of early colonization and agricultural expansion in the vicinity of Jamari, Rond6nia. Multi-date Landsat Thematic Mapper (TM) data between 1984 and 1992 was examined in a 94 370-ha area of active deforestation to map land cover change. The Tasseled Cap (TC) transformation was used to enhance the contrast between forest, cleared areas, and regrowth. TC images were stacked into a composite multi-date TC and used in a principal components (PC) transformation to identify change components. In addition, consecutive TC image pairs were differenced and stacked into a composite multi-date differenced image. A maximum likelihood classification of each image composite was compared for identification of land cover change. The multi-date TC composite classification had the best accuracy of 78.1% (kappa). By 1984, only 5% of the study area had been cleared, but by 1992, 11% of the area had been deforested, primarily for pasture and 7% lost due to hydroelectric dam flooding. Finally, discrimination of pasture versus cultivation was improved due to the ability to detect land under sustained clearing opened to land exhibiting regrowth with infrequent clearing.

Guild, Liane S.↗