Results for “FARMS” — Page 18

NASA NTRS2021

Midwest Food Security & Agriculture II: Leveraging NASA Earth Observations to Analyze and Display Crop Phenology Data and Weather Conditions to Support Expansion of Small Grain Crops in the Midwest

Agriculture in the Midwest is dominated by monoculture systems that strip the soil of nutrients, decrease yields, and worsen water quality. Crop diversification and cultivating small grains is economically and ecologically advantageous, but limited in practice due to a lack of data about small-grain crop performance as well as monoculture-favoring insurance coverage, economic incentives, and sociocultural traditions. Practical Farmers of Iowa (PFI) strives to create more sustainable agriculture and supports Midwestern farmers in adding small grains into their crop rotations. The DEVELOP team partnered with the USDA Agricultural Research Service and the USA National Phenology Network to assist PFI in applying NASA Earth observation data to track small-grain crop performance. This project developed a Google Earth Engine user interface that enables PFI farmers to compare satellite-assessed vegetation production and climatic conditions of their farm with other PFI farmers. The team assessed the crop performance through Normalized Difference Vegetation Index (NDVI) values derived from Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Landsat 8 Operational Land Imager (OLI). Additionally, the team created a regression model to analyze the predictive properties of vegetation indices and crop yield, ultimately establishing a relationship with mean NDVI from the early growing season. PFI farmers can utilize these products to make informed decisions about their crop production as well as advocate for more expansive insurance policies to protect small-grain crops.

Sophie Barrowman↗

NASA NTRS2022

Groundwater Variability Across India, Under Contrasting Human and Natural Conditions

Characterizing local to regional scale water cycles and water resources will be crucial for achieving the United Nations' water-related Sustainable Developmental Goals. However, quantification and understanding of groundwater extraction across scales have been hampered by inadequate water usage reporting and limited information on irrigation practices. Here we analyze observations from ∼15,000 groundwater monitoring wells and the Gravity Recovery and Climate Experiment satellites together with irrigation, agricultural, and meteorological datasets to show how drought-induced coupling between natural and anthropogenic groundwater storage variations has caused sustainability challenges in India, the world's biggest consumer of groundwater for irrigation. Notably, the mechanisms and consequences of such coupling differ significantly depending on aquifer types. In Andhra Pradesh's hard rock aquifer, groundwater declines have been limited, despite the nearly constant water scarcity that its farmers face. Moreover, its free farm power policy involves an annual irrigation energy consumption of 26 billion kWh that costs US$ 2.5 billion, possibly unparalleled compared to any other part of the world of similar size (0.27 million km2). In West Bengal's highly permeable alluvial aquifer, the water table is declining rapidly (15 cm/yr) due to a policy that encourages irrigation. Situated between these two states, Odisha's aquifer shows substantial resilience to drought, owing to the state's relatively natural landscape and forest restoration policy. The findings of this study provide new insights to understand the divergent aspects of groundwater irrigation in north versus south India, which can enable development of adaptation and mitigation strategies to avert the looming water crisis.

Dileep K Panda↗

NASA NTRSDate not supplied

Options for Offloading a 90-Ton Common Habitat from its Lander on the Surface of Mars

The Common Habitat is a large, long-duration habitat being explored as part of a conceptual study (not an active NASA program) that uses an SLS core stage liquid oxygen (LOX) tank as its primary structure. Measuring 8.4 meters in diameter and 15.6 meters in length, it is manufactured as a habitat and launched as such into space. It is intended for use on the Moon as part of a permanently occupied outpost, on Mars as part of an outpost that will be occupied for hundreds of days at a time, and in deep space as part of the Deep Space Exploration Vehicle where it will support crewed missions up to 1200 days in duration. A study of internal orientation and crew size resulted in a Common Habitat configuration sized for a crew of eight with a three-deck horizontal orientation. There are obvious challenges associated with the delivery of such a large habitat, which may mass as much as 90-tons when initially deployed. The Mars destination in particular imposes extreme challenges due to Martian gravity. This paper identifies initial options for the offloading of a 90-ton Common Habitat from a lander spacecraft on the surface of Mars. On Mars, the Common Habitat is part of a surface outpost where a Habitation Zone includes the Common Habitat docked to a two-chamber airlock node, up to two logistics modules, and up to two pressurized rovers. It is connected by underground conduit to a radiator farm and communications tower assembly. These elements and other surface infrastructure, including robotic systems for surface preparation, are landed prior to the Common Habitat. In the baseline Common Habitat Architecture, the Common Habitat is delivered on the third heavy cargo flight. The Habitation Zone configuration dictates that the Common Habitat needs to be offloaded from the lander. All of the docked elements require direct access to the surface and the Common Habitat must actually be placed in a trench to lower its docking ports to be level with those of the mated elements. Additionally, the habitat must be emplaced in a horizontal configuration, while for any conceivable Earth launch system it must be launched in a vertical configuration. It is true that the Common Habitat must be offloaded from its lander on both the Moon and Mars and a common offloading system must therefore work in both destinations. Mars, however, is considered the driving case for offloading in most, but not all, aspects. A four-day internal study in 2021 recommended that a modified Starship be used to land the Common Habitat on Mars and considered multiple approaches to offload the Common Habitat from the payload section and lower it to the surface. The topic was presented at a public hackathon organized by the Johnson Space Center’s Emerge Employee Resource Group. One team took on the challenge and proposed a concept in some ways similar to the previously considered jib crane. Despite the excellent innovation in the team’s work, a number of study refinements are necessary to truly establish feasibility. These and other future work needed to mature the concept are discussed in this work.

Lander Offloading↗

NASA NTRSDate not supplied

Morphological evolution and transition at nanoscale in BSTO ceramic materials

Considerable efforts have been devoted for the development of low cost ferroelectric and clean energy storage multifunctional materials. Modification in design and production of a low cost material with well proven process provides pathway for high energy density dielectric energy storage. We studied fluorine doped a commercially well-established material system barium strontium titanate with two different concentrations of dopants and studied the morphological transition and its effect on properties. It was observed that sample with higher concentration transitioned much faster into glassy state, followed by growth of fibers which turned into a self-arranged bird nest type shape. The sample with lower concentration changed slowly into glassy state and only few fibers were farmed. Dielectric was highly dependent on processing methods and shows variation with crystallinity of material, temperature and cooling conditions during processing. In the higher concentration range, we observed nano-scale interface breakdown very similar to that of solid-liquid interface breakdown during crystal growth.

dielectric↗

NASA NTRS2023

Sizing and Design Tool for Tall Lunar Tower

Tall lunar towers enable direct collection of solar energy using solar panels that can generate power exceeding 50kW. Tall lunar towers also support solar reflectors and concentrators for solar farms, which enable various mission architectures on the lunar surface. The Tall Lunar Tower project at NASA Langley Research Center is focused on the design, modeling, fabrication, and testing of an assembled tall lunar tower engineering development unit. This paper presents the development of a sizing and design tool for the tall lunar tower. The predicted frequency and buckling responses of the tall lunar tower from the tool are compared with the results obtained from finite element analysis.

Solar Tower↗

NASA NTRS2023

Sizing and Design Tool for Tall Lunar Tower

Tall lunar towers enable direct collection of solar energy using solar panels that can generate power exceeding 50kW. Tall lunar towers also support solar reflectors and concentrators for solar farms, which enable various mission architectures on the lunar surface. The Tall Lunar Tower project at NASA Langley Research Center is focused on the design, modeling, fabrication, and testing of an assembled tall lunar tower engineering development unit. This paper presents the development of a sizing and design tool for the tall lunar tower. The predicted frequency and buckling responses of the tall lunar tower from the tool are compared with the results obtained from finite element analysis.

Solar Tower↗

NASA NTRSDate not supplied

A Strategic Approach for Dense, Integrated, Vehicle Navigation

Drone usage has been on the rise in recent years with applications that include parcel delivery, wildlife protection, precision farming, law enforcement, and industrial inspection, just to name a few. Once regulations and safety policies are put in place to allow for the widespread use of unmanned drones, the number of aircraft in the National Airspace System (NAS) is expected to skyrocket to millions, potentially congesting the airspace which increases the likelihood of separation violations and possibly incidents. Currently, flight infrastructure can only support a few thousand aircraft flying over the United States National Airspace System (NAS) at any given time. A delay at one airport can send ripple effects throughout the system, causing more delays and missed connections. In air traffic control, separation is the concept of keeping an “ownship” aircraft outside a minimum distance from “intruder” aircraft to reduce the risk of the aircraft colliding, as well as preventing accidents due to secondary factors, such as wake turbulence. Maintaining proper separation is often a safety critical property for fixed-wing drones in the airspace. This paper addresses drone separation in time and distance for high volume corridors (en route) and lanes (on ground), merging as well as crossing intersections of multiple corridors/lanes. In this paper, the term drone is applied to both Unmanned Aerial Vehicle (UAV) and small Unmanned Aircraft System (UAS) vehicles operating autonomously. There exists a gamut of approaches to the merging and crossing problems. At one end of the extreme are the conservative yet low cost and verifiable solutions of today that deal with two drones at a time. At the other end are complex Machine Learning-based solutions with high computing requirements for fully autonomous drones of the future that are expected to handle all contentions. This paper presents a feasible and verifiable strategic approach to these problems that is based on distributed cooperation between the drones and the infrastructure. Three phases of the strategic approach (Prepare, Adjust, Commit) are presented. Simulation results are presented that show the proposed approach is stable and resilient to induced perturbations and guarantees a set of fixed-wing drones to merge and cross intersections by adjusting their speed based on their distance to the aircraft in front of them while remaining in the equilibrium state. The equilibrium state is defined as the state when a set of n aircraft move at a relatively constant speed and uniform spacing from each other in a congested system. A congested system is defined as the state when at least one aircraft cannot move at its maximum allowed speed. Unlike existing centralized and pre-planned approaches, the proposed solution is fully distributed and enables autonomous aircraft to decide to adjust their speed and distance with respect to the preceding aircraft, dynamically. Simulation results are presented that assess the feasibility of the approach.

Distributed↗

NASA NTRSDate not supplied

A Strategic Approach for Dense, Integrated, Vehicle Navigation

Drone usage has been on the rise in recent years with applications that include parcel delivery, wildlife protection, precision farming, law enforcement, and industrial inspection, just to name a few. Once regulations and safety policies are put in place to allow for the widespread use of unmanned drones, the number of aircraft in the National Airspace System (NAS) is expected to skyrocket to millions, potentially congesting the airspace which increases the likelihood of separation violations and possibly incidents. Currently, flight infrastructure can only support a few thousand aircraft flying over the United States National Airspace System (NAS) at any given time. A delay at one airport can send ripple effects throughout the system, causing more delays and missed connections. In air traffic control, separation is the concept of keeping an “ownship” aircraft outside a minimum distance from “intruder” aircraft to reduce the risk of the aircraft colliding, as well as preventing accidents due to secondary factors, such as wake turbulence. Maintaining proper separation is often a safety critical property for fixed-wing drones in the airspace. This paper addresses drone separation in time and distance for high volume corridors (en route) and lanes (on ground), merging as well as crossing intersections of multiple corridors/lanes. In this paper, the term drone is applied to both Unmanned Aerial Vehicle (UAV) and small Unmanned Aircraft System (UAS) vehicles operating autonomously. There exists a gamut of approaches to the merging and crossing problems. At one end of the extreme are the conservative yet low cost and verifiable solutions of today that deal with two drones at a time. At the other end are complex Machine Learning-based solutions with high computing requirements for fully autonomous drones of the future that are expected to handle all contentions. This paper presents a feasible and verifiable strategic approach to these problems that is based on distributed cooperation between the drones and the infrastructure. Three phases of the strategic approach (Prepare, Adjust, Commit) are presented. Simulation results are presented that show the proposed approach is stable and resilient to induced perturbations and guarantees a set of fixed-wing drones to merge and cross intersections by adjusting their speed based on their distance to the aircraft in front of them while remaining in the equilibrium state. The equilibrium state is defined as the state when a set of n aircraft move at a relatively constant speed and uniform spacing from each other in a congested system. A congested system is defined as the state when at least one aircraft cannot move at its maximum allowed speed. Unlike existing centralized and pre-planned approaches, the proposed solution is fully distributed and enables autonomous aircraft to decide to adjust their speed and distance with respect to the preceding aircraft, dynamically. Simulation results are presented that assess the feasibility of the approach.

Distributed↗

NASA NTRSDate not supplied

A Strategic Approach for Dense, Integrated, Vehicle Navigation

Drone usage has been on the rise in recent years with applications that include parcel delivery, wildlife protection, precision farming, law enforcement, and industrial inspection, just to name a few. This paper addresses drone separation in time and distance for high volume corridors (en route) and lanes (on ground), merging as well as crossing intersections of multiple corridors/lanes. There exists a gamut of approaches to solving merging and intersection crossing problems. At one end of the extreme are the conservative yet low cost and verifiable solutions of today that deal with two drones at a time. At the other end are complex Machine Learning-based solutions with high computing requirements for fully autonomous drones of the future that are expected to handle all contentions. This paper presents a feasible and verifiable strategic approach to solving these problems that is based on distributed cooperation between the UAVs/UASs and the infrastructure. Unlike existing centralized and pre-planned approaches, the proposed solution is fully distributed and enables autonomous aircraft to decide to adjust their speed and distance with respect to the preceding aircraft, dynamically. Three phases of the strategic approach (Prepare, Adjust, Commit) are presented. Simulation results are presented that show the proposed approach is stable and resilient to induced perturbations and guarantees a set of fixed-wing UAVs/UASs to merge and cross intersections by adjusting their speed based on their distance to the aircraft in front of them.

Distributed↗

NASA NTRS2022

Shoshone River Water Resources: Assessing Sediment Inputs into the Shoshone River in Wyoming to Determine Areas for Protection and Restoration Practices

In 2016, a routine repair operation at the Willwood Dam released tons of built-up sediment into the Shoshone River, polluting the river and negatively impacting the ecosystem. This release greatly affected the communities that rely on the river for farming, recreation, and tourism. In partnership with the Wyoming Department of Environmental Quality (WYDEQ), Shoshone River Partners, and the United States Geological Survey (USGS) Wyoming–Montana Water Science Center, this project utilized satellite imagery and precipitation data to examine turbidity patterns in the Shoshone River between the Buffalo Bill Dam and the Willwood Dam. We used PlanetScope satellite images to assess changes in surface reflectance of the river in response to precipitation events and Global Precipitation Measurement (GPM) Integrated Multi-Spectral Retrieval (IMERG) precipitation data to estimate the lag time between rainfall events and increased turbidity. The National Land Cover Dataset (2019) was used to identify the main land cover types within each sub-basin. The end products included a turbidity analysis, land cover analysis, and precipitation analysis that provided the partners with a better understanding of sediment dynamics in the river. The results demonstrated the feasibility of using PlanetScope data to examine turbidity spatially along small rivers. Sediment plumes from tributaries were visually identified for multiple high turbidity events, and we calibrated an equation that translated reflectance to turbidity, accurately representing plume extent. Inconsistent spectral quality of PlanetScope data, however, limited our ability to assess the relative sediment contribution of the tributaries.

tributaries↗

NASA NTRSDate not supplied

Assessing Sediment Inputs into the Shoshone River in Wyoming to Determine Areas for Protection and Restoration Practices

In 2016, a routine repair operation at the Willwood Dam released tons of built-up sediment into the Shoshone River, polluting the river and killing thousands of fish. This release greatly concerned the communities that rely on the river for farming, recreation, and tourism. In partnership with the Wyoming Department of Environmental Quality (WDEQ), Shoshone River Partners, and the United States Geological Survey (USGS) Wyoming-Montana Water Science Center, this multipart project illustrated the application of high-resolution satellite imagery and hydrological modeling techniques to identify major tributaries contributing to sediment influxes into the Shoshone River between the Buffalo Bill Dam and the Willwood Dam. The team used PlanetScope and Sentinel-2 Multi-Spectral Instrument (MSI) satellite images to assess changes in the surface reflectance of the river in response to precipitation events. To determine these storm events, the team selected dates of interest using Global Precipitation Measurement (GPM) Integrated Multi-Spectral Retrieval (IMERG) and gauge precipitation data from the Global Historical Climatology Network Daily (GHCNd). The continuation of this research further quantified sediment influx in the Shoshone River following snowfall and melt events using the Soil & Water Assessment Tool (SWAT). The precipitation analysis and sediment contribution maps helped the partner organizations prioritize their current decision making and best management practices to specific sites along the river. The results demonstrated the feasibility of using PlanetScope data for categorizing sediment in the Shoshone River.

Caroline Williams↗

NASA NTRSDate not supplied

Linking Individual Variation in Movement Behavior to Infection Dynamics in Highly Mobile Species

Animal movements are linked to infectious disease dynamics in wildlife through multiple mechanisms across various spatial and temporal scales. For example, infections can impede the movement of infected individuals, but infected hosts can also disperse infectious agents as they move. Individuals inevitably vary in their responses to infections and their roles in determining infection dynamics, which means that considering variation among individuals – whether across species, across time, or within populations – is important for understanding movement-disease relationships and their implications for epidemiology. Here, I draw on studies from multiple systems to examine how variation in movement behavior links to infectious disease epidemiology. For example, a comparative study of habitat selection across multiple waterfowl species highlights that diel behavioral patterns, rather than individual or seasonal variation, is the most important driver of the risk of overlap between waterfowl and poultry farms, and therefore for the risk of avian influenza spillover. Together, these studies show that individual traits interact with the environment to influence the roles of individuals for infectious disease ecology.

Claire Stewart Teitelbaum↗

NASA NTRS2021

Hybrid phenology matching model for robust crop phenological retrieval

Crop phenology regulates seasonal agroecosystem carbon, water, and energy exchanges, and is a key component in empirical and process-based crop models for simulating biogeochemical cycles of farmlands, assessing gross and net primary production, and forecasting the crop yield. The advances in phenology matching models provide a feasible means to monitor crop phenological progress using remote sensing observations, with a priori information of reference shapes and reference phenological transition dates. Yet the underlying geometrical scaling assumption of models, together with the challenge in defining phenological references, hinders the applicability of phenology matching in crop phenological studies. The objective of this study is to develop a novel hybrid phenology matching model to robustly retrieve a diverse spectrum of crop phenological stages using satellite time series. The devised hybrid model leverages the complementary strengths of phenometric extraction methods and phenology matching models. It relaxes the geometrical scaling assumption and can characterize key phenological stages of crop cycles, ranging from farming practice-relevant stages (e.g., planted and harvested) to crop development stages (e.g., emerged and mature). To systematically evaluate the influence of phenological references on phenology matching, four representative phenological reference scenarios under varying levels of phenological calibrations in terms of time and space are further designed with publicly accessible phenological information. The results indicate that the hybrid phenology matching model can achieve high accuracies for estimating corn and soybean phenological growth stages in Illinois, particularly with the year- and region-adjusted phenological reference (R-squared higher than 0.9 and RMSE less than 5 days for most phenological stages). The inter-annual and regional phenological patterns characterized by the hybrid model correspond well with those in the crop progress reports (CPRs) from the USDA National Agricultural Statistics Service (NASS). Compared to the benchmark phenology matching model, the hybrid model is more robust to the decreasing levels of phenological reference calibrations, and is particularly advantageous in retrieving crop early phenological stages (e.g., planted and emerged stages) when the phenological reference information is limited. This innovative hybrid phenology matching model, together with CPR-enabled phenological reference calibrations, holds 3 considerable promise in revealing spatio-temporal patterns of crop phenology over extended geographical regions.

Phenology↗

NASA NTRSDate not supplied

Sizing, Buckling, and Thermal-Structural Analysis of Tall Lunar Tower

Tall lunar towers enable direct collection of solar energy using solar panels that can generate power exceeding 100-kW above shadowed regions on the surface. Tall lunar towers also support solar reflectors and concentrators for solar farms, which enable various mission architectures on the lunar surface. The Tall Lunar Tower (TLT) project at NASA Langley Research Center is focused on the design, modeling, fabrication, and testing of an assembled TLT Engineering Development Unit (EDU). In this paper, the design and analysis plan of a TLT is presented and predicted buckling and thermal-structural response of the TLT EDU on the lunar surface are investigated.

Kyongchan Song↗

NASA NTRSDate not supplied

AgMIP Local, National and Global Assessments of Food System Challenges in A Changing Climate

Food systems connect a diverse network of stakeholders around the world, with complex dynamics governing production, processing, transportation, trade and consumption of food products. Extreme conditions can disrupt multiple components of the food system, with systemic connections providing structure that can both buffer and exacerbate risks. Climate change is shifting current practices in agricultural production and the broader food system, encouraging shifts toward more diverse value chains capable of drawing from multiple food producing regions to reduce the chance that an entire value chain be subject to simultaneous impacts. The IPCC Working Group I report assessed that heat waves, fires, floods and severe storms are becoming more pronounced and widespread with each degree of global warming, increasing food system risk. Food system disruptions can also come from outside the climate system, including from viral outbreaks, geopolitical conflict and socioeconomic changes. This presentation will highlight how the Agricultural Model Intercomparison and Improvement Project (AgMIP) develops modeling approaches that connect climate, biophysical and socioeconomic models in order to capture complex responses of the food system and potential interventions by diverse stakeholders in the public and private sectors. Models are applied on a range of scales that match decision contexts. These include households in specific agricultural production regions (e.g., within a country), national-level policymakers considering policies, sustainability and development priorities for a country’s agricultural sector, and global food market models that balance production and consumption around the world with competition for land, water, energy and sustainability priorities. Models are capable of capturing many important responses, but further development is needed to represent key systemic risks and the possibility for additional interventions beyond the farm gate. Improved food system models will provide important insights into our society’s ability to cope with climate change, as well as our ability to identify agricultural adaptation and mitigation opportunities to reduce overall risk.

Food systems↗

NASA NTRS2023

Bhutan Agriculture III: Monitoring Cropland Changes in Bhutan using Remote Sensing to Bolster Food Security and Support Crop Monitoring

The Bhutan Agriculture III team aimed to improve agricultural efficiency in Bhutan. Bhutan is a nation heavily reliant on agriculture, but it faces challenges such as geophysical limitations and lack of scientific agricultural practice. The team partnered with a primary end user, Bhutan’s Department of Agriculture (DoA), and with collaborators; the Bhutan Foundation, National Plant Protection Centre (NPPC), Agricultural Research Department Centre (ARDC), National Statistics Bureau (NSB), and the Ugyen Wangchuck Institute for Conservation and Environment Research (UWICER). Advised by NASA SERVIR, the team developed crop masks and monitored rice distribution from 2015 to 2022 utilizing Earth observations such as Landsat 8 Operational Land Imager (OLI), Landsat 9 OLI-2, Sentinel-1 C-Band Synthetic Aperture Radar (C-SAR), Sentinel-2 MultiSpectral Instrument (MSI) and Shuttle Radar Topography Mission (SRTM). The team gathered 5,000 points from the five dzongkhags that yield the most rice in Bhutan (Paro, Punakha, Samtse, Sarpang and Wangue Phodrang) using Collect Earth Online (CEO). With the data collected, the team split the data into training and validation data on Google Earth Engine (GEE) for a random forest (RF) classifier for rice and non-rice classification. After running the data on the Random Forest (RF) model, the team got an accuracy score of 81.48%, a kappa score of 55.75% and an F1 score of 86.11%. This data supports better agricultural decision-making for the governing body of Bhutan, helps enhance farming efficiency and foster sustainable practices, assists in overcoming data inaccuracy and bolsters food security in the country.

Sonam Seldon Tshering↗

NASA NTRSDate not supplied

Sizing, Buckling, and Thermal-Structural Analysis of Tall Lunar Tower

Tall lunar towers enable direct collection of solar energy using solar panels that can generate power exceeding 100-kW above shadowed regions on the surface. Tall lunar towers also support solar reflectors and concentrators for solar farms, which enable various mission architectures on the lunar surface. The Tall Lunar Tower (TLT) project at NASA Langley Research Center is focused on the design, modeling, fabrication, and testing of an assembled TLT Engineering Development Unit (EDU). In this paper, the design and analysis plan of a TLT is presented and predicted buckling and thermal-structural response of the TLT EDU on the lunar surface are investigated.

Kyongchan Song↗

NASA NTRS2023

Rising to the Challenge: Producing and Sustaining a Nutrient-Dense and Climate-Resilient Food Basket for All

Rapidly destabilizing climatic and other biophysical conditions, competition for natural resources, geopolitical conflicts, and market pressures will continue to impose constraints and shocks to the food system, the greatest impacts of which will be felt by nutritionally vulnerable populations. Creating a just, nutritious, and sustainable food system that feeds the world requires a paradigm shift on where, what, and how we grow food while ensuring equitable channels of distribution. Moving forward, we must generate new science, reorient policies, and invest in a suite of environmental, technological, and sociocultural transformations from farm to fork.

Food supply↗