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At least 73 records · Page 4

Declining Global Per Capita Agricultural Production and Warming Oceans Threaten Food Security

Despite accelerating globalization, most people still eat food that was grown locally. Developing countries with weak purchasing power tend to import as little food as possible from global markets, suffering consumption deficits during times of high prices or production declines. Local agricultural production, therefore, is critical to both food security and economic development among the rural poor. The level of local agricultural production, in turn, will be controlled by the amount and quality of arable land, the amount and quality of agricultural inputs (fertilizer, seeds, pesticides, etc.), as well as farm-related technology, practices, and policies. In this paper we discuss several emerging threats to global and regional food security, including declining yield gains that are failing to keep up with population increases, and warming in the tropical Indian Ocean and its impact on rainfall. If yields continue to grow more slowly than per capita harvested area, parts of Africa, Asia, and Central and Southern America will experience substantial declines in per capita cereal production. Global per capita cereal production will potentially decline by 14 percent between 2008 and 2030. Climate change is likely to further affect food production, particularly in regions that have very low yields due to lack of technology. Drought, caused by anthropogenic warming in the Indian and Pacific Oceans, may also reduce 21 st century food availability by disrupting Indian Ocean moisture transports and tilting the 21 st century climate toward a more El Nino-like state. The impacts of these circulation changes over Asia remain uncertain. For Africa, however, Indian Ocean warming appears to have already reduced main growing season rainfall along the eastern edge of tropical Africa, from southern Somalia to northern parts of the Republic of South Africa. Through a combination of quantitative modeling of food balances and an examination of climate change, we present an analysis of emerging threats to global food security.

Funk, Chris C.↗

Circular Economy Contributions to Decarbonizing the US Steel Sector

The potential benefits of the circular economy (CE) for decarbonization have recently attracted much attention in the academic and grey literature. The department of energy (DOE) industrial decarbonization roadmap highlight that in addition to the four pillars (energy efficiency, electrification, low-carbon fuels, feedstocks, and energy sources, and carbon capture, utilization, and storage (CCUS)) identified in the roadmap, "scenarios [...] will need to be developed that incorporate materials efficiency and circular economy strategies". Moreover, the roadmap identifies hard-to-abate CO2 emissions across the five industrial subsectors included in the analysis (iron & steel, chemical, food & beverage, refining, and cement manufacturing). Thus, additional options to decarbonize the industrial sector, like the CE, could prove beneficial to address those hard-to-abate emissions. Moreover, they may be less costly, require less R&D or incentives, and be more readily adopted than other strategies such as energy efficiency and CCUS. While the Industrial Decarbonization Roadmap includes some CE strategies (e.g., the increasing market share of steel from electric arc furnaces - which incorporate steel scrap), a deeper dive into what role the CE could play in the United States (US) industrial decarbonization is needed. In this work, we present several industrial decarbonization scenarios that incorporate materials efficiency and circular economy strategies for the iron & steel subsector. The scenarios identify barriers (including technical limits and constraints), opportunities, and R&D needs.Moreover, we estimate the contribution of those scenarios to reducing the industrial sector's CO2 emissions and their potential synergies with the Industrial Decarbonization Roadmap's four pillars. Iron & steel manufacturing was responsible for 90 million tons of industrial CO2 emissions in 2020 - 7% of the industrial sector's total process- related emissions. Besides recycling - which presents technical limitations due to trace contaminants - CE strategies on the demand side could lower iron & steel manufacturing emissions (e.g., the development of lighter products or business models that encourage a more intensive use). This study reviews barriers, opportunities, and trade-offs for 5 material efficiency strategies. Many topics explored in the review call for further research.

barriers↗

Ecosystem consequences of a nitrogen-fixing proto-organelle

Microscale symbioses can be critical to ecosystem functions, but the mechanisms of these interactions in nature are often cryptic. Here, we use a combination of stable isotope imaging and tracing to reveal carbon (C) and nitrogen (N) exchanges among three symbiotic primary producers that fuel a salmon-bearing river food web. Bulk isotope analysis, nanoSIMS (secondary ion mass spectrometry) isotope imaging, and density centrifugation for quantitative stable isotope probing enabled quantification of organism-specific C- and N-fixation rates from the subcellular scale to the ecosystem. After winters with riverbed-scouring floods, the macroalga Cladophora glomerata uses nutrients in spring runoff to grow streamers up to 10 m long. During summer flow recession, riverine N concentrations wane and Cladophora becomes densely epiphytized by three species of Epithemia, diatoms with N-fixing endosymbionts (proto-organelles) descended from a free-living Crocosphaera cyanobacterium. Over summertime epiphyte succession on Cladophora, N-fixation rates increased as Epithemia spp. became dominant, Cladophora C-fixation declined to near zero, and Epithemia C-fixation increased. Carbon transfer to caddisflies grazing on Cladophora with high densities of Epithemia was 10-fold higher than C transfer to caddisflies grazing Cladophora with low Epithemia loads. In response to demand for N, Epithemia allocates high levels of newly fixed C to its endosymbiont. Consequently, these endosymbionts have the highest rates of C and N accumulation of any taxon in this tripartite symbiosis during the biologically productive season and can produce one of the highest areal rates of N-fixation reported in any river ecosystem.

Marks, Jane C. [Northern Arizona Univ., Flagstaff,↗

Food depot: Apollo-Soyuz test project

The Food Depot operations required to produce the ASTP Food System, the food system and some analysis and recommendations related to future operations are described.

Bourland, C. T.↗

Nominal 30-M Cropland Extent Map of Continental Africa by Integrating Pixel-Based and Object-Based Algorithms Using Sentinel-2 and Landsat-8 Data on Google Earth Engine

A satellite-derived cropland extent map at high spatial resolution (30-m or better) is a must for food and water security analysis. Precise and accurate global cropland extent maps, indicating cropland and non-cropland areas, is a starting point to develop high-level products such as crop watering methods (irrigated or rainfed), cropping intensities (e.g., single, double, or continuous cropping), crop types, cropland fallows, as well as assessment of cropland productivity (productivity per unit of land), and crop water productivity (productivity per unit of water). Uncertainties associated with the cropland extent map have cascading effects on all higher-level cropland products. However, precise and accurate cropland extent maps at high spatial resolution over large areas (e.g., continents or the globe) are challenging to produce due to the small-holder dominant agricultural systems like those found in most of Africa and Asia. Cloud-based Geospatial computing platforms and multi-date, multi-sensor satellite image inventories on Google Earth Engine offer opportunities for mapping croplands with precision and accuracy over large areas that satisfy the requirements of broad range of applications. Such maps are expected to provide highly significant improvements compared to existing products, which tend to be coarser in resolution, and often fail to capture fragmented small-holder farms especially in regions with high dynamic change within and across years. To overcome these limitations, in this research we present an approach for cropland extent mapping at high spatial resolution (30-m or better) using the 10-day, 10 to 20-m, Sentinel-2 data in combination with 16-day, 30-m, Landsat-8 data on Google Earth Engine (GEE). First, nominal 30-m resolution satellite imagery composites were created from 36,924 scenes of Sentinel-2 and Landsat-8 images for the entire African continent in 2015-2016. These composites were generated using a median-mosaic of five bands (blue, green, red, near-infrared, NDVI) during each of the two periods (period 1: January-June 2016 and period 2: July-December 2015) plus a 30-m slope layer derived from the Shuttle Radar Topographic Mission (SRTM) elevation dataset. Second, we selected Cropland/Non-cropland training samples (sample size 9791) from various sources in GEE to create pixel-based classifications. As supervised classification algorithm, Random Forest (RF) was used as the primary classifier because of its efficiency, and when over-fitting issues of RF happened due to the noise of input training data, Support Vector Machine (SVM) was applied to compensate for such defects in specific areas. Third, the Recursive Hierarchical Segmentation (RHSeg) algorithm was employed to generate an object-oriented segmentation layer based on spectral and spatial properties from the same input data. This layer was merged with the pixel-based classification to improve segmentation accuracy. Accuracies of the merged 30-m crop extent product were computed using an error matrix approach in which 1754 independent validation samples were used. In addition, a comparison was performed with other available cropland maps as well as with LULC maps to show spatial similarity. Finally, the cropland area results derived from the map were compared with UN FAO statistics. The independent accuracy assessment showed a weighted overall accuracy of 94, with a producers accuracy of 85.9 (or omission error of 14.1), and users accuracy of 68.5 (commission error of 31.5) for the cropland class. The total net cropland area (TNCA) of Africa was estimated as 313 Mha for the nominal year 2015.

Cropland mapping; cropland areas; 30-m; Landsat-8;↗

Leveraging artificial intelligence and advanced food processing techniques for enhanced food safety, quality, and security: a comprehensive review

Artificial intelligence is emerging as a transformative force in addressing the multifaceted challenges of food safety, food quality, and food security. This review synthesizes advancements in AI-driven technologies, such as machine learning, deep learning, natural language processing, and computer vision, and their applications across the food supply chain, based on a comprehensive analysis of literature published from 1990 to 2024. AI enhances food safety through real-time contamination detection, predictive risk modeling, and compliance monitoring, reducing public health risks. It improves food quality by automating defect detection, optimizing shelf-life predictions, and ensuring consistency in taste, texture, and appearance. Furthermore, AI addresses food security by enabling resource-efficient agriculture, yield forecasting, and supply chain optimization to ensure the availability and accessibility of nutritious food resources. This review also highlights the integration of AI with advanced food processing techniques such as high-pressure processing, ultraviolet treatment, pulsed electric fields, cold plasma, and irradiation, which ensure microbial safety, extend shelf life, and enhance product quality. Additionally, the integration of AI with emerging technologies such as the Internet of Things, blockchain, and AI-powered sensors enables proactive risk management, predictive analytics, and automated quality control. By examining these innovations' potential to enhance transparency, efficiency, and decision-making within food systems, this review identifies current research gaps and proposes strategies to address barriers such as data limitations, model generalizability, and ethical concerns. These insights underscore the critical role of AI in advancing safer, higher-quality, and more secure food systems, guiding future research and fostering sustainable food systems that benefit public health and consumer trust.

AI↗

Future Food Production System Development Pulling from Space Biology Crop Growth Testing in Veggie

Preliminary crop testing using Veggie indicates the environmental conditions provided by the ISS are generally suitable for food crop production. When plant samples were returned to Earth for analysis, their levels of nutrients were comparable to Earth-grown ground controls. Veggie-grown produce food safety microbiology analysis indicated that space-grown crops are safe to consume. Produce sanitizing wipes were used on-orbit to further reduce risk of foodborne illness. Validation growth tests indicated abiotic challenges of insufficient or excess fluid delivery, potentially reduced air flow leading to excess water, elevated CO2 leading to physiological responses, and microorganisms that became opportunistic pathogens. As NASA works to develop future space food production, several areas of research to define these systems pull from the Veggie technology validation tests. Research into effective, reusable water delivery and water recovery methods for future food production systems arises from abiotic challenges observed. Additionally, impacts of elevated CO2 and refinement of fertilizer and light recipes for crops needs to be assessed. Biotic pulls include methods or technologies to effectively sanitize produce with few consumables and low inputs; work to understand the phytomicrobiome and potentially use it to protect crops or enhance growth; selection of crops with high harvest index and desirable flavors for supplemental nutrition; crops that provide psychosocial benefits, and custom space crop development. Planning for future food production in a deep space gateway or a deep space transit vehicle requires methods of handling and storing seeds, and ensuring space seeds are free of contaminants and long-lived. Space food production systems may require mechanization and autonomous operation, with preliminary testing initiated to identify operations and capabilities that are candidates for automation. Food production design is also pulling from Veggie logistics lessons, as we learn about growing at different scales and move toward developing systems that require less launch mass. Veggie will be used as a test bed for novel food production technologies. Veggie is a relatively simple precursor food production system but the knowledge gained from space biology validation tests in Veggie will have far reaching repercussions on future exploration food production.

Veggie↗

Future Food Production System Development Pulling From Space Biology Crop Growth Testing in Veggie

Preliminary crop testing using Veggie indicates the environmental conditions provided by the ISS are generally suitable for food crop production. When plant samples were returned to Earth for analysis, their levels of nutrients were comparable to Earth-grown ground controls. Veggie-grown produce food safety microbiology analysis indicated that space-grown crops are safe to consume. Produce sanitizing wipes were used on-orbit to further reduce risk of foodborne illness. Validation growth tests indicated abiotic challenges of insufficient or excess fluid delivery, potentially reduced air flow leading to excess water, elevated CO2 leading to physiological responses, and microorganisms that became opportunistic pathogens. As NASA works to develop future space food production, several areas of research to define these systems pull from the Veggie technology validation tests. Research into effective, reusable water delivery and water recovery methods for future food production systems arises from abiotic challenges observed. Additionally, impacts of elevated CO2 and refinement of fertilizer and light recipes for crops needs to be assessed. Biotic pulls include methods or technologies to effectively sanitize produce with few consumables and low inputs; work to understand the phytomicrobiome and potentially use it to protect crops or enhance growth; selection of crops with high harvest index and desirable flavors for supplemental nutrition; crops that provide psychosocial benefits, and custom space crop development. Planning for future food production in a deep space gateway or a deep space transit vehicle requires methods of handling and storing seeds, and ensuring space seeds are free of contaminants and long-lived. Space food production systems may require mechanization and autonomous operation, with preliminary testing initiated to identify operations and capabilities that are candidates for automation. Food production design is also pulling from Veggie logistics lessons, as we learn about growing at different scales and move toward developing systems that require less launch mass. Veggie will be used as a test bed for novel food production technologies. Veggie is a relatively simple precursor food production system but the knowledge gained from space biology validation tests in Veggie will have far reaching repercussions on future exploration food production. This work is supported by NASA.

Plants↗

The nutrition advisor expert system

The Nutrition Advisor Expert System (NAES) is an expert system written in the C Language Integrated Production System (CLIPS). NAES provides expert knowledge and guidance into the complex world of nutrition management by capturing the knowledge of an expert and placing it at the user's fingertips. Specifically, NAES enables the user to: (1) obtain precise nutrition information for food items; (2) perform nutritional analysis of meal(s), flagging deficiencies based upon the U.S. Recommended Daily Allowances; (3) predict possible ailments based upon observed nutritional deficiency trends; (4) obtain a top ten listing of food items for a given nutrient; and (5) conveniently upgrade the data base. An explanation facility for the ailment prediction feature is also provided to document the reasoning process.

Huse, Scott M.↗

Hydroxyapatite catalyzed hydrothermal liquefaction transforms food waste from an environmental liability to renewable fuel

Food waste is an abundant and inexpensive resource for the production of renewable fuels. Biocrude yields obtained from hydrothermal liquefaction (HTL) of food waste can be boosted using hydroxyapatite (HAP) as an inexpensive and abundant catalyst. Combining HAP with an inexpensive homogeneous base increased biocrude yield from 14 ± 1 to 37 ± 3%, resulting in the recovery of 49 ± 2% of the energy contained in the food waste feed. Detailed product analysis revealed the importance of fatty-acid oligomerization during biocrude formation, highlighting the role of acid-base catalysts in promoting condensation reactions. Economic and environmental analysis found that the new technology has the potential to reduce US greenhouse gas emissions by 2.6% while producing renewable diesel with a minimum fuel selling price of $1.06/GGE. HAP can play a role in transforming food waste from a liability to a renewable fuel.

09 BIOMASS FUELS↗

Safety Analysis of Soybean Processing for Advanced Life Support

Soybeans (cv. Hoyt) is one of the crops planned for food production within the Advanced Life Support System Integration Testbed (ALSSIT), a proposed habitat simulation for long duration lunar/Mars missions. Soybeans may be processed into a variety of food products, including soymilk, tofu, and tempeh. Due to the closed environmental system and importance of crew health maintenance, food safety is a primary concern on long duration space missions. Identification of the food safety hazards and critical control points associated with the closed ALSSIT system is essential for the development of safe food processing techniques and equipment. A Hazard Analysis Critical Control Point (HACCP) model was developed to reflect proposed production and processing protocols for ALSSIT soybeans. Soybean processing was placed in the type III risk category. During the processing of ALSSIT-grown soybeans, critical control points were identified to control microbiological hazards, particularly mycotoxins, and chemical hazards from antinutrients. Critical limits were suggested at each CCP. Food safety recommendations regarding the hazards and risks associated with growing, harvesting, and processing soybeans; biomass management; and use of multifunctional equipment were made in consideration of the limitations and restraints of the closed ALSSIT.

Hentges, Dawn L.↗

Changing food nitrogen flow in a food-exporting city

Introduction Nitrogen (N) plays a significant role in food systems, but only a fraction of N is effectively utilized and the rest is lost to the environment and negatively affects the ecosystem. So far, there has been relatively little research on N flow associated with the food production and consumption of production-oriented cities in developing countries. Methods In this study, we present a comprehensive analysis of N flow in the food production and consumption system of Changchun in China between 1991 and 2014, and define three types of nitrogen use efficiency (NUE) and compare them. Results (1) Total new N input into the food system in Changchun increased by 63.75% (240.8 to 394.3 Gg N yr −1 ) during the study period, mainly attributable to the high volume of food exports(total output from 47.63 to 72.51 Gg N yr −1 ). (2) Changchun typically exhibited lower apparent NUE and virtual NUE of the food system, while its actual NUE was typically higher, compared to food-importing cities. (3) The consumption of crop food witnessed a decrease from 24.2 Gg N in 1991 to 18.7 Gg N in 2014, whereas the consumption of animal food showed an upward trend from 2.5 Gg N to 7.7 Gg N. Both urban and rural residents consumed less grain food but more fruits and meat. (4) The total N loss has increased from 131.3 Gg N in 1991 to 266.6 Gg N in 2014. The crop production caused 58.1% of the total N loss in 2014, and the atmospheric loss accounted for 40.2% of the total. Conclusion The study has revealed the distinctive features, fluctuations, and underlying drivers of N flow in the food-exporting city, setting it apart from food-importing city. These findings provide a valuable point of reference for the implementation of customized and diversified nitrogen management strategies in these specific urban areas.

Huang, Wei↗

Machine Learning Prototype App For Recognition of Fruits

As the incidence of obesity and associated negative health consequences is rising, it becomes crucial to monitor the dietary choices of individuals. Unfortunately, traditional methods to collect this information involve collecting food frequency questionnaires from individuals using paper. Electronic food trackers have been developed to collect food data, but they require participants to manually label and describe the content of their meals, and which may be difficult for researchers to interpret in a standardized fashion. Machine learning, however, provides an easy and efficient method for both participants and researchers to label food items with standardized descriptions. This project aims to create a prototype phone application that can identify and label photos of apples. This is done by making a machine learning model through Turicreate, a python module, which is then implemented into an iOS app through Xcode and Swift. The modules used in Swift include CoreML and AVFoundation. This machine learning application will be incorporated with a MealLogger phone app that is also under development. The MealLogger app will be used to keep track of participants' calorie intake and other personal details throughout the sleep study. The machine learning model will present several potential identities of the foods found in the photo, and the user will only need to select the correct option. This will be a user-friendly method for participants to easily log their food consumption without the hard work of manually inputting each and every description. Some limitations to this project include the wide variety of food, including those within different cultures. To deal with this, the model will include the most generic food categories, which the participant may select, and produce a drop-down menu of more specific dishes under that specified category, with the option of self-input. Additional questionnaires may be implemented according to the food type selected This will allow the process to be quick and easy, but also specific for the purpose of analysis. The release of the application will require a much longer process, but the machine learning prototype presents a first step toward an application that may change data analysis for researchers interested in collecting food intake from individuals living in the real world.

Food tracker↗

Novel Microgreen Crop Testing for Space

Long-duration missions beyond low-Earth orbit will encounter challenges in maintaining adequate nutrition and crew acceptability in the food system. In situ production of fresh produce can supplement nutrient deficiencies in the prepackaged diet. Currently, there are a relatively small number of crops that can be reliably grown in space for space crop production efforts. An intriguing area of new investigation involves novel types of microgreens that have the potential to be sources of calories, fat, carbohydrates, and protein. These sources of nutrition are not obtainable in significant quantities with current pick and eat crops. Many microgreen cultivars are also sources of nutrients of interest, such as Vitamins B1, C, and K, and elements such as potassium. Microgreens should be selected to address specific nutritional deficits, as identified by NASA’s Human Research Program, with an emphasis on having a diversity of crops to meet nutritional requirements and crew acceptability. To achieve this, the concept of Crop Readiness Level (CRL) has been developed to gauge readiness of crops for spaceflight applications. CRL includes assessing environmental compatibility, food safety considerations, relevant nutritional analysis, and sensory analysis. Recent testing at Kennedy Space Center has focused on advancing the CRL of a variety of novel microgreens. These varieties were grown under 150 µmol m -2 s -1 PPFD from LED lights, 3000 ppm CO 2 , and 23°C to simulate an ISS environment. Crops were harvested and yield was assessed. Then, baseline microbiological and nutritional analysis (Vitamins B1, C, K; mineral analysis; proximate analysis) and sensory evaluation were performed. These baseline data are essential to selecting candidate crops for future missions and assessing crop production hardware and changes in environmental conditions on future crop performance and nutritional quality.

nutrition↗

Extension of Space Food Shelf Life Through Hurdle Approach

The processed and prepackaged space food system is the main source of crew nutrition, and hence central to astronaut health and performance. Unfortunately, space food quality and nutrition degrade to unacceptable levels in two to three years with current food stabilization technologies. Future exploration missions will require a food system that remains safe, acceptable and nutritious through five years of storage within vehicle resource constraints. The potential of stabilization technologies (alternative storage temperatures, processing, formulation, ingredient source, packaging, and preparation procedures), when combined in hurdle approach, to mitigate quality and nutritional degradation is being assessed. Sixteen representative foods from the International Space Station food system were chosen for production and analysis and will be evaluated initially and at one, three, and five years with potential for analysis at seven years if necessary. Analysis includes changes in color, texture, nutrition, sensory quality, and rehydration ratio when applicable. The food samples will be stored at -20 C, 4 C, and 21 C. Select food samples will also be evaluated at -80 C to determine the impacts of ultra-cold storage after one and five years. Packaging film barrier properties and mechanical integrity will be assessed before and after processing and storage. At the study conclusion, if tested hurdles are adequate, formulation, processing, and storage combinations will be uniquely identified for processed food matrices to achieve a five-year shelf life. This study will provide one of the most comprehensive investigations of long duration food stability ever completed, and the achievement of extended food system stability will have profound impacts to health and performance for spaceflight crews and for relief efforts and military applications on Earth.

Cooper, M. R.↗

Influence of Hydroponically Grown Hoyt Soybeans and Radiation Encountered on Mars Missions on the Yield and Quality of Soymilk and Tofu

Soybeans were chosen for hmar and planetary missions due to their nutritive value and ability to produce oil and protein for further food applications. However, soybeans must be processed into foods prior to crew consumption. Wilson et al. (2003) raised questions about (1) the influence of radiation (on germination and functional properties) that the soybeans would be exposed to during bulk storage for a Mars mission, and (2) the impact of using hydroponically grown versus field grown soybeans on the yield and quality of soyfoods. The influence of radiation can be broken down into two components: (A) affect of surface pasteurization to ensure the astronauts safety from food-borne illnesses (a Hazard Analysis Critical Control Point), and (B) affect of the amount of radiation the soybeans receive during a Mars mission. Decreases in the amount of natural antioxidants and free radical formation and oxidation induced changes in the soybean (lipid, protein, etc.) will influence the nutritional value, texture, quality, and safety of soyfoods made from them. The objectives of this project are to (1) evaluate the influence of gamma and electron beam radiation on bulk soybeans (HACCP, CCP) on the microbial load, germination, ease of processing, and quality of soymilk and tofu; (2) provide scale up and mass balance data for Advanced Life Support subsystems including Biomass, Solid Waste Processing, and Water Recovery Systems; and (3) to compare Hoyt field grown to hydroponically grown Hoyt soybeans for soymilk and tofu production. The soybean cultivar Hoyt, a small standing, high protein cultivar that could grow hydroponically in the AIMS facility on Mars) was evaluated for the production of soymilk and tofu. The quality and yield of the soymilk and tofu from hydroponic Hoyt, was compared to Vinton 81 (a soyfood industry standard), field Hoyt, IA 2032LS (lipoxygenase-free), and Proto (high protein and antioxidant potential). Soymilk and tofu were produced using the Japanese method. The soymilk was coagulated with calcium sulfate dihydrate. Soybeans and tofu were evaluated using chemical, microbial, and instrumental sensory methods. The surface radiation of whole dry soybeans using electron beam or gamma rays at 10 or 30 kGy did provide microbial safety for the astronauts. However, these doses caused oxidative changes that resulted in tofu with rancid aroma, darkening of the tofu, lower tofu yields, more solid waste, and loss of the ability of the seeds to germinate. While lower doses may reduce these problems, we lose the ability to insure microbial safety (cross-contamination) of bulk soybeans for the astronauts. Counter measures could include vacuum packaging, radiating under freezing conditions. A No Effect Dose for food quality, below 10 kGy needs to be determined. Better estimates of the radiation that the food will be exposed to need to determined and shared. Appropriate shielding for the food as well as the astronauts needs to be developed. The Hoyt soybean did not provide a high yielding, high quality tofu. A new small scale system for evaluating soybeans was developed using 50 g quantities of soybeans.

Wilson, Lester A.↗