Results for “crop breeding”

NASA NTRS2014

Reconsidering Tree Fruit as Candidate Crops Through the Use of Rapid Cycle Crop Breeding Technologies

Tree fruit, although desirable from a crew nutrition and menu diversity perspective, have long been dismissed as candidate crops based on their long juvenile phase, large architecture, low short-term harvest index, and dormancy requirements. Recent developments in Rapid Cycle Crop Breeding (RCCB) have overcome these historical limitations, opening the door to a new era in candidate crop research. Researchers at the United States Department of Agriculture (USDA) have developed FT-construct (Flowering Locus T) dwarf plum lines that have a very short juvenile phase, vine-like architecture, and no obligate dormancy period. In a collaborative research effort, NASA and the USDA are evaluating the performance of these FT-lines under controlled environment conditions relevant to spaceflight.

PtFT1↗

DOE OSTI2025

Is more better? Polyploidy in crops with diverse end uses and the potential for future applications

Increasing the number of chromosome sets can increase cell size and improve yields in some crops. Breeding polyploid crops introduces unique challenges compared to diploid species, which has deterred many from exploring the potential benefits. Despite this, recent technological advancements have alleviated some of the challenges related to complex genomes and enabled the improvement of many polyploid crops. Given these advancements, there is a need to review the use of higher ploidy crops and explore potential opportunities for increased chromosome number. Many of the leading bioenergy crops are polyploids and there may be additional opportunities to further diversify feedstocks for emerging bioenergy markets. Such diversification would help to meet the anticipated increase in renewable and sustainable energy demands. Here, in this perspective review, we review polyploid crops and the extent to which ploidy level impacts improvement and production. The advantages and disadvantages of each crop are discussed in the context of their ploidy level and end-use. Particular emphasis is given to the current role and potential of polyploidy in creating the next generation of bioenergy feedstocks. Polyploids present challenges to crop improvement due to their complex genomes, but many of these difficulties can and have been overcome with technological advancements. Approaches that facilitate the use of higher ploidy crops open a path to capturing the many benefits of polyploidy, such as increased fruit and seed size, vigour, diversity, biomass and yield quality. However, these benefits are not observed across all species. This further emphasizes the need to study higher ploidy in traditionally diploid crops.

bioenergy↗

DOE OSTI2024

Data‐driven identification of environmental variables influencing phenotypic plasticity to facilitate breeding for future climates

Summary Phenotypic plasticity describes a genotype's ability to produce different phenotypes in response to different environments. Breeding crops that exhibit appropriate levels of plasticity for future climates will be crucial to meeting global demand, but knowledge of the critical environmental factors is limited to a handful of well‐studied major crops. Using 727 maize ( Zea mays L.) hybrids phenotyped for grain yield in 45 environments, we investigated the ability of a genetic algorithm and two other methods to identify environmental determinants of grain yield from a large set of candidate environmental variables constructed using minimal assumptions. The genetic algorithm identified pre‐ and postanthesis maximum temperature, mid‐season solar radiation, and whole season net evapotranspiration as the four most important variables from a candidate set of 9150. Importantly, these four variables are supported by previous literature. After calculating reaction norms for each environmental variable, candidate genes were identified and gene annotations investigated to demonstrate how this method can generate insights into phenotypic plasticity. The genetic algorithm successfully identified known environmental determinants of hybrid maize grain yield. This demonstrates that the methodology could be applied to other less well‐studied phenotypes and crops to improve understanding of phenotypic plasticity and facilitate breeding crops for future climates.

Kusmec, Aaron↗

DOE OSTI2026

Optimizing resource allocation in Miscanthus breeding via sparse testing designs for genomic prediction

Phenotyping high-biomass perennial crops is laborious and the rate of genetic gain in conventional perennial crop breeding programs is typically low. So, it is especially important to identify methods that produce efficiency gains in the breeding process. Miscanthus is a C4 perennial grass with favorable characteristics for producing biomass as a feedstock for biofuels and diverse bio-based products. Increasing biomass yield will increase profitability and environmental benefits, so it is a key target for Miscanthus breeding. In addition, the identification of well-adapted genotypes across a wide range of environmental conditions requires the establishment of multi-environment trials (METs). Sparse testing is a genomic prediction-based strategy that reduces the phenotyping costs in METs by selecting a subset of genotypes to evaluate in a subset of environments and then predicts the performance of the unobserved genotype-environment combinations. A Miscanthus sacchariflorus (MSA) population comprising 336 genotypes observed across three environments was analyzed implementing sparse testing designs. Three prediction models considering main effects (environments, genotypes, genomic) and interaction effects (genotype-by-environment; G×E interaction) were implemented for forecasting dry biomass yield (YDY), total culm (TCM), average internode length (AIL), and culm node number (CNN). Multiple calibration sets based on different compositions and sizes were considered to evaluate performance in terms of the predictive ability (PA) and the mean square error (MSE) for a fixed testing set size. The training set size ranged from 52 to 112 to predict a fixed set of 224 unobserved genotypes across all three environments. The results showed that the model accounting for G×E interaction consistently presented the highest PA and the lowest MSE: for CNN (PA: ~0.77, MSE: ~0.5) and YDY (PA: ~0.70, MSE: ~1.3) while for TCM and AIL these ranged from ~0.28 to 0.41 and ~1.3 to 4.3, respectively. Overall, varying training sets and allocation strategies did not affect PA and MSE, with 52 non-overlapping and 0 overlapping genotypes per environment as the optimal cost-effective allocation framework. This suggests that implementing sparse testing designs could significantly reduce phenotyping costs by fivefold, without compromising PA in breeding programs for perennial crops such as Miscanthus.

Miscanthus sacchariflorus (MSA)↗

DOE OSTI2023

A large sequenced mutant library – valuable reverse genetic resource that covers 98% of sorghum genes

SUMMARY Mutant populations are crucial for functional genomics and discovering novel traits for crop breeding. Sorghum , a drought and heat‐tolerant C4 species, requires a vast, large‐scale, annotated, and sequenced mutant resource to enhance crop improvement through functional genomics research. Here, we report a sorghum large‐scale sequenced mutant population with 9.5 million ethyl methane sulfonate (EMS)‐induced mutations that covered 98% of sorghum's annotated genes using inbred line BTx623. Remarkably, a total of 610 320 mutations within the promoter and enhancer regions of 18 000 and 11 790 genes, respectively, can be leveraged for novel research of cis ‐regulatory elements. A comparison of the distribution of mutations in the large‐scale mutant library and sorghum association panel (SAP) provides insights into the influence of selection. EMS‐induced mutations appeared to be random across different regions of the genome without significant enrichment in different sections of a gene, including the 5′ UTR, gene body, and 3′‐UTR. In contrast, there were low variation density in the coding and UTR regions in the SAP. Based on the K a / K s value, the mutant library (~1) experienced little selection, unlike the SAP (0.40), which has been strongly selected through breeding. All mutation data are publicly searchable through SorbMutDB ( https://www.depts.ttu.edu/igcast/sorbmutdb.php ) and SorghumBase ( https://sorghumbase.org/ ). This current large‐scale sequence‐indexed sorghum mutant population is a crucial resource that enriched the sorghum gene pool with novel diversity and a highly valuable tool for the Poaceae family, that will advance plant biology research and crop breeding.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRSDate not supplied

Selection Factors for Space Crops

NASA is actively researching space crop production to determine its potential to contribute to food system security on long duration missions beyond Low Earth Orbit. Our near-term focus is on nutrient and variety supplementation of prepackaged food with fresh produce that requires little or no processing. The longer-term goal is caloric replacement to become less dependent on Earth, and this will require cultivation of staple crops, processing and cooking equipment, integration with spacecraft air, water, and power systems, and automation. There are numerous technology and knowledge gaps remaining for sustainable space crop production systems, but one high-impact area is in the development of crops specifically customized to meet the needs of controlled environment crop production, astronaut health and well-being, and space-unique environments. Modern crop breeding and genome engineering tools are allowing for rapid development of new genotypes with incredible specificity. Targeted aspects to optimize crops for space have been identified and characterized into five categories: plant growth and development, plant physiology, produce nutrition, produce organoleptic acceptability, and postharvest characteristics. Within each category there are several targets that further the development of crop production systems for spaceflight, such as crop size and harvest index, tolerance to specific environmental stresses, optimizing target nutrients that are low or degrade in the packaged diet, maintenance time requirements, and less indigestible structural material. NASA-funded PIs are already beginning to develop candidate crops, and spaceflight testing and validation of novel space crops is on the horizon. Crops developed for space also have the potential to benefit terrestrial controlled environment agriculture crop production systems. This research was supported by NASA’s Space Biology and Human Research Programs.

Space Crop Production↗

NASA NTRSDate not supplied

Selection Factors for Space Crops

NASA is actively researching space crop production to determine its potential to contribute to food system security on long duration missions beyond Low Earth Orbit. Our near-term focus is on nutrient and variety supplementation of prepackaged food with fresh produce that requires little or no processing. The longer-term goal is caloric replacement to become less dependent on Earth, and this will require cultivation of staple crops, processing and cooking equipment, integration with spacecraft air, water, and power systems, and automation. There are numerous technology and knowledge gaps remaining for sustainable space crop production systems, but one high-impact area is in the development of crops specifically customized to meet the needs of controlled environment crop production, astronaut health and well-being, and space-unique environments. Modern crop breeding and genome engineering tools are allowing for rapid development of new genotypes with incredible specificity. Targeted aspects to optimize crops for space have been identified and characterized into five categories: plant growth and development, plant physiology, produce nutrition, produce organoleptic acceptability, and postharvest characteristics. Within each category there are several targets that further the development of crop production systems for spaceflight, such as crop size and harvest index, tolerance to specific environmental stresses, optimizing target nutrients that are low or degrade in the packaged diet, maintenance time requirements, and less indigestible structural material. NASA-funded PIs are already beginning to develop candidate crops, and spaceflight testing and validation of novel space crops is on the horizon. Crops developed for space also have the potential to benefit terrestrial controlled environment agriculture crop production systems. This research was supported by NASA’s Space Biology and Human Research Programs.

Space Crop Production↗

DOE OSTI2024

Major impacts of widespread structural variation on sorghum

Genetic diversity is critical to crop breeding and improvement, and dissection of the genomic variation underlying agronomic traits can both assist breeding and give insight into basic biological mechanisms. Although recent genome analyses in plants reveal many structural variants (SVs), most current studies of crop genetic variation are dominated by single-nucleotide polymorphisms (SNPs). The extent of the impact of SVs on global trait variation, as well as their utility in genome-wide selection, is not yet understood. In this study, we built an SV data set based on whole-genome resequencing of diverse sorghum lines (n = 363), validated the correlation of photoperiod sensitivity and variety type, and identified SV hotspots underlying the divergent evolution of cellulosic and sweet sorghum. In addition, we showed the complementary contribution of SVs for heritability of traits related to sorghum adaptation. Importantly, inclusion of SV polymorphisms in association studies revealed genotype–phenotype associations not observed with SNPs alone. Three-way genome-wide association studies (GWAS) based on whole-genome SNP, SV, and integrated SNP + SV data sets showed substantial associations between SVs and sorghum traits. The addition of SVs to GWAS substantially increased heritability estimates for some traits, indicating their important contribution to functional allelic variation at the genome level. Our discovery of the widespread impacts of SVs on heritable gene expression variation could render a plausible mechanism for their disproportionate impact on phenotypic variation. This study expands our knowledge of SVs and emphasizes the extensive impacts of SVs on sorghum.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1990

Cloning crops in a CELSS via tissue culture: Prospects and problems

Micropropagation is currently used to clone fruits, nuts, and vegetables and involves controlling the outgrowth in vitro of basal, axillary, or adventitious buds. Following clonal multiplication, shoots are divided and rooted. This process has greatly reduced space and energy requirements in greenhouses and field nurseries and has increased multiplication rates by greater than 20 fold for some vegetatively propagated crops and breeding lines. Cereal and legume crops can also be cloned by tissue culture through somatic embryogenesis. Somatic embryos can be used to produce 'synthetic seed', which can tolerate desiccation and germinate upon rehydration. Synthetic seed of hybrid wheat, rice, soybean and other crops could be produced in a controlled ecological life support system. Thus, yield advantages of hybreds over inbreds (10 to 20 percent) could be exploited without having to provide additional facilities and energy for parental-line and hybrid seed nurseries.

Carman, John G.↗

DOE OSTI2024

Integrating multi-modal remote sensing, deep learning, and attention mechanisms for yield prediction in plant breeding experiments

In both plant breeding and crop management, interpretability plays a crucial role in instilling trust in AI-driven approaches and enabling the provision of actionable insights. The primary objective of this research is to explore and evaluate the potential contributions of deep learning network architectures that employ stacked LSTM for end-of-season maize grain yield prediction. A secondary aim is to expand the capabilities of these networks by adapting them to better accommodate and leverage the multi-modality properties of remote sensing data. In this study, a multi-modal deep learning architecture that assimilates inputs from heterogeneous data streams, including high-resolution hyperspectral imagery, LiDAR point clouds, and environmental data, is proposed to forecast maize crop yields. The architecture includes attention mechanisms that assign varying levels of importance to different modalities and temporal features that, reflect the dynamics of plant growth and environmental interactions. The interpretability of the attention weights is investigated in multi-modal networks that seek to both improve predictions and attribute crop yield outcomes to genetic and environmental variables. This approach also contributes to increased interpretability of the model's predictions. The temporal attention weight distributions highlighted relevant factors and critical growth stages that contribute to the predictions. The results of this study affirm that the attention weights are consistent with recognized biological growth stages, thereby substantiating the network's capability to learn biologically interpretable features. Accuracies of the model's predictions of yield ranged from 0.82-0.93 R 2 ref in this genetics-focused study, further highlighting the potential of attention-based models. Further, this research facilitates understanding of how multi-modality remote sensing aligns with the physiological stages of maize. The proposed architecture shows promise in improving predictions and offering interpretable insights into the factors affecting maize crop yields, while demonstrating the impact of data collection by different modalities through the growing season. By identifying relevant factors and critical growth stages, the model's attention weights provide valuable information that can be used in both plant breeding and crop management. The consistency of attention weights with biological growth stages reinforces the potential of deep learning networks in agricultural applications, particularly in leveraging remote sensing data for yield prediction. To the best of our knowledge, this is the first study that investigates the use of hyperspectral and LiDAR UAV time series data for explaining/interpreting plant growth stages within deep learning networks and forecasting plot-level maize grain yield using late fusion modalities with attention mechanisms.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Impact of genotype‐calling methodologies on genome‐wide association and genomic prediction in polyploids

Abstract Discovery and analysis of genetic variants underlying agriculturally important traits are key to molecular breeding of crops. Reduced representation approaches have provided cost‐efficient genotyping using next‐generation sequencing. However, accurate genotype calling from next‐generation sequencing data is challenging, particularly in polyploid species due to their genome complexity. Recently developed Bayesian statistical methods implemented in available software packages, polyRAD, EBG, and updog, incorporate error rates and population parameters to accurately estimate allelic dosage across any ploidy. We used empirical and simulated data to evaluate the three Bayesian algorithms and demonstrated their impact on the power of genome‐wide association study (GWAS) analysis and the accuracy of genomic prediction. We further incorporated uncertainty in allelic dosage estimation by testing continuous genotype calls and comparing their performance to discrete genotypes in GWAS and genomic prediction. We tested the genotype‐calling methods using data from two autotetraploid species, Miscanthus sacchariflorus and Vaccinium corymbosum , and performed GWAS and genomic prediction. In the empirical study, the tested Bayesian genotype‐calling algorithms differed in their downstream effects on GWAS and genomic prediction, with some showing advantages over others. Through subsequent simulation studies, we observed that at low read depth, polyRAD was advantageous in its effect on GWAS power and limit of false positives. Additionally, we found that continuous genotypes increased the accuracy of genomic prediction, by reducing genotyping error, particularly at low sequencing depth. Our results indicate that by using the Bayesian algorithm implemented in polyRAD and continuous genotypes, we can accurately and cost‐efficiently implement GWAS and genomic prediction in polyploid crops.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1997

Selection of Cultivars for use in Controlled Environment Life Support System (CELSS) Human Rated Test Facility (HRTF) Trials

The aims under this training grant, as under the subsequent fellowship, were to elaborate the theory and technique of cultivar evaluation for specialized controlled environments, then to employ the technique on selected crops, ultimately conducting cultivar trials, and making the knowledge gained available for use in NASA's space program. We undertook a comprehensive search of the Cornell agricultural library (Mann library) and its data-bases for any and all material relating to cultivar evaluation of vegetable crops, and also developed the logic of how to go about narrowing down the field of contending cultivars when undertaking cultivar trials. The results of this work, the principal outcome of the grant, are reflected in his MS thesis, particularly in Chapter 2, "Commercial and Scientific Literature," and even more so in Chapter 8, "Selecting cultivars and lines for screening." David also attended annual conferences of vegetable crop plant breeders, annual yield trials and breeding trials for vegetable crops, as well as relevant professional conferences such as the ASHS annual meetings, and the others.

Langhans, Robert W.↗

NASA NTRSDate not supplied

Space Crop Production Gaps and Challenges

As astronauts venture farther from Earth, and stay for longer periods, the space food system will increase in importance. Crop production can supplement a pre-packaged space diet to provide nutrition and dietary variety for space crews. In future missions, bioregenerative approaches may be used to generate a larger percentage of the diet, as well as help to reduce life support system burdens and resupply from Earth. Plants may also provide behavioral health benefits to crew members living in the isolated, confined environment of a space habitat. A number of unique challenges exist for growth of plants in microgravity and on other reduced gravity surfaces like the moon and Mars. Testing plant growth inside the Veggie and Advanced Plant Habitat (APH) chambers on the International Space Station is allowing us to understand the impacts of gravity and spaceflight on crop growth, nutritional content, acceptability, and the importance of plants to astronauts living and working away from Earth. We are also gaining a better understanding of food safety concerns and the behavior of space plant microbiomes and plant pathogens, but major gaps in knowledge remain. As we move from research towards operational space crop production to enable exploration, there are numerous gaps in technology, knowledge, and practice related to space crop growth that must be addressed. Research and development in key focus areas such as effective water and nutrient delivery at variable gravity levels, autonomous plant health monitoring, growth system cleaning and disinfection, and selection of ideal space crops are needed to fill these gaps. Breeding or engineering custom space crops may impact areas including plant growth and development, plant physiology, produce nutrition, organoleptic acceptability, and post-harvest characteristics, and these may further enable space crop production scenarios. Space crop challenges are multifaceted and require diverse interdisciplinary teams working together to develop effective solutions. Solving these requires an array of skill sets from across the biological and physical sciences, engineering, and human social sciences. Solutions to help ensure food security off-Earth may also translate to more sustainable terrestrial crop production approaches, and regular dialog between industry, academia, and government organizations working in related fields benefit all. Additional help can come from engagement with student researchers at various levels through courses, participatory science projects, and open science activities which can provide useful data. Global coordination and integration between space agencies and partners will be essential.

Gioia Donna Massa↗

NASA NTRSDate not supplied

Space Crop Production Gaps and Challenges

As astronauts venture farther from Earth, and stay for longer periods, the space food system will increase in importance. Crop production can supplement a pre-packaged space diet to provide nutrition and dietary variety for space crews. In future missions, bioregenerative approaches may be used to generate a larger percentage of the diet, as well as help to reduce life support system burdens and resupply from Earth. Plants may also provide behavioral health benefits to crew members living in the isolated, confined environment of a space habitat. A number of unique challenges exist for growth of plants in microgravity and on other reduced gravity surfaces like the moon and Mars. Testing plant growth inside the Veggie and Advanced Plant Habitat (APH) chambers on the International Space Station is allowing us to understand the impacts of gravity and spaceflight on crop growth, nutritional content, acceptability, and the importance of plants to astronauts living and working away from Earth. We are also gaining a better understanding of food safety concerns and the behavior of space plant microbiomes and plant pathogens, but major gaps in knowledge remain. As we move from research towards operational space crop production to enable exploration, there are numerous gaps in technology, knowledge, and practice related to space crop growth that must be addressed. Research and development in key focus areas such as effective water and nutrient delivery at variable gravity levels, autonomous plant health monitoring, growth system cleaning and disinfection, and selection of ideal space crops are needed to fill these gaps. Breeding or engineering custom space crops may impact areas including plant growth and development, plant physiology, produce nutrition, organoleptic acceptability, and post-harvest characteristics, and these may further enable space crop production scenarios. Space crop challenges are multifaceted and require diverse interdisciplinary teams working together to develop effective solutions. Solving these requires an array of skill sets from across the biological and physical sciences, engineering, and human social sciences. Solutions to help ensure food security off-Earth may also translate to more sustainable terrestrial crop production approaches, and regular dialog between industry, academia, and government organizations working in related fields benefit all. Additional help can come from engagement with student researchers at various levels through courses, participatory science projects, and open science activities which can provide useful data. Global coordination and integration between space agencies and partners will be essential.

Gioia Massa↗

DOE OSTI2025

Which Plant Traits Increase Soil Carbon Sequestration? Empirical Evidence From a Long‐Term Poplar Genetic Diversity Trial

Plants play a key role in mediating soil response to global change, and breeding or engineering crops to increase soil organic carbon (SOC) storage is a potential route to land-based carbon dioxide removal in agricultural systems. However, due to limited observational datasets plus shifting paradigms of SOC stabilization, it is unclear which plant traits are most important for enhancing different types of soil organic matter. Existing long-term common gardens of genetically diverse plant populations may provide an opportunity to evaluate biological controls on SOC, separate from environmental or management variability. Here we report on soil and root chemical data collected for 24 genotypes within a 13-year-old common garden in northwestern Oregon planted with a large natural variant population of Populus trichocarpa. Fractionating surface soil (0–15 cm) revealed substantial variation in stocks of mineral-associated organic matter (MAOM; 18–67 t C/ha) and particulate organic matter (POM; 2–22 t C/ha). Tree genotype explained 24% and 26% of the MAOM and POM stock variability, respectively, after controlling for background variability. We found minimal association between SOC concentration and either aboveground tree productivity or root biomass recalcitrance (C/N ratios and lignin content). In contrast, root elemental content appeared influential for MAOM-C concentration, which showed a strong positive association with root aluminum (Al) and a strong negative association with root boron (B) and magnesium (Mg). Furthermore, root concentrations of these elements were highly heritable (57%–78%) and not simply a reflection of background variation in soil elemental concentrations. We estimate that surface SOC stocks under these 24 genotypes have diverged at rates of up to 1.2–4.3 t C/ha/year. These results suggest that long-term genetic diversity trials have value for elucidating biological controls on soil organic matter dynamics, and that traits associated with root elemental content may be a useful target for enhancing biosequestration.

biomass recalcitrance↗

DOE OSTI2024

Exploring genetic diversity, population structure, and subgenome differences in the allopolyploid Camelina sativa : implications for future breeding and research studies

Abstract Camelina (Camelina sativa), an allohexaploid species, is an emerging aviation biofuel crop that has been the focus of resurgent interest in recent decades. To guide future breeding and crop improvement efforts, the community requires a deeper comprehension of subgenome dominance, often noted in allopolyploid species, “alongside an understanding of the genetic diversity” and population structure of material present within breeding programs. We conducted population genetic analyses of a C. sativa diversity panel, leveraging a new genome, to estimate nucleotide diversity and population structure, and analyzed for patterns of subgenome expression dominance among different organs. Our analyses confirm that C. sativa has relatively low genetic diversity and show that the SG3 subgenome has substantially lower genetic diversity compared to the other two subgenomes. Despite the low genetic diversity, our analyses identified 13 distinct subpopulations including two distinct wild populations and others putatively representing founders in existing breeding populations. When analyzing for subgenome composition of long non-coding RNAs, which are known to play important roles in (a)biotic stress tolerance, we found that the SG3 subgenome contained significantly more lincRNAs compared to other subgenomes. Similarly, transcriptome analyses revealed that expression dominance of SG3 is not as strong as previously reported and may not be universal across all organ types. From a global analysis, SG3 “was only significant higher expressed” in flower, flower bud, and fruit organs, which is an important discovery given that the crop yield is associated with these organs. Collectively, these results will be valuable for guiding future breeding efforts in camelina.

Agriculture↗

DOE OSTI2025

Scaffolded and annotated nuclear and organelle genomes of the North American brown alga Saccharina latissima

Increasing the genomic resources of emerging aquaculture crop targets can expedite breeding processes as seen in molecular breeding advances in agriculture. High quality annotated reference genomes are essential to implement this relatively new molecular breeding scheme and benefit research areas such as population genetics, gene discovery, and gene mechanics by providing a tool for standard comparison. The brown macroalga Saccharina latissima (sugar kelp) is an ecologically and economically important kelp that is found in both the northern Pacific and Atlantic Oceans. Cultivation of Saccharina latissima for human consumption has increased significantly this century in both North America and Europe, and its single blade morphology allows for dense seeding practices used in the cultivation of its Asian sister species, Saccharina japonica. While Saccharina latissima has potential as a human food crop, insufficient information from genetic resources has limited molecular breeding in sugar kelp aquaculture. We present scaffolded and annotated Saccharina latissima nuclear and organelle genomes from a female gametophyte collected from Black Ledge, Groton, Connecticut. This Saccharina latissima genome compares well with other published kelp genomes and contains 218 scaffolds with a scaffold N50 of 1.35 Mb, a GC content of 49.84%, and 25,012 predicted genes. We also validated this genome by comparing the synteny and completeness of this Saccharina latissima genome to other kelp genomes. Our team has successfully performed initial genomic selection trials with sugar kelp using a draft version of this genome. This Saccharina latissima genome expands the genetic toolkit for the economically and ecologically important sugar kelp and will be a fundamental resource for future foundational science, breeding, and conservation efforts.

DeWeese, Kelly↗

NASA NTRS2009

Roadmaps and Strategies for Crop Research for Bioregenerative Life Support Systems A Compilation of Findings from NASA’s Advanced Life Support Meetings

Extensive testing with plants for bioregenerative life support systems has been conducted by NASA for nearly 40 years, both through university grants and work at NASA field centers. During this time, numerous meetings were held to develop strategies and roadmaps for implementing bioregenerative life support systems. Findings from several of these meetings are summarized in this report. In nearly all cases, the recommendations included an active ground-based research program and integration tests with other life support subsystems, followed by eventual spaceflight testing. The most recent roadmap of NASA’s Exploration Life Support Crop Element suggests a sequence of first developing a modular vegetable production unit (VPU) to provide perishable foods to supplement the crew’s diet. A similar system could then be used on the lunar surface, with additional modules added as the lunar outpost expands. Eventually, these modules could be transferred to a dedicated pressurized logistics module (PLM) for crop production. Experience from the lunar tests could then be used to conduct a similar buildup for Mars missions, where in situ food production and bioregeneration would be important for achieving outpost autonomy. To date, most trade studies of bioregenerative life support systems indicate that reducing the costs associated with crop lighting systems are key, and use of light-emitting diodes (LEDs) or direct solar lighting offers promising options. Likewise, sustaining high yields and high harvest index (% edible biomass) will be important for minimizing costs, and this can be achieved by optimizing growth environments and through selecting, breeding, and genetically engineering crops suitable for space environments. Collectively, these strategies and roadmaps suggest that a combined approach of fundamental research, hardware (plant chamber) development, and operational testing is required to achieve reliable bioregenerative life support systems.

Bioregenerative↗