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At least 145 records · Page 8

Suggestions for crops grown in controlled ecological life-support systems, based on attractive vegetarian diets

Assuming that crops grown in controlled ecological life-support systems (CELSS) should provide a basis for meals that are both nutritious and attractive (to taste and vision), and that CELSS diets on the moon or Mars or in space-craft during long voyages will have to be mostly vegetarian, a workshop was convened at the Johnson Space Center, Houston, Texas, U.S.A. on 19 to 21 January, 1994. Participants consisted of trained nutritionists and others; many of the approximately 18 presenters who discussed possible diets were practicing vegetarians, some for more than two decades. Considering all the presentations, seven conclusions (or points for discussion) could be formulated: nutritious vegetarian diets are relatively easily to formulate, vegetarian diets are healthy, variety is essential in vegetarian diets, some experiences (e.g., Bios-3 and Biosphere 2) are relevant to planning of CELSS diets, physical constraints will limit the choice of crops, a preliminary list of recommended crops can be formulated, and this line of research has some potential practical spinoffs. The list of crops and the reasons for including specific crops might be of interest to professionals in the field of health and nutrition as well as to those who are designing closed ecological systems.

NASA Program CELSS↗

Impacts of El Nino Southern Oscillation on the Global Yields of Major Crops

The monitoring and prediction of climate-induced variations in crop yields, production and export prices in major food-producing regions have become important to enable national governments in import-dependent countries to ensure supplies of affordable food for consumers. Although the El Nino/Southern Oscillation (ENSO) often affects seasonal temperature and precipitation, and thus crop yields in many regions, the overall impacts of ENSO on global yields are uncertain. Here we present a global map of the impacts of ENSO on the yields of major crops and quantify its impacts on their global-mean yield anomalies. Results show that El Nino likely improves the global-mean soybean yield by 2.15.4 but appears to change the yields of maize, rice and wheat by -4.3 to +0.8. The global-mean yields of all four crops during La Nina years tend to be below normal (-4.5 to 0.0).Our findings highlight the importance of ENSO to global crop production.

Crops↗

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

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

crop-model ensembles↗

VEG-04 PICK-AND-EAT CROP PRODUCTION AND HUMAN RESEARCH ON THE INTERNATIONAL SPACE STATION

Growing fresh, nutritious, palatable produce for crew consumption during spaceflight may provide health-promoting, bioavailable nutrients and enhance the astronaut dietary experience as we move toward longer-duration missions. Tending plants may also serve as a countermeasure for crew psychological stresses associated with spaceflight. However, requirements to support consistent growth of a variety of nutritious crops under spaceflight environmental conditions remain unclear. This study explores the potential to grow crops for consumption on the International Space Station (ISS) using the Veggie vegetable-production system. VEG-04A and B were two flight tests conducted in 2019 with the leafy green crop Mizuna mustard. Mizuna was grown in two Veggie chambers simultaneously, with the chambers set to different red-to-blue light formulations; one Veggie was programmed as “red-rich” and the second as “blue-rich.” Light quality is known to impact plant growth, nutrition, microbiology, and organoleptic characteristics on Earth, and the Veggie flight tests examined how these impacts might differ in microgravity. VEG-04A was a 35-day growth test with a single harvest. VEG-04B, a 58-day test with harvests at four, six, and eight weeks from the same plants, assessed sustained productivity. Challenges with the watering program occurred early during VEG-04A, and several plants failed to survive in both the flight and ground control operations. Thus, prior to VEG-04B, an extra test was conducted to tailor water timing and volumes. This test allowed a fine tuning of methods for VEG-04B, and generally plant survival was better in that experiment. At each harvest, the astronauts froze half of the edible plant tissue to return to Earth and weighed the remaining half using the ISS Mass Measurement Device (MMD). Weighed samples were then cleaned with produce-sanitizing wipes, and consenting crew members participated in organoleptic evaluation of the fresh produce. Organoleptic evaluations were conducted on the Mizuna crops grown in both light treatments, and data from these tests are compared to ground data collected at JSC. The remaining sanitized produce was available for crew consumption as desired. Frozen flight samples were returned for microbial and chemical analyses to assess food safety and nutritional quality. Microbial assessments included culturing and identifying aerobic bacteria, yeasts, and molds, and screening for specific human pathogens. Chemical nutrient analyses included assessing elements, antioxidants, and phenolics in plant tissues. Crew members involved in plant operations completed behavioral health surveys pre-flight, in-flight associated with plant growth and harvest activities, and post-flight. Surveys captured the amount of time spent on different plant-related operations, enjoyment of the different activities, engagement with Veggie, experience interacting with Veggie, and sensory stimulation associated with growing plants in Veggie. Within each study, plant growth did not differ across light treatment or location (flight versus ground). In general, more biomass was produced in most treatments during the longer study, but growth of this crop declined over time with the repeated harvests. On average, bacterial and fungal counts were significantly lower on ground control samples than flight samples, and microbial counts increased with repeated harvests. Light treatment did not influence any elements in tissues tested; however, the growth duration did impact levels of several elements. Organoleptic scores were generally higher in flight, and ground tasters considered samples more bitter. Amount of interaction and responses to Veggie varied widely by individual. Enjoyable tasks had higher impact than non-enjoyable tasks and interacting with Veggie was generally viewed as positive. These tests on ISS are helping to mitigate the risk of an inadequate food supply for long-duration missions by adding fresh vegetables and key nutrients to the crew diet, and indicating which plant care activities are providing behavioral health benefits for the crew. This research was co-funded by the Human Research Program and Space Biology (MTL#1075) in the ILSRA 2015 NRA call. Videos due Jan. 25th.

Veggie↗

Climate Impacts on Global Agriculture Emerge Earlier in New Generation of Climate and Crop Models

Potential climate-related impacts on future crop yield are a major societal concern. Previous projections of the Agricultural Model Intercomparison and Improvement Project’s Global Gridded Crop Model Intercomparison based on the Coupled Model Intercomparison Project Phase 5 identified substantial climate impacts on all major crops, but associated uncertainties were substantial. Here we report new twenty-first-century projections using ensembles of latest-generation crop and climate models. Results suggest markedly more pessimistic yield responses for maize, soybean and rice compared to the original ensemble. Mean end-of-century maize productivity is shifted from +5% to −6% (SSP126) and from +1% to −24% (SSP585)—explained by warmer climate projections and improved crop model sensitivities. In contrast, wheat shows stronger gains (+9% shifted to +18%, SSP585), linked to higher CO 2 concentrations and expanded high-latitude gains. The ‘emergence’ of climate impacts consistently occurs earlier in the new projections—before 2040 for several main producing regions. While future yield estimates remain uncertain, these results suggest that major breadbasket regions will face distinct anthropogenic climatic risks sooner than previously anticipated.

crop model↗

Heat Stress to Jeopardize Crop Production in the US Corn Belt Based on Downscaled CMIP5 Projections

CONTEXT Global food security faces increasing challenges from the changing climate. Changes of agricultural output from some of the most productive regions such as the US Corn Belt can largely affect the world's food market. Developing predictive understanding of the agricultural risk of climate change and potential mitigation strategies is critical for the global food security. OBJECTIVE The objective of this study is to assess the responses of maize and soybean yield to projected climate changes in the Corn Belt, identify the shifting environment stressors on crop yield, and tackle potential climate adaptation strategies. METHODS We drive a process-based model, the Decision Support System for Agrotechnology Transfer, with high-resolution statistically downscaled and bias-corrected historical and future climates from ten CMIP5 models in the MACA-2 database. RESULTS AND CONCLUSIONS The multi-model ensemble mean suggests a 12% decrease of maize yield by mid-century and 40% by late century, with a high degree of model consensus in the direction of changes; for individual models, the projected decrease of maize yield by late century ranges from <5% to over 80%, with the worst crop outcome corresponding to the most sensitive climate models. Soybean yield is projected to increase by midcentury with a high degree of model consensus, but such consensus is lost by late century as some projections shift to significant decreases. Crop yield in the Corn Belt is currently limited by water stress, but is projected to be increasingly limited by heat stress as well after the midcentury. The mounting heat stress will drive the most productive zone for maize to shift from central to northern part of the Corn Belt, but the projected increase in the northern states cannot fully compensate for the decrease in the south, causing the total production to decrease if agricultural practice stays the same. Earlier planting can alleviate only a small fraction of the heat-induced crop loss in a warmer climate. Climate change will (at least partially) offset the yield boost caused by agricultural technology and intensification. SIGNIFICANCE This study advances our predictive understanding of crop yield responses to climate change, and suggests that a multitude of strategies will be needed to address the climate change challenges for the U.S. agriculture.

Crop yield↗

Northern Brazil Agriculture: Measuring Soybean Yields in Northern Brazil During El Niño-Southern Oscillation Conditions to Evaluate Trends in Agricultural Production and Support Crop Forecasting, 1984 – 2023

As one of the largest agricultural exporters in the world, Brazil’s crop productivity is highly influential to the world’s food supply. Crop productivity across Brazil is heavily influenced by climatic factors, such as the El Niño-Southern Oscillation (ENSO), which drives spatially heterogenous effects on growing conditions. To understand the relationship between ENSO conditions and staple crop productivity, the team used 1984 – 2023 climatic data and vegetation indices for four Brazilian states: Bahia, Mato Grosso, Pará, and Tocantins. The team focused on soybean growing areas in each state derived from annual land use/land cover classifications. Monthly mean Normalized Difference Vegetation Index (NDVI) per state were calculated using multispectral imagery from the Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), and Landsat 8 Operational Land Imagery (OLI) sensors. In addition, the team used crop production indices, ENSO anomalies, temperature, and precipitation data in this study. The team found that although monthly ENSO anomaly did have a positive relationship between temperature and a slight negative relationship with precipitation, ENSO and monthly soy NDVI were not significantly correlated. Results find no association between ENSO conditions and NDVI in the study area at the state level spatial resolution during the study period. Furthermore, the team found that there was no correlation between cumulative growing season soy NDVI and detrended soy production yield for this study region at the spatial and temporal scale of the analysis. Findings from this project will be used by the United States Department of Agriculture’s Foreign Agriculture Service to inform crop productivity forecasting.

remote sensing↗

Human Heat Stress Could Offset Potential Economic Benefits of CO 2 Fertilization in Crop Production Under a High-Emissions Scenario

Climate change can significantly impact agriculture, leading to food security challenges. Most previous studies have investigated the direct climate impact on crops while neglecting the impact of heat stress on agricultural labor. Here, we assess the economic consequences of climate impacts on four major crops—maize, soybean, wheat, and rice—for scenarios involving low and high greenhouse gas emissions. Our analysis is based on the output from a new generation of global climate and crop models to drive a multiregional economic model. We find that, even under a high-emission scenario, the effect of CO 2 fertilization could lead to higher yields, resulting in lower prices for major crops, except for maize. However, heat-induced losses in agricultural labor could offset the potential economic benefits of CO 2 fertilization in crop production in Asia and Africa. Our findings emphasize the importance of addressing heat-stress impacts on agricultural labor through proactive adaptation measures.

climate change↗

Crop identification and acreage measurement utilizing ERTS imagery

The Statistical Reporting Service of the U.S. Department of Agriculture is evaluating ERTS-1 imagery as a potential tool for estimating crop acreage. A main data source for the estimates is obtained by enumerating small land parcels that have been randomly selected from the total U.S. land area. These small parcels are being used as ground observations in this investigation. The test sites are located in Missouri, Kansas, Idaho, and South Dakota. The major crops of interest are wheat, cotton, corn, soybeans, sugar beets, potatoes, oats, alfalfa, and grain sorghum. Some of the crops are unique to a given site while others are common in two or three states. This provides an opportunity to observe crops grown under different conditions. Results for the Missouri test site are presented. Results of temporal overlays, unequal prior probabilities, and sample classifiers are discussed. The amount of improvement that each technique contributes is shown in terms of overall performance. The results show that useful information for making crop acreage estimates can be obtained from ERTS-1 data.

Wigton, W. H.↗

A preliminary study of the statistical analyses and sampling strategies associated with the integration of remote sensing capabilities into the current agricultural crop forecasting system

Extending the crop survey application of remote sensing from small experimental regions to state and national levels requires that a sample of agricultural fields be chosen for remote sensing of crop acreage, and that a statistical estimate be formulated with measurable characteristics. The critical requirements for the success of the application are reviewed in this report. The problem of sampling in the presence of cloud cover is discussed. Integration of remotely sensed information about crops into current agricultural crop forecasting systems is treated on the basis of the USDA multiple frame survey concepts, with an assumed addition of a new frame derived from remote sensing. Evolution of a crop forecasting system which utilizes LANDSAT and future remote sensing systems is projected for the 1975-1990 time frame.

Sand, F.↗

Results from the crop identification technology assessment for remote sensing /CITARS/ project

The CITARS (Crop Identification Technology Assessment for Remote Sensing) task design, objectives, and results are reviewed along with relevant conclusions and recommendations. The principal assessment concern crop identification performance for corn and soybeans in six sites in Illinois and Indiana. Use of quantitative measures of classification performance and statistical evaluations of the results have been important parts of the technology assessment. Relation of crop and sensor characteristics is discussed. Factors affecting crop identification performance are identified as crop maturity and site characteristics, type of single-date automatic data processing procedure used for local recognition, nonlocal recognition with and without processing for extension of recognition signatures, and use of multidate or multitemporal data. In particular, the probability of correct classification of field center pixels is not well correlated and thus is not a reliable indicator of proportion estimation performance.

Bizzell, R. M.↗

The use of temporal data in Landsat crop surveys

Multidate Landsat imagery has been applied for crop identification purposes in Kern County, California. The county's arid climate provides complete sets of cloud-free imagery throughout the crop-growing season. Both manual and digital techniques are used to study the value of the data, and a semiautomated video system is used to extract densitometric data from Landsat transparencies. It is noted that temporal variations in single-date classification performance and increases in multidate performance are caused by the physiological and phenological differences between types of crops. These differences may be used to introduce crop calendar data into satellite crop surveys.

Tinney, L. R.↗

Area estimation of crops by digital analysis of Landsat data

The study for which the results are presented had these objectives: (1) to use Landsat data and computer-implemented pattern recognition to classify the major crops from regions encompassing different climates, soils, and crops; (2) to estimate crop areas for counties and states by using crop identification data obtained from the Landsat identifications; and (3) to evaluate the accuracy, precision, and timeliness of crop area estimates obtained from Landsat data. The paper describes the method of developing the training statistics and evaluating the classification accuracy. Landsat MSS data were adequate to accurately identify wheat in Kansas; corn and soybean estimates for Indiana were less accurate. Systematic sampling of entire counties made possible by computer classification methods resulted in very precise area estimates at county, district, and state levels.

Bauer, M. E.↗

Modeling the growth dynamics of four candidate crops for Controlled Ecological Life Support Systems (CELSS)

The production of food for human life support for advanced space missions will require the management of many different crops. The research to design these food production capabilities along with the waste management to recycle human metabolic wastes and inedible plant components are parts of Controlled Ecological Life Support Systems (CELSS). Since complete operating CELSS were not yet built, a useful adjunct to the research developing the various pieces of a CELSS are system simulation models that can examine what is currently known about the possible assembly of subsystems into a full CELSS. The growth dynamics of four crops (wheat, soybeans, potatoes, and lettuce) are examined for their general similarities and differences within the context of their important effects upon the dynamics of the gases, liquids, and solids in the CELSS. Data for the four crops currently under active research in the CELSS program using high-production hydroponics are presented. Two differential equations are developed and applied to the general characteristics of each crop growth pattern. Model parameters are determined by closely approximating each crop's data.

Volk, Tyler↗

Determining the potential productivity of food crops in controlled environments

The quest to determine the maximum potential productivity of food crops is greatly benefitted by crop growth models. Many models have been developed to analyze and predict crop growth in the field, but it is difficult to predict biological responses to stress conditions. Crop growth models for the optimal environments of a Controlled Environment Life Support System (CELSS) can be highly predictive. This paper discusses the application of a crop growth model to CELSS; the model is used to evaluate factors limiting growth. The model separately evaluates the following four physiological processes: absorption of PPF by photosynthetic tissue, carbon fixation (photosynthesis), carbon use (respiration), and carbon partitioning (harvest index). These constituent processes determine potentially achievable productivity. An analysis of each process suggests that low harvest index is the factor most limiting to yield. PPF absorption by plant canopies and respiration efficiency are also of major importance. Research concerning productivity in a CELSS should emphasize: (1) the development of gas exchange techniques to continuously monitor plant growth rates and (2) environmental techniques to reduce plant height in communities.

Bugbee, Bruce↗

Recycle of Inorganic Nutrients for Hydroponic Crop Production Following Incineration of Inedible Biomass

Recovery of resources from waste streams is essential for future implementation and reliance on a regenerative life support system. The major waste streams of concern are from human activities and plant wastes. Carbon, water and inorganics are the primary desired raw materials of interest. The goal of resource recovery is maintenance of product quality to insure support of reliable and predictable levels of life support function performance by the crop plant component. Further, these systems must be maintained over extended periods of time, requiring maintenance of nutrient solutions to avoid toxicity and deficiencies. Today, reagent grade nutrients are used to make nutrient solutions for hydroponic culture and these solutions are frequently changed during the life cycle or sometimes managed for only one crop life cycle. The focus of this study was to determine the suitability of the ash product following incineration of inedible biomass as a source of inorganic nutrients for hydroponic crop production. Inedible wheat biomass was incinerated and ash quality characterized. The incinerator ash was dissolved in adequate nitric acid to establish a consistent nitrogen concentration in all nutrient solution treatments. Four experimental nutrient treatments were included: control, ash only, ash supplemented to match control, and ash only quality formulated with reagent grade chemicals. When nutrient solutions are formulated using only ash following-incineration of inedible biomass, a balance in solution is established representing elemental retention following incineration and nutrient proportions present in the original biomass. The resulting solution is not identical to the control. This imbalance resulted in suppression of crop growth. When the ash is supplemented with nutrients to establish the same balance as in the control, growth is identical to the control. The ash appears to carry no phytotoxic materials. Growth in solution formulated with reagent grade chemicals but matching the quality of the ash only treatment resulted in growth similar to that of the ash only treatment. The ash product resulting from incineration of inedible biomass appears to be a suitable form for recycle of inorganic nutrients to crop production.

Bubenheim, David L.↗

A multiple chamber, semicontinuous, crop carbon dioxide exchange system: design, calibration, and data interpretation

Long-term, whole crop CO2 exchange measurements can be used to study factors affecting crop growth. These factors include daily carbon gain, cumulative carbon gain, and carbon use efficiency, which cannot be determined from short-term measurements. We describe a system that measures semicontinuously crop CO2 exchange in 10 chambers over a period of weeks or months. Exchange of CO2 in every chamber can be measured at 5 min intervals. The system was designed to be placed inside a growth chamber, with additional environmental control provided by the individual gas exchange chambers. The system was calibrated by generating CO2 from NaHCO3 inside the chambers, which indicated that accuracy of the measurements was good (102% and 98% recovery for two separate photosynthesis systems). Since the systems measure net photosynthesis (P-net, positive) and dark respiration(R-dark, negative), the data can be used to estimate gross photosynthesis, daily carbon gain, cumulative carbon gain, and carbon use efficiency. Continuous whole-crop measurements are a valuable tool that complements leaf photosynthesis measurements. Multiple chambers allow for replication and comparison among several environmental or cultural treatments that may affect crop growth. Example data from a 2 week study with petunia (Petunia x hybrida Hort. Vilm.-Andr.) are presented to illustrate some of the capabilities of this system.

NASA Discipline Life Support Systems↗

Solutions Network Formulation Report. Using NASA Sensors to Perform Crop Type Assessment for Monitoring Insect Resistance in Corn

The EPA (U.S. Environmental Protection Agency) is tasked to monitor for insect pest resistance to transgenic crops. Several models have been developed to understand the resistance properties of insects. The Population Genetics Simulator model is used in the EPA PIRDSS (Pest Infestation and Resistance Decision Support System). The EPA Office of Pesticide Programs uses the DSS to help understand the potential for insect pest resistance development and the likelihood that insect pest resistance will negatively affect transgenic corn. Once the DSS identifies areas of concern, crews are deployed to collect insect pest samples, which are tested to identify whether they have developed resistance to the toxins in transgenic corn pesticides. In this candidate solution, VIIRS (Visible/Infrared Imager/Radiometer Suite) vegetation index products will be used to build hypertemporal layerstacks for crop type and phenology assessment. The current phenology attribute is determined by using the current time of year to index the expected growth stage of the crop. VIIRS might provide more accurate crop type assessment and also might give a better estimate on the crop growth stage.

Lewis, David↗