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At least 163 records · Page 9

Land use mapping in Erie County, Pennsylvania: A pilot study

The author has identified the following significant results. A pilot study was conducted to determine the feasibility of mapping land use in the Great Lakes Basin area utilizing ERTS-1 data. Small streams were clearly defined by the presence of trees along their length in predominantly agricultural country. Field patterns were easily differentiated from forested areas; dairy and beef farms were differentiated from other farmlands, but no attempt was made to identify crops. Large railroad lines and major highway systems were identified. The city of Erie and several smaller towns were identified, as well as residential areas between these towns, and docks along the shoreline in Erie. Marshes, forests, and beaches within Presque Isle State Park were correctly identified, using the DCLUS program. Bay water was differentiated from lake water, with a small amount of misclassification.

Mcmurtry, G. J.↗

NASA's Agricultural Program: A USDA/Grower Partnership

Ag20/20 is a partnership between USDA, NASA, and four national commodity associations. It is driven by the information needs of U.S. farmers. Ag20/20 is focused on utilization of earth science and remote sensing for decision-making and oriented toward economically viable operational solutions. Its purpose is to accelerate the use of remote sensing and other geospatial technologies on the farm to: 1) Increase the production efficiency of the American farmer; 2) Reduce crop production risks; 3) Improve environmental stewardship tools for agricultural production.

McKellip, Rodney↗

Outdoor annual algae productivity improvements at the pre-pilot scale through crop rotation and pond operational management strategies

The Development of Integrated Screening, Cultivar Optimization, and Verification Research (DISCOVR) collaborative consortium operated pre-pilot scale outdoor ponds to deliver much-needed multi-year, long-term and consistent, algae cultivation data relevant to understanding the current state of technology in terms of expected seasonal algae biomass productivity. Over the course of four years from 2018 to 2021, twelve identical 4.2 m 2 mini-ponds were run in triplicate sets to test strains and operational strategies demonstrated in small-, indoor photobioreactors, in pursuit of increasing overall algae areal productivity and projected farm yield. Fourteen different cultivars derived from a strain screening pipeline were tested. Through deliberate seasonal crop rotation and improvements in operational strategies, annual biomass productivity increased from 11.6 to 17.6 g m -2 day -1 , a > 50% increase over the 2018 baseline. Both brackish and marine strains were included and four out of the fourteen strains consistently yielded high productivity across multiple years; brackish strains Monoraphidium minutum (26BAM) and Scenedesmus obliquus (UTEX393), and marine strains Tetraselmis striata (LANL1001) and Picochlorum celeri (TG2). These freely available datasets, which represent nearly complete annual daily coverage of cultivation metrics including weather, pond temperature and pH, nutrients, and productivity, are unique in the public domain and seek to fill agronomic and operational knowledge gaps to help in the eventual commercialization of algal biofuels and bioproducts.

09 BIOMASS FUELS↗

Meteorological models for estimating phenology of corn

Knowledge of when critical crop stages occur and how the environment affects them should provide useful information for crop management decisions and crop production models. Two sources of data were evaluated for predicting dates of silking and physiological maturity of corn (Zea mays L.). Initial evaluations were conducted using data of an adapted corn hybrid grown on a Typic Agriaquoll at the Purdue University Agronomy Farm. The second phase extended the analyses to large areas using data acquired by the Statistical Reporting Service of USDA for crop reporting districts (CRD) in Indiana and Iowa. Several thermal models were compared to calendar days for predicting dates of silking and physiological maturity. Mixed models which used a combination of thermal units to predict silking and days after silking to predict physiological maturity were also evaluated. At the Agronomy Farm the models were calibrated and tested on the same data. The thermal models were significantly less biased and more accurate than calendar days for predicting dates of silking. Differences among the thermal models were small. Significant improvements in both bias and accuracy were observed when the mixed models were used to predict dates of physiological maturity. The results indicate that statistical data for CRD can be used to evaluate models developed at agricultural experiment stations.

Daughtry, C. S. T.↗

Heat stress on agricultural workers exacerbates crop impacts of climate change

Abstract The direct impacts of climate change on crop yields and human health are individually well-studied, but the interaction between the two have received little attention. Here we analyze the consequences of global warming for agricultural workers and the crops they cultivate using a global economic model (GTAP) with explicit treatment of the physiological impacts of heat stress on humans’ ability to work. Based on two metrics of heat stress and two labor functions, combined with a meta-analysis of crop yields, we provide an analysis of climate, impacts both on agricultural labor force, as well as on staple crop yields, thereby accounting for the interacting effect of climate change on both land and labor. Here we analyze the two sets of impacts on staple crops, while also expanding the labor impacts to highlight the potential importance on non-staple crops. We find, worldwide, labor and yield impacts within staple grains are equally important at +3 ∘ C warming, relative to the 1986–2005 baseline. Furthermore, the widely overlooked labor impacts are dominant in two of the most vulnerable regions: sub-Saharan Africa and Southeast Asia. In those regions, heat stress with 3 ∘ C global warming could reduce labor capacity in agriculture by 30%–50%, increasing food prices and requiring much higher levels of employment in the farm sector. The global welfare loss at this level of warming could reach $136 billion, with crop prices rising by 5%, relative to baseline.

de Lima, Cicero Z. (ORCID:0000000297005435)↗

Bioenergy’s Role in Soil Carbon Storage Decarbonizing Transportation, Agriculture, and Industrial Sectors Workshop Summary Report

On March 28–29, 2022, the U.S. Department of Energy’s (DOE) Bioenergy Technologies Office (BETO) hosted the public virtual workshop “Bioenergy’s Role in Soil Carbon Storage.” Given the recent emphasis of the Biden administration on decarbonizing transportation, agriculture, and industrial sectors of the U.S. economy, this workshop examined how decarbonization through enhanced soil carbon storage while growing bioenergy crops is possible by discussing challenges and opportunities that affect soil carbon levels. Stakeholders representing academia, industry, the farming community, agricultural and forestry sectors, municipalities, and federal agencies involved in soil carbon storage participated in this workshop. A series of keynote presentations, plenary presentations, and stakeholder input sessions provided opportunities for sharing knowledge and identifying research and development (R&D) needs for future advances in soil carbon storage in relation to bioenergy crops. This document provides an overview of the content discussed in the presentations, as well as a summary of the stakeholder input received during the session discussions.

09 BIOMASS FUELS↗

Optimizing tradeoffs implicit during bioenergy crop improvement: Understanding the effect of altered cell wall and sugar content on sorghum-associated pathogenic bacteria

Plant-derived production of renewable fuels and chemicals has the potential to reduce fossil fuel dependency, increase domestic energy security, enhance US farming and agricultural economic opportunities, and reduce greenhouse gas emissions. Realizing the potential of these alternate energy sources necessitates the development of high biomass-yielding crops. To limit competition with the production of food and feed, these specialized crop varieties, many of which will harbor modifications to cell wall structures and display altered carbon partitioning, will be cultivated on marginal land that does not provide ideal growing conditions. Consequently, the plants are anticipated to be more vulnerable to diseases.

09 BIOMASS FUELS↗

Novel technologies for emission reduction complement conservation agriculture to achieve negative emissions from row-crop production

Plants remove carbon dioxide from the atmosphere through photosynthesis. Because agriculture’s productivity is based on this process, a combination of technologies to reduce emissions and enhance soil carbon storage can allow this sector to achieve net negative emissions while maintaining high productivity. Unfortunately, current row-crop agricultural practice generates about 5% of greenhouse gas emissions in the United States and European Union. Here, to reduce these emissions, significant effort has been focused on changing farm management practices to maximize soil carbon. In contrast, the potential to reduce emissions has largely been neglected. Through a combination of innovations in digital agriculture, crop and microbial genetics, and electrification, we estimate that a 71% (1,744 kg CO 2 e/ha) reduction in greenhouse gas emissions from row crop agriculture is possible within the next 15 y. Importantly, emission reduction can lower the barrier to broad adoption by proceeding through multiple stages with meaningful improvements that gradually facilitate the transition to net negative practices. Emerging voluntary and regulatory ecosystems services markets will incentivize progress along this transition pathway and guide public and private investments toward technology development. In the difficult quest for net negative emissions, all tools, including emission reduction and soil carbon storage, must be developed to allow agriculture to maintain its critical societal function of provisioning society while, at the same time, generating environmental benefits.

54 ENVIRONMENTAL SCIENCES↗

AmeriFlux FLUXNET-1F US-CF1 CAF-LTAR Cook East

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-CF1 CAF-LTAR Cook East. This is the FLUXNET version of the carbon flux data for the site US-CF1 CAF-LTAR Cook East produced by applying the standard ONEFlux (1F) software. Site Description - CF1 has operated since May 2017 at the R.J. Cook Agronomy Farm outside of Pullman, Washington, and monitors the no-till side of a paired-catchment study that is part of the Longterm Agroecosystem Research (LTAR) site common experiment. CF1 is located in “Cook East,” a field that has been in no-till management since 1998, and represents the Alternative treatment of the LTAR common experiment. It is paired with the CF2 tower location in “Cook West,” which has been in conventional tillage since prior to 1998 and represents the Prevalent treatments of the common experiment. Cook Agronomy Farm is in the high precipitation agroecological zone of the Columbia Plateau’s dryland cropping region. Crop rotations are wheat-based and include winter wheat, spring wheat, chickpea, spring canola, and winter peas. Wheat is the principal cash crop, with other crops grown in rotation for diversity, nutrient, and pest management. Soils are predominantly silt loam texture Mollisols in the Palouse, Thatuna, Naff soil series. The CF1 tower replaced US-RC1, which operated 2012-2016 in a neighboring field that was also in no-till management since 1998. CF1 and RC1 have distinct footprints, aspects, and soil series compositions.

Phillips, Claire L.↗

AmeriFlux FLUXNET-1F US-RC1 Cook Agronomy Farm - No Till

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-RC1 Cook Agronomy Farm - No Till. This is the FLUXNET version of the carbon flux data for the site US-RC1 Cook Agronomy Farm - No Till produced by applying the standard ONEFlux (1F) software. Site Description - RC1 operated from 2013-2016 at the R.J. Cook Agronomy Farm, as part of a cluster of 5 towers (RC1 to RC5) operated for the Regional Approaches to Climate Change (REACCH) USDA-supported research project. The tower predates the Longterm Agroecosystem Research (LTAR) site common experiment, which was established in nearby fields at the Cook Agronomy Farm in 2017. Cook Agronomy Farm is in the high precipitation agroecological zone of the Columbia Plateau’s dryland cropping region. Wheat-based crop rotations are grown on an annual planting schedule. RC1 was in no-till management since 1998, and was contrasted with RC2, which had conventional, reduced-tillage management. RC1 captured the same tillage practices as the US-CF1 site established in 2017 as part of LTAR common experiment. However, the towers have distinct footprints, aspects, and soil series composition.

Chi, Jinshu [The Hong Kong University of Science a↗

A Predictive Model for Lake Chad Total Surface Water Area Using Remotely Sensed and Modeled Hydrological and Meteorological Parameters and Multivariate Regression Analysis

Lake Chad is an endorheic lake in the Sahel region of Africa at the southern edge of the Sahara Desert. The lake, which is well known for its dramatic decrease in surface area during the 1970s and 1980s, experiences an annual flood resulting in a maximum total surface water area generally during February or March, though sometimes earlier or later. People along the shores of Lake Chad make their living fishing, farming, and raising livestock and have a vested interest in knowing when and how extensive the annual flooding will be, particularly those practicing recession farming in which the fertile ground of previously flooded area is used for planting crops. In this study, the authors investigate the relationship between lake and basin parameters, including rainfall, basin evapotranspiration, lake evapotranspiration, lake elevation, total surface water area, and the previous year’s total surface water area, and develop equations for each dry season month (except November) linking total surface water area to the other parameters. The resulting equations allow the user to estimate the December average monthly total surface water area of the lake in late November, and to make the estimates for January to May in early December. Based on the results of a Leave One Out Cross Validation analysis, the equations for lake area are estimated to have an average absolute error ranging from 5.3 percent (for February estimates) to 7.6 percent (for May estimates).

Lake Chad↗

AmeriFlux FLUXNET-1F US-RC2 Cook Agronomy Farm - Conventional Till

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-RC2 Cook Agronomy Farm - Conventional Till. This is the FLUXNET version of the carbon flux data for the site US-RC2 Cook Agronomy Farm - Conventional Till produced by applying the standard ONEFlux (1F) software. Site Description - RC2 operated from 2013-2016 at the R.J. Cook Agronomy Farm, as part of a cluster of 5 towers (RC1 to RC5) operated for the Regional Approaches to Climate Change (REACCH) USDA-supported research project. The tower predates the Longterm Agroecosystem Research (LTAR) site common experiment, which was established in nearby fields at the Cook Agronomy Farm in 2017. Cook Agronomy Farm is in the high-precipitation agroecological zone of the Columbia Plateau’s dryland cropping region. Wheat-based crop rotations are grown annually. RC2 had conventional tillage management (reduced-till) since at least 1998. It was contrasted with RC1, which had no-till management over the same time period. RC2 captured the same tillage practices as the US-CF2 site established in 2017 as part of LTAR common experiment. However, the towers have distinct footprints, aspects, and soil series composition.

Chi, Jinshu [The Hong Kong University of Science a↗

Improving Flood and Drought Management in Agricultural River Basins: An Application to the Mun River Basin in Thailand

Agriculture productivity is regularly affected by floods and droughts, and the severity is likely to increase in the future. Even if significant efforts are spent on water development projects, ineffective project planning often means that they continue to occur or are only partly mitigated, for example, in the Mun River Basin, Thailand, where 1000s of water projects have been implemented. Despite this, the basin regularly experiences floods and droughts. In this study, an analysis of the adverse impacts of basin-scale floods and droughts on rice cultivation in the Mun River Basin is conducted, and an estimation of the coping capacity of existing measures. The results demonstrate that while the total storage capacity of in-situ and ongoing projects would be sufficient to tackle both hazards, it can only be achieved if the projects are effectively utilised. Based on this, proposed solutions for the region include small farm ponds, a subsurface floodwater harvesting system, and oxbow lake reconnections. The suggested measures are practicable, economical, environmentally low-impact, and their implementation (if executed with appropriate care) would reduce flood and drought problems in the basin. Notably, the measures and calculation methods proposed for this basin can also be applied to other crops and regions.

Farm pond↗

Shifting agricultural practices to produce sustainable, low carbon intensity feedstocks for biofuel production

The carbon intensity (CI) of biofuel's well-to-pump life cycle is calculated by life cycle analysis (LCA) to account for the energy/material inputs of the feedstock production and fuel conversion stages and the associated greenhouse gas (GHG) emissions during these stages. The LCA is used by the California Air Resources Board's Low Carbon Fuel Standard (LCFS) program to calculate CI and monetary credits are issued based on the difference between a given fuel's CI and a reference fuel's CI. Through the Tier 2 certification program under which individual fuel production facilities can submit their own CIs with their facility input data, the LCFS has driven innovative technologies to biofuel conversion facilities, resulting in substantial reductions in GHG emissions as compared to the baseline gasoline or diesel. A similar approach can be taken to allow feedstock petition in the LCFS so that lower-CI feedstock can be rewarded. Here we examined the potential for various agronomic practices to improve the GHG profiles of corn ethanol by performing feedstock-level CI analysis for the Midwestern United States. Our system boundary covers GHG emissions from the cradle-to-farm-gate activities (i.e. farm input manufacturing and feedstock production), along with the potential impacts of soil organic carbon change during feedstock production. We conducted scenario-based CI analysis of ethanol, coupled with regionalized inventory data, for various farming practices to manage corn fields, and identified key parameters affecting cradle-to-farm-gate GHG emissions. The results demonstrate large spatial variations in CI of ethanol due to farm input use and land management practices. In particular, adopting conservation tillage, reducing nitrogen fertilizer use, and implementing cover crops has the potential to reduce GHG emissions per unit corn produced when compared to a baseline scenario of corn–soybean rotation. This work shows a large potential emission offset opportunity by allowing feedstock producers a path to Tier 2 petitions that reward low-CI feedstocks and further reduce biofuels' CI. The prevalence of significant acreage that has not been optimized for CI suggests that policy changes that incentivize optimization of this parameter could provide significant additionality over current trends in farm efficiency and adoption of conservation practice.

09 BIOMASS FUELS↗

Soil, water, and vegetation conditions in south Texas

The author has identified the following significant results. Software development for a computer-aided crop and soil survey system is nearing completion. Computer-aided variety classification accuracies using LANDSAT-1 MSS data for a 600 hectare citrus farm were 83% for Redblush grapefruit and 91% for oranges. These accuracies indicate that there is good potential for computer-aided inventories of grapefruit and orange citrus orchards with LANDSAT-type MSS data. Mean digital values of clouds differed statistically from those for crop, soil, and water entities, and those for cloud shadows were enough lower than sunlit crop and soil to be distinguishable. The standard errors of estimate for the calibration of computer compatible tape coordinate system (pixel and record) to earth coordinate system (longitude and latitude) for 6 LANDSAT scenes ranged from 0.72 to 1.50 pixels and from 0.58 to 1.75 records.

Wiegand, C. L.↗

Ecologically-Informed Precision Conservation: A framework for increasing biodiversity in intensively managed agricultural landscapes with minimal sacrifice in crop production

Conservation actions are urgently needed to tackle biodiversity loss in intensively managed agricultural landscapes. Production lands are usually heterogeneous and contain low-yield areas that can be set aside for biodiversity conservation without serious yield losses. Here, we introduce Ecologically-Informed Precision Conservation, a framework that integrates yield mapping and ecological theory to select the best areas to create new set-asides while ensuring high crop yields at the farm/landscape level. Long-term yield maps can be generated using globally available satellite data and basic information on field/farm crop yield from farmers. Ecological principles are then used to select the subset of areas with the highest potential for biodiversity conservation by prioritising those that increase connectivity, maximise habitat heterogeneity and decrease landscape grain size. Here, the created non-crop habitats can be permanent and thus ensure biodiversity support over time. In addition, agricultural management efficiency can be enhanced by improving field shapes. The framework provides the basis for a practical, user-friendly tool that informs all interested stakeholders on how to rationalise existing agricultural landscapes using already-existing farming systems and available technologies. High cost-effectiveness from an economic and conservation perspective, along with the creation of heterogeneous non-crop habitats, make our framework a promising solution to re-design agricultural landscapes.

Precision agriculture↗

AmeriFlux US-VT1 Vermillion Tributary Paired Cropland – Site 1 (Corn/Soy; No Cover Crops)

This is the AmeriFlux version of the carbon flux data for the site US-VT1 Vermillion Tributary Paired Cropland – Site 1 (Corn/Soy; No Cover Crops). Site Description - US-VT1 is located on flat, actively managed farmland operated by working farmers, following a conventional no-till corn–soybean rotation in the U.S. Midwest. US-VT1 is one of two paired working farm sites on the same property; both are managed using similar conventional practices, with the key difference being that the paired site (US-VT2) incorporates cover crops into its rotation. This paired design enables direct site-to-site comparisons to assess the impacts of cover cropping on carbon, water, and energy fluxes.

Key, Kesondra [Indiana University - Bloomington]↗

AmeriFlux FLUXNET-1F US-Ro6 Rosemount I18_North

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Ro6 Rosemount I18_North. This is the FLUXNET version of the carbon flux data for the site US-Ro6 Rosemount I18_North produced by applying the standard ONEFlux (1F) software. Site Description - This tower is located in a farm field farmed in accordance with a conservation type agricultural practice in the region: a corn/soybean/clover (living mulch/cover crop) rotation with chisel plow tillage in the fall following corn harvest and in the spring following soybeans.

Baker, John↗