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At least 91 records · Page 5

Sun-Induced Chlorophyll Fluorescence, Photosynthesis, and Light Use Efficiency of a Soybean Field from Seasonally Continuous Measurements

Recent development of sun-induced chlorophyll fluorescence (SIF) technology is stimulating studies to remotely approximate canopy photosynthesis (measured as gross primary production, GPP). While multiple applications have advanced the empirical relationship between GPP and SIF, mechanistic understanding of this relationship is still limited. GPP:SIF relationship, using the standard light use efficiency framework, is determined by absorbed photosynthetically active radiation (APAR) and the relationship between photosynthetic light use efficiency (LUE) and fluorescence yield (SIF y ). While previous studies have found that APAR is the dominant factor of the GPP:SIF relationship, the LUE:SIF y relationship remains unclear. For a better understanding of the LUE:SIF y relationship, in this paper we deployed a ground-based system (FluoSpec2), with an eddy-covariance flux tower at a soybean field in the Midwestern U.S. during the 2016 growing season to collect SIF and GPP data simultaneously. With the measurements categorized by plant growth stages, light conditions, and time scales, we confirmed that a strong positive GPP:SIF relationship was dominated by an even stronger linear SIF:APAR relationship. By normalizing both GPP and SIF by APAR, we found that under sunny conditions our soybean field exhibited a clear positive SIF y :APAR relationship and a weak negative LUE:SIF y relationship, opposite to the positive LUE:SIF y relationship reported previously in other ecosystems. Our study provides a first continuous SIF record over multiple growth stages for agricultural systems and reveals a distinctive pattern related to the LUE:SIF y relationship compared with previous work. Finally, the observed positive relationship of SIF y :APAR at the soybean site provides new insights of the previous understanding on the SIF's physiological implications.

58 GEOSCIENCES↗

Rye-soybean double-crop: planting method and N fertilization effects in the North Central US

Double-cropping winter rye cover crops (CC) with soybean in the North Central US could help with the global effort to sustainably intensify agriculture. Studies addressing the management of these systems are limited. Therefore, a field study was conducted from 2017 to 2019 in Central Iowa, US to evaluate winter rye CC biomass production, aboveground N accumulation, estimated economics, estimated within-field energy balance and estimated greenhouse gas (GHG) emissions under three N application rates (0, 60, 120 kg N ha –1 ) and three planting methods (pre- and post-harvest broadcast and post-harvest drilling). Averaged over N rates, all planting methods resulted in >5.0 Mg ha –1 year –1 rye aboveground biomass dry matter. Averaged over the 2-year study and compared with unfertilized treatments, applying 60 kg N ha –1 produced 1.1 Mg ha –1 more aboveground biomass (6.1 vs 5.0 Mg ha –1 ), accumulated 30 kg ha –1 more N in aboveground biomass (88 vs 58 kg N ha –1 ), and led to 20 GJ ha –1 more net energy. Biomass production was not significantly higher with 120 kg N ha –1 compared with the 60 kg N ha –1 rate. Even when accounting for an estimated 0.75 Mg ha –1 of above ground rye biomass left in the field after harvesting, more N was removed than applied at the 60 kg N ha –1 rate. The minimum rye prices over the 2-year study needed for double-cropping winter rye CC to be profitable (breakeven prices) averaged $117 and $104 Mg –1 for the 0 and 60 kg N ha –1 rates, which factors in estimated soybean yield reductions in 2019 compared with local averages but not off-site transportation. GHG emissions were estimated to increase approximately threefold between the unfertilized and 60 kg N ha –1 rates without considering bioenergy offsets. While environmental tradeoffs need further study, results suggest harvesting fertilized rye CC biomass before planting soybean is a promising practice for the North Central US to maximize total crop and net energy production.

59 BASIC BIOLOGICAL SCIENCES↗

Measured and Simulated Carbon Dynamics in Midwestern U.S. Corn‐Soybean Rotations

Abstract Corn ( Zea mays L.) and soybean ( Glycine max [L.] Merr.) production dominate Midwestern U.S. agriculture and impact the regional carbon and nitrogen cycles. Sustaining soil carbon is important for corn‐soybean production (CS); however, quantifying soil carbon changes requires long‐term field measurements and/or model simulations. In this study, changes in soil organic (SOC), inorganic (SIC), and total (TC) carbon; pH; total nitrogen (TN); and net ecosystem production (NEP) were measured in a conventional corn‐soybean rotation in central Iowa. Soil samples ( n = 42; 0–120 cm depth) were collected from two adjacent fields in 2005 and 2016. Eddy‐flux stations set up in the fields continuously monitored NEP from 2005–2016, and net biome production (NBP) was calculated using yield records. The DayCENT model was used to simulate the effects of conventional management practices on soil carbon and calibrated with field‐measured NEP and SOC. Measured soil TC (0–120 cm) decreased by −14.19 ± 6.25 Mg ha −1 , with highest reductions in SOC and SIC ( p < 0.05) at 0–15 and 90–120 cm, respectively. Measured TN decreased by −0.7 ± 0.29 Mg ha −1 with N‐accumulation at 60–90 cm ( p < 0.05). Eddy‐flux NBP decreased by −13.19 ± 0.05 Mg ha −1 . Soil and eddy‐flux records show a carbon reduction by −1.14 ± 0.63 and −1.20 ± 0.06 Mg ha −1 yr −1 , respectively. The validated DayCENT model suggests that all SOC pools declined. We postulate that conventional CS production has adverse effects on C and N dynamics in Midwestern United States.

Dold, C.↗

Assembly, comparative analysis, and utilization of a single haplotype reference genome for soybean

Cultivar Williams 82 has served as the reference genome for the soybean research community since 2008, but is known to have areas of genomic heterogeneity among different sub-lines. This work provides an updated assembly (version Wm82.a6) derived from a specific sub-line known as Wm82-ISU-01 (seeds available under USDA accession PI 704477). The genome was assembled using Pacific BioSciences HiFi reads and integrated into chromosomes using HiC. The 20 soybean chromosomes assembled into a genome of 1.01Gb, consisting of 36 contigs. The genome annotation identified 48 387 gene models, named in accordance with previous assembly versions Wm82.a2 and Wm82.a4. Comparisons of Wm82.a6 with other near-gapless assemblies of Williams 82 reveal large regions of genomic heterogeneity, including regions of differential introgression from the cultivar Kingwa within approximately 30 Mb and 25 Mb segments on chromosomes 03 and 07, respectively. Additionally, our analysis revealed a previously unknown large (> 20 Mb) heterogeneous region in the pericentromeric region of chromosome 12, where Wm82.a6 matches the ‘Williams’ haplotype while the other two near-gapless assemblies do not match the haplotype of either parent of Williams 82. In addition to the Wm82.a6 assembly, we also assembled the genome of ‘Fiskeby III,’ a rich resource for abiotic stress resistance genes. A genome comparison of Wm82.a6 with Fiskeby III revealed the nucleotide and structural polymorphisms between the two genomes within a QTL region for iron deficiency chlorosis resistance. The Wm82.a6 and Fiskeby III genomes described here will enhance comparative and functional genomics capacities and applications in the soybean community.

59 BASIC BIOLOGICAL SCIENCES↗

AmeriFlux US-Ne3 Mead - rainfed maize-soybean rotation site

This is the AmeriFlux version of the carbon flux data for the site US-Ne3 Mead - rainfed maize-soybean rotation site. Site Description - The study site is one of three fields (all located within 1.6 km of each other) at the University of Nebraska Agricultural Research and Development Center near Mead, Nebraska. While the other two sites are equipped with irrigation systems, this site relies on rainfall. A tillage operation (disking) was done just prior to the 2001 planting to homogenize the top 0.1 m of soil, incorporate P and K fertilizers, as well as previously accumulated surface residues. Since initiation of the study in 2001, this site has been under a strictly no-till, maize-soybean rotation (maize odd years and soybean even years).

Suyker, Andy↗

AmeriFlux FLUXNET-1F US-MN1 Morris: Corn-Soybean with Cover Crops, Strip Tillage

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-MN1 Morris: Corn-Soybean with Cover Crops, Strip Tillage. This is the FLUXNET version of the carbon flux data for the site US-MN1 Morris: Corn-Soybean with Cover Crops, Strip Tillage produced by applying the standard ONEFlux (1F) software. Site Description - Cropland, 2-year rotation (corn-soybean), strip tillage with winter cover crops (annual rye), nutrient management by soil tests, uniform pest management, tile drainage

Helseth, Christina [USDA-ARS LTAR]↗

AmeriFlux FLUXNET-1F US-MN2 Morris: Corn-Soybean-Wheat with Cover Crops, Minimal Tillage

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-MN2 Morris: Corn-Soybean-Wheat with Cover Crops, Minimal Tillage. This is the FLUXNET version of the carbon flux data for the site US-MN2 Morris: Corn-Soybean-Wheat with Cover Crops, Minimal Tillage produced by applying the standard ONEFlux (1F) software. Site Description - Cropland, 3-year rotation (corn-soybean-wheat), cover crops (winter camelina and pennycress), minimum tillage, nutrient management by soil tests, uniform pest management, tile drainage

Helseth, Christina [USDA-ARS LTAR]↗

AmeriFlux FLUXNET-1F US-MN3 Morris: Corn-Soybean, Conventional Tillage

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-MN3 Morris: Corn-Soybean, Conventional Tillage. This is the FLUXNET version of the carbon flux data for the site US-MN3 Morris: Corn-Soybean, Conventional Tillage produced by applying the standard ONEFlux (1F) software. Site Description - Cropland, 2-year rotation (corn-soybean), conventional (deep rip) tillage, uniform nutrient management, uniform pest management, tile drainage

Helseth, Christina [USDA-ARS LTAR]↗

Modeled and Measured Ecosystem Respiration in Maize-Soybean Systems Over 10 Years

Crop residue is an abundant resource for the potential production of biofuels, but a better understanding of its use on net carbon emissions must be developed to mitigate climate change. This analysis combines two established crop growth models (Hybrid-Maize and Soysim) with a simple soil and crop residue respiration model to estimate daily ecosystem respiration (ERe) from maize and soybean; ERe was estimated to be the sum of CO 2 emissions from the oxidation of the growing crop, crop residue, and soil organic carbon (SOC). Model-estimated CO 2 fluxes from irrigated continuous maize and irrigated maize–soybean cropping systems in eastern Nebraska were compared with tower eddy covariance measurements of CO 2 fluxes from 2001 to 2010 from those fields. Modeled C emissions closely estimated measured seasonal patterns of CO 2 dynamics and measured daily ERe ( R 2 : 0.87, 0.84). Measured and modeled annual ERe values were also compared and better agreement was found in maize compared to soybean. As there are limited comparisons of modeled soil emissions with eddy covariance measured CO 2 fluxes, this study is important for the validation of these types of models and to support their potential use in quantifying emissions from crop residue for biofuels.

54 ENVIRONMENTAL SCIENCES↗

Crop identification studies using Landsat data Separation of barley from other spring small grains and corn and soybean decision logic

Two labeling procedures were developed which identify various agricultural crops through the use of Landsat data. One procedure separates barley from other spring small grains, and the other identifies corn and soybeans. For both procedures, a minimum data set (critical acquisition time) has been designated. Landsat data in both image format and various graphic displays were used along with ancillary data to obtain information which aided in labeling the spectral signatures. The corn and soybean procedure also employed a structured decision logic. Test results for the barley separation procedure emphasized the importance of obtaining a critical acquisition and showed some success especially in areas where spring crops followed the expected growth patterns. Two tests of the corn and soybean procedure produced good labeling accuracies. Problems with the procedure were easy to identify, and some solutions were implemented for the second test. Automation of various parts of the procedure and extension to other crops and regions were recommended.

Dailey, C. L.↗

AgRISTARS: Foreign commodity production forecasting. The 1980 US corn and soybeans exploratory experiment

The U.S. corn and soybeans exploratory experiment is described which consisted of evaluations of two technology components of a production forecasting system: classification procedures (crop labeling and proportion estimation at the level of a sampling unit) and sampling and aggregation procedures. The results from the labeling evaluations indicate that the corn and soybeans labeling procedure works very well in the U.S. corn belt with full season (after tasseling) LANDSAT data. The procedure should be readily adaptable to corn and soybeans labeling required for subsequent exploratory experiments or pilot tests. The machine classification procedures evaluated in this experiment were not effective in improving the proportion estimates. The corn proportions produced by the machine procedures had a large bias when the bias correction was not performed. This bias was caused by the manner in which the machine procedures handled spectrally impure pixels. The simulation test indicated that the weighted aggregation procedure performed quite well. Although further work can be done to improve both the simulation tests and the aggregation procedure, the results of this test show that the procedure should serve as a useful baseline procedure in future exploratory experiments and pilot tests.

Malin, J. T.↗

Fiscal year 1981 US corn and soybeans pilot preliminary experiment plan, phase 1

A draft of the preliminary experiment plan for the foreign commodity production forecasting project fiscal year 1981 is presented. This draft plan includes: definition of the phase 1 and 2 U.S. pilot objectives; the proposed experiment design to evaluate crop calendar, area estimation, and area aggregation components for corn and soybean technologies using 1978/1979 crop-year data; a description of individual sensitivity evaluations of the baseline corn and soybean segment classification procedure; and technology and data assessment in support of the corn and soybean estimation technology for use in the U.S. central corn belt.

Livingston, G. P.↗

Soybean canopy reflectance as a function of view and illumination geometry

The results of an experiment designed to characterize a soybean field by its reflectance at various view and illumination angles and by its physical and agronomic attributes are presented. Reflectances were calculated from measurements at four wavelength bands through eight view azimuth and seven view zenith directions for various solar zenith and azimuth angles during portions of three days. An ancillary data set consisting of the agronomic and physical characteristics of the soybean field is described. The results indicate that the distribution of reflectance from a soybean field is a function of the solar illumination and viewing geometry, wavelength and row direction, as well as the state of development of the canopy. Shadows between rows greatly affected the reflectance in the visible wavelength bands and to a lesser extent in the near infrared wavelengths. A model is proposed that describes the reflectance variation as a function of projected solar and projected viewing angles. The model appears to approximate the reflectance variations in the visible wavelength bands from a canopy with well defined row structure.

Bauer, M. E.↗

Analysis of the profile characteristics of corn and soybeans using field reflectance data

The typical patterns of spectral development (profiles) for corn and soybeans are presented, based on field-collected reflectance data transformed to correspond to LANDSAT-MSS Tasseled Cap coordinates. Reasonable variations in field conditions and cultural practices are shown to significantly influence profile features. The separability of the two crops is determined to be primarily related to the maximum value of the reflectance equivalent of Greenness, and to the plateau effect seen in corn Greenness profiles. The impact of changes in conditions on separability is described. In addition, association is made between profile features and stages of development for corn and soybeans. Corn is shown to peak at a stage well before tasseling or maximum LAI, while the characteristics of the soybean profile are shown to be unrelated to any particular stage of development.

Crist, E. P.↗

Use of microwaves to improve nutritional value of soybeans for future space inhabitants

Whole soybeans from four different varieties at different moisture contents were microwaved for varying times to determine the conditions for maximum destruction of trypsin inhibitor and lipoxygenase activities, and optimal growth of chicks. Microwaving 150 gm samples of soybeans (at 14 to 28% moisture) for 1.5 min was found optimal for reduction of trypsin inhibitor and lipoxygenase activities. Microwaving 1 kgm samples of soybeans for 9 minutes destroyed 82% of the trypsin inhibitor activity and gave optimal chick growth. It should be pointed out that the microwaving time would vary according to the weight of the sample and the power of the microwave oven. The microwave oven used in the above experiments was rated at 650 watts 2450 MHz.

Singh, G.↗

Corn and soybean Landsat MSS classification performance as a function of scene characteristics

In order to fully utilize remote sensing to inventory crop production, it is important to identify the factors that affect the accuracy of Landsat classifications. The objective of this study was to investigate the effect of scene characteristics involving crop, soil, and weather variables on the accuracy of Landsat classifications of corn and soybeans. Segments sampling the U.S. Corn Belt were classified using a Gaussian maximum likelihood classifier on multitemporally registered data from two key acquisition periods. Field size had a strong effect on classification accuracy with small fields tending to have low accuracies even when the effect of mixed pixels was eliminated. Other scene characteristics accounting for variability in classification accuracy included proportions of corn and soybeans, crop diversity index, proportion of all field crops, soil drainage, slope, soil order, long-term average soybean yield, maximum yield, relative position of the segment in the Corn Belt, weather, and crop development stage.

Batista, G. T.↗