Search

Northern peatlands cover approximately four million km2, and about half of these peatlands are estimated to contain permafrost and periglacial landforms, like palsas and peat plateaus. In northeastern Canada, peatland permafrost is predicted to be concentrated in the western interior of Labrador but is assumed to be largely absent along the Labrador Sea coastline. However, the paucity of observations of peatland permafrost in the interior, coupled with traditional and ongoing use of perennially frozen peatlands along the coast by Labrador Inuit and Innu, suggests a need for re-evaluation of the reliability of existing peatland permafrost distribution estimates for the region. In this study, we develop a multi-stage consensus-based point inventory of peatland permafrost complexes in coastal Labrador and adjacent parts of Quebec using high-resolution satellite imagery, and we validate it with extensive field visits and low-altitude aerial photography and videography. A subset of 2092 wetland complexes that potentially contained peatland permafrost were inventoried, of which 1119 were classified as likely containing peatland permafrost. Likely peatland permafrost complexes were mostly found in lowlands within 22 km of the coastline, where mean annual air temperatures often exceed +1 ∘C. A clear gradient in peatland permafrost distribution exists from the outer coasts, where peatland permafrost is more abundant, to inland peatlands, where permafrost is generally absent. This coastal gradient may be attributed to a combination of climatic and geomorphological influences which lead to lower insolation, thinner snowpacks, and poorly drained, frost-susceptible materials along the coast. The results of this study suggest that existing estimates of permafrost distribution for southeastern Labrador require adjustments to better reflect the abundance of peatland permafrost complexes to the south of the regional sporadic discontinuous permafrost limit. This study constitutes the first dedicated peatland permafrost inventory for Labrador and provides an important baseline for future mapping, modelling, and climate change adaptation strategy development in the region.

IntroductionLight response curves are widely used to quantify phenotypic expression of photosynthesis by measuring a single sample and sequentially altering light intensity within a chamber (sequential method) or by measuring different samples that are each acclimated to a different light level (non-sequential method). Both methods are often conducted in controlled environments to achieve steady-state results, and neither method involves equilibrating the entire plant to the specific light level. MethodsHere, we compare sequential and non-sequential methods in controlled (greenhouse), semi-controlled (plant grown in growth chamber and acclimated to field conditions 2-3 days before measurements), and field environments. We selected seven diverse rice genotypes (five genotypes from the USDA rice minicore collection: 310588, 310723, 311644, 311677, 311795; and 2 additional genotypes: Nagina 22 and Zhe 733) to understand (1) the limitations of different methods, and (2) phenotypic plasticity of photosynthesis in rice grown under different environments. ResultsOur results show that the non-sequential method was time-efficient and captured more variability of field conditions than the sequential method, but the model parameters were generally similar between two methods except the maximum photosynthesis rate (Amax). Amax was significantly lower across all genotypes under greenhouse conditions compared to the growth chamber and field conditions consistent with prior work, but surprisingly the apparent quantum yield (α) and the mitochondrial respiration (Rd) were generally not different among growing environments or measurement methods. DiscussionOur results suggest that field conditions are best suited to quantify phenotypic differences across different genotypes and nonsequential method was better at capturing the variability in photosynthesis.

Background: Young people with Special Educational Needs and Disabilities (SEND) are especially vulnerable to physical inactivity. Research has demonstrated the effectiveness of tailored cycle training for children with SEND, however, it is unclear whether this then results in a greater uptake of cycling. Aims: To determine parent based perceptions of a SEND cycle training programme, factors which predict intention to cycle more and ongoing barriers to cycling. Methods: A tailored questionnaire was distributed to parents of children who took part in the cycle training. Results: Parents reported increased confidence in their child's ability to cycle independently with many also highlighting improvements in confidence and resilience. The outcome of the cycle training (level of enjoyment and change in cycling ability) had a positive influence on intention to cycle more while cycling frequency prior to training had a negative influence. Continuing barriers to cycling were identified which included difficulties accessing specialised equipment and a need for additional on-road cycle training. Conclusions and implications: This study demonstrates the success of a specialised cycle training programme for children with SEND in terms of improvement to cycling and influences on the intention to cycle more.

Abstract Improving water use efficiency (WUE) for soybean [Glycine max (L.) Merr.] through selection for high carbon isotope (C13) ratio may increase drought tolerance, but increased WUE may limit growth in productive environments. An ideal genotype would be plastic for C13 ratio; that is, be able to alter C13 ratio in response to the environment. Our objective was to identify genomic regions associated with C13 ratio plasticity, C13 ratio stability, and overall C13 ratio in two panels of diverse Maturity Group IV soybean accessions. A second objective was to identify accessions that differed in their C13 ratio plasticity. Panel 1 (205 accessions) was evaluated in seven irrigated and four drought environments, and Panel 2 (373 accessions) was evaluated in four environments. Plasticity was quantified as the slope from regressing C13 ratio of individual genotypes against an environmental index calculated based on the mean within and across environments. The regression intercept was considered a measure of C13 ratio over all environments, and the root mean square error was considered a measure of stability. Combined over both panels, genome‐wide association mapping (GWAM) identified 19 single nucleotide polymorphisms (SNPs) for plasticity, 39 SNPs for C13 ratio, and 16 SNPs for stability. Among these SNPs, 71 candidate genes had annotations associated with transpiration or water conservation and transport, root development, root hair elongation, and stomatal complex morphogenesis. The genomic regions associated with plasticity and stability identified in the current study will be a useful resource for implementing genomic selection for improving drought tolerance in soybean.

Abstract Background Genomic selection is a powerful tool in plant breeding. By building a prediction model using a training set with markers and phenotypes, genomic estimated breeding values (GEBVs) can be used as predictions of breeding values in a target set with only genotype data. There is, however, limited information on how prediction accuracy of genomic prediction can be optimized. The objective of this study was to evaluate the performance of 11 genomic prediction models across species in terms of prediction accuracy for two traits with different heritabilities using several subsets of markers and training population proportions. Species studied were maize (Zea mays, L.), soybean (Glycine max, L.), and rice (Oryza sativa, L.), which vary in linkage disequilibrium (LD) decay rates and have contrasting genetic architectures. Results Correlations between observed and predicted GEBVs were determined via cross validation for three training-to-testing proportions (90:10, 70:30, and 50:50). Maize, which has the shortest extent of LD, showed the highest prediction accuracy. Amongst all the models tested, Bayes B performed better than or equal to all other models for each trait in all the three crops. Traits with higher broad-sense and narrow-sense heritabilities were associated with higher prediction accuracy. When subsets of markers were selected based on LD, the accuracy was similar to that observed from the complete set of markers. However, prediction accuracies were significantly improved when using a subset of total markers that were significant at P ≤ 0.05 or P ≤ 0.10. As expected, exclusion of QTL-associated markers in the model reduced prediction accuracy. Prediction accuracy varied among different training population proportions. Conclusions We conclude that prediction accuracy for genomic selection can be improved by using the Bayes B model with a subset of significant markers and by selecting the training population based on narrow sense heritability.

Planting date and cultivar maturity group (MG) are major management factors affecting soybean [Glycine max (L.) Merr.] yield, but their effect on seed oil and protein concentration, and in particular meal protein concentration, is less understood. We quantified changes in seed oil and protein, and estimated meal protein concentration, and total oil and protein yield in response to planting date and cultivar MG ranging from 3 to 6 and across locations comprising a 8.3° range in latitude in the U.S. Midsouth. Our results show that delayed planting date and later cultivar maturity reduced oil concentration, and this was partially associated with a decrease in temperature during the seed fill phase. Thus, optimum cultivar MG recommendations to maximize total oil yield (in kg ha–1) for planting dates in May and June required relatively earlier cultivar MGs than those recommended to maximize seed yield. For planting dates in April, short-season MG 3 cultivars did not increase oil yield compared to full-season MG 4 or 5 cultivars due to a quadratic yield response to planting date at most locations. Planting date and cultivar maturity effects on seed protein concentration were not always consistent with the effects on estimated meal protein concentration after oil extraction. Meal protein concentration decreased with lower temperatures during seed fill, and when the start of seed fill occurred after August 15, but relatively short-season cultivar MGs reduced the risk of low meal protein concentration. Meal protein concentration is a trait of interest for the feed industry that would be beneficial to report in future studies evaluating genetic, management, and environmental effects on seed protein concentration.

Limited knowledge about how nitrogen (N) dynamics are affected by climate change, weather variability, and crop management is a major barrier to improving the productivity and environmental performance of soybean-based cropping systems. To fill this knowledge gap, we created a systems understanding of agroecosystem N dynamics and quantified the impact of controllable (management) and uncontrollable (weather, climate) factors on N fluxes and soybean yields. We performed a simulation experiment across 10 soybean production environments in the United States using the Agricultural Production Systems sIMulator (APSIM) model and future climate projections from five global circulation models. Climate change (2020–2080) increased N mineralization (24%) and N2O emissions (19%) but decreased N fixation (32%), seed N (20%), and yields (19%). Soil and crop management practices altered N fluxes at a similar magnitude as climate change but in many different directions, revealing opportunities to improve soybean systems’ performance. Among many practices explored, we identified two solutions with great potential: improved residue management (short-term) and water management (long-term). Inter-annual weather variability and management practices affected soybean yield less than N fluxes, which creates opportunities to manage N fluxes without compromising yields, especially in regions with adequate to excess soil moisture. This work provides actionable results (tradeoffs, synergies, directions) to inform decision-making for adapting crop management in a changing climate to improve soybean production systems.

Abstract The separation of biomarkers from blood is straightforward in most molecular biology laboratories. However, separation in resource-limited settings, allowing for the successful removal of biomarkers for diagnostic applications, is not always possible. The situation is further complicated by the need to separate hydrophobic signatures such as lipids from blood. Herein, we present a microfluidic device capable of centrifugal separation of serum from blood at the point of need with a system that is compatible with biomarkers that are both hydrophilic and hydrophobic. The cross-flow filtration device separates serum from blood as efficiently as traditional methods and retains amphiphilic biomarkers in serum for detection.

Abstract A consistent risk for soybean (Glycine max L.) production is the impact of drought on growth and yield. Canopy temperature (CT) is an indirect measure of transpiration rate and stomatal conductance and may be valuable in distinguishing differences among genotypes in response to drought. The objective of this study was to map quantitative trait loci (QTLs) associated with CT using thermal infrared imaging in a population of recombinant inbred lines developed from a cross between KS4895 and Jackson. Heritability of CT was 35% when estimated across environments. QTL analysis identified 11 loci for CT distributed on eight chromosomes that individually explained between 4.6 and 12.3% of the phenotypic variation. The locus on Gm11 was identified in two individual environments and across environments and explained the highest proportion of phenotypic variation (9.3% to 11.5%) in CT. Several of these CT loci coincided with the genomic regions from previous studies associated with canopy wilting, canopy temperature, water use efficiency, and other morpho-physiological traits related with drought tolerance. Candidate genes with biological function related to transpiration, root development, and signal transduction underlie these putative CT loci. These genomic regions may be important resources in soybean breeding programs to improve tolerance to drought.

Abstract Dental health is deeply rooted in the primary care of an individual such that an individual's overall health status and behaviours may be determined by their oral health status. Oral diseases are a major cause of morbidity and are among the most prevalent diseases worldwide. Despite the risk these diseases pose to global health, they remain a largely neglected facet of healthcare. In this article, we discuss why predominantly preventable oral diseases persist with high prevalence and suggest how to address the global oral disease epidemic. People living in rural areas are particularly disadvantaged, due to insufficient oral care in remote locations, lack of transport and an overall under‐resourced health care infrastructure. In cases where oral health programmes exist, they are usually directed only at certain groups. Dental tourism has been increasing in popularity over the last two decades. Eastern Europe has become one of the leading destinations for patients seeking dental care across borders. However, negative findings regarding the quality of dental procedures in these destinations have been highlighted in many studies, with some pointing out that only a small fraction of patients received sufficient quality, and that only very simple dental treatments were actually evaluated as cost‐effective. Low‐income countries are hindered not only by lack of dentists, but by lack of public health initiatives such as fluoridation of water and toothpastes. The integration of oral health into medical education and primary care could improve the common risk factor approach between the specialties and improve preventative measures and screening for better patient outcomes and reduction in cost of care.

Abstract Background First Nations peoples of Australia, New Zealand, the United States of America (USA) and Canada are more likely to be non-drinkers than other people in these countries. However, those who do drink may be at greater risk of alcohol-related harms (at a population level) due to the ongoing impacts from colonisation and associated oppression. Addressing unhealthy drinking (drinking above recommended limits including alcohol use disorders) in primary care settings is one important way to increase accessibility of treatment. Methods This systematic review identifies peer-reviewed studies of alcohol treatments delivered in primary care or other non-residential settings for First Nations peoples of Australia, New Zealand, USA and Canada. Literature searches were conducted in seven academic databases from their inception until March, 2020. We assessed evidence of treatment or implementation effectiveness, perceived acceptability or accessibility, and the study quality as assessed by the AXIS tool and by a measure of community participation in the research process. Results Twenty-eight studies were included, published between 1968 and 2018. Studies reported on a range of alcohol treatments, from brief intervention to ambulatory withdrawal management, relapse prevention medicines, and cultural therapies. Brief intervention was the most studied approach. Cultural healing practices and bicultural approaches were a key theme amongst several studies. Four studies measured treatment effectiveness, including one randomised controlled trial (naltrexone vs naltrexone plus sertraline vs placebo) and two uncontrolled trials of disulfiram. Of the six implementation studies, three were (hybrid) effectiveness-implementation designs. Most of the remaining studies (n = 21) focused on treatment accessibility or acceptability. Community participation in the research process was poorly reported in most studies. Conclusions Research evidence on how best to care for First Nations peoples with unhealthy alcohol use is limited. Trials of naltrexone and disulfiram presented promising results. Cultural and bicultural care were perceived as highly important to clinical staff and clients in several studies. More effectiveness studies on the full scope of alcohol treatments are needed. Greater community participation in research and more transparent reporting of this in study methods will be key to producing quality research that combines scientific rigour with cultural appropriateness.

Soybean [Glycine max (L.) Merr.] nitrogen fixation is sensitive differentially to drought among different genotypes at different growth and development stages, which directly affects soybean yield. Acetylene reduction activity (ARA) response to a gradual drought and rewatering period at late podding (late R3) and late seed fill (late R5) were evaluated in two different water use efficiency (WUE) genotypes. Drought-stressed plants with high WUE (PI 372413) decreased ARA more insensitively than that of low WUE (PI 548534), and drought-stressed plants with low WUE (PI 548534) maintained low ARA level after stress alleviation at late R5. The recovery ability of N2 fixation was a genotypic difference with WUE at late reproductive development (late R5), especially. Analysing relation between fraction of transpirable soil water (FTSW) and relative ARA, it was confirmed that PI 372413 with high WUE was more insensitive to water deficit and had drought tolerance by N2 fixation and recovery ability with a threshold of 0.139-0.147 FTSW than PI 548534 with a threshold of 0.192-0.209 FTSW. The ability to recover N2 fixation following drought during the reproductive developmental stage would be of an important value in the actual planting environment.

Several models have been proposed to simulate the leaf area index (LAI) in soybean (Glycine max L.); however, these models do not directly account for the effect of branch growth. Because the increases in branches and branch node vary with plant density, the evaluation of branch growth is necessary for the application of the LAI model at various plant densities. In this study, we developed an LAI model for soybean, considering the branch growth and leaf elongation at each node. To simplify this model, we estimated the rate of branch and branch node increase based on the rate of main stem node increase. Branch growth was assumed to be restricted when the fraction of canopy radiation interception was increased. Moreover, we calculated the leaf area growth at each node based on leaf elongation at each leaflet. This LAI model was validated using the data of different years and plant densities for model calibration, and it estimated the LAI with a root mean square error of 0.76, which accounted for 92% of the variation in the data. Although further evaluation is needed, the LAI model proposed in this study reveals a high potential for accurate estimation of LAI at various plant densities.

Low seed and meal protein concentration in modern high-yielding soybean [Glycine max L. (Merr.)] cultivars is a major concern but there is limited information on effective cultural practices to address this issue. In the objective of dealing with this problem, this study conducted field experiments in 2019 and 2020 to evaluate the response of seed and meal protein concentrations to the interactive effects of late-season inputs [control, a liquid Bradyrhizobium japonicum inoculation at R3, and 202 kg ha−1 nitrogen (N) fertilizer applied after R5], previous cover crop (fallow or cereal cover crop with residue removed), and short- and full-season maturity group cultivars at three U.S. locations (Fayetteville, Arkansas; Lexington, Kentucky; and St. Paul, Minnesota). The results showed that cover crops had a negative effect on yield in two out of six site-years and decreased seed protein concentration by 8.2 mg g−1 on average in Minnesota. Inoculant applications at R3 did not affect seed protein concentration or yield. The applications of N fertilizer after R5 increased seed protein concentration by 6 to 15 mg g−1, and increased yield in Arkansas by 13% and in Minnesota by 11% relative to the unfertilized control. This study showed that late-season N applications can be an effective cultural practice to increase soybean meal protein concentration in modern high-yielding cultivars above the minimum threshold required by the industry. New research is necessary to investigate sustainable management practices that increase N availability to soybeans late in the season.

Many caribou populations are declining across the Circumpolar North, presenting challenges for many Indigenous Peoples who have deep and enduring relationships with this animal. In Labrador, Canada, caribou herds have recently experienced population declines, including the George River herd, which has dropped by 99% from its peak, leading to the enactment of a total hunting ban in 2013 issued by the Government of Newfoundland and Labrador. The decline and subsequent hunting ban have affected various aspects of Inuit well-being. Using Inuit-led multi-media methods, this project heard voices of Inuit across the Nunatsiavut and NunatuKavut regions in Labrador, Canada, which (1) described the importance of caribou for Inuit social connections, (2) explored the ways in which the changes in caribou populations and management strategies are influencing these social connections, and (3) discussed the meaning and value of these social connections for Inuit well-being and the sustainability of Inuit-caribou relationships into the future. Data from video interviews (Nunatsiavut region: n = 54; NunatuKavut region: n = 30) were collected and analyzed using video and photography-based methods. Results characterized how caribou are important social connectors: human-caribou relationships are core to Inuit socialization, inter-connection, and shared experience and memory regarding families, communities, and food and knowledge sharing across Labrador’s landscape. Thus, declines in caribou populations and associated social interaction have had serious implications for Inuit identity, livelihoods, emotional well-being, cultural continuity, and knowledge transfer. In order to support the broader social-ecological system and the well-being of those who are connected to caribou, increased understanding and integration of these social connections into caribou-related decision making and research is recommended.

Blow fly development is important in decomposition ecology, agriculture, and forensics. Much of the impact of these species is from immature samples, thus knowledge of their development is important to enhance or ameliorate their effects. One application of this information is the estimation of immature insect age to provide temporal information for death investigations. While traditional markers of age such as stage and size are generally accurate, they lack precision in later developmental stages. We used miRNA sequencing to measure miRNA expression, throughout development, of the secondary screwworm, Cochliomyia macellaria (Fabricius) (Diptera: Calliphoridae) and identified 217 miRNAs present across the samples. Ten were identified to be significantly differentially expressed in larval samples and seventeen were found to be significantly differentially expressed in intrapuparial samples. Twenty-eight miRNAs were identified to be differentially expressed between sexes. Expression patterns of two miRNAs, miR-92b and bantam, were qPCR-validated in intrapuparial samples; these and likely food-derived miRNAs appear to be stable markers of age in C. macellaria. Our results support the use of miRNAs for developmental markers of age and suggest further investigations across species and under a range of abiotic and biotic conditions.

Drought causes significant soybean [Glycine max (L.) Merr.] yield losses each year in rain-fed production systems of many regions. Genetic improvement of soybean for drought tolerance is a cost-effective approach to stabilize yield under rain-fed management. The objectives of this study were to confirm previously reported soybean loci and to identify novel loci associated with canopy wilting (CW) using a panel of 200 diverse maturity group (MG) IV accessions. These 200 accessions along with six checks were planted at six site-years using an augmented incomplete block design with three replications under irrigated and rain-fed treatments. Association mapping, using 34,680 single nucleotide polymorphisms (SNPs), identified 188 significant SNPs associated with CW that likely tagged 152 loci. This includes 87 SNPs coincident with previous studies that likely tagged 68 loci and 101 novel SNPs that likely tagged 84 loci. We also determined the ability of genomic estimated breeding values (GEBVs) from previous research studies to predict CW in different genotypes and environments. A positive relationship (P ≤ 0.05;0.37 ≤ r ≤ 0.5) was found between observed CW and GEBVs. In the vicinity of 188 significant SNPs, 183 candidate genes were identified for both coincident SNPs and novel SNPs. Among these 183 candidate genes, 57 SNPs were present within genes coding for proteins with biological functions involved in plant stress responses. These genes may be directly or indirectly associated with transpiration or water conservation. The confirmed genomic regions may be an important resource for pyramiding favorable alleles and, as candidates for genomic selection, enhancing soybean drought tolerance.

Biological nitrogen (N)-fixation is the most important source of N for soybean [Glycine max (L.) Merr.], with considerable implications for sustainable intensification. Therefore, this study aimed to investigate the relevance of environmental factors driving N-fixation and to develop predictive models defining the role of N-fixation for improved productivity and increased seed protein concentration. Using the elastic net regularization of multiple linear regression, we analyzed 40 environmental factors related to weather, soil, and crop management. We selected the most important factors associated with the relative abundance of ureides (RAU) as an indicator of the fraction of N derived from N-fixation. The most relevant RAU predictors were N fertilization, atmospheric vapor pressure deficit (VPD) and precipitation during early reproductive growth (R1–R4 stages), sowing date, drought stress during seed filling (R5–R6), soil cation exchange capacity (CEC), and soil sulfate concentration before sowing. Soybean N-fixation ranged from 60 to 98% across locations and years (n = 95). The predictive model for RAU showed relative mean square error (RRMSE) of 4.5% and an R2 value of 0.69, estimated via cross-validation. In addition, we built similar predictive models of yield and seed protein to assess the association of RAU and these plant traits. The variable RAU was selected as a covariable for the models predicting yield and seed protein, but with a small magnitude relative to the sowing date for yield or soil sulfate for protein. The early-reproductive period VPD affected all independent variables, namely RAU, yield, and seed protein. The elastic net algorithm successfully depicted some otherwise challenging empirical relationships to assess with bivariate associations in observational data. This approach provides inference about environmental variables while predicting N-fixation. The outcomes of this study will provide a foundation for improving the understanding of N-fixation within the context of sustainable intensification of soybean production.

Abstract Background Selection of an appropriate statistical significance threshold in genome-wide association studies is critical to differentiate true positives from false positives and false negatives. Different multiple testing comparison methods have been developed to determine the significance threshold; however, these methods may be overly conservative and may lead to an increase in false negatives. Here, we developed an empirical formula to determine the statistical significance threshold that is based on the marker-based heritability of the trait. To develop a formula for a significance threshold, we used 45 simulated traits in soybean, maize, and rice that varied in both broad sense heritability and the number of QTLs. Results A formula to determine a significance threshold was developed based on a regression equation that used one independent variable, marker-based heritability, and one response variable, − log10 (P)-values. For all species, the threshold –log10 (P)-values increased as both marker-based and broad-sense heritability increased. Higher broad sense heritability in these crops resulted in higher significant threshold values. Among crop species, maize, with a lower linkage disequilibrium pattern, had higher significant threshold values as compared to soybean and rice. Conclusions Our formula was less conservative and identified more true positive associations than the false discovery rate and Bonferroni correction methods.

Core Ideas Soybean yield and crop growth was measured in high‐yield contest fields. Radiation use efficiency and nitrogen uptake were greater than recorded values. Yield was grossly under‐predicted using default growth parameters. Yield predictions were greatly improved using measured growth parameters. Crop models have played important roles in identifying potential constraints for crop growth and yield. A relatively simple soybean [Glycine max (L.) Merr.] model consisting of a daily C, N, and water budget was used to simulate yields for optimum production environments at Fayetteville, AR, and at a farmer's contest field in Missouri for 2012 to 2013. Data were collected on radiation use efficiency (RUE), N accumulation rate, specific leaf nitrogen (SLN), and the dry matter accumulation coefficient (DMAC) as a measure of whole‐crop seed growth rate. In Fayetteville, measured yields ranged from 4977 to 7144 kg ha−1, and simulated yields averaged 34.0% below the measured yields using the default model parameters. Using measured parameters in a modified model, predicted yields were 2.8% above observed. Default parameter simulations for the contest fields were 39.0% below measured yield and were 18.7% below measured yield when using measured parameters. Sensitivity analyses indicated that lower DMAC values increased yields due to slower seedfill rates, allowing additional N accumulation and a slower translocation of N to the growing seeds. Simulating an increased SLN and RUE increased predicted yields in 2012 and 2013 when N accumulation rates were great enough to supply the required N for new biomass. Alternatively, increasing N accumulation rates increased yield up to a plateau when all N requirements were met. These results illustrate the importance and interconnectivity of the crop growth processes relating to C and N metabolism and that current bounds for crop growth characteristics should be reconsidered.

Abstract Background Photosynthesis is able to convert solar energy into chemical energy in the form of biomass, but the efficiency of photosynthetic solar energy conversion is low. Chlorophyll fluorescence measurements are rapid, non-destructive, and can provide a wealth of information about the efficiencies of the photosynthetic light reaction processes. Efforts aimed at assessing genetic variation and/or mapping of genetic loci associated with chlorophyll fluorescence phenotypes have been rather limited. Results Evaluation of SoySNP50K iSelect SNP Beadchip data from the 189 genotypes phenotyped in this analysis identified 32,453 SNPs with a minor allele frequency (MAF) ≥ 5%. A total of 288 (non-unique) SNPs were significantly associated with one or more of the 21 chlorophyll fluorescence phenotypes. Of these, 155 were unique SNPs and 100 SNPs were only associated with a single fluorescence phenotype, while 28, 11, 2, and 14 SNPs, were associated with two, three, four and five or more fluorescence phenotypes, respectively. The 288 non-unique SNPs represent 155 unique SNPs that mark 53 loci. The 155 unique SNPs included 27 that were associated with three or more phenotypes, and thus were called multi-phenotype SNPs. These 27 multi-phenotype SNPs marked 13 multi-phenotype loci (MPL) identified by individual SNPs associated with multiple chlorophyll fluorescence phenotypes or by more than one SNP located within 0.5 MB of other multi-phenotype SNPs. Conclusion A search in the genomic regions highlighted by these 13 MPL identified genes with annotations indicating involvement in photosynthetic light dependent reactions. These, as well as loci associated with only one or two chlorophyll fluorescence traits, should be useful to develop a better understanding of the genetic basis of photosynthetic light dependent reactions as a whole as well as of specific components of the electron transport chain in soybean. Accordingly, additional genetic and physiological analyses are necessary to determine the relevance and effectiveness of the identified loci for crop improvement efforts.

Association mapping (AM) is a powerful tool for fine mapping complex trait variation down to nucleotide sequences by exploiting historical recombination events. A major problem in AM is controlling false positives that can arise from population structure and family relatedness. False positives are often controlled by incorporating covariates for structure and kinship in mixed linear models (MLM). These MLM-based methods are single locus models and can introduce false negatives due to over fitting of the model. In this study, eight different statistical models, ranging from single-locus to multilocus, were compared for AM for three traits differing in heritability in two crop species: soybean (Glycine max L.) and maize (Zea mays L.). Soybean and maize were chosen, in part, due to their highly differentiated rate of linkage disequilibrium (LD) decay, which can influence false positive and false negative rates. The fixed and random model circulating probability unification (FarmCPU) performed better than other models based on an analysis of Q-Q plots and on the identification of the known number of quantitative trait loci (QTLs) in a simulated data set. These results indicate that the FarmCPU controls both false positives and false negatives. Six qualitative traits in soybean with known published genomic positions were also used to compare these models, and results indicated that the FarmCPU consistently identified a single highly significant SNP closest to these known published genes. Multiple comparison adjustments (Bonferroni, false discovery rate, and positive false discovery rate) were compared for these models using a simulated trait having 60% heritability and 20 QTLs. Multiple comparison adjustments were overly conservative for MLM, CMLM, ECMLM, and MLMM and did not find any significant markers; in contrast, ANOVA, GLM, and SUPER models found an excessive number of markers, far more than 20 QTLs. The FarmCPU model, using less conservative methods (false discovery rate, and positive false discovery rate) identified 10 QTLs, which was closer to the simulated number of QTLs than the number found by other models.

Abstract Applying supplemental fertilizer N or inoculating soybean [Glycine max (L.) Merr.] seed with Bradyrhizobium japonicum led to mixed yield responses. We assessed the profitability of seed inoculation, fertilizing with N, or both, across different planting dates using maturity group (MG) IV and MG V soybean cultivars under irrigated conditions. Planting dates ranged from late May to late June at Fayetteville, AR, and Pine Tree, AR, from 2017 to 2019. Urea fertilizer was applied at R2 at 0 or 56 kg N ha−1 using inoculated soybean. Similarly, non‐inoculated treatments ranged from 0, 28, 56, 112, to 168 kg N ha−1. Although fertilizer did increase yield, the response varied by planting date, was small, and only significant at p = .141 and .171 for linear and non‐linear effects of N, respectively. Seed inoculation had a small negative impact (89 kg ha−1) on yield (p = .0157). Using historical prices over the last 10 yr, optimal fertilizer rates ranged from 3.6 to 6.6 kg N ha−1 with an attendant average yield increase of 32 kg ha−1 for early planting and from 2.6 to 4.1 kg N ha−1 for late planting with an average yield gain of 24 kg ha−1. Regardless of timing of planting, the added yield less attendant fertilizer cost resulted in an average net gain of US$7.39 and $6.00 ha−1, for early and late planting, respectively. That net gain was insufficient to cover additional custom fertilizer application charges of $17.30 ha−1. Hence, inoculation and fertilizer N are not recommended.

Abstract Manipulation of soybean [Glycine max (L.) Merr.] maturity group (MG) and planting date will increase the yield of a soybean crop while simultaneously influencing the potential soil‐nitrogen (N) credits. Variations in N returned to the soil by soybean can significantly affect the amount of fertilizer‐N needed for the subsequent crop. Four soybean MGs (3.5, 4.7, 5.4, and 5.6) were evaluated at optimal and late planting dates in Arkansas. Grain yield was significantly different among MGs in 2016 (P = .0012) and 2017 (P = .0004), with the 4.7 MG consistently yielding the highest at 3,232 kg ha−1. Plant total aboveground N uptake (TNU) increased with increasing grain yield (P = .0167) and was significantly higher when planted in an optimal planting window (P = .0004). The N removed from the cropping system through grain harvest (147–201 kg N ha−1) was significantly different among MGs in 2016 (P

Soybean [Glycine max (L.) Merr.] seed composition and yield are a function of genetics (G), environment (E), and management (M) practices, but contribution of each factor to seed composition and yield are not well understood. The goal of this synthesis-analysis was to identify the main effects of G, E, and M factors on seed composition (protein and oil concentration) and yield. The entire dataset (13,574 data points) consisted of 21 studies conducted across the United States (US) between 2002 and 2017 with varying treatments and all reporting seed yield and composition. Environment (E), defined as site-year, was the dominant factor accounting for more than 70% of the variation for both seed composition and yield. Of the crop management factors: (i) delayed planting date decreased oil concentration by 0.007 to 0.06% per delayed week (R2∼0.70) and a 0.01 to 0.04 Mg ha-1 decline in seed yield per week, mainly in northern latitudes (40–45 N); (ii) crop rotation (corn-soybean) resulted in an overall positive impact for both seed composition and yield (1.60 Mg ha-1 positive yield difference relative to continuous soybean); and (iii) other management practices such as no-till, seed treatment, foliar nutrient application, and fungicide showed mixed results. Fertilizer N application in lower quantities (10–50 kg N ha-1) increased both oil and protein concentration, but seed yield was improved with rates above 100 kg N ha-1. At southern latitudes (30–35 N), trends of reduction in oil and increases in protein concentrations with later maturity groups (MG, from 3 to 7) was found. Continuing coordinated research is critical to advance our understanding of G × E × M interactions.

The difference in yields of cultivars may be causing difference in soybean yield between Japan and the USA. The objective of this study was to identify the effect of the cultivar on dry matter production and to reveal the key factors causing the differences in yield by focusing utilization of solar radiation in recent Japanese and US soybean cultivars. Field experiments were conducted during two seasons in Takatsuki, Japan (34°50′), and in a single season in Fayetteville (36°04′), AR, USA. Five Japanese and 10 US cultivars were observed under near-optimal conditions in order to achieve yields as close to their physiological potential as possible. The seed yield and total aboveground dry matter (TDM) were measured at maturity as long as radiation was intercepted by the canopy. The seed yield ranged from 3.10t ha−1 to 5.91t ha−1. Throughout the three environments, the seed yield of US cultivars was significantly higher than that of Japanese cultivars. The seed yield correlated with the TDM rather than the HI with correlation coefficients from .519 to .928 for the TDM vs. .175 to .800 for the HI, for each of the three environments. The higher TDM of US cultivars was caused by a higher radiation use efficiency rather than higher total intercepted radiation throughout the three environments. The seasonal change in the TDM observed in four cultivars indicated that dry matter productivity was different between cultivars, specifically during the seed-filling period.

Carbon isotope ratio (δC) has been used as a proxy for water use efficiency (WUE) in several crops. We compared δC of soybean [ (L.) Merr.] tissues sampled at bloom with δC of mature seed (MS). Twenty Maturity Group IV accessions with contrasting δC values were evaluated in three environments. Genotype and environment effects on δC were significant for the uppermost mature trifoliolate leaf, center leaflets from main stems, whole shoot, and MS, but there were no significant genotype by environment interactions, indicating that genotype rankings were similar among environments. Repeatability of δC among tissues ranged from 0.79 to 0.94, and MS δC values were significantly correlated with δC from other tissues ( ≥ 0.69). For genotypes of similar maturity, MS δC may be used as a selection tool for WUE, simplifying the use of δC for high-throughput phenotyping.

The mineral composition of crop shoot tissues is important for yield formation and nutrient remobilization to seeds. The natural diversity that exists within crop species can be used to investigate mechanisms that define plant mineral composition and to identify important genomic loci for these processes. The objective of this study was to determine shoot mineral nutrient concentrations in genetically diverse soybean [ (L.) Merr.] genotypes and to identify genomic regions associated with concentrations of different nutrients in shoot tissue. The genotypes were grown at two locations in 2 yr and characterized for macronutrient (Ca, Mg, P, K, and S) and micronutrient (B, Cu, Fe, Mn, and Zn) concentrations in shoot tissues. Genome-wide association studies were conducted with 31,748 single nucleotide polymorphisms (SNPs) via a unified mixed model to identify SNPs associated with macro- and micronutrient concentrations. The number of putative loci identified for the macronutrients ranged from 11 for Ca to 20 for K. For the micronutrients, the number ranged from 10 for Mn to 24 for Fe. In addition to colocated loci for multiple nutrients, 22 individual SNPs were associated with more than one nutrient such that 11 different nutrient combinations were encompassed by these SNPs. Ultimately, the putative loci identified in this study will need to be confirmed and are expected to aid in the identification of new sources of variation for use in soybean breeding programs as well as for mechanistic studies aimed at understanding the regulation of mineral nutrient uptake, translocation, and shoot tissue concentrations.