Mapping of flumioxazin tolerance in a snap bean diversity panel leads to the discovery of a master genomic region controlling multiple stress resistance genes.

Introduction: Effective weed management tools are crucial for maintaining the profitable production of snap bean (Phaseolus vulgaris L.). Preemergence herbicides help the crop to gain a size advantage over the weeds, but the few preemergence herbicides registered in snap bean have poor waterhemp (Amaranthus tuberculatus) control, a major pest in snap bean production. Waterhemp and other difficult-to-control weeds can be managed by flumioxazin, an herbicide that inhibits protoporphyrinogen oxidase (PPO). However, there is limited knowledge about crop tolerance to this herbicide. We aimed to quantify the degree of snap bean tolerance to flumioxazin and explore the underlying mechanisms. Methods: We investigated the genetic basis of herbicide tolerance using genome-wide association mapping approach utilizing field-collected data from a snap bean diversity panel, combined with gene expression data of cultivars with contrasting response. The response to a preemergence application of flumioxazin was measured by assessing plant population density and shoot biomass variables. Results: Snap bean tolerance to flumioxazin is associated with a single genomic location in chromosome 02. Tolerance is influenced by several factors, including those that are indirectly affected by seed size/weight and those that directly impact the herbicide's metabolism and protect the cell from reactive oxygen species-induced damage. Transcriptional profiling and co-expression network analysis identified biological pathways likely involved in flumioxazin tolerance, including oxidoreductase processes and programmed cell death. Transcriptional regulation of genes involved in those processes is possibly orchestrated by a transcription factor located in the region identified in the GWAS analysis. Several entries belonging to the Romano class, including Bush Romano 350, Roma II, and Romano Purpiat presented high levels of tolerance in this study. The alleles identified in the diversity panel that condition snap bean tolerance to flumioxazin shed light on a novel mechanism of herbicide tolerance and can be used in crop improvement.

First report of severe tolpyralate sensitivity in corn (Zea mays) discovers a novel genetic factor conferring crop response to a herbicide.

BACKGROUND: Tolpyralate, a relatively new inhibitor of 4-hydroxyphenylpyruvate dioxygenase (HPPD), is registered for postemergence use in all types of corn (Zea mays L.) and has a record of excellent crop tolerance. A report of severe crop injury to sweet corn inbred (XSEN187) led to the following objectives: (i) determine whether sensitivity to tolpyralate in XSEN187 exists, and if confirmed, (ii) determine the genetic basis of tolpyralate sensitivity, and (iii) screen other corn germplasm for sensitivity to tolpyralate. RESULTS: Inbred XSEN187 was confirmed sensitive to tolpyralate. Inclusion of methylated seed oil or nonionic surfactant in the spray volume was necessary for severe crop injury. Tolpyralate sensitivity in XSEN187 is not conferred by alleles at Nsf1, a cytochrome P450-encoding gene (CYP81A9) conferring tolerance to many corn herbicides. Evidence suggests that tolpyralate sensitivity in XSEN187 is conferred by a single gene mapped to the Chr05: 283 240-1 222 909 bp interval. Moreover, tolpyralate sensitivity was observed in 48 other sweet corn and field corn inbreds. CONCLUSIONS: Severe sensitivity to tolpyralate exists in sweet corn and field corn germplasm when the herbicide is applied according to label directions. Whereas the corn response to several other herbicides, including HPPD-inhibitors, is conferred by the Nsf1 locus, corn sensitivity to tolpyralate is the result of a different locus. The use of tolpyralate should consider herbicide tolerance in inbred lines from which corn hybrids were derived, whereas alleles that render corn germplasm sensitive to tolpyralate should be eliminated from breeding populations, inbreds, and commercial cultivars. © 2023 Illinois Foundation Seeds, Inc and The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

The silver bullet that wasn't: Rapid agronomic weed adaptations to glyphosate in North America.

The rapid adoption of glyphosate-resistant crops at the end of the 20th century caused a simplification of weed management that relied heavily on glyphosate for weed control. However, the effectiveness of glyphosate has diminished. A greater understanding of trends related to glyphosate use will shed new light on weed adaptation to a product that transformed global agriculture. Objectives were to (1) quantify the change in weed control efficacy from postemergence (POST) glyphosate use on troublesome weeds in corn and soybean and (2) determine the extent to which glyphosate preceded by a preemergence (PRE) improved the efficacy and consistency of weed control compared to glyphosate alone. Herbicide evaluation trials from 24 institutions across the United States of America and Canada from 1996 to 2021 were compiled into a single database. Two subsets were created; one with glyphosate applied POST, and the other with a PRE herbicide followed by glyphosate applied POST. Within each subset, mean and variance of control ratings for seven problem weed species were regressed over time for nine US states and one Canadian province. Mean control with POST glyphosate alone decreased over time while variability in control increased. Glyphosate preceded by a labeled PRE herbicide showed little change in mean control or variability in control over time. These results illustrate the rapid adaptation of agronomically important weed species to the paradigm-shifting product glyphosate. Including more diversity in weed management systems is essential to slowing weed adaptation and prolonging the usefulness of existing and future technologies.

Evidence of sweet corn yield losses from rising temperatures.

Crop production is sensitive to anomalous weather conditions, but vegetable crops can be highly sensitive to environmental changes. Using sweet corn data collected on 16,040 fields over a 27-year period, we: (a) estimate yield sensitivities to changes in growing season temperature and total precipitation, (b) estimate critical thresholds in non-linear temperature effects on sweet corn yield across diverse environments, and (c) quantify yield losses from surpassing the upper temperature threshold during anthesis in sweet corn. Our results show growing-season temperatures exceeding 30 [Formula: see text] were detrimental to crop yield. Each additional degree day spent above 30 [Formula: see text] during anthesis reduced crop yields by 0.5% and 2% in irrigated and rainfed fields, respectively. This study shows evidence for sweet corn yield losses across broad spatial domains in the wake of climate change and underscores the urgency to accelerate crop adaptation strategies to sustain production of this highly popular crop.

Deteriorating weed control and variable weather portends greater soybean yield losses in the future.

Since the 1950's much of the US soybean growing region has experienced rising temperatures, more variable rainfall, and increased carbon emissions. These trends are predicted to continue throughout the 21st century. Variable weather and weed interference influence crop performance; however, their combined effects on soybean yield are poorly understood. Using machine learning techniques on a database of herbicide trials spanning 28 years and 106 weather environments we modeled the most important relationships among weed control, weather variability, and crop management on soybean yield loss. When late-season weeds were poorly controlled, average soybean yield losses of 48% were observed. Additionally, when weeds were not completely controlled, low rainfall and high temperatures during seed fill exacerbated soybean yield loss due to weeds. Since much of the US soybean growing region is heading towards drier, warmer conditions, coupled with growing herbicide resistance, future soybean yield loss will increase without significant improvements in weed management systems.

Historical Trends in Sweet Corn Plant Density Tolerance Using Era Hybrids (1930-2010s).

Over the last six decades, steady improvement in plant density tolerance (PDT) has been one of the largest contributors to genetic yield gain in field corn. While recent research indicates that PDT in modern sweet corn hybrids could be exploited to improve yield, historical changes in PDT in sweet corn are unknown. The objectives of this study were to: (a) quantify the extent to which PDT has changed since introduction of hybrid sweet corn and (b) determine the extent to which changes over time in PDT are associated with plant morpho-physiological and ear traits. An era panel was assembled by recreating 15 sugary1 sweet corn hybrids that were widely used at one time in the United States, representing hybrids since the 1930s. Era hybrids were evaluated in field experiments in a randomized complete block design with a split-plot arrangement of treatments, including hybrid as the main factor and density as the split-plot factor. Plant density treatments included "Low" plant density (9,900 plants/ha) free of crowding stress or "High" plant density (79,000 plants/ha) with crowding stress. On average, per-area marketable ear mass (Mt/ha) increased at a rate of 0.8 Mt/ha/decade at High densities, whereas per-plant yield (i.e., kg/plant) remained unchanged over time regardless of the density level. Crate yield, a fresh market metric, improved for modern hybrids. However, processing sweet corn yield metrics like fresh kernel mass and recovery (amount of kernel mass contributing to the fresh ear mass) showed modest or no improvement over time, respectively. Modern sweet corn hybrids tend to have fewer tillers and lower fresh shoot biomass, potentially allowing the use of higher plant density; however, plant architecture alone does not accurately predict PDT of individual hybrids.

Diminishing weed control exacerbates maize yield loss to adverse weather.

Both weed interference and adverse weather can cause significant maize yield losses. However, most climate change projections on maize yields ignore the fact that weeds are widespread in maize production. Herein, we examine the effects of weed control and weather variability on maize yield loss due to weeds by using machine learning techniques on an expansive database of herbicide efficacy trials spanning 205 weather environments and 27 years. Late-season control of all weed species was the most important driver of maize yield loss due to weeds according to multiple analyses. Average yield losses of 50% were observed with little to no weed control. Furthermore, when the highest levels of weed control were not achieved, drier, hotter conditions just before and during silking exacerbated maize yield losses due to weeds. Current climate predictions suggest much of the US maize-growing regions will experience warmer, drier summers. This, coupled with the growing prevalence of herbicide resistance, increases the risk of maize yield loss due to weeds in the future without transformational change in weed management systems.

Transcriptional analysis of sweet corn hybrids in response to crowding stress.

Crop tolerance to crowding stress, specifically plant population density, is an important target to improve productivity in processing sweet corn. Due to limited knowledge of biological mechanisms involved in crowding stress in sweet corn, a study was conducted to 1) investigate phenotypic and transcriptional response of sweet corn hybrids under different plant densties, 2) compare the crowding stress response mechanisms between hybrids and 3) identify candidate biological mechanisms involved in crowding stress response. Yield per hectare of a tolerant hybrid (DMC21-84) increased with plant density. Yield per hectare of a sensitive hybrid (GSS2259P) declined with plant density. Transcriptional analysis found 694, 537, 359 and 483 crowding stress differentially expressed genes (DEGs) for GSS2259P at the Fruit Farm and Vegetable Farm and for DMC21-84 at the Fruit Farm and Vegetable Farm, respectively. Strong transcriptional change due to hybrid was observed. Functional analyses of DEGs involved in crowding stress also revealed that protein folding and photosynthetic processes were common response mechanisms for both hybrids. However, DEGs related to starch biosynthetic, carbohydrate metabolism, and ABA related processes were significant only for DMC21-84, suggesting the genes have closer relationship to plant productivity under stress than other processes. These results collectively provide initial insight into potential crowding stress response mechanisms in sweet corn.

Future efficacy of pre-emergence herbicides in corn (Zea mays) is threatened by more variable weather.

BACKGROUND: By 2050, weather is expected to become more variable with a shift towards higher temperatures and more erratic rainfall throughout the U.S. Corn Belt. The effects of this predicted weather change on pre-emergence (PRE) herbicide efficacy have been inadequately explored. Using an extensive database, spanning 252 unique weather environments, the efficacy of atrazine, acetochlor, S-metolachlor, and mesotrione, applied PRE alone and in combinations, was modeled on common weed species in corn (Zea mays L.). RESULTS: Adequate rainfall to dissolve the herbicide into soil water solution so that it could be absorbed by developing weed seedlings within the first 15 days after PRE application was essential for effective weed control. Across three annual weed species, the probability of effective control increased as rainfall increased and was maximized when rainfall was 10 cm or more. When rainfall was less than 10 cm, increasing soil temperatures had either a positive or negative effect on the probability of effective control, depending on the herbicide(s) and weed species. Herbicide combinations required less rainfall to maximize the probability of effective control and had higher odds of successfully controlling weeds compared with the herbicides applied individually. CONCLUSIONS: Results of this study highlight the importance of rainfall following PRE herbicide application. As rainfall becomes more variable in future, the efficacy of common PRE herbicides will likely decline. However, utilizing combinations of PRE herbicides along with additional cultural, mechanical, biological, and chemical weed control methods will create a more sustainable integrated weed management system and help U.S. corn production adapt to more extreme weather. © 2021 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Expression and comparison of sweet corn CYP81A9s in relation to nicosulfuron sensitivity.

BACKGROUND: Nicosulfuron, a sulfonylurea herbicide widely used for grass weed control in corn production, injures some sweet corn hybrids and inbreds. A specific cytochrome P450 (P450), CYP81A9, is suggested to be responsible for sensitivity to nicosulfuron and other P450-metabolized herbicides. Corn CYP81A9 enzymes were expressed in E. coli and investigated to find the factor(s) associated with their function and variation in metabolizing nicosulfuron. RESULT: Recombinant expressed CYP81A9s from tolerant sweet corn inbreds produced an active form of P450, while CYP81A9 from a sensitive inbred produced an inactive form. Nicosulfuron bound to tolerant CYP81A9s, and produced reverse-type I ligand, while sensitive CYP81A9 showed no interaction with nicosulfuron. Investigation of 106 sweet corn inbreds showed variation in nicosulfuron injury. A survey of sweet corn CYP81A9 sequences showed mutations in codons for amino acids at 269, 284, 375, and 477 occurred in sweet corn inbreds with complete loss of P450 function (with mean injury >91%) and amino acid changes at 208 and 472 occurred in inbreds with moderate and complete loss of P450 function (with mean injury >14%). CONCLUSION: Our results support that CYP81A9 enzyme is responsible for metabolizing nicosulfuron in sweet corn, and different types of amino acid changes in CYP81A9 sequence are associated with variation in nicosulfuron injury. Therefore, a careful selection of the tolerant allele will be critical for improving tolerance to nicosulfuron and several other P450-metabolized herbicides. © 2020 Society of Chemical Industry.

Understanding variability in optimum plant density and recommendation domains for crowding stress tolerant processing sweet corn.

Recent research shows significant economic benefit if the processing sweet corn [Zea mays L. var. rugosa (or saccharata)] industry grew crowding stress tolerant (CST) hybrids at their optimum plant densities, which may exceed current plant densities by up to 14,500 plants ha-1. However, optimum plant density of individual fields varies over years and across the Upper Midwest (Illinois, Minnesota and Wisconsin), where processing sweet corn is concentrated. The objectives of this study were to: (1) determine the extent to which environmental and management practices affect optimum plant density and, (2) identify the most appropriate recommendation domain for making decisions on plant density. To capture spatial and temporal variability in optimum plant density, on-farm experiments were conducted at thirty fields across the states of Illinois, Minnesota and Wisconsin, from 2013 to 2017. Exploratory factor analysis of twelve environmental and management variables revealed two factors, one related to growing period and the other defining soil type, which explained the maximum variability observed across all the fields. These factors were then used to quantify the strength of associations with optimum plant density. Pearson's partial correlation coefficients of 'growing period' and 'soil type' with optimum plant density were low (ρ1 = -0.14 and ρ2 = -0.09, respectively) and non-significant (P = 0.47 and 0.65, respectively). To address the second objective, six candidate recommendation domain models (RDM) were developed and tested. Linear mixed effects models describing crop response to plant density were fit to each level of each candidate RDM. The difference in profitability observed at the current plant density for a field and the optimum plant density under RDM level represented the additional processor profit ($ ha-1) from a field. The RDM built around 'Production Area' (RDMPA) appears most suitable, because plant density recommendations based on RDMPA maximized processor profits as well grower returns better than other RDMs. Compared to current plant density, processor profits and grower returns increased by $448 ha-1 and $82 ha-1, respectively at plant densities under RDMPA.

Soil Microbial Communities in Diverse Agroecosystems Exposed to the Herbicide Glyphosate.

Despite glyphosate's wide use for weed control in agriculture, questions remain about the herbicide's effect on soil microbial communities. The existing scientific literature contains conflicting results, from no observable effect of glyphosate to the enrichment of agricultural pathogens such as Fusarium spp. We conducted a comprehensive field-based study to compare the microbial communities on the roots of plants that received a foliar application of glyphosate to adjacent plants that did not. The 2-year study was conducted in Beltsville, MD, and Stoneville, MS, with corn and soybean crops grown in a variety of organic and conventional farming systems. By sequencing environmental metabarcode amplicons, the prokaryotic and fungal communities were described, along with chemical and physical properties of the soil. Sections of corn and soybean roots were plated to screen for the presence of plant pathogens. Geography, farming system, and season were significant factors determining the composition of fungal and prokaryotic communities. Plots treated with glyphosate did not differ from untreated plots in overall microbial community composition after controlling for other factors. We did not detect an effect of glyphosate treatment on the relative abundance of organisms such as Fusarium spp.IMPORTANCE Increasing the efficiency of food production systems while reducing negative environmental effects remains a key societal challenge to successfully meet the needs of a growing global population. The herbicide glyphosate has become a nearly ubiquitous component of agricultural production across the globe, enabling an increasing adoption of no-till agriculture. Despite this widespread use, there remains considerable debate on the consequences of glyphosate exposure. In this paper, we examine the effect of glyphosate on soil microbial communities associated with the roots of glyphosate-resistant crops. Using metabarcoding techniques, we evaluated prokaryotic and fungal communities from agricultural soil samples (n = 768). No effects of glyphosate were found on soil microbial communities associated with glyphosate-resistant corn and soybean varieties across diverse farming systems.

Optimum plant density for crowding stress tolerant processing sweet corn.

Globally, gains in sweet corn [Zea mays L.var. rugosa (or saccharata)] are a fraction of the yield advances made in field corn (Zea mays L.) in the last half-century. Grain yield improvement of field corn is associated with increased tolerance to higher plant densities (i.e., crowding stress). Processing sweet corn hybrids that tolerate crowding stress have been identified; however, such hybrids appear to be under-planted in the processing sweet corn. Using crowding stress tolerant (CST) hybrids, the objectives of this study were to: (1) identify optimum plant densities for a range of growing conditions; (2) quantify gaps in production between current and optimum plant densities; and (3) enumerate changes in yield and ear traits when shifting from current to optimum plant densities. Using a CST shrunken-2 (sh2) processing sweet corn hybrid, on-farm plant density trials were conducted in thirty fields across the states of Illinois, Minnesota and Wisconsin, from 2013 to 2017 in order to capture a wide variety of growing conditions. Linear mixed-effects models were used to identify the optimum plant density corresponding to maximum ear mass (Mt ha-1), case production (cases ha-1), and profitability to the processor ($ ha-1). Kernel moisture, indicative of plant development, was unaffected by plant density. Ear traits, such as ear number and ear mass per plant, average ear length, and filled ear length declined linearly with increasing plant density. Nonetheless, there was a large economic benefit to the grower and processor by shifting to higher plant densities in most environments. This research shows that increasing plant densities of CST hybrids from current (58,475 plants ha-1) to optimum (73,075 plants ha-1) could improve processing sweet corn green ear yield and processor profitability on average of 1.13 Mt ha-1 and $525 ha-1, respectively.

Glyphosate Resistance Technology Has Minimal or No Effect on Maize Mineral Content and Yield.

Controversy continues to exist regarding whether the transgene for glyphosate resistance (GR) and/or glyphosate applied to GR crops adversely affect plant mineral content. Field studies were conducted in 2013 and 2014 in Stoneville, MS and Urbana, IL to examine this issue in maize. At each location, the experiment was conducted in fields with no history of glyphosate application and fields with several years of glyphosate use preceding the study. Neither glyphosate nor the GR transgene affected yield or mineral content of leaves or seed, except for occasional (<5%) significant effects that were inconsistent across minerals, treatments, and environments. Glyphosate and AMPA (aminomethylphosphonic acid), a main degradation product of glyphosate, were found in leaves from treated plants, but little or no glyphosate and no AMPA was found in maize seeds. These results show that the GR transgene and glyphosate application, whether used for a single year or several years, have no deleterious effect on mineral nutrition or yield of GR maize.

Lack of transgene and glyphosate effects on yield, and mineral and amino acid content of glyphosate-resistant soybean.

BACKGROUND: There has been controversy as to whether the glyphosate resistance gene and/or glyphosate applied to glyphosate-resistant (GR) soybean affect the content of cationic minerals (especially Mg, Mn and Fe), yield and amino acid content of GR soybean. A two-year field study (2013 and 2014) examined these questions at sites in Mississippi, USA. RESULTS: There were no effects of glyphosate, the GR transgene or field crop history (for a field with both no history of glyphosate use versus one with a long history of glyphosate use) on grain yield. Furthermore, these factors had no consistent effects on measured mineral (Al, As, Ba, Cd, Ca, Co, Cr, Cs, Cu, Fe, Ga, K, Li, Mg, Mn, Ni, Pb, Rb, Se, Sr, Tl, U, V, Zn) content of leaves or harvested seed. Effects on minerals were small and inconsistent between years, treatments and mineral, and appeared to be random false positives. No notable effects on free or protein amino acids of the seed were measured, although glyphosate and its degradation product, aminomethylphosphonic acid (AMPA), were found in the seed in concentrations consistent with previous studies. CONCLUSIONS: Neither glyphosate nor the GR transgene affect the content of the minerals measured in leaves and seed, harvested seed amino acid composition, or yield of GR soybean. Furthermore, soils with a legacy of GR crops have no effects on these parameters in soybean. © 2017 Society of Chemical Industry.

Changes in field workability and drought risk from projected climate change drive spatially variable risks in Illinois cropping systems.

As weather patterns become more volatile and extreme, risks introduced by weather variability will become more critical to agricultural production. The availability of days suitable for field work is driven by soil temperature and moisture, both of which may be altered by climate change. We projected changes in Illinois season length, spring field workability, and summer drought risk under three different emissions scenarios (B1, A1B, and A2) down to the crop district scale. Across all scenarios, thermal time units increased in parallel with a longer frost-free season. An increase in late March and Early April field workability was consistent across scenarios, but a decline in overall April through May workable days was observed for many cases. In addition, summer drought metrics were projected to increase for most scenarios. These results highlight how the spatial and temporal variability in climate change may present unique challenges to mitigation and adaptation efforts.

Identification of Crowding Stress Tolerance Co-Expression Networks Involved in Sweet Corn Yield.

Tolerance to crowding stress has played a crucial role in improving agronomic productivity in field corn; however, commercial sweet corn hybrids vary greatly in crowding stress tolerance. The objectives were to 1) explore transcriptional changes among sweet corn hybrids with differential yield under crowding stress, 2) identify relationships between phenotypic responses and gene expression patterns, and 3) identify groups of genes associated with yield and crowding stress tolerance. Under conditions of crowding stress, three high-yielding and three low-yielding sweet corn hybrids were grouped for transcriptional and phenotypic analyses. Transcriptional analyses identified from 372 to 859 common differentially expressed genes (DEGs) for each hybrid. Large gene expression pattern variation among hybrids and only 26 common DEGs across all hybrid comparisons were identified, suggesting each hybrid has a unique response to crowding stress. Over-represented biological functions of DEGs also differed among hybrids. Strong correlation was observed between: 1) modules with up-regulation in high-yielding hybrids and yield traits, and 2) modules with up-regulation in low-yielding hybrids and plant/ear traits. Modules linked with yield traits may be important crowding stress response mechanisms influencing crop yield. Functional analysis of the modules and common DEGs identified candidate crowding stress tolerant processes in photosynthesis, glycolysis, cell wall, carbohydrate/nitrogen metabolic process, chromatin, and transcription regulation. Moreover, these biological functions were greatly inter-connected, indicating the importance of improving the mechanisms as a network.