Multi-year evaluation and release of improved soybean lines for resistance to Phomopsis seed decay

Shuxian Li; James R. Smith; Anne M. Gillen; Quentin D. Read

doi:10.1371/journal.pone.0354166

Abstract

Soybean [Glycine max (L.) Merr.] is one of the most economically important oilseed crops grown in the world. Soybean diseases not only affect yield but can also affect seed quality resulting in significant economic losses. Phomopsis seed decay (PSD) causes poor seed quality and is one of the most damaging soybean seed diseases. Diaporthe longicolla (syn. Phomopsis longicolla) and other pathogens in the Diaporthe/Phomopsis complex are the cause of PSD. Developing and releasing PSD-resistant germplasm lines is an important step toward the development of resistant cultivars that can protect soybean from PSD seed damage. The objective of this study was to identify improved soybean lines with PSD resistance for the mid-southern U.S. after inoculation with D. longicolla in a 5-year delayed-harvest field trial. In this study, seed assays were conducted to evaluate a total of 266 soybean entries in field experiments with inoculation of D. longicolla from 2019 to 2023. Results from five years of testing showed that maturity group (MG) late III 65-414-132-1 (DS65-1) had significantly less infection (38.6%) than susceptible late III LG03-4561-14 (86.2%). Early MG IV lines 14119-211-10 and 10031-243-12 (released as DS31-243) had statistically lower levels of PSD (29.9% and 46.6%, respectively) than susceptible early IV ‘LD00-3309’ (63.9%). These improved breeding lines were derived from PI 587982A. Moreover, early MG V 10049-142-31 (released as DS49-142) had less infection (7.9%) than early V ‘AG5335’ (25.4%), and late MG IV 12060-260-2 (released as DS1260-2) had less infection (19.6%) than susceptible late IV ‘P46T59R’ (55.3%). DS1260–2 was derived from PI 587982A, and DS49-142 was derived from PI 603756. Resistant lines were transferred to breeders for potential use in developing soybean cultivars with resistance to PSD. This research provides useful information for the development of durable resistance to PSD, which will aid in the management of soybean seed decay.

Citation: Li S, Smith JR, Gillen AM, Read QD (2026) Multi-year evaluation and release of improved soybean lines for resistance to Phomopsis seed decay. PLoS One 21(8): e0354166. https://doi.org/10.1371/journal.pone.0354166

Editor: Ömer Faruk Coşkun, Mustafa Kemal University: Hatay Mustafa Kemal Universitesi, TÜRKIYE

Received: March 3, 2026; Accepted: July 4, 2026; Published: August 24, 2026

This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

Data Availability: The relevant raw data is available in the Ag Data Commons at DOI: 10.15482/USDA.ADC/32091706.v2.

Funding: USDA-ARS Project 6066-21220-014-000D and 6066-21220-016-00D, Crop Genetics Research Unit at Stoneville, MS. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Soybean [Glycine max (L.) Merr.] is a major source of plant-based protein and oil for animal and human nutrition, and one of the most economically important oilseed crops grown [1,2]. Worldwide consumption and demand for soybean have markedly increased [3], but high seed quality is crucial for successful soybean production and marketing. Soybean diseases are a threat to both of these, as they can affect not only yield but also seed quality resulting in significant economic losses [https://cropprotectionnetwork.org/yield-loss-calculator/soybean-diseases].

Phomopsis seed decay (PSD) is one of the most damaging soybean seed diseases and causes poor seed quality [4–7]. PSD occurs in almost every soybean growing area worldwide. It is especially prominent in the mid-southern U.S., where warm and humid conditions often occur during late seed fill and full maturity (R8) [8–10]. Rain at this critical time can potentially prevent the entry of harvest machinery into the field and thereby delay harvest. Such conditions favor disease development, causing severe seed decay that negatively impacts soybean production and profit margins [7,11,12]. PSD has caused substantial yield losses to soybean [13–15], although losses have varied across years due to differing environmental conditions. In 2018, soybean yield loss attributed to PSD in the top 29 production states of the U.S was 0.2 million metric tons (MMT) [https://cropprotectionnetwork.org/publications/soybean-disease-loss-estimates-2018], and in 2023, soybean yield losses from PSD were estimated to be about 0.03 MMT [https://cropprotectionnetwork.org/publications/soybean-disease-loss-estimates-from-the-united-states-and-ontario-canada-2023/].

The most characteristic symptoms of PSD include, but are not limited to, seed that is discolored, elongated, shriveled, and cracked. In soybean, seed severely infected with the fungal Diaporthe/Phomopsis complex can appear moldy with a chalk-white color. However, infected soybean seed may also have no visible symptoms [16]. Soybean seed with symptoms, as well as symptomless seed with infections by the pathogens of the Diaporthe/Phomopsis complex can both show poor emergence, reduced seedling vigor, damping-off, and seedling death [17]. It has also been reported that oil quality of soybean seed can be reduced, and other seed components negatively altered by infection with D. longicolla [18].

The primary causal agent of PSD was first identified as Phomopsis longicolla in 1985 [4] but was renamed Diaporthe longicolla (Hobbs) J. M. Santos (syn. Phomopsis longicolla) in 2011 [19]. Hosseini et al. (2025) used a molecular approach to identify two mating type genes (MAT1-1-1 and MAT1-2-1) in D. longicolla isolates and predicted sexual capability of D. longicolla [20]. However, information about the sexual structures (such as perithecia) of D. longicolla is lacking. Multiple studies have indicated that not only is D. longicolla a cause of PSD, but other Diaporthe species can also cause PSD, including D. caulivora (syn. D. phaseolorum var. caulivora) and D. sojae (syn. D. phaseolorum var. sojae), as well as other species of Diaporthe [7,21–25]. In 1985, Anderson reported that a single seed could be infected by either one pathogen or any combination of D. caulivora, D. sojae, and D. longicolla [26]. Most importantly, research suggests that PSD is more likely the result of a complex interaction of fungal species rather than just a single fungal entity. In studies to evaluate the pathogenicity of D. longicolla isolates collected from soybean and non-soybean hosts from different geographic regions, Li et al. (2010, 2018) reported differences among isolates in aggressiveness on soybean [27,28]. In addition, comparison of the mitochondrial genome sequences of eight D. longicolla isolates indicated that different numbers of introns and repetitive elements in specific isolates contributed to the differences in genome size [29]. Analysis of whole genome sequences and protein–protein interactions identified conserved global networks and pathogenicity subnetworks in D. longicolla, as well as an abundance of genes encoding cell-wall degrading enzymes that play important roles in pathogenicity [30,31].

Common strategies for managing PSD include crop rotation with non-hosts, tillage, fungicide application during pod-fill, and timely harvest shortly after R8 when weather permits [32,33]. Recently, the sensitivities of D. longicolla and other Diaporthe spp. to difenoconazole and fluopyram fungicides were evaluated, providing valuable information to aid in the development of Diaporthe disease management programs [34]. However, control of PSD could also be enhanced by planting PSD-resistant cultivars [35–42]. Multiple exotic soybean accessions [plant introductions (PI)] from the USDA soybean germplasm collection and breeding lines derived from these PIs were screened for more than a decade for seed infection by Diaporthe species at Stoneville, Mississippi [11,12,42,43]. The most promising of these are being utilized to develop and release new germplasm lines that have improved adaptation to the mid-southern U.S., along with reduced seed infection caused by Diaporthe species. We hypothesized that PSD-resistant gene(s) exist in our improved breeding lines, that can be utilized to develop improved cultivars with resistance to PSD for growers.

To achieve this goal, the specific objectives of this study were (i) to evaluate new improved soybean breeding lines for their reactions to Diaporthe spp. infection after inoculation in a 5-year delayed-harvest field trial; and (ii) to identify improved lines with resistance to Phomopsis seed decay. Four soybean lines, DS25−1 (PI 684675), DS31−243 (PI 700941), DS49−142 (PI 703498), and DS1260−2 (PI 705148), tested in this study have been released and are available for research purposes and breeding through the USDA soybean collection via the Germplasm Resources Information Network (GRIN, https://npgsweb.ars-grin.gov/gringlobal/search). These and other breeding lines have been transferred via material transfer agreements to public and private soybean breeders for their potential use in developing soybean cultivars with improved resistance.

Materials and methods

Plant materials

A total of 266 soybean entries were evaluated, including breeding lines, cultivars, eight resistant checks, and 12 susceptible checks (S1Table). For comparison, some previously released germplasm lines were also included (S1Table). Available information for these soybean entries, such as accession number, other names, maturity group, and pedigree of entries tested in this study are also in S1Table. As part of an ongoing effort to improve overall seed quality, breeding lines included in this study were selectively advanced based on seed germination data, frequencies of hard seed (impermeable seed coat) and wrinkled seed, as well as on the incidence of Phomopsis seed decay (PSD), in high-temperature environments with natural infection of PSD [43–46]. Impermeable seed coat can delay the uptake of water into the seed and hence delay seed pathogen development, while high temperatures can lower seed viability by directly damaging the seed. Wrinkled seed is evidence of seed damage resulting from weathering and/or heat [45].

Compared to previous studies, the current study used breeding lines derived from additional germplasm sources, as well as material derived from pyramided sources. For example, DS43–72 (11043-225-72) was derived from PIs 417050 and 587982A, 11030-541-28 was derived from PIs 424324B and 587982A, and 16027-312-12 was derived from PIs 594445 and 587982A. Each of these PIs was identified in previous studies and now tied into this study through breeding lines derived from multiple sources. Hence, our current work reports the results of the improved breeding lines derived from these (PIs 587982A, 417050, 424324B, and 594445) and other resistance sources (PI 417479, PI 423941, PI 594619, and PI 603756 [10,39,42]. Further, improved resistant breeding lines were crossed with cultivars and selected for improved seed yield, while also selecting to maintain their improved resistance to PSD. Such was the case for DS1260–2, which was created from DS34–1 × ‘LD00-3309.’ In the pedigree breeding process [47], susceptible breeding lines were dropped when identified. Selected lines received additional testing in yield trials, with some being later shared with public and private soybean breeders. Breeding lines released from our program for improved grain quality include DS25–1, DS31–243, and DS1260–2 (derived from PI 587982A) and DS49–142 (derived from PI 603756) [42]. In addition, the current study covers more years than previous studies. Hence the recommendations for which lines are most useful to breeders are stronger in the current study because they are based on more data.

Field experiments

Field experiments for evaluation of soybean lines were conducted at Stoneville, Mississippi (MS) on a Sharkey clay soil (very-fine, smectitic, thermictic Chromic Epiaquert) from 2019 to 2023. Planting and harvest dates of the field trials are listed for each year from 2019 to 2023 in Table 1. An Almaco plot planter (model AJ4RP2) with research cones was used for planting. The seeding rate was 25 seed m^-1 of row. Plots (experimental units) consisted of single rows 3 m long with a row spacing of 0.66 m. A total of 798 plots were tested over the five-year field trial (2019–2023). Furrow irrigation was used to apply water as needed throughout the growing season to alleviate moisture-deficit stress. At the R3 to R5 growth stages [10], inoculum of D. longicolla, as described below, was applied to all plots. To promote pathogen infection, irrigation with an overhead watering system commenced after plots were inoculated [42].

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Table 1. Planting, inoculation, and delayed harvest dates of the field trials from 2019 to 2023.

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A randomized complete block design (RCBD) with three replications was utilized each year. In 2019 and 2020 the nursery was set up as one trial combining both early (MG III) and late (MGs IV and V) maturing lines. From 2021 through 2023, the nursery was divided into an early maturing trial (Early Test; MG III and early MG IV) and a later maturing trial (Late Test; late MG IV and early MG V). Each plot was hand-harvested two weeks after the R8 (full maturity) date of that plot [10], which was referred to as a “delayed harvest” in this study. Harvested plant materials were placed in an air-conditioned humidity-controlled building. They were stored and allowed to uniformly dry, preparatory to being threshed in a bundle thresher (Almaco Low Profile Plot Thresher). Once threshed, seed was stored at 21°C and 60% relative humidity. They were assayed for Phomopsis seed decay, caused by species in the Diaporthe/Phomopsis complex, as described below.

Weather data of total precipitation, number of rainy days, average maximum temperatures, and maximum relative humidity during the growing seasons were obtained from the Stoneville, MS, weather station (https://deltaweather.extension.msstate.edu/stoneville-aws).

Inoculum preparation and application

The isolate MSPL 10−6 of D. longicolla, one of the most aggressive isolates in our tests [28], was originally collected from field-grown soybean plants at Stoneville, MS and was used for inoculation in the experiments. Inoculum was prepared as previously reported [11,43,44] but is briefly described as follows: isolate was grown at 24°C on potato dextrose agar (Difco Laboratories, Detroit, MI) that was adjusted to pH 4.8 with 25% lactic acid (APDA) after autoclaving. Sporulation of the culture was induced under a fluorescent light output of 300 µmol m^-2 s^-1 with a 12-h photoperiod for 30–45 days. Sporulating cultures in each Petri dish were then flooded with approximately 25 ml sterile deionized water, then the fungal colony was gently scraped with a sterile Corning spatula (Corning Inc. Corning, NY) to dislodge conidiospores, which were then filtered with four layers of sterile cheesecloth to eliminate the agar. Concentrations of conidiospores were adjusted to approximately 1.0 × 10⁶/ml in 2019 and 1.0 × 10⁵/ml in 2020–2023, which were determined using a hemocytometer (Hausser Scientific, Blue Bell, PA). A backpack sprayer (Stihl, Model SG 20, Virginia Beach, VA) was used for field inoculations. The sprayer consisted of a hand-held boom containing a single nozzle with an adjustable orifice. In each plot, the conidiospore suspension was sprayed directly onto the soybean pods under the canopy and then evenly across the top of the canopy. Each plot was sprayed using approximately 86 ml of the conidiospore suspension.

Seed plating assays

Soybean seed samples (25 randomly chosen seeds per plot) that excluded mechanically damaged seed, such as seed with splits or cracked seed coats, were collected from each manually-harvested and threshed plot. Seed plating assays were conducted to determine the percentage of seed infection by Diaporthe spp. following a previously reported method [11,12,43,44]. Briefly, seed were surface-disinfected in 0.5% sodium hypochlorite for 3 min, rinsed in sterile distilled water three times, and then placed on APDA [11,12,43,44]. Five seeds were placed uniformly on APDA in each 100 mm × 15 mm Petri dish. Hence, five Petri dishes of five seeds per dish were used to estimate the infection severity of each plot. All seed plates were incubated for four days at 24°C. The number of seeds infected with Diaporthe spp. was recorded and the infection rate was expressed as a percentage of seed infection by Diaporthe spp. including the inoculated D. longicolla isolate and naturally occurring members of the Diaporthe/Phomopsis complex in the field. Identification of those PSD-causing pathogens at the Diaporthe genus level was accomplished using both cultural morphology and the sequence analysis of the internal transcribed spacer (ITS) regions as previously reported [44]. Briefly, 10 putative D. longicolla colonies from the seed assay plates with similar cultural morphology to the MSPL10−6 isolate, along with the type strain TWH P74 and isolate MS-SSC91 of D. aspalathi, that causes stem canker on soybean, were transferred to PDA or water agar with autoclaved soybean stem pieces or Williams 82 seeds for 45 days under incubation conditions [44]. Observations under the Olympus SZX12 dissecting microscope were conducted from 10 to 20 days after incubation to determine if any isolates formed perithecia. Perithecia have not been found in D. longicolla but have been reported to be produced by other fungal pathogens in the Diaporthe-Phomopsis complex, such as D. aspalathi and D. caulivora. Extraction of total genomic DNA from four putative D. longicolla isolates was carried out as described previously [30,31,44]. Mycelial plugs (3-mm in diameter) from the margins of 10-day old cultures on APDA were cut and placed in potato dextrose broth (Difco Laboratories, Detroit, MI). After 4 days of incubation at 24°C under 12-h light-and dark cycles, mycelia were collected on sterile cheesecloth, washed with sterile water, immediately frozen with liquid nitrogen, and lyophilized with a freeze-drier (IMC Instruments, Inc., Wisconsin, USA). Fungal mycelia were ground with a mortar and pestle and pulverized in liquid nitrogen. Genomic DNA was extracted using a Qiagen DNeasy Plant Mini Kit (Qiagen Inc., Valencia, CA) following the manufacturer’s instruction and qualified with Nanodrop (Thermo Scientific, Waltham, MA, USA) [30,31,44].

Data analysis

A generalized linear mixed model (GLMM) with binomial error distribution and logit link function was fitted to the combined data of percentage of seed infection by Diaporthe spp. from all five years, including all checks, using the package glmmTMB v1.1.11 [48] in R software v4.5.0 [49]. The response variable was the percentage of seed infection by Diaporthe spp. out of the total number of seeds in each of the five Petri dishes for each replication of each soybean entry. Entry, year (discrete), test (Early Test vs. Late Test) and their interactions were treated as fixed effects. A random intercept was fitted for each replicate nested within year. The resulting mixed-model equation for the probability of infection for entry i in test j in year k in replicate l was:

where the indexed β coefficients are the fixed effect terms for the main effects and interactions, and the u term is the random intercept.

Because there were some cases of complete separation where some entry-year combinations had zero observed pathogens for all replicates, a weakly informative normal prior distribution with mean 0 and standard deviation 5 was assigned to the fixed effects to regularize the estimates. Simulated residuals were used to test for overdispersion; the estimated dispersion φ = 1.07 was sufficiently close to the value of φ = 1 assumed by the binomial GLMM. Marginal means for each entry were estimated, first individually within the Early Test and the Late Test for each year and then averaged over all Early Tests and Late Tests across all years, inverted from the logit scale. Percentages of seed infection by Diaporthe spp. presented in the results represent modeled marginal estimates of infection probability. The z-statistic was used for pairwise mean comparisons and to construct 95% asymptotic confidence intervals around the mean estimates. The Sidak adjustment was used to adjust the 95% confidence intervals for multiple comparisons. Pairwise comparisons for all entries within and across years were taken as odds ratios. Multiple comparison letters were also generated to summarize the significant difference between means, both within each year and averaged across years. Joint chi-squared deviance tests were conducted to assess whether variances due to entry were significant within each test in each year. All post-hoc analyses were done using the R package emmeans v1.11.1 [50].

Results

From the seed plating assay, 10 putative D. longicolla colonies that had typical morphology similar to isolate MSPL 10−6 and the type strain TWH P74 (ATCC 60325) were reisolated. None of them produced perithecia from 10 to 45-day old cultures on either PDA plates or water agar with soybean stem pieces as observed under the Olympus SZX12 dissecting microscope. However, D. aspalathi isolate MS-SSC91, the causal agent of stem canker, formed perithecia in the side-by-side comparison with isolates of D. longicolla. Results of analyses of DNA sequences of four putative D. longicolla isolates were identical with our previous D. longicolla isolates, deposited to Genbank, at the ITS region (Accession MF134860) and in the TEF-1α gene (Accession MF189565) [44]. Other unidentified Diaporthe spp, with similar morphology were also found. Therefore, even though D. longicolla was the prevalent species used for inoculation, the data presented in this paper are the percentage of seed infection by Diaporthe spp.

The daily maximum air temperatures for the growing season of April through October in 2019 averaged 30.0˚C and ranged from 23.1˚C to 35.7˚C, with similar temperatures observed across the remaining years of the study period. The average daily maximum air temperatures for August 2019–2023 were between 32.1˚C and 35.2 ˚C, much higher than the 24˚C, optimal temperature for PSD. In 2019, totals for precipitation in June, July, and August were 172, 121, and 92 mm, respectively, followed by 161, 67, and 173 mm in 2020; 129, 200, and 142 mm in 2021; 108, 113, and 77 mm in 2022; and 85, 59, and 74 mm in 2023 (S1 Fig.). Maximum relative humidities (RH) in each month across all years were generally in the mid-to-upper 90s%, ranging from 92 to 99%. However, RHs for October of 2022 and 2023 were lower at 88% and 90%, respectively.

Joint deviance tests of seed infection by Diaporthe spp. for the tests in each year (2019–2023) indicated that there were significant differences (P < 0.05) among entries. The mean percentage of seed infection in each year is shown in Tables 2–6.

In 2019, the range of seed infections was from 5.4 to 94.4% among entries in the Early Test for soybean MGs III through early IV. The impermeable seed coat-resistant check PI 594619 [51] had the lowest level (5.4%) of seed infection by Diaporthe spp., whereas susceptible check ‘LD06-7620’ had the greatest percentage of seed infection (94.4%). Three other susceptible checks, ‘Progeny 4211’, ‘Pella 86’, and ‘CZ3841LL’, had seed infections of 75.8, 81.2, 86.5%, respectively. Among soybean entries from MGs late IV through early V in the Late Test, breeding line DA1239−09 had the lowest score of seed infection (6.7%), which was similar to resistant check 10049-142-31 (8.1%), whereas the susceptible check of comparable maturity, ‘AG5335’, had 29.3% seed infection (Fig 1). The susceptible check ‘P46T59R’ had the greatest score of seed infection (60.0.%). Other susceptible checks, ‘P48A60X’ and ‘AG4632’, had seed infection scores of 55.8 and 58.6%, respectively (Table 2).

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Table 2. Mean percent seed infection by Diaporthe spp. on soybean breeding lines along with resistant and susceptible checks in replicated field tests with inoculation treatment and delayed harvest at Stoneville, Mississippi in 2019.

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Fig 1. Reaction of resistant vs. susceptible soybean entries to Phomopsis seed decay using the seed plating assay.

Resistant line 10049-142-31 (DS49-142) lacked Diaporthe spp. (left), while susceptible cultivar AG 5335 manifested the pathogen (right). Seeds were collected from a replicated field test with inoculation treatment and delayed harvest at Stoneville, Mississippi. The photo was taken 7 days after the seed plating assay.

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Results from the tests in 2020 are presented in Table 3. Among soybean lines in MGs III through early IV in the Early Test, breeding line 14119-211-10 had the lowest percent seed infection by Diaporthe spp. (6.7%). The most susceptible entry in the test was ‘Clark’ maturity isoline L94-1110, which had the greatest percentage of seed infection (65.3%), almost 10 times higher than that of the most resistant breeding line 14119-211-10. In the Late Test for soybean entries of MGs late IV through early V, seed infection by Diaporthe spp. ranged from 11.9% (entry 10049-142-31) to 55.9% (entry D13062004F). Resistant check DS25−1 had 22.5% seed infection, which was not different from that of 10049-142-31 (OR = 2.17, 95% CI [0.39, 12.50], P = 1.0; Table 3).

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Table 3. Mean percent seed infection by Diaporthe spp. on soybean breeding lines along with resistant and susceptible checks in replicated field tests with inoculation treatment and delayed harvest at Stoneville, Mississippi in 2020.

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In 2021, the overall seed infection by Diaporthe spp. in the Early Test for soybean entries of MGs III through early IV was more severe than in other years (Table 4). Entry LG03-4561-14 [46] had the greatest seed infection of 98.7%, whereas the lowest entry (15097-225-21) had seed infection of 18.6%. Resistant check SS93−6181 (derived from PI 417479) had 77.5% seed infection in 2021, 64.4% in 2019 (Table 2), 20.0% in 2020 (Table 3), 34.6% in 2022 (Table 5), and 42.8% in 2023 (Table 6), demonstrating how each year’s environment can differ and result in differing severities of the same “resistant” line across environments. Results from the Late Test for soybean entries of MGs late IV through early V indicated that most entries had relatively high levels of seed infection, which obscured meaningful differences among the lines. The range of seed infections was from 34.5% (entry 10049-142-31) to 89.1% (entry AG4632). The resistant check DS25−1 had a seed infection of 66.7%, which was significantly (OR = 3.80, 95% CI [1.04, 13.93], P = 0.03) greater than the infection in 10049-142-31, but not significantly (OR = 0.24, 95% CI [0.04, 1.59], P = 0.75) different from that of AG4632 (Table 4).

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Table 4. Mean percent seed infection by Diaporthe spp. on soybean breeding lines along with resistant and susceptible checks in replicated field tests with inoculation treatment and delayed harvest at Stoneville, Mississippi in 2021.

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Table 5. Mean percent seed infection by Diaporthe spp. on soybean breeding lines along with resistant and susceptible checks in replicated field tests with inoculation treatment and delayed harvest at Stoneville, Mississippi in 2022.

https://doi.org/10.1371/journal.pone.0354166.t005

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Table 6. Mean percent seed infection by Diaporthe spp. on soybean breeding lines along with resistant and susceptible checks in replicated field tests with inoculation treatment and delayed harvest at Stoneville, Mississippi in 2023.

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In 2022, four entries had less than 3% seed infection by Diaporthe spp. in the Early Test, 16031-131-2 (1.5%), DA1570-25F (1.5%), DA1570-29F (2.8%) and DA1571-18F (2.8%), whereas the susceptible check of comparable maturity, Progeny 4211, had a seed infection of 30.6% (Table 5). Another susceptible check, LG03-4561-14, had the greatest seed infection of 83.0%. Results of the Late Test for soybean entries of MGs late IV through early V showed lower seed infection compared to tests in other years with a range from 0.3 (D49-2491) to 25.2% (P46T59R), indicating an overall environment of less severity for the late test in 2022. As an example of the effect of environment, the seed infection of susceptible check P46T59R was 25.2% in 2022, but was 60.0% in 2019, 34.2% in 2020, 82.8% in 2021, and 69.3% in 2023 (Tables 2–6). September 2022 had only 1 mm of precipitation and October 2022 had the lowest percent RH (88%) of any single month of the 5-year period (S1 Fig.), possibly contributing to lower levels of seed infection during those periods.

In 2023, the percentage of seed infection by Diaporthe spp. ranged from 8.1 to 68.1% in the Early Test, and from 2.7 to 81.2% in the Late Test (Table 6). The three entries with the lowest seed infections in the Early Test were 1623-516-141 (8.05%), 16023-617-32 (8.1%), and 1623-516-151 (12.0%), which all have the hard seed trait (impermeable seed coat) [51] derived from PI 594619 (Table 6). Entries 10049-142-31, released as DS49−142 (resistant check), 16027-312-12, and 16022-113-23 had the lowest seed infection scores of 2.7, 2.7, and 4.1%, respectively, in the Late Test (Table 6). Breeding line 16027-312-12 was derived from two sources of resistance, PI 587982A and PI 594445 (S1 Table), which indicates the potential for stacking multiple sources of resistance in a single line.

In view of the results of the multi-year average of mean percent seed infection by Diaporthe spp. on soybean breeding lines from MGs III through early IV in the Early Test, breeding lines DA1570-25F, DA1571-10F, and 16016-114-21 had less than 5% seed infection across two years (2022 and 2023) (Table 7). In the Late Test, the resistant check 10049-142-31(released as DS49–142, Fig 1), tested in all 5 years, had an overall mean of 7.9%, which was significantly (OR = 0.25, 95% CI [0.08, 0.83], P = 0.002) lower than susceptible check AG5335 (25.4%, Fig 1) in five years of testing. Also tested over all five years, entry 12060-260-2 (released as DS1260–2, Fig 2) [42] had significantly (OR = 0.20, 95% CI [0.09, 0.45], P < 1 × 10^-13) lower seed infection by Diaporthe spp. pathogens (19.6%) than susceptible check P46T59R (55.3%), which was also tested for five years (Table 7, Fig 2). The modeled probability of soybean percent seed infection by Diaporthe spp. in the tests of soybean entries from MGs III through early IV, and from late MGs IV through early V are presented in S2 Fig and S3 Fig, respectively.

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Table 7. Overall mean percent seed infection by Diaporthe spp. on soybean breeding lines along with resistant and susceptible checks in replicated field tests with inoculation treatment and delayed harvest at Stoneville, Mississippi across years in 2019, 2020, 2021, 2022, and 2023.

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Fig 2. Healthy vs. Phomopsis decayed soybean seeds.

Resistant line 12060-260-2 (DS1260−2) (left), and susceptible cultivar P46T59R (right). Seeds were collected from a replicated field test with inoculation treatment and delayed harvest at Stoneville, Mississippi. The photo was taken 7 days after the seed plating assay.

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Discussion

Diseases caused by pathogens are the major cause of yield loss and poor seed quality, greatly impairing the stability of crop production in the world. Breeding for plant disease resistance is crucial for sustainable agriculture. Utilizing and releasing disease-resistant lines and cultivars can provide long-term plant protection against pathogens and is a cost-effective and environmentally friendly way to manage crop diseases.

Seed quality is important for successful crop production, which can be affected by plant pathogens, environmental conditions, and their interactions [52,53]. Soybean seed quality has become a growing concern, as poor grain quality can be price-discounted when sold and can also limit the use of harvested seed for replanting [54,55]. Poor soybean quality is often associated with Phomopsis seed decay (PSD). As our specific goal has been to develop and release soybean lines with improved levels of PSD-resistance, we developed protocols to evaluate breeding lines and identify promising lines under field conditions using a multiyear approach.

When field trials are used to identify potentially resistant breeding lines, there are multiple issues to manage. For example, without artificial inoculation, susceptible plants may not always have a similar opportunity to be infected by the pathogen. This may be due to environments that are unfavorable to fungal growth and disease development in certain years. In addition, the pathogen may not be distributed evenly in the field, permitting disease or pathogen escapes and resulting in false identification of host resistance [12,43]. These potential problems need to be managed and identified when they occur. Based on our past years of experience in screening soybean for resistance to PSD in the field at Stoneville, MS [11,12,43,44], we determined that artificial inoculation with the pathogen helps to ensure a more uniform distribution of the pathogen and to reduce the possibility of disease “escapes” [56,57]. Hence, in this study soybean lines were evaluated under inoculated treatments, which increased confidence in the significant differences observed for percentages of seed infection by Diaporthe spp. Because different fungal pathogens with similar cultural morphology in the Diaporthe/Phomopsis complex have recently been reported to cause PSD [24], this study reports the percentage of seed infection by Diaporthe spp., as opposed to reporting infection at the species level.

To better manage environmental biases, we inoculated each plot in our field study and harvested each plot two weeks after it matured (R8) [10]. Our previous study [44] indicated that mean seed infection by D. longicolla was more severe after delayed harvest than when plots were harvested promptly after maturity. Using delayed harvesting helps ensure more disease severity and reduces the likelihood of “disease escapes,” because moisture close to the seed (due to high humidity or precipitation) after maturity and dry down is a key factor affecting the extent of damage by PSD [58]. In addition, early (April) planting in the midsouth also encourages more seed damage at senescence and maturity because April-planted early-maturing soybean generally mature in August through early September, when the environment is usually hot and humid and can thus be more conducive to severe PSD [59]. However, even when utilizing inoculated plots, overhead irrigation, delayed harvest, and early plantings, the effect of each year’s environment can still promote too little or too much severity such that the statistical separation of “resistant” and “susceptible” genotypes may still be difficult or questionable. Therefore, experimental testing over multiple years (four or five are preferable) is required to separate with confidence resistant and susceptible breeding lines. Many breeding lines can appear favorable after one or two years of testing, but lines that perform well over four or five years of testing may be considered for release and recommended for use. Early IV breeding line 14119-211-10 had a significantly lower percentage of seed infection score (29.9%) over four years of testing than susceptible early IV cultivars Progeny 4211 (55.7% over five years), Clark (56.7% over four years), and LD00−3309 (63.9% over four years of testing) (Table 7). Likewise, late III 65-414-132-1 (DS65−1) [39] and early IV 10031-243-12 (released as DS31−243) [43] had significantly less infection (38.6% and 46.6%, respectively) over five years and four years, respectively, than susceptible late III LG03-4561-14 (86.2% in five years of testing) (Table 7). These three improved breeding lines, all derived from PI 587982A, are recommended for use in developing early-maturing PSD-resistant cultivars.

Later-maturing breeding lines may avoid PSD infection because they senesce in a cooler environment, where Diaporthe spp. are generally less active. Even so, our protocol was still able to detect significant differences among late IV and early V soybean lines over multiple years. Over five years of testing, early V 10049-142-31 (released as DS49–142) [42] had a lower percentage of infection (7.9%) than early V cultivar AG5335 (25.4%) (Table 7). Likewise, late IV 12060-260-2 (released as DS1260–2, Fig 2) [42] had a lower percentage of seed infection (19.6%) than susceptible late IVs P48A60X (40.8%) and P46T59R (55.3%) (Table 7). We therefore recommend, based on five years of testing, DS1260–2, derived from PI 587982A, and DS49–142, derived from PI 603756, for use in developing group IV and V soybeans with resistance to PSD.

As shown from limited testing (2022 and 2023) in this work, the hard seed trait (impermeable seed coat) may have potential for preserving seed quality under adverse weather conditions in MG IV soybean in the mid-southern U.S. Potts et al. [60] compared MG V cultivar Dare with hard seeded D67-5677-1 and suggested the possibility of using the hard seed trait for preserving seed quality for soybean in the south. Hartwig and Potts [61] went on to demonstrate that the hard seed trait derived from wild soybean (Glycine soja Sieb. and Zucc.) could protect soybean seed viability in soybean lines derived from MG V cultivar Forrest. They found that the hard seed line D81-9776 had 96% viable seed when harvested at maturity and 86% viable seed when harvested four to six weeks after maturity, compared to Forrest, which had 96% and 5% viable seed, respectively. Kebede et al. [51] later identified a single gene in G. max PI 594619 that codes for the hard seed trait. The current work tested five improved MG IV hard seeded breeding lines derived from PI 594619. 16023-617-32 (Early Test) and 16023-616-42 (Late Test) were tested across 2022 and 2023 and had PSD infections of 12.8% and 8.5%, respectively, whereas 1623-516-141, 1623-516-151, and 1623-516-143 (all Early Test) were tested only in 2023 and had infections of 8.1%, 12.0%, and 13.4%, respectively. The hard seed trait could be effective in maintaining seed quality under environmental weathering with PSD, but the main impractical issue for using the hard seed trait would be in producing seed beans that would promptly germinate the next year in grower fields. Either mechanical scarification or some sort of seed treatment might likely be needed for prompt and uniform germination after sewing. Under natural conditions in the soil, the hard seed trait breaks down gradually and unevenly, producing gradual and uneven germination that could result in uneven maturation of the crop. Uneven maturation could cause delays in harvest unless a desiccant were applied for uniform crop dry down, which is actually a common current practice in the mid-southern U.S.

To assist in the development of PSD-resistant cultivars, and to aid in studies related to seed quality, improved germplasms late MG IV DS25−1 (PI 684675), early MG IV DS31−243 (PI 700941,10031-243-12), early MG V DS49−142 (PI 703498, 10049-142-31), and late MG IV DS1260−2 (PI 705148, 12060-260-2) were publicly released by USDA and are available for research and breeding purposes from the Germplasm Resources Information Network (GRIN, https://npgsweb.ars-grin.gov/gringlobal/search). Prior to release, these lines were also transferred by Material Transfer Agreement (MTA) to public and private breeding and research entities, both in the USA and internationally. In addition, DS65−1 (65-414-132-1), DS43−72 (11043-225-72), DS34−1 (4034-312-41), 11069-323-11, 11069-333-11, 11069-122-11, 11043-224-91, and 10061-236-11 were transferred by MTA to public and private breeding and research entities for potential use in developing improved cultivars and for ongoing research on seed quality issues. Further, records from the USDA soybean germplasm collection (personal communication from Todd Bedford) indicate that released germplasm lines DS25−1 (PI 684675), DS31−243 (PI 700941), DS49−142 (PI 703498), and DS1260−2 (PI 705148) have all been requested by and transferred to public researchers/breeders. Additionally, DS25−1 and DS1260−2 were requested by and transferred to multiple private researchers/breeders. The transfer of improved material with resistance to PSD to commercial and public breeders with access to the appropriate intellectual property rights for marketing the genetically modified organism (GMO) traits that producers desire represents an important step in the process of developing soybean cultivars for producers with improved resistance to PSD.

In conclusion, developing, releasing and utilizing PSD-resistant cultivars is an economical and environmentally friendly strategy to protect soybean from disease-induced seed damage, especially when using the popular early soybean production system (ESPS) [62] in mid-southern states of the U.S. Because Phomopsis seed decay is one of the most economically important soybean seed diseases in the southern states of the U.S, utilizing effective methods to identify sources of resistance to the fungal pathogens in the Diaporthe/Phomopsis complex that causes PSD is essential for the development of durable resistance to PSD and to aid in the management of soybean seed decay during soybean production in the mid-southern U.S.

Supporting information

S1 Table. A list of soybean breeding lines evaluated in this study.

Entry: Name of seed samples assayed each year; MG: Maturity group; Early: tested soybean entries from maturity group (MG) III through early MG IV; Late: tested soybean entries from late MG IV through early MG V. Check: S is susceptible check; R is resistant check.

https://doi.org/10.1371/journal.pone.0354166.s001

(PDF)

S1 Fig. Average daily maximum temperatures, average daily maximum relative humidity, total precipitation and number of rainy days during the soybean growing seasons for the months of April through October from 2019 to 2023 at Stoneville, Mississippi.

https://doi.org/10.1371/journal.pone.0354166.s002

(DOCX)

S2 Fig. The modeled probability of soybean percentage of seed infection by Diaporthe spp. in the tests of soybean entries from maturity group (MG) III through early MG IV.

Solid error bars represent 95% confidence intervals of each mean, and gray shaded error bars represent 95% comparison intervals: two entry means whose comparison intervals do not overlap are significantly different at the adjusted P < 0.05.

https://doi.org/10.1371/journal.pone.0354166.s003

(PNG)

S3 Fig. The modeled probability of soybean percentage of seed infection by Diaporthe spp. in the tests of soybean entries from late maturity group (MG) IV through early MG V.

Solid error bars represent 95% confidence intervals of each mean, and gray shaded error bars represent 95% comparison intervals: two entry means whose comparison intervals do not overlap are significantly different at the adjusted P < 0.05.

https://doi.org/10.1371/journal.pone.0354166.s004

(PNG)

Acknowledgments

We are grateful to Lilli St. Amant, Eugenia Crowley, Hans Hinrichsen, Philip Handly, Matt Kersh, Will Marlow and numerous temporary employees for their assistance with this research. Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture. The findings and conclusions in this publication are those of the authors and should not be construed to represent any official USDA or U.S. Government determination or policy. USDA is an equal opportunity provider and employer.

References

1. Hrustić M, Miladinović J. Importance, origin and expansion of soybean. In: Miladinović J, Hrustić M, Vidić M, editors. Soybean. Novi Sad: Institute of Field and Vegetable Crops. 2011. p. 11–44.
2. Wilcox JR. World distribution and trade of soybean. In: Boerma HR, Specht JE, editors. Soybeans: improvement, production, and uses. Madison: American Society of Agronomy, Crop Science Society of America, Soil Science Society of America. 2004. p. 1–13.
3. Ray DK, Mueller ND, West PC, Foley JA. Yield trends are insufficient to double global crop production by 2050. PLoS One. 2013;8(6):e66428. pmid:23840465
- View Article
- PubMed/NCBI
- Google Scholar
4. Hobbs TW, Schmitthenner AF, Kuter GA. A new Phomopsis species from soybean. Mycologia. 1985;77(4):535.
- View Article
- Google Scholar
5. Li S. Phomopsis seed decay of soybean. Soybean - Molecular aspects of breeding. InTech. 2011.
- View Article
- Google Scholar
6. Li S, Chen P, Hartman GL. Phomopsis seed decay. In: Hartman GL, Rupe JC, Sikora EJ, Domier LL, Davis JA, Steffey KL, editors. Compendium of soybean diseases and pests. Fifth ed. Minnesota, USA: APS Press. 2015. p. 47–8.
7. Sinclair JB. Phomopsis seed decay of soybeans- A prototype for studying seed disease. Plant Dis. 1993;77(4):329.
- View Article
- Google Scholar
8. Balducchi AJ. Environmental factors influencing infection of soybean seeds by Phomopsis and Diaporthe species during seed maturation. Plant Dis. 1987;71(3):209.
- View Article
- Google Scholar
9. TeKrony DM. Relationship between weather and soybean seed infection by Phomopsis sp. Phytopathology. 1983;73(6):914.
- View Article
- Google Scholar
10. Fehr WR, Caviness CE. Stages of soybean development. 80. Ames, IA, USA: Iowa State Univ. 1977.
11. Li S, Smith JR, Nelson RL. Resistance to Phomopsis seed decay identified in maturity group V soybean plant introductions. Crop Sci. 2011;51(6):2681–8.
- View Article
- Google Scholar
12. Li S, Rupe J, Chen P, Shannon G, Wrather A, Boykin D. Evaluation of diverse soybean germplasm for resistance to Phomopsis seed decay. Plant Dis. 2015;99(11):1517–25. pmid:30695950
- View Article
- PubMed/NCBI
- Google Scholar
13. Baird RE, Abney TS, Mullinix BG. Fungi associated with pods and seeds during the R6 and R8 stages of four soybean cultivars in southwestern Indiana. Phytoprotection. 2005;82(1):1–11.
- View Article
- Google Scholar
14. Wrather JA, Sleper DA, Stevens WE, Shannon JG, Wilson RF. Planting date and cultivar effects on soybean yield, seed quality, and Phomopsis sp. seed infection. Plant Dis. 2003;87(5):529–32. pmid:30812953
- View Article
- PubMed/NCBI
- Google Scholar
15. Wrather JA, Koenning SR. Effects of diseases on soybean yields in the United States 1996 to 2007. Plant Health Prog. 2009.
- View Article
- Google Scholar
16. Kulik MM, Sinclair JB. Phomopsis seed decay. In: Hartman GL, Sinclair JB, Rupe JC, editors. Compendium of soybean diseases. Minnesota, USA: APS Press. 1999. p. 31–2.
17. Gleason ML. Influence of soil water potential on performance of soybean seeds infected by Phomopsis sp. Phytopathology. 1985;75(11):1236.
- View Article
- Google Scholar
18. Hepperly PR. Quality losses in Phomopsis-infected soybean seeds. Phytopathology. 1978;68(12):1684.
- View Article
- Google Scholar
19. Santos JM, Vrandečić K, Cosić J, Duvnjak T, Phillips AJL. Resolving the Diaporthe species occurring on soybean in Croatia. Persoonia. 2011;27:9–19. pmid:22403474
- View Article
- PubMed/NCBI
- Google Scholar
20. Hosseini B, Käfer LS, Link TI. Mating-type analysis in Diaporthe isolates from soybean in Central Europe. J Fungi. 2025;11(4):251.
- View Article
- Google Scholar
21. Hosseini B, El-Hasan A, Link T, Voegele RT. Analysis of the species spectrum of the Diaporthe/Phomopsis complex in European soybean seeds. Mycol Prog. 2000;19:455–69. https://doi.org/10.1007/s11557-020-01570-y
- View Article
- Google Scholar
22. Floyd CM, Malvick DK. Diaporthe species associated with symptomatic and asymptomatic infection of soybean stems in Minnesota: identity, virulence, and growth characteristics. Can J Plant Pathol. 2022;44(6):858–73.
- View Article
- Google Scholar
23. Stovold G, Francis A. Incidence of Phomopsis phaseoli (Desm.) Sacc. in crops and seed of soybean in New South Wales. Aust J Exp Agric. 1987;27(2):317–21.
- View Article
- Google Scholar
24. Petrović K, Skaltsas D, Castlebury LA, Kontz B, Allen TW, Chilvers MI, et al. Diaporthe seed decay of soybean [Glycine max (L.) Merr.] is endemic in the United States, but new fungi are involved. Plant Dis. 2021;105(6):1621–9. pmid:33231523
- View Article
- PubMed/NCBI
- Google Scholar
25. Xue AG, Morrison MJ, Cober E, Anderson TR, Rioux S, Ablett GR, et al. Frequency of isolation of species of Diaporthe and Phomopsis from soybean plants in Ontario and benefits of seed treatments. Can J Plant Pathol. 2007;29(4):354–64.
- View Article
- Google Scholar
26. Anderson TR. Seed molds of soybean in Ontario and the influence of production area on the incidence of Diaporthe phaseolorum var.caulivora and Phomopsis sp. Can J Plant Pathol. 1985;7(1):74–8.
- View Article
- Google Scholar
27. Li S, Hartman GL, Boykin DL. Aggressiveness of Phomopsis longicolla and Other Phomopsis spp. on Soybean. Plant Dis. 2010;94(8):1035–40. pmid:30743477
- View Article
- PubMed/NCBI
- Google Scholar
28. Li S. Development of a seedling inoculation technique for rapid evaluation of soybean for resistance to Phomopsis longicolla under controlled conditions. Plant Methods. 2018;14:81. pmid:30214468
- View Article
- PubMed/NCBI
- Google Scholar
29. Li S, Hu X, Song Q. Comparative analysis of the mitochondrial genome sequences of Diaporthe longicolla (syn. Phomopsis longicolla) isolates causing Phomopsis seed decay in soybean. J Fungi (Basel). 2024;10(8):570. pmid:39194896
- View Article
- PubMed/NCBI
- Google Scholar
30. Li S, Darwish O, Alkharouf NW, Musungu B, Matthews BF. Analysis of the genome sequence of Phomopsis longicolla: a fungal pathogen causing Phomopsis seed decay in soybean. BMC Genomics. 2017;18(1):688. pmid:28870170
- View Article
- PubMed/NCBI
- Google Scholar
31. Li S, Musungu B, Lightfoot D, Ji P. The interactomic analysis reveals pathogenic protein networks in Phomopsis longicolla underlying seed decay of soybean. Front Genet. 2018;9:104. pmid:29666630
- View Article
- PubMed/NCBI
- Google Scholar
32. Cross C, Wrather A, Fothergill K, Shannon G, Li S, Shumway C, et al. Effect of lactofen, azoxystrobin, and genotypes on charcoal rot, Phomopsis seed decay, and pod and stem blight in soybean. Plant Dis. 2012;96(8):1154–8. pmid:30727092
- View Article
- PubMed/NCBI
- Google Scholar
33. Wrather JA, Shannon JG, Stevens WE, Sleper DA, Arelli AP. Soybean cultivar and foliar fungicide effects on Phomopsis sp. seed infection. Plant Dis. 2004;88(7):721–3. pmid:30812482
- View Article
- PubMed/NCBI
- Google Scholar
34. Mohan K, Barnes S, Rasuleva D, Mukaila T, Allen TW, Bergstrom GC, et al. Sensitivity of soybean (Glycine max) pathogens Diaporthe aspalathi, D. caulivora, and D. longicolla to difenoconazole and fluopyram fungicides. Plant Health Prog. 2025; doi.org/10.1094/PHP-08-24-0078-RS
- View Article
- Google Scholar
35. Brown EA, Minor HC, Calvert OH. A soybean genotype resistant to Phomopsis seed decay. Crop Sci. 1987;27(5):895–8.
- View Article
- Google Scholar
36. Jackson EW, Fenn P, Chen P. Inheritance of resistance to Phomopsis seed decay in soybean PI 80837 and MO/PSD-0259 (PI 562694). Crop Sci. 2005;45:2400–4.
- View Article
- Google Scholar
37. Jackson EW, Feng C, Fenn P, Chen P. Genetic mapping of resistance to Phomopsis seed decay in the soybean breeding line MO/PSD-0259 (PI562694) and Plant Introduction 80837. J Hered. 2009;100(6):777–83. pmid:19589849
- View Article
- PubMed/NCBI
- Google Scholar
38. Li S, Chen P. Resistance to Phomopsis seed decay in soybean. ISRN Agronomy. 2013;2013:1–8.
- View Article
- Google Scholar
39. Pathan MS, Clark KM, Wrather JA, Sciumbato GL, Shannon JG, Nguyen HT, et al. Registration of soybean germplasm SS93‐6012 and SS93‐6181 resistant to Phomopsis seed decay. J Plant Regist. 2009;3(1):91–3.
- View Article
- Google Scholar
40. Zimmerman MS, Minor HC. Inheritance of Phomopsis seed decay resistance in soybean PI 417479. Crop Sci. 1993;33(1):96–100.
- View Article
- Google Scholar
41. Minor HC, Brown EA, Zimmerman MS. Developing soybean varieties with genetic resistance to Phomopsis spp. J Am Oil Chem Soc. 1995;72(12):1431–4.
- View Article
- Google Scholar
42. Smith JR, Gillen AM, Li S, Abbas HK, Sulyok M, Shier WT, et al. Registration of soybean germplasm DS1260‐2, with improved tolerance to mature seed damage and Phomopsis seed decay. J Plant Regist. 2025;19(1).
- View Article
- Google Scholar
43. Li S, Sciumbato G, Rupe J, Shannon G, Chen P, Boykin D. Evaluation of commercial soybean cultivars for reaction to Phomopsis seed decay. Plant Dis. 2017;101(12):1990–7. pmid:30677383
- View Article
- PubMed/NCBI
- Google Scholar
44. Li S, Smith JR, Zhang L. Evaluation of exotic soybean accessions and their use in developing improved soybean lines with resistance to Phomopsis seed decay. PLoS One. 2023;18(6):e0286519. pmid:37294788
- View Article
- PubMed/NCBI
- Google Scholar
45. Smith JR, Mengistu A, Nelson RL, Paris RL. Identification of soybean accessions with high germinability in high‐temperature environments. Crop Sci. 2008;48(6):2279–88.
- View Article
- Google Scholar
46. Smith JR, Gillen AM, Nelson RL, Bruns A, Mengistu A, Li S, et al. Registration of high‐yielding exotically derived soybean germplasm line LG03‐4561‐14. J Plant Regist. 2019;13(2):237–44.
- View Article
- Google Scholar
47. Briggs FN, Knowles PF. Introduction to plant Bbeeding. USA: Reinhold Publishing Corporation; 1967.
48. Brooks ME, Kristensen K, van Benthem KJ, Magnusson A, Berg CW, Nielsen A, et al. glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal. 2017;9:378–400.
- View Article
- Google Scholar
49. R Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. 2025.
50. Lenth RV. Emmeans: Estimated marginal means, aka least-squares means. 2025.
51. Kebede H, Smith JR, Ray JD. Identification of a single gene for seed coat impermeability in soybean PI 594619. Theor Appl Genet. 2014;127(9):1991–2003. pmid:25104325
- View Article
- PubMed/NCBI
- Google Scholar
52. Sabry GE. The importance of using high quality seeds in agriculture systems. Agric Res. & Technol. 2018;15(4):00100.
- View Article
- Google Scholar
53. Telem RS, Akoijam R, Jyotsna N. Importance of quality seed in crop production. BioRes Today. 2021;3:773–4.
- View Article
- Google Scholar
54. Rupe J, Luttrell RG. Effect of pests and diseases on soybean quality. In: Johnson LA, White PJ, Gallowed R, editors. Soybeans. Elsevier. 2008. p. 93–116.
- View Article
- Google Scholar
55. Sinclair JB. Discoloration of soybean seeds- an indicator of quality. Plant Dis. 1992;76(11):1087.
- View Article
- Google Scholar
56. de Farias Neto AL, Hartman GL, Pedersen WL, Li S, Bollero GA, Diers BW. Irrigation and inoculation treatments that increase the severity of soybean sudden death syndrome in the field. Crop Sci. 2006;46(6):2547–54.
- View Article
- Google Scholar
57. Hartman GL, Rupe JC, Sikora EJ, Domier LL, Davis JA, Steffey KL. Compendium of soybean diseases and pests. Minnesota, USA: American Phytopathological Society (APS) Press. 2015.
58. Rupe JC. Effects of pod moisture on soybean seed infection by Phomopsis sp. Phytopathology. 1986;76(3):273.
- View Article
- Google Scholar
59. Mayhew WL, Caviness CE. Seed quality and yield of early-planted, short-season soybean genotype. Agron J. 1994;86:16–9.
- View Article
- Google Scholar
60. Potts HC, Duangpatra J, Hairston WG, Delouche JC. Some influences of hardseededness on soybean seed quality. Crop Sci. 1978;18(2):221–4.
- View Article
- Google Scholar
61. Hartwig EE, Potts HC. Development and evaluation of impermeable seed coats for preserving soybean seed quality. Crop Sci. 1987;27(3):506–8.
- View Article
- Google Scholar
62. Heatherly L. Early soybean production system (ESPS). Soybean production in the midsouth. CRC Press. 1998.
- View Article
- Google Scholar

[ref1] 1. Hrustić M, Miladinović J. Importance, origin and expansion of soybean. In: Miladinović J, Hrustić M, Vidić M, editors. Soybean. Novi Sad: Institute of Field and Vegetable Crops. 2011. p. 11–44.

[ref2] 2. Wilcox JR. World distribution and trade of soybean. In: Boerma HR, Specht JE, editors. Soybeans: improvement, production, and uses. Madison: American Society of Agronomy, Crop Science Society of America, Soil Science Society of America. 2004. p. 1–13.

[ref3] 3. Ray DK, Mueller ND, West PC, Foley JA. Yield trends are insufficient to double global crop production by 2050. PLoS One. 2013;8(6):e66428. pmid:23840465
View Article
PubMed/NCBI
Google Scholar

[4] View Article

[5] PubMed/NCBI

[6] Google Scholar

[ref4] 4. Hobbs TW, Schmitthenner AF, Kuter GA. A new Phomopsis species from soybean. Mycologia. 1985;77(4):535.
View Article
Google Scholar

[8] View Article

[9] Google Scholar

[ref5] 5. Li S. Phomopsis seed decay of soybean. Soybean - Molecular aspects of breeding. InTech. 2011.
View Article
Google Scholar

[11] View Article

[12] Google Scholar

[ref6] 6. Li S, Chen P, Hartman GL. Phomopsis seed decay. In: Hartman GL, Rupe JC, Sikora EJ, Domier LL, Davis JA, Steffey KL, editors. Compendium of soybean diseases and pests. Fifth ed. Minnesota, USA: APS Press. 2015. p. 47–8.

[ref7] 7. Sinclair JB. Phomopsis seed decay of soybeans- A prototype for studying seed disease. Plant Dis. 1993;77(4):329.
View Article
Google Scholar

[15] View Article

[16] Google Scholar

[ref8] 8. Balducchi AJ. Environmental factors influencing infection of soybean seeds by Phomopsis and Diaporthe species during seed maturation. Plant Dis. 1987;71(3):209.
View Article
Google Scholar

[18] View Article

[19] Google Scholar

[ref9] 9. TeKrony DM. Relationship between weather and soybean seed infection by Phomopsis sp. Phytopathology. 1983;73(6):914.
View Article
Google Scholar

[21] View Article

[22] Google Scholar

[ref10] 10. Fehr WR, Caviness CE. Stages of soybean development. 80. Ames, IA, USA: Iowa State Univ. 1977.

[ref11] 11. Li S, Smith JR, Nelson RL. Resistance to Phomopsis seed decay identified in maturity group V soybean plant introductions. Crop Sci. 2011;51(6):2681–8.
View Article
Google Scholar

[25] View Article

[26] Google Scholar

[ref12] 12. Li S, Rupe J, Chen P, Shannon G, Wrather A, Boykin D. Evaluation of diverse soybean germplasm for resistance to Phomopsis seed decay. Plant Dis. 2015;99(11):1517–25. pmid:30695950
View Article
PubMed/NCBI
Google Scholar

[28] View Article

[29] PubMed/NCBI

[30] Google Scholar

[ref13] 13. Baird RE, Abney TS, Mullinix BG. Fungi associated with pods and seeds during the R6 and R8 stages of four soybean cultivars in southwestern Indiana. Phytoprotection. 2005;82(1):1–11.
View Article
Google Scholar

[32] View Article

[33] Google Scholar

[ref14] 14. Wrather JA, Sleper DA, Stevens WE, Shannon JG, Wilson RF. Planting date and cultivar effects on soybean yield, seed quality, and Phomopsis sp. seed infection. Plant Dis. 2003;87(5):529–32. pmid:30812953
View Article
PubMed/NCBI
Google Scholar

[35] View Article

[36] PubMed/NCBI

[37] Google Scholar

[ref15] 15. Wrather JA, Koenning SR. Effects of diseases on soybean yields in the United States 1996 to 2007. Plant Health Prog. 2009.
View Article
Google Scholar

[39] View Article

[40] Google Scholar

[ref16] 16. Kulik MM, Sinclair JB. Phomopsis seed decay. In: Hartman GL, Sinclair JB, Rupe JC, editors. Compendium of soybean diseases. Minnesota, USA: APS Press. 1999. p. 31–2.

[ref17] 17. Gleason ML. Influence of soil water potential on performance of soybean seeds infected by Phomopsis sp. Phytopathology. 1985;75(11):1236.
View Article
Google Scholar

[43] View Article

[44] Google Scholar

[ref18] 18. Hepperly PR. Quality losses in Phomopsis-infected soybean seeds. Phytopathology. 1978;68(12):1684.
View Article
Google Scholar

[46] View Article

[47] Google Scholar

[ref19] 19. Santos JM, Vrandečić K, Cosić J, Duvnjak T, Phillips AJL. Resolving the Diaporthe species occurring on soybean in Croatia. Persoonia. 2011;27:9–19. pmid:22403474
View Article
PubMed/NCBI
Google Scholar

[49] View Article

[50] PubMed/NCBI

[51] Google Scholar

[ref20] 20. Hosseini B, Käfer LS, Link TI. Mating-type analysis in Diaporthe isolates from soybean in Central Europe. J Fungi. 2025;11(4):251.
View Article
Google Scholar

[53] View Article

[54] Google Scholar

[ref21] 21. Hosseini B, El-Hasan A, Link T, Voegele RT. Analysis of the species spectrum of the Diaporthe/Phomopsis complex in European soybean seeds. Mycol Prog. 2000;19:455–69. https://doi.org/10.1007/s11557-020-01570-y
View Article
Google Scholar

[56] View Article

[57] Google Scholar

[ref22] 22. Floyd CM, Malvick DK. Diaporthe species associated with symptomatic and asymptomatic infection of soybean stems in Minnesota: identity, virulence, and growth characteristics. Can J Plant Pathol. 2022;44(6):858–73.
View Article
Google Scholar

[59] View Article

[60] Google Scholar

[ref23] 23. Stovold G, Francis A. Incidence of Phomopsis phaseoli (Desm.) Sacc. in crops and seed of soybean in New South Wales. Aust J Exp Agric. 1987;27(2):317–21.
View Article
Google Scholar

[62] View Article

[63] Google Scholar

[ref24] 24. Petrović K, Skaltsas D, Castlebury LA, Kontz B, Allen TW, Chilvers MI, et al. Diaporthe seed decay of soybean [Glycine max (L.) Merr.] is endemic in the United States, but new fungi are involved. Plant Dis. 2021;105(6):1621–9. pmid:33231523
View Article
PubMed/NCBI
Google Scholar

[65] View Article

[66] PubMed/NCBI

[67] Google Scholar

[ref25] 25. Xue AG, Morrison MJ, Cober E, Anderson TR, Rioux S, Ablett GR, et al. Frequency of isolation of species of Diaporthe and Phomopsis from soybean plants in Ontario and benefits of seed treatments. Can J Plant Pathol. 2007;29(4):354–64.
View Article
Google Scholar

[69] View Article

[70] Google Scholar

[ref26] 26. Anderson TR. Seed molds of soybean in Ontario and the influence of production area on the incidence of Diaporthe phaseolorum var.caulivora and Phomopsis sp. Can J Plant Pathol. 1985;7(1):74–8.
View Article
Google Scholar

[72] View Article

[73] Google Scholar

[ref27] 27. Li S, Hartman GL, Boykin DL. Aggressiveness of Phomopsis longicolla and Other Phomopsis spp. on Soybean. Plant Dis. 2010;94(8):1035–40. pmid:30743477
View Article
PubMed/NCBI
Google Scholar

[75] View Article

[76] PubMed/NCBI

[77] Google Scholar

[ref28] 28. Li S. Development of a seedling inoculation technique for rapid evaluation of soybean for resistance to Phomopsis longicolla under controlled conditions. Plant Methods. 2018;14:81. pmid:30214468
View Article
PubMed/NCBI
Google Scholar

[79] View Article

[80] PubMed/NCBI

[81] Google Scholar

[ref29] 29. Li S, Hu X, Song Q. Comparative analysis of the mitochondrial genome sequences of Diaporthe longicolla (syn. Phomopsis longicolla) isolates causing Phomopsis seed decay in soybean. J Fungi (Basel). 2024;10(8):570. pmid:39194896
View Article
PubMed/NCBI
Google Scholar

[83] View Article

[84] PubMed/NCBI

[85] Google Scholar

[ref30] 30. Li S, Darwish O, Alkharouf NW, Musungu B, Matthews BF. Analysis of the genome sequence of Phomopsis longicolla: a fungal pathogen causing Phomopsis seed decay in soybean. BMC Genomics. 2017;18(1):688. pmid:28870170
View Article
PubMed/NCBI
Google Scholar

[87] View Article

[88] PubMed/NCBI

[89] Google Scholar

[ref31] 31. Li S, Musungu B, Lightfoot D, Ji P. The interactomic analysis reveals pathogenic protein networks in Phomopsis longicolla underlying seed decay of soybean. Front Genet. 2018;9:104. pmid:29666630
View Article
PubMed/NCBI
Google Scholar

[91] View Article

[92] PubMed/NCBI

[93] Google Scholar

[ref32] 32. Cross C, Wrather A, Fothergill K, Shannon G, Li S, Shumway C, et al. Effect of lactofen, azoxystrobin, and genotypes on charcoal rot, Phomopsis seed decay, and pod and stem blight in soybean. Plant Dis. 2012;96(8):1154–8. pmid:30727092
View Article
PubMed/NCBI
Google Scholar

[95] View Article

[96] PubMed/NCBI

[97] Google Scholar

[ref33] 33. Wrather JA, Shannon JG, Stevens WE, Sleper DA, Arelli AP. Soybean cultivar and foliar fungicide effects on Phomopsis sp. seed infection. Plant Dis. 2004;88(7):721–3. pmid:30812482
View Article
PubMed/NCBI
Google Scholar

[99] View Article

[100] PubMed/NCBI

[101] Google Scholar

[ref34] 34. Mohan K, Barnes S, Rasuleva D, Mukaila T, Allen TW, Bergstrom GC, et al. Sensitivity of soybean (Glycine max) pathogens Diaporthe aspalathi, D. caulivora, and D. longicolla to difenoconazole and fluopyram fungicides. Plant Health Prog. 2025; doi.org/10.1094/PHP-08-24-0078-RS
View Article
Google Scholar

[103] View Article

[104] Google Scholar

[ref35] 35. Brown EA, Minor HC, Calvert OH. A soybean genotype resistant to Phomopsis seed decay. Crop Sci. 1987;27(5):895–8.
View Article
Google Scholar

[106] View Article

[107] Google Scholar

[ref36] 36. Jackson EW, Fenn P, Chen P. Inheritance of resistance to Phomopsis seed decay in soybean PI 80837 and MO/PSD-0259 (PI 562694). Crop Sci. 2005;45:2400–4.
View Article
Google Scholar

[109] View Article

[110] Google Scholar

[ref37] 37. Jackson EW, Feng C, Fenn P, Chen P. Genetic mapping of resistance to Phomopsis seed decay in the soybean breeding line MO/PSD-0259 (PI562694) and Plant Introduction 80837. J Hered. 2009;100(6):777–83. pmid:19589849
View Article
PubMed/NCBI
Google Scholar

[112] View Article

[113] PubMed/NCBI

[114] Google Scholar

[ref38] 38. Li S, Chen P. Resistance to Phomopsis seed decay in soybean. ISRN Agronomy. 2013;2013:1–8.
View Article
Google Scholar

[116] View Article

[117] Google Scholar

[ref39] 39. Pathan MS, Clark KM, Wrather JA, Sciumbato GL, Shannon JG, Nguyen HT, et al. Registration of soybean germplasm SS93‐6012 and SS93‐6181 resistant to Phomopsis seed decay. J Plant Regist. 2009;3(1):91–3.
View Article
Google Scholar

[119] View Article

[120] Google Scholar

[ref40] 40. Zimmerman MS, Minor HC. Inheritance of Phomopsis seed decay resistance in soybean PI 417479. Crop Sci. 1993;33(1):96–100.
View Article
Google Scholar

[122] View Article

[123] Google Scholar

[ref41] 41. Minor HC, Brown EA, Zimmerman MS. Developing soybean varieties with genetic resistance to Phomopsis spp. J Am Oil Chem Soc. 1995;72(12):1431–4.
View Article
Google Scholar

[125] View Article

[126] Google Scholar

[ref42] 42. Smith JR, Gillen AM, Li S, Abbas HK, Sulyok M, Shier WT, et al. Registration of soybean germplasm DS1260‐2, with improved tolerance to mature seed damage and Phomopsis seed decay. J Plant Regist. 2025;19(1).
View Article
Google Scholar

[128] View Article

[129] Google Scholar

[ref43] 43. Li S, Sciumbato G, Rupe J, Shannon G, Chen P, Boykin D. Evaluation of commercial soybean cultivars for reaction to Phomopsis seed decay. Plant Dis. 2017;101(12):1990–7. pmid:30677383
View Article
PubMed/NCBI
Google Scholar

[131] View Article

[132] PubMed/NCBI

[133] Google Scholar

[ref44] 44. Li S, Smith JR, Zhang L. Evaluation of exotic soybean accessions and their use in developing improved soybean lines with resistance to Phomopsis seed decay. PLoS One. 2023;18(6):e0286519. pmid:37294788
View Article
PubMed/NCBI
Google Scholar

[135] View Article

[136] PubMed/NCBI

[137] Google Scholar

[ref45] 45. Smith JR, Mengistu A, Nelson RL, Paris RL. Identification of soybean accessions with high germinability in high‐temperature environments. Crop Sci. 2008;48(6):2279–88.
View Article
Google Scholar

[139] View Article

[140] Google Scholar

[ref46] 46. Smith JR, Gillen AM, Nelson RL, Bruns A, Mengistu A, Li S, et al. Registration of high‐yielding exotically derived soybean germplasm line LG03‐4561‐14. J Plant Regist. 2019;13(2):237–44.
View Article
Google Scholar

[142] View Article

[143] Google Scholar

[ref47] 47. Briggs FN, Knowles PF. Introduction to plant Bbeeding. USA: Reinhold Publishing Corporation; 1967.

[ref48] 48. Brooks ME, Kristensen K, van Benthem KJ, Magnusson A, Berg CW, Nielsen A, et al. glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal. 2017;9:378–400.
View Article
Google Scholar

[146] View Article

[147] Google Scholar

[ref49] 49. R Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. 2025.

[ref50] 50. Lenth RV. Emmeans: Estimated marginal means, aka least-squares means. 2025.

[ref51] 51. Kebede H, Smith JR, Ray JD. Identification of a single gene for seed coat impermeability in soybean PI 594619. Theor Appl Genet. 2014;127(9):1991–2003. pmid:25104325
View Article
PubMed/NCBI
Google Scholar

[151] View Article

[152] PubMed/NCBI

[153] Google Scholar

[ref52] 52. Sabry GE. The importance of using high quality seeds in agriculture systems. Agric Res. & Technol. 2018;15(4):00100.
View Article
Google Scholar

[155] View Article

[156] Google Scholar

[ref53] 53. Telem RS, Akoijam R, Jyotsna N. Importance of quality seed in crop production. BioRes Today. 2021;3:773–4.
View Article
Google Scholar

[158] View Article

[159] Google Scholar

[ref54] 54. Rupe J, Luttrell RG. Effect of pests and diseases on soybean quality. In: Johnson LA, White PJ, Gallowed R, editors. Soybeans. Elsevier. 2008. p. 93–116.
View Article
Google Scholar

[161] View Article

[162] Google Scholar

[ref55] 55. Sinclair JB. Discoloration of soybean seeds- an indicator of quality. Plant Dis. 1992;76(11):1087.
View Article
Google Scholar

[164] View Article

[165] Google Scholar

[ref56] 56. de Farias Neto AL, Hartman GL, Pedersen WL, Li S, Bollero GA, Diers BW. Irrigation and inoculation treatments that increase the severity of soybean sudden death syndrome in the field. Crop Sci. 2006;46(6):2547–54.
View Article
Google Scholar

[167] View Article

[168] Google Scholar

[ref57] 57. Hartman GL, Rupe JC, Sikora EJ, Domier LL, Davis JA, Steffey KL. Compendium of soybean diseases and pests. Minnesota, USA: American Phytopathological Society (APS) Press. 2015.

[ref58] 58. Rupe JC. Effects of pod moisture on soybean seed infection by Phomopsis sp. Phytopathology. 1986;76(3):273.
View Article
Google Scholar

[171] View Article

[172] Google Scholar

[ref59] 59. Mayhew WL, Caviness CE. Seed quality and yield of early-planted, short-season soybean genotype. Agron J. 1994;86:16–9.
View Article
Google Scholar

[174] View Article

[175] Google Scholar

[ref60] 60. Potts HC, Duangpatra J, Hairston WG, Delouche JC. Some influences of hardseededness on soybean seed quality. Crop Sci. 1978;18(2):221–4.
View Article
Google Scholar

[177] View Article

[178] Google Scholar

[ref61] 61. Hartwig EE, Potts HC. Development and evaluation of impermeable seed coats for preserving soybean seed quality. Crop Sci. 1987;27(3):506–8.
View Article
Google Scholar

[180] View Article

[181] Google Scholar

[ref62] 62. Heatherly L. Early soybean production system (ESPS). Soybean production in the midsouth. CRC Press. 1998.
View Article
Google Scholar

[183] View Article

[184] Google Scholar

Figures

Abstract

Introduction

Materials and methods

Plant materials

Field experiments

Inoculum preparation and application

Seed plating assays

Data analysis

Results

Discussion

Supporting information

S1 Table. A list of soybean breeding lines evaluated in this study.

S1 Fig. Average daily maximum temperatures, average daily maximum relative humidity, total precipitation and number of rainy days during the soybean growing seasons for the months of April through October from 2019 to 2023 at Stoneville, Mississippi.

S2 Fig. The modeled probability of soybean percentage of seed infection by Diaporthe spp. in the tests of soybean entries from maturity group (MG) III through early MG IV.

S3 Fig. The modeled probability of soybean percentage of seed infection by Diaporthe spp. in the tests of soybean entries from late maturity group (MG) IV through early MG V.

Acknowledgments

References