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Cucumber vein yellowing virus (CVYV) is an emerging virus on cucurbits in the Mediterranean Basin, against which few resistance sources are available, particularly in melon. The melon accession PI 164323 displays complete resistance to isolate CVYV-Esp, and accession HSD 2458 presents a tolerance, i.e., very mild symptoms despite virus accumulation in inoculated plants. The resistance is controlled by a dominant allele Cvy-11, while the tolerance is controlled by a recessive allele cvy-2, independent from Cvy-11. Before introducing the resistance or tolerance in commercial cultivars through a long breeding process, it is important to estimate their specificity and durability. Upon inoculation with eight molecularly diverse CVYV isolates, the resistance was found to be isolate-specific because many CVYV isolates induced necrosis on PI 164323, whereas the tolerance presented a broader range. A resistance-breaking isolate inducing severe mosaic on PI 164323 was obtained. This isolate differed from the parental strain by a single amino acid change in the VPg coding region. An infectious CVYV cDNA clone was obtained, and the effect of the mutation in the VPg cistron on resistance to PI 164323 was confirmed by reverse genetics. This represents the first determinant for resistance-breaking in an ipomovirus. Our results indicate that the use of the Cvy-11 allele alone will not provide durable resistance to CVYV and that, if used in the field, it should be combined with other control methods such as cultural practices and pyramiding of resistance genes to achieve long-lasting resistance against CVYV.

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Policymakers and donors often need to identify the locations where technologies are most likely to have important effects, to increase the benefits from agricultural development or extension efforts. Higher-quality information may help to target the high-benefit locations, but often actions are needed with limited information. The value of information (VOI) in this context is formalized by evaluating the results of decision making guided by a set of specific information compared with the results of acting without considering that information. We present a framework for management performance mapping that includes evaluating the VOI for decision making about geographic priorities in regional intervention strategies, in case studies of Andean and Kenyan potato seed systems. We illustrate the use of recursive partitioning, XGBoost, and Bayesian network models to characterize the relationships among seed health and yield responses and environmental and management predictors used in studies of seed degeneration. These analyses address the expected performance of an intervention based on geographic predictor variables. In the Andean example, positive selection of seed from asymptomatic plants was more effective at high altitudes in Ecuador. In the Kenyan example, there was the potential to target locations with higher technology adoption rates and with higher potato cropland connectivity, i.e., a likely more important role in regional epidemics. Targeting training to high management performance areas would often provide more benefits than would random selection of target areas. We illustrate how assessing the VOI can contribute to targeted development programs and support a culture of continuous improvement for interventions.[Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

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Banana cultivation has increased significantly over the last century to meet the growing demand for this popular fruit. Originating in Southeast Asia, bananas are now produced in >135 different countries in tropical and subtropical regions of the world. Most of this expansion of production is based on a single banana variety, Cavendish, which makes up almost all the export trade grown in large-scale monocultures and a large part of the local trade and represents >40% of all bananas grown globally. Over the last century several major diseases of the banana have emerged and widely expanded their geographic ranges. Cultivars within the Cavendish variety are highly susceptible to these diseases, including yellow Sigatoka, black leaf streak, Eumusae leaf spot, freckle, Fusarium wilt tropical race 4, banana bunchy top, and the bacterial wilts Moko, Xanthomonas wilt, and banana Blood disease. This review graphically illustrates the emergence and rapid intercontinental spread of these diseases and discusses several major disease epidemics in bananas. Evidently, the large-scale monoculture based on the single variety Cavendish has resulted in an extreme level of genetic vulnerability. The resistance to diversification in the Cavendish production chain and the lack of investment in genetics and plant breeding in the recent past means that currently limited genetic solutions are available to replace the Cavendish banana with a set of market acceptable resistant varieties from a range of different genetic backgrounds.

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Phomopsis cane and leaf spot (PCLS) is an important disease of grapevines that is mainly caused by Diaporthe ampelina. Dispersal dynamics of D. ampelina spores were investigated in two vineyards, one in northern Italy and one in Montenegro, by using spore samplers that collected α- and ß-conidia from rain water running off from PCLS-affected canes. The canes were collected from each vineyard, deployed, and overwintered in the corresponding vineyards. In each of three years (2016, 2017, and 2018), conidial dispersal was investigated during one (Montenegro) or two (Italy) growing seasons following the deployment of the PCLS-affected canes. In the first growing season following cane deployment in both vineyards, α-conidia were mostly found in runoff water after grapevine bud break, especially in April and May, and ß-conidia were regularly found in numbers comparable to those of α-conidia, most frequently from June to September. In Italy, high numbers of α- and ß-conidia were also collected during the second growing season following cane deployment. The dispersal dynamics of α-conidia over time were described by a Gompertz equation using hydrothermal time (i.e., the accumulated effect of temperature on the maturation rate of pycnidia on days in which the number of hours of wetness was ≥6 or 9 h), with R2 and concordance correlation coefficient >0.9. Rain (≥0.2 mm) was a good predictor of conidial dispersal, with an overall accuracy of 0.97. These results increase our understanding of D. ampelina spore dispersal and should be integrated into warning systems for PCLS management.

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The aggressiveness of Spanish isolates of Xylella fastidiosa, representing different sequence types, were studied in almond plants of several cultivars by means of the dynamics of the population levels and symptoms, colonization and spread, and dose-effect relationships. Pathogen dynamics in almond plants under greenhouse conditions showed doubling times of 2.1 to 2.5 days during the exponential growth phase, with a maximum population size of about 35 days postinoculation (dpi). Differences in patterns in population dynamics were observed between sap and xylem tissue after the exponential growth, as population levels in the xylem tissue remained stable while viable cells in sap decreased. Population levels were higher in two upward zones than in the downward zone with respect to the inoculation area. The first symptoms were observed between 20 and 60 dpi, and disease severity increased over time at doubling times of 30 days, with a maximum observed at 120 dpi. Strains tested showed differences in population levels in the cultivars studied and were able to spread with different intensity from contaminated plant parts to new growing shoots after pruning. Two almond isolates showed different performance in dose-effect relationships when inoculated in cultivar Avijor. Whereas IVIA 5387.2 reached high population levels but showed high median effective dose (ED50) and minimal infective dose (MID) values, IVIA 5901.2 showed low population levels and low ED50 and MID values. This study has implications for the epidemiology of X. fastidiosa in almond crops, estimating doubling times of the pathogen in planta and of symptom development and showing differences in aggressiveness between strains.

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Asian grapevine leaf rust, caused by Neophysopella meliosmae-myrianthae and N. tropicalis, is often controlled by quinone outside inhibitor (QoI) and demethylation inhibitor (DMI) fungicides in Brazil. Here, we evaluated the sensitivity of 55 Neophysopella spp. isolates to pyraclostrobin (QoI) and tebuconazole (DMI). To elucidate the resistance mechanisms, we analyzed the sequences of the cytochrome b (CYTB) and cytochrome P450 sterol 14α-demethylase (CYP51) target proteins of QoI and DMI fungicides, respectively. The CYP51 expression levels were also determined in a selection of isolates. In leaf disc assays, the mean 50% effective concentration (EC50) value for pyraclostrobin was about 0.040 µg/ml for both species. CYTB sequences were identical among all 55 isolates, which did not contain an intron immediately after codon 143. No amino acid substitution was identified at codons 129, 137, and 143. The mean EC50 value for tebuconazole was 0.62 µg/ml for N. tropicalis and 0.46 µg/ml for N. meliosmae-myrianthae, and no CYP51 sequence variation was identified among isolates of the same species. However, five N. meliosmae-myrianthae isolates grew on leaf discs treated at 10 µg/ml tebuconazole, and these were further exposed to tebuconazole selection pressure. Tebuconazole-adapted laboratory isolates of N. meliosmae-myrianthae showed an eight- to 25-fold increase in resistance after four rounds of selection that was not associated with CYP51 target alterations. In comparison with sensitive isolates, CYP51 expression was induced in the presence of tebuconazole in three out of four tebuconazole-adapted isolates tested. These results suggest a potential risk for QoI and DMI resistance development in Neophysopella spp.

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Stripe rust, caused by Puccinia striiformis f. sp. tritici, is a devastating disease of wheat (Triticum aestivum) in the United States. The fungal pathogen can rapidly evolve, producing new virulent races infecting previously resistant cultivars and genotypes adapting to different environments. The objective of this study was to investigate the long-term population dynamics of P. striiformis f. sp. tritici in the United States. Through genotyping 1,083 isolates taken from 1968 to 2009, using 14 simple sequence repeat (SSR) markers and 92 secreted protein single nucleotide polymorphism (SP-SNP) markers, 614 and 945 genotypes were detected, respectively. In general, the two types of markers produced consistent genetic relationships among the P. striiformis f. sp. tritici populations over the 40-year period. The prior-to-2000 and the 2000-to-2009 populations were significantly different, with the latter showing higher genotypic diversity and higher heterozygosity than the earlier populations. Clustering analyses using genotypes of either SSR or SP-SNP markers revealed three molecular groups (MGs), MG1, MG2, and MG3. The prior-to-2000 and the 2000-to-2009 groups both had evidence of MG1 and MG2; however, MG3 was only found in the 2000-to-2009 population. Some of the isolates in the period of 2000 to 2009 formed individual clusters, suggesting exotic incursions. Other isolates of the same period were clustered with prior-to-2000 isolates, indicating that they were developed from the previously established populations. The data suggest the coexistence of newly introduced populations alongside established populations in the United States. Twenty SP-SNP markers were significantly associated to individual avirulence genes. These results are useful for developing more accurate monitoring systems and provide guidance for disease management.

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Sampling strategies that effectively assess disease intensity in the field are important to underpin management decisions. To develop a sequential sampling plan for the incidence of Cercospora leaf spot (CLS), caused by Cercospora beticola, 31 table beet fields were assessed in the state of New York. Assessments of CLS incidence were performed in six leaves arbitrarily selected in 51 sampling locations along each of three to six linear transects per field. Spatial pattern analyses were performed, and results were used to develop sequential sampling estimation and classification models. CLS incidence (p) ranged from 0.13 to 0.92 with a median of 0.31, and beta-binomial distribution, which is reflective of aggregation, best described the spatial patterns observed. Aggregation was commonly detected (>95%) by methods using the point-process approach, runs analyses, and autocorrelation up to the fourth spatial lag. For Spatial Analysis by Distance Indices, or SADIE, 45% of the datasets were classified as a random pattern. In the sequential sampling estimation and classification models, disease units are sampled until a prespecified target is achieved. For estimation, the goal was sampling CLS incidence with a preselected coefficient of variation (C). Achieving the C = 0.1 was challenging with <51 sampling units, and only observed on datasets with incidence >0.3. Reducing the level of precision, i.e., increasing C to 0.2, allowed the preselected C to be achieved with a lower number of sampling units and with an estimated incidence ([Formula: see text]) close to the true value of p. For classification, the goal was to classify the datasets above or below prespecified thresholds (pt) used for CLS management. The average sample number, or ASN, was determined by Monte Carlo simulations, and was between 20 and 45 at disease incidence values close to pt, and approximately 11 when far from pt. Correct decisions occurred in >76% of the validation datasets. Results indicated these sequential sampling plans can be used to effectively assess CLS incidence in table beet fields.

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Rice blast, caused by the filamentous ascomycete Pyricularia oryzae, is one of the most devastating diseases of rice. Four genetic clusters were previously identified, and three have a large geographic distribution. Asia is the center of diversity and the origin of most migrations to other continents, and sexual reproduction persisted only in the South China-Laos-North Thailand region, which was identified as the putative center of origin of all P. oryzae populations on rice. Despite the importance of rice blast disease, little is known about the diversity and the population structure of the pathogen in Africa (including Madagascar). The present study was intended to describe the structure of African populations of P. oryzae and identify the relationship between African and worldwide genetic clusters. A set of 2,057 strains (937 African and 1,120 Madagascan strains) were genotyped with 12 simple sequence repeat markers to assess the diversity and the population structure of P. oryzae. Four genetic clusters were identified in Africa and Madagascar. All four clusters previously identified are present in Africa. Populations from West Africa, East Africa, and Madagascar are highly differentiated. The geographic structure is consistent with limited dispersion and with some migration events between neighboring countries. The two mating types are present in Africa with a dominance of Mat1.2, but no female-fertile strain was detected, supporting the absence of sexual reproduction on this continent. This study showed an unsuspected high level of genetic diversity of P. oryzae in Africa and suggested several independent introductions.[Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

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Logistic regression models were developed from 5 years (2014 to 2018) of disease severity and weather data in an attempt to predict brown rust of sugarcane at the Everglades Research and Education Center in Belle Glade, Florida. Disease severity (percentage area of the top visible dewlap leaf covered by rust) was visually assessed in the field every 2 weeks for two varieties susceptible to brown rust. A total of 250 variables were derived from weather data for 10- to 40-day periods before each brown rust assessment day. A subset of these variables were then evaluated as potential predictors of severity of brown rust based on their individual correlation or their biological meaningfulness. Analyses of correlation and stepwise logistic regression allowed us to identify afternoon humid thermal ratio (AHTR), temperature-based duration variables, and their interaction terms as the most significant variables associated with brown rust epidemics of sugarcane in Florida. The nine best predictive models were identified based on model accuracy, sensitivity, specificity, and estimates of the prediction error. The prediction accuracy of these models ranged from 73 to 85%. Single-variable model BR2 (based on AHTR) classified 89% of the epidemic and 81% of the nonepidemic status of the disease. More than 83% of the epidemics and 81% of the nonepidemic status of sugarcane brown rust was correctly classified via multiple-variable models. These models can be used as components of a rust disease warning system to assist in the management of brown rust epidemics of sugarcane in south Florida.

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Phytophthora capsici is a soilborne oomycete plant pathogen that causes severe vegetable crop losses in New York (NY) state and worldwide. This pathogen is difficult to manage, in part due to its production of long-lasting sexual spores and its tendency to quickly evolve fungicide resistance. We single nucleotide polymorphism (SNP) genotyped 252 P. capsici isolates, predominantly from NY, in order to conduct a genome-wide association study for mating type and mefenoxam sensitivity. The population structure and extent of chromosomal copy number variation in this collection of isolates were also characterized. Population structure analyses showed isolates largely clustered by the field site where they were collected, with values of FST between pairs of fields ranging from 0.10 to 0.31. Thirty-three isolates were putative aneuploids, demonstrating evidence for having up to four linkage groups present in more than two copies, and an additional two isolates appeared to be genome-wide triploids. Mating type was mapped to a region on scaffold 4, consistent with previous findings, and mefenoxam sensitivity was associated with several SNP markers at a novel locus on scaffold 62. We identified several candidate genes for mefenoxam sensitivity, including a homolog of yeast ribosome synthesis factor Rrp5, but failed to locate near the scaffold 62 locus any subunits of RNA polymerase I, the hypothesized target site of phenylamide fungicides in oomycetes. This work expands our knowledge of the population biology of P. capsici and provides a foundation for functional validation of candidate genes associated with epidemiologically important phenotypes.

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Pseudomonas syringae pv. actinidiae is a quarantine bacterium affecting all the Portuguese main areas of kiwifruit production. We report the draft genome of six P. syringae pv. actinidiae strains isolated from symptomatic leaves of Actinidia chinensis var. deliciosa in a study that determined the genetic population structure of the endophytic and epiphytic populations in two consecutive seasons. Average nucleotide identity values were above 99% similarity with reference strains from P. syringae pv. actinidiae biovar 3. The genomic differences found between these strains confirm the genetic diversity described for P. syringae pv. actinidiae population in Portugal. Furthermore, data provide evidence that the initial clonal expansion of P. syringae pv. actinidiae in Europe was followed by a genomic diversification constituting a valuable resource for epidemiological and evolutionary studies, namely when adopting strategies for epidemics management.

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Circular leaf spot (CLS), caused by Plurivorosphaerella nawae, is a serious disease affecting persimmon (Diospyros kaki) that is characterized by necrotic lesions on leaves, defoliation, and fruit drop. Under Mediterranean conditions, P. nawae forms pseudothecia in the leaf litter in winter, and ascospores are released in spring, infecting susceptible leaves. Persimmon growers are advised to apply fungicides for CLS control during the period of inoculum availability, which was previously defined based on ascospore counts under the microscope. A model of inoculum availability of P. nawae was developed and evaluated as an alternative to ascospore counts. Leaf litter samples were collected weekly in L'Alcúdia (Spain) from 2010 to 2015. Leaves were soaked and placed in a wind tunnel, and the released ascospores of P. nawae were counted. Hierarchical Bayesian beta regression methods were used to model the dynamics of ascospore production in the leaf litter. The selected model included accumulated degree-days (ADDs) and ADDs taking into account the vapor pressure deficit (ADDvpd) as fixed effects and year as random effect. This model had a mean absolute error of 0.042 and a root mean square error of 0.062. The beta regression model was evaluated in four orchards from 2010 to 2015. Higher accuracy was obtained at the beginning and the end of the ascospore production period, which are the events of interest to schedule fungicide sprays for CLS control in Spain. This same modeling framework can be extended to other fungal plant pathogens whose inoculum dynamics are expressed as proportion data.[Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

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Trichoderma gamsii T6085 has been investigated for many years as a beneficial isolate for use in the biocontrol of Fusarium head blight (FHB) of wheat caused primarily by Fusarium graminearum. Previous work focused on application of T6085 to wheat spikes at anthesis, whereas application to soil before or at sowing has received limited attention. In the present study, the competitive ability of T6085 on plant residues against F. graminearum was investigated. Results showed a significant reduction of wheat straw colonization by the pathogen and of the development of perithecia, not only when T6085 was applied alone but also in the presence of a F. oxysporum isolate (7121), well known as a natural competitor on wheat plant residues. T6085 was able to endophytically colonize wheat roots, resulting in internal colonization of the radical cortex area, without reaching the vascular system, as confirmed by confocal microscopy. This intimate interaction with the plant resulted in a significant increase of the expression of the plant defense-related genes PAL1 and PR1. Taken together, competitive ability, endophytic behavior, and host resistance induction represent three important traits that can be of great use in the application of T6085 against FHB not only on spikes at anthesis but potentially also in soil before or at sowing.

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Botryosphaeria dothidea is a fungal pathogen causing canker, dieback, and fruit rot of apple trees worldwide. Ascospores are an important source of inoculum of Botryosphaeria canker in China. Experiments were conducted under both controlled and natural conditions to study perithecium formation in relation to environmental conditions. Perithecia of B. dothidea were detected on cankered lesions throughout the apple growing season except in July and in some years including August under natural conditions. On newly formed canker lesions, the first perithecium was detected as early as August, about 1 week after rainfall. Perithecia matured successively, lasting from early August to June of the next year, with a peak in late September or early October. Temperature and rainfall are two key environmental factors affecting perithecium formation. Under controlled conditions, perithecia were produced only on cankered shoots incubated at test temperatures of 20 and 25°C and wetted by >3 days of simulated rainfall per week. The number of perithecia produced on canker lesions increased with the increase in rainfall duration. Perithecia were formed on canker shoots exposed to rainfall only in June, July, and August but not in September. Rainfall of >3 days per week can be used to predict the initial formation of perithecia in the main apple production areas in China to assist disease management.

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Cacao is a commodity crop from the tropics cultivated by about 6 million smallholder farmers. The tree, Theobroma cacao, originated in the Upper Amazon where it was domesticated ca. 5450 to 5300 B.P. From this center of origin, cacao was dispersed and cultivated in Mesoamerica as early as 3800 to 3000 B.P. After the European conquest of the Americas (the 1500s), cacao cultivation intensified in several loci, primarily Mesoamerica, Trinidad, Venezuela, and Ecuador. It was during the colonial period that cacao diseases began emerging as threats to production. One early example is the collapse of the cacao industry in Trinidad in the 1720s, attributed to an unknown disease referred to as the "blast". Trinidad would resurface as a production center due to the discovery of the Trinitario genetic group, which is still widely used in breeding programs around the world. However, a resurgence of diseases like frosty pod rot during the republican period (the late 1800s and early 1900s) had profound impacts on other centers of Latin American production, especially in Venezuela and Ecuador, shifting the focus of cacao production southward, to Bahia, Brazil. Production in Bahia was, in turn, dramatically curtailed by the introduction of witches' broom disease in the late 1980s. Today, most of the world's cacao production occurs in West Africa and parts of Asia, where the primary Latin American diseases have not yet spread. In this review, we discuss the history of cacao cultivation in the Americas and how that history has been shaped by the emergence of diseases.

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Indicator species analysis (ISA) uses indices of an organism's relative abundance and occurrence to estimate the strength of its associations with a priori groups of interest and a simple randomization test to evaluate the probability of association. Because ISA values tend to be greatest when a species is both relatively more abundant than other species in a particular group and it occurs more frequently in that same group (the expectations of a causal agent in diseased plants), ISA should be useful for identifying and narrowing the list of potential causal agents from a pool of pathogens in both emerging plant diseases and when the causal agent is unclear. Recent ISA plant disease applications suggests it may either directly identify a single causal agent from a pool of potential pathogens or narrow the pool of pathogens as candidates for pathogenicity tests in the process of fulfilling Koch's postulates. In this letter, we explain the underpinnings of ISA, summarize the known applications to plant pathosystems, offer caveats about the analysis, and suggest scenarios where ISA may be broadly applicable for plant disease studies.

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In pathogenic fungi and oomycetes, interspecific hybridization may lead to the formation of new species having a greater impact on natural ecosystems than the parental species. From the early 1990s, a severe alder (Alnus spp.) decline due to an unknown Phytophthora species was observed in several European countries. Genetic analyses revealed that the disease was caused by the triploid hybrid P. × alni, which originated in Europe from the hybridization of P. uniformis and P. × multiformis. Here, we investigated the population structure of P. × alni (158 isolates) and P. uniformis (85 isolates) in several European countries using microsatellite markers. Our analyses confirmed the genetic structure previously observed in other European populations, with P. uniformis populations consisting of at most two multilocus genotypes (MLGs) and P. × alni populations dominated by MLG Pxa-1. The genetic structure of P. × alni populations in the Czech Republic, Hungary and Sweden seemed to reflect the physical isolation of river systems. Most rare P. × alni MLGs showed a loss of heterozygosity (LOH) at one or a few microsatellite loci compared with other MLGs. This LOH may allow a stabilization within the P. × alni genome or a rapid adaptation to stress situations. Alternatively, alleles may be lost because of random genetic drift in small, isolated populations, with no effect on fitness of P. × alni. Additional studies would be necessary to confirm these patterns of population diversification and to better understand the factors driving it.

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Trials were conducted to quantify the stability (or lack of G × E interaction) of 15 maize hybrids to Gibberella ear rot (GER; caused by Fusarium graminearum) and deoxynivalenol (DON) contamination of grain across 30 Ohio environments (3 years × 10 locations). In each environment, one plot of each hybrid was planted and 10 ears per plot were inoculated via the silk channel. GER severity (proportion of ear area diseased) and DON contamination of grain (ppm) were quantified. Multiple rank-based methods, including Kendall's concordance coefficient (W) and Piepho's U, were used to quantify hybrid stability. The results found insufficient evidence to suggest crossover G × E interaction of ranks, with W greater than zero for GER (W = 0.28) and DON (W = 0.26), and U not statistically significant for either variable (P > 0.20). Linear mixed models (LMMs) were also used to quantify hybrid stability, accounting for crossover or noncrossover G × E interaction of transformed observed data. Based on information criteria and likelihood ratio tests for GER and DON response variables, the models with more complex variance-covariance structures-heterogeneous compound symmetry and factor-analytic-provided a better fit than the model with the simpler compound symmetry structure, indicating that one or more hybrids differed in stability. Overall, hybrids were stable based on rank-based methods, which indicated a lack of crossover G × E interaction, but the LMMs identified a few hybrids that were sensitive to environment. Resistant hybrids were generally more stable than susceptible hybrids.

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