About

Peter Balint-Kurti is an adjunct professor and USDA-ARS research geneticist whose work focuses on understanding the genetic and mechanistic bases of disease resistance in maize. His research aims to improve the resilience of maize crops by analyzing various aspects of disease resistance, including quantitative (partial, polygenic) resistance, the maize hypersensitive defense response, basal responses to microbes in maize and sorghum, and multiple disease resistance mechanisms. His work involves genetic and biochemical analysis, microbiome studies, and the development of maize populations for gene discovery and resistance characterization. Balint-Kurti's research also extends to the molecular and cellular bases of plant-pathogen interactions, particularly the role of effectors and resistance proteins such as NLRs in maize. He investigates the regulation of immune responses, including the degradation of activated resistance proteins via the ERAD pathway, and explores the broader implications for plant immunity and crop improvement. His contributions include elucidating key defense mechanisms in maize, which is a model species for plant genetics and the top crop in the U.S., with findings relevant to other crop species as well.

Selected publications

• Maize Hybrids Exhibit Reduction in an Elicitor-Triggered Defense Response Compared with Their Inbred Parents

  Molecular Plant-Microbe Interactions · 2026-02-02

  articleOpen accessSenior author

  Heterosis is the increased performance of hybrids relative to their parental genotypes. Heterosis for growth may be mediated by underlying traits, including traits affecting host-microbe interactions. A trade-off between growth and defense is often observed in plant disease studies, such that a stronger defense response is often associated with slower growth and lower yield. We investigated the production of reactive oxygen species (ROS) following treatment with microbial elicitors, an early component of the pattern-triggered immunity (PTI) response, in maize hybrids and their inbred parents. ROS production was often reduced in hybrids compared with inbred parents, and this effect was dependent on genotype, elicitor used, and time of day. These results identify PTI as a response displaying heterosis whose regulation might contribute to heterosis in other traits, such as growth and yield. [Formula: see text] Copyright © 2026 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

  PublisherDOI

• Genotype-Dependent Systemic Resistance in Maize Caused by Foliar Infection and by Foliar Damage

  PhytoFrontiers™ · 2026-01-22

  articleOpen accessSenior author

  Systemic resistance (SR) occurs when systemic signals derived from sites of previous pathogen attacks result in increased resistance levels to subsequent pathogenesis at distal sites. Although much research on this phenomenon has been conducted in dicotyledonous species, little is known about SR in monocotyledonous models. In this study, we investigate SR in maize caused by foliar infection with Cochliobolus heterostrophus—the causal agent of southern leaf blight (SLB) disease—and by leaf damage. In juvenile maize, we observed that both prior infection with C. heterostrophus and cutting of the third and fourth leaves led to enhanced resistance to SLB in the fifth leaf. Levels of SR induction were variable between genotypes and between growth conditions. C. heterostrophus infection induced local and systemic expression of the defense-associated transcript ZmPR1. We discuss the implications of these findings that provide insights into the systemic disease resistance response in maize. [Formula: see text] The author(s) have dedicated the work to the public domain under the Creative Commons CC0 “No Rights Reserved” license by waiving all of his or her rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law, 2026.

  PublisherOA PDFDOI

• The Interaction Between Abiotic and Biotic Soil Factors Modulates Heterosis Expression in Maize

  Phytobiomes Journal · 2025-09-16

  articleOpen access

  Heterosis, or hybrid vigor, refers to the phenotypic superiority of hybrids relative to their parental inbred lines. Recent work showed that manipulation of the soil microbial community consistently altered heterosis, but the direction of the effect was dependent on microbiome composition, environment, or both. Abiotic factors such as temperature, water availability, and soil nutrients are known modifiers of heterosis expression; however, whether interactions between the soil microbial community and abiotic properties affect heterosis is largely unknown. To further understand how microbes influence heterosis, we characterized variation in maize heterosis when grown in soil inocula derived from historical maize farms or prairies. Although we did not observe consistent differences in heterosis among plants grown in these inocula, our observations affirm that microbial effects on heterosis are likely specific to the local microbial community. The introduction of a nutrient amendment resulted in greater heterosis in the presence of an agricultural soil inoculum than in the presence of a prairie soil inoculum. In addition, the interaction between soil inoculum and nutrient treatment structured bacterial and fungal community composition in the root endosphere. Root bacterial diversity was also significantly higher under nutrient-limited conditions. These results suggest that the contributions of genotype-by-environment interactions to heterosis are dependent on microbial context. They also provide direct evidence for the interactive effect of the soil microbial community and abiotic environment on heterosis and suggest that consideration of the soil microbial community may be helpful for breeding hybrid maize varieties for high performance in diverse environmental contexts. [Formula: see text] Copyright © 2026 The Author(s). This is an open access article distributed under the CC BY 4.0 International license .

  PublisherDOI

• Author Correction: The ZmCPK39–ZmDi19–ZmPR10 immune module regulates quantitative resistance to multiple foliar diseases in maize

  Nature Genetics · 2025-01-21 · 1 citations

  erratumOpen access
  PublisherOA PDFDOI

• A maize near-isogenic line population designed for gene discovery and characterization of allelic effects

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-02-02 · 1 citations

  preprintOpen accessCorresponding

  Abstract In this study we characterized a panel of 1,264 maize near-isogenic lines (NILs), developed from crosses between 18 diverse inbred lines and the recurrent parent B73, referred to as nested NILs (nNILs). 884 of the nNILs were genotyped using genotyping-by-sequencing (GBS). Subsequently, 24 of these nNILs, and all the parental lines, were re-genotyped using a high-density SNP chip. A novel pipeline for calling introgressions, which does not rely on knowing the donor parent of each nNIL, was developed based on a hidden Markov model (HMM) algorithm. By comparing the introgressions detected using GBS data with those identified using chip data, we optimized the HMM parameters for analyzing the entire nNIL population. A total of 2,972 introgressions were identified across the 884 nNILs. Individual introgression blocks ranged from 21 bp to 204 Mbp, with an average size of 17 Mbp. By comparing SNP genotypes within introgressed segments to the known genotypes of the donor lines we determined that in about one third of the lines, the identity of the donors did not match expectation based on their pedigrees. We characterized the entire nNIL population for three foliar diseases. Using these data, we mapped a number of quantitative trait loci (QTL) for disease resistance in the nNIL population and observed extensive variation in effects among the alleles from different donor parents at most QTL identified. This population will be of significant utility for dissecting complex agronomic traits and allelic series in maize. Significance Statement The study reports the characterization of a publicly available population of 1,264 maize near-isogenic lines largely derived from a single recurrent parent and 18 donor lines. This population is likely to be of significant utility for the characterization of allelic series at loci of interest.

  PublisherOA PDFDOI

• A maize near‐isogenic line population designed for gene discovery and characterization of allelic effects

  The Plant Journal · 2025-06-01 · 1 citations

  articleOpen accessCorresponding

  In this study, we characterized a panel of 1264 maize near-isogenic lines (NILs), developed from crosses between 18 diverse inbred lines and the recurrent parent B73, referred to as nested NILs (nNILs). In this study, 888 of the nNILs were genotyped using genotyping-by-sequencing (GBS). Subsequently, 24 of these nNILs, and all the parental lines, were re-genotyped using a high-density single nucleotide polymorphism (SNP) chip. A novel pipeline for calling introgressions, which does not rely on knowing the donor parent of each nNIL, was developed based on a hidden Markov model (HMM) algorithm. By comparing the introgressions detected using GBS data with those identified using chip data, we optimized the HMM parameters for analyzing the entire nNIL population. A total of 2969 introgressions were identified across the 888 nNILs. Individual introgression blocks ranged from 21 bp to 204 Mbp, with an average size of 17 Mbp. By comparing SNP genotypes within introgressed segments to the known genotypes of the donor lines, we determined that in about one third of the lines, the identity of the donors did not match expectation based on their pedigrees. We characterized the entire nNIL population for three foliar diseases. Using these data, we mapped a number of quantitative trait loci (QTL) for disease resistance in the nNIL population and observed extensive variation in effects among the alleles from different donor parents at most QTL identified. This population will be of significant utility for dissecting complex agronomic traits and allelic series in maize.

  PublisherOA PDFDOI

• It‘s Complicated: Why Are There So Few Commercially Successful Crop Varieties Engineered for Disease Resistance?

  Molecular Plant Pathology · 2025-03-01 · 2 citations

  reviewOpen access1st authorCorresponding

  It is more than 40 years since the era of transgenic plants began and more than 30 years after the cloning of the first plant disease resistance genes. Despite extensive progress in our mechanistic understanding and despite considerable sustained efforts in the commercial, nonprofit, academic and governmental sectors, the prospect of commercially viable plant varieties carrying disease resistance traits endowed by biotechnological approaches remains elusive. The cost of complying with the regulations governing the release of transgenic plants is often cited as the main reason for this lack of success. While this is undeniably a substantial hurdle, other transgenic traits have been successfully commercialised. We argue that a significant portion of the challenges of producing crop varieties engineered for disease resistance is intrinsic to the trait itself. In this review, we briefly discuss the main approaches used to engineer plant disease resistance. We further discuss possible reasons why they have not been successful in a commercial context and, finally, we try to derive some lessons to apply to future efforts.

  PublisherOA PDFDOI

• Mueller matrix spectral and polarimetric imaging for high throughput plant phenotyping

  2025-03-19

  articleSenior author
  PublisherDOI

• Diverse modes of gene action contribute to heterosis for quantitative disease resistance in maize

  Genetics · 2025-03-24 · 2 citations

  articleSenior author

  Disease resistance in plants can be conferred by single genes of large effect or by multiple genes each conferring incomplete resistance. The latter case, termed quantitative resistance, may be difficult for pathogens to overcome through evolution due to the low selection pressures exerted by the actions of any single gene and, for some diseases, is the only identified source of genetic resistance. We evaluated quantitative resistance to 2 diseases of maize in a biparental mapping population as well as backcrosses to both parents. Quantitative trait locus analysis shows that the genetic architecture of resistance to these diseases is characterized by several modes of gene action including additivity as well as dominance, overdominance, and epistasis. Heterosis or hybrid vigor, the improved performance of a hybrid compared with its parents, can be caused by nonadditive gene action and is fundamental to the breeding of several crops including maize. In the backcross populations and a diverse set of maize hybrids, we find heterosis for resistance in many cases and that the degree of heterosis appears to be dependent on both hybrid genotype and disease.

  PublisherDOI

• Cross-variety validation of a polarimetric glare correction algorithm for maize

  2025-09-17

  article

  Remote phenotyping in maize is hindered by glare, contaminating spectral data. This study expands on prior work using a Mueller matrix bidirectional reflectance distribution function (mmBRDF) model and correction network (CN) to mitigate this. We tested the mmBRDF/CN’s applicability across three maize varieties (B73, MO17, and a Pioneer Hybrid) using a multistatic fiber-based instrument. Leaf sample measurements, model parameter analysis, and Monte Carlo simulations were used to quantify CN performance. Refractive index (n) was consistent. Additionally, vairance in σ may aid in varietal differentiation. The CN significantly reduced error and variance in GNDVI across all varieties, with RMSE decreasing from approximately 0.10 to 0.035, and standard deviation decreasing by a factor of 2. As expected, outlier analysis showed low sun angles and specular viewing caused most residual error; yet, generally, the CN had broad applicability for correcting glare in the tested genotypes.

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Labs

• Peter Balint-KurtiPI

Awards & honors

• NSF CAREER Award (2022)
• USDA - National Institute of Food and Agriculture (NIFA) Gra…
• National Science Foundation (NSF) Grant (2022-2026)