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Artikel ; Online: Genomic and metabolomic diversity within a familial population of Aspergillus flavus.

Moore, Geromy G / Mack, Brian M / Wendt, Karen L / Castano-Duque, Lina / Anderson, Victoria M / Cichewicz, Robert H

2024 Band 121, Heft 5, Seite(n) 927–939

Abstract: Aspergillus flavus is an agriculturally significant micro-fungus having potential to contaminate food and feed crops with toxic secondary metabolites such as aflatoxin (AF) and cyclopiazonic acid (CPA). Research has shown A. flavus strains can overcome ... ...

Abstract	Aspergillus flavus is an agriculturally significant micro-fungus having potential to contaminate food and feed crops with toxic secondary metabolites such as aflatoxin (AF) and cyclopiazonic acid (CPA). Research has shown A. flavus strains can overcome heterokaryon incompatibility and undergo meiotic recombination as teleomorphs. Although evidence of recombination in the AF gene cluster has been reported, the impacts of recombination on genotype and metabolomic phenotype in a single generation are lacking. In previous studies, we paired an aflatoxigenic MAT1-1 A. flavus strain with a non-aflatoxigenic MAT1-2 A. flavus strain that had been tagged with green fluorescent protein and then 10 F1 progenies (a mix of fluorescent and non-fluorescent) were randomly selected from single-ascospore colonies and broadly examined for evidence of recombination. In this study, we determined four of those 10 F1 progenies were recombinants because they were not vegetatively compatible with either parent or their siblings, and they exhibited other distinctive traits that could only result from meiotic recombination. The other six progenies examined shared genomic identity with the non-aflatoxigenic, fluorescent, and MAT1-2 parent, but were metabolically distinct. This study highlights phenotypic and genomic changes that may occur in a single generation from the outcrossing of sexually compatible strains of A. flavus.
Mesh-Begriff(e)	Aspergillus flavus/genetics ; Aspergillus flavus/metabolism ; Aflatoxins/metabolism ; Aflatoxins/genetics ; Genome, Fungal/genetics ; Recombination, Genetic ; Genomics ; Metabolomics ; Genotype ; Phenotype ; Multigene Family ; Genetic Variation ; Indoles/metabolism ; Meiosis/genetics
Sprache	Englisch
Erscheinungsdatum	2024-02-23
Erscheinungsland	England
Dokumenttyp	Journal Article
ZDB-ID	619315-8
ISSN	1365-2958 ; 0950-382X
ISSN (online)	1365-2958
ISSN	0950-382X
DOI	10.1111/mmi.15244
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: Flavonoids Modulate

Castano-Duque, Lina / Lebar, Matthew D / Carter-Wientjes, Carol / Ambrogio, David / Rajasekaran, Kanniah

Journal of fungi (Basel, Switzerland)

2022 Band 8, Heft 11

Abstract: Aflatoxins are carcinogenic mycotoxins produced ... ...

Abstract	Aflatoxins are carcinogenic mycotoxins produced by
Sprache	Englisch
Erscheinungsdatum	2022-11-16
Erscheinungsland	Switzerland
Dokumenttyp	Journal Article
ZDB-ID	2784229-0
ISSN	2309-608X ; 2309-608X
ISSN (online)	2309-608X
ISSN	2309-608X
DOI	10.3390/jof8111211
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel: Gradient boosting and bayesian network machine learning models predict aflatoxin and fumonisin contamination of maize in Illinois - First USA case study.

Castano-Duque, Lina / Vaughan, Martha / Lindsay, James / Barnett, Kristin / Rajasekaran, Kanniah

Frontiers in microbiology

2022 Band 13, Seite(n) 1039947

Abstract: Mycotoxin contamination of corn results in significant agroeconomic losses and poses serious health issues worldwide. This paper presents the first report utilizing machine learning and historical aflatoxin and fumonisin contamination levels in-order-to ... ...

Abstract	Mycotoxin contamination of corn results in significant agroeconomic losses and poses serious health issues worldwide. This paper presents the first report utilizing machine learning and historical aflatoxin and fumonisin contamination levels in-order-to develop models that can confidently predict mycotoxin contamination of corn in Illinois, a major corn producing state in the USA. Historical monthly meteorological data from a 14-year period combined with corresponding aflatoxin and fumonisin contamination data from the State of Illinois were used to engineer input features that link weather, fungal growth, and aflatoxin production in combination with gradient boosting (GBM) and bayesian network (BN) modeling. The GBM and BN models developed can predict mycotoxin contamination with overall 94% accuracy. Analyses for aflatoxin and fumonisin with GBM showed that meteorological and satellite-acquired vegetative index data during March significantly influenced grain contamination at the end of the corn growing season. Prediction of high aflatoxin contamination levels was linked to high aflatoxin risk index in March/June/July, high vegetative index in March and low vegetative index in July. Correspondingly, high levels of fumonisin contamination were linked to high precipitation levels in February/March/September and high vegetative index in March. During corn flowering time in June, higher temperatures range increased prediction of high levels of fumonisin contamination, while high aflatoxin contamination levels were linked to high aflatoxin risk index. Meteorological events prior to corn planting in the field have high influence on predicting aflatoxin and fumonisin contamination levels at the end of the year. These early-year events detected by the models can directly assist farmers and stakeholders to make informed decisions to prevent mycotoxin contamination of Illinois grown corn.
Sprache	Englisch
Erscheinungsdatum	2022-11-10
Erscheinungsland	Switzerland
Dokumenttyp	Journal Article
ZDB-ID	2587354-4
ISSN	1664-302X
ISSN	1664-302X
DOI	10.3389/fmicb.2022.1039947
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel: Gradient boosting machine learning model to predict aflatoxins in Iowa corn.

Branstad-Spates, Emily H / Castano-Duque, Lina / Mosher, Gretchen A / Hurburgh, Charles R / Owens, Phillip / Winzeler, Edwin / Rajasekaran, Kanniah / Bowers, Erin L

Frontiers in microbiology

2023 Band 14, Seite(n) 1248772

Abstract: Introduction: Aflatoxin (AFL), a secondary metabolite produced from filamentous fungi, contaminates corn, posing significant health and safety hazards for humans and livestock through toxigenic and carcinogenic effects. Corn is widely used as an ... ...

Abstract	Introduction: Aflatoxin (AFL), a secondary metabolite produced from filamentous fungi, contaminates corn, posing significant health and safety hazards for humans and livestock through toxigenic and carcinogenic effects. Corn is widely used as an essential commodity for food, feed, fuel, and export markets; therefore, AFL mitigation is necessary to ensure food and feed safety within the United States (US) and elsewhere in the world. In this case study, an Iowa-centric model was developed to predict AFL contamination using historical corn contamination, meteorological, satellite, and soil property data in the largest corn-producing state in the US. Methods: We evaluated the performance of AFL prediction with gradient boosting machine (GBM) learning and feature engineering in Iowa corn for two AFL risk thresholds for high contamination events: 20-ppb and 5-ppb. A 90%-10% training-to-testing ratio was utilized in 2010, 2011, 2012, and 2021 ( Results: The GBM model had an overall accuracy of 96.77% for AFL with a balanced accuracy of 50.00% for a 20-ppb risk threshold, whereas GBM had an overall accuracy of 90.32% with a balanced accuracy of 64.88% for a 5-ppb threshold. The GBM model had a low power to detect high AFL contamination events, resulting in a low sensitivity rate. Analyses for AFL showed satellite-acquired vegetative index during August significantly improved the prediction of corn contamination at the end of the growing season for both risk thresholds. Prediction of high AFL contamination levels was linked to aflatoxin risk indices (ARI) in May. However, ARI in July was an influential factor for the 5-ppb threshold but not for the 20-ppb threshold. Similarly, latitude was an influential factor for the 20-ppb threshold but not the 5-ppb threshold. Furthermore, soil-saturated hydraulic conductivity (Ksat) influenced both risk thresholds. Discussion: Developing these AFL prediction models is practical and implementable in commodity grain handling environments to achieve the goal of preventative rather than reactive mitigations. Finding predictors that influence AFL risk annually is an important cost-effective risk tool and, therefore, is a high priority to ensure hazard management and optimal grain utilization to maximize the utility of the nation's corn crop.
Sprache	Englisch
Erscheinungsdatum	2023-09-01
Erscheinungsland	Switzerland
Dokumenttyp	Journal Article
ZDB-ID	2587354-4
ISSN	1664-302X
ISSN	1664-302X
DOI	10.3389/fmicb.2023.1248772
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: Genes and genetic mechanisms contributing to fall armyworm resistance in maize.

Warburton, Marilyn L / Woolfolk, Sandra W / Smith, J Spencer / Hawkins, Leigh K / Castano-Duque, Lina / Lebar, Matthew D / Williams, W Paul

The plant genome

2023 Band 16, Heft 2, Seite(n) e20311

Abstract: Maize (Zea mays L.) is a crop of major economic and food security importance globally. The fall armyworm (FAW), Spodoptera frugiperda, can devastate entire maize crops, especially in countries or markets that do not allow the use of transgenic crops. ... ...

Abstract	Maize (Zea mays L.) is a crop of major economic and food security importance globally. The fall armyworm (FAW), Spodoptera frugiperda, can devastate entire maize crops, especially in countries or markets that do not allow the use of transgenic crops. Host-plant insect resistance is an economical and environmentally benign way to control FAW, and this study sought to identify maize lines, genes, and pathways that contribute to resistance to FAW. Of the 289 maize lines phenotyped for FAW damage in artificially infested, replicated field trials over 3 years, 31 were identified with good levels of resistance that could donate FAW resistance into elite but susceptible hybrid parents. The 289 lines were genotyped by sequencing to provide single nucleotide polymorphism (SNP) markers for a genome-wide association study (GWAS), followed by a metabolic pathway analysis using the Pathway Association Study Tool (PAST). GWAS identified 15 SNPs linked to 7 genes, and PAST identified multiple pathways, associated with FAW damage. Top pathways, and thus useful resistance mechanisms for further study, include hormone signaling pathways and the biosynthesis of carotenoids (particularly zeaxanthin), chlorophyll compounds, cuticular wax, known antibiosis agents, and 1,4-dihydroxy-2-naphthoate. Targeted metabolite analysis confirmed that maize genotypes with lower levels of FAW damage tend to have higher levels of chlorophyll a than genotypes with high FAW damage, which tend to have lower levels of pheophytin, lutein, chlorophyll b and β-carotene. The list of resistant genotypes, and the results from the genetic, pathway, and metabolic study, can all contribute to efficient creation of FAW resistant cultivars.
Mesh-Begriff(e)	Animals ; Zea mays/genetics ; Spodoptera/genetics ; Chlorophyll A ; Genome-Wide Association Study ; Larva
Chemische Substanzen	Chlorophyll A (YF5Q9EJC8Y)
Sprache	Englisch
Erscheinungsdatum	2023-03-02
Erscheinungsland	United States
Dokumenttyp	Journal Article
ZDB-ID	2375444-8
ISSN	1940-3372 ; 0011-183X
ISSN (online)	1940-3372
ISSN	0011-183X
DOI	10.1002/tpg2.20311
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: Genes and genetic mechanisms contributing to fall armyworm resistance in maize

Warburton, Marilyn L. / Woolfolk, Sandra W. / Smith, J. Spencer / Hawkins, Leigh K. / Castano‐Duque, Lina / Lebar, Matthew D. / Williams, W. Paul

The Plant Genome. 2023 June, v. 16, no. 2 p.e20311-

2023

Abstract	Maize (Zea mays L.) is a crop of major economic and food security importance globally. The fall armyworm (FAW), Spodoptera frugiperda, can devastate entire maize crops, especially in countries or markets that do not allow the use of transgenic crops. Host‐plant insect resistance is an economical and environmentally benign way to control FAW, and this study sought to identify maize lines, genes, and pathways that contribute to resistance to FAW. Of the 289 maize lines phenotyped for FAW damage in artificially infested, replicated field trials over 3 years, 31 were identified with good levels of resistance that could donate FAW resistance into elite but susceptible hybrid parents. The 289 lines were genotyped by sequencing to provide single nucleotide polymorphism (SNP) markers for a genome‐wide association study (GWAS), followed by a metabolic pathway analysis using the Pathway Association Study Tool (PAST). GWAS identified 15 SNPs linked to 7 genes, and PAST identified multiple pathways, associated with FAW damage. Top pathways, and thus useful resistance mechanisms for further study, include hormone signaling pathways and the biosynthesis of carotenoids (particularly zeaxanthin), chlorophyll compounds, cuticular wax, known antibiosis agents, and 1,4‐dihydroxy‐2‐naphthoate. Targeted metabolite analysis confirmed that maize genotypes with lower levels of FAW damage tend to have higher levels of chlorophyll a than genotypes with high FAW damage, which tend to have lower levels of pheophytin, lutein, chlorophyll b and β‐carotene. The list of resistant genotypes, and the results from the genetic, pathway, and metabolic study, can all contribute to efficient creation of FAW resistant cultivars.
Schlagwörter	Spodoptera frugiperda ; Zea mays ; antibiosis ; biochemical pathways ; biosynthesis ; chlorophyll ; corn ; cultivars ; epicuticular wax ; food security ; genetically modified organisms ; genome ; genome-wide association study ; genotyping ; host plants ; hybrids ; insect resistance ; lutein ; metabolic studies ; metabolites ; single nucleotide polymorphism ; zeaxanthin
Sprache	Englisch
Erscheinungsverlauf	2023-06
Erscheinungsort	John Wiley & Sons, Ltd
Dokumenttyp	Artikel ; Online
Anmerkung	JOURNAL ARTICLE
ZDB-ID	2375444-8
ISSN	1940-3372 ; 0011-183X
ISSN (online)	1940-3372
ISSN	0011-183X
DOI	10.1002/tpg2.20311
Datenquelle	NAL Katalog (AGRICOLA)

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Artikel ; Online: An epigenetic pathway in rice connects genetic variation to anaerobic germination and seedling establishment.

Castano-Duque, Lina / Ghosal, Sharmistha / Quilloy, Fergie A / Mitchell-Olds, Thomas / Dixit, Shalabh

Plant physiology

2021 Band 186, Heft 2, Seite(n) 1042–1059

Abstract: Rice production is shifting from transplanting seedlings to direct sowing of seeds. Following heavy rains, directly sown seeds may need to germinate under anaerobic environments, but most rice (Oryza sativa) genotypes cannot survive these conditions. To ... ...

Abstract	Rice production is shifting from transplanting seedlings to direct sowing of seeds. Following heavy rains, directly sown seeds may need to germinate under anaerobic environments, but most rice (Oryza sativa) genotypes cannot survive these conditions. To identify the genetic architecture of complex traits, we quantified percentage anaerobic germination (AG) in 2,700 (wet-season) and 1,500 (dry-season) sequenced rice genotypes and performed genome-wide association studies (GWAS) using 693,502 single nucleotide polymorphisms. This was followed by post-GWAS analysis with a generalized SNP-to-gene set analysis, meta-analysis, and network analysis. We determined that percentage AG is intermediate-to-high among indica subpopulations, and AG is a polygenic trait associated with transcription factors linked to ethylene responses or genes involved in metabolic processes that are known to be associated with AG. Our post-GWAS analysis identified several genes involved in a wide variety of metabolic processes. We subsequently performed functional analysis focused on the small RNA and methylation pathways. We selected CLASSY 1 (CLSY1), a gene involved in the RNA-directed DNA methylation (RdDm) pathway, for further analyses under AG and found several lines of evidence that CLSY1 influences AG. We propose that the RdDm pathway plays a role in rice responses to water status during germination and seedling establishment developmental stages.
Mesh-Begriff(e)	Anaerobiosis/genetics ; Epigenesis, Genetic ; Ethylenes/metabolism ; Genetic Variation ; Genome-Wide Association Study ; Genotype ; Germination/genetics ; Oryza/genetics ; Oryza/physiology ; Plant Growth Regulators/metabolism ; Polymorphism, Single Nucleotide/genetics ; Seedlings/genetics ; Seedlings/physiology ; Seeds/genetics ; Seeds/physiology ; Water/physiology
Chemische Substanzen	Ethylenes ; Plant Growth Regulators ; Water (059QF0KO0R) ; ethylene (91GW059KN7)
Sprache	Englisch
Erscheinungsdatum	2021-02-27
Erscheinungsland	United States
Dokumenttyp	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	208914-2
ISSN	1532-2548 ; 0032-0889
ISSN (online)	1532-2548
ISSN	0032-0889
DOI	10.1093/plphys/kiab100
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel: Protein networks reveal organ-specific defense strategies in maize in response to an aboveground herbivore

Castano-Duque, Lina / Dawn S. Luthe

Arthropod-plant interactions. 2018 Feb., v. 12, no. 1

2018

Abstract: Many of the proteins and defense pathways in maize that are activated in an organ-specific manner in leaves and roots during aboveground caterpillar attack have not yet been identified. In this study, we examined systemic and organ-specific defenses in ... ...

Abstract	Many of the proteins and defense pathways in maize that are activated in an organ-specific manner in leaves and roots during aboveground caterpillar attack have not yet been identified. In this study, we examined systemic and organ-specific defenses in the insect-resistant maize genotype, Mp708, when infested aboveground with fall armyworm (FAW, Spodoptera frugiperda). We used proteomic and network biology analyses and then integrated these data with known FAW resistance QTL to create a protein abundance QTL (pQTL) subnetwork. Using 10-plex tandem mass spectrometry tags (TMT) proteomics technique, we identified a total of 4675 proteins in leaves and roots of control and FAW-infested plants. Among the identified proteins, 794 had significant differences in abundance in response to FAW herbivory. Proteins that were upregulated in leaves during FAW infestation included jasmonic acid biosynthetic enzymes, cysteine proteases, protease inhibitors, REDOX-related proteins, and peroxidases. In roots, highly abundant proteins were involved in ET biosynthesis, DNA expression regulation, and pyruvate biosynthesis. We found many proteins that possibly contribute different defense functions to FAW resistance in Mp708. One potential resistance mechanism identified was that trade-offs between growth and defense responses were reduced in Mp708. Some of the proteins involved in this trade-off that were found within the pQTL subnetwork were the Kinesin-like protein (GRMZM2G046186_P01) and Pi starvation-induced protein (GRMZM2G118037_P01). We proposed other mechanisms contributing to resistance that suggest that jasmonic acid and ethylene control the local accumulation of insecticidal cysteine protease (MIR1-CP) in leaves, while ethylene controlled the systemic accumulation of MIR1-CP in roots. Finally, we hypothesized that receptor kinases such as receptor protein kinase 1 (GRMZM2G055678) could be involved in the activation of root-specific defense responses during aboveground insect infestation.
Schlagwörter	DNA ; Spodoptera frugiperda ; biosynthesis ; corn ; cysteine proteinases ; ethylene ; genotype ; herbivores ; insect infestations ; jasmonic acid ; leaves ; peroxidases ; protein kinases ; proteinase inhibitors ; proteins ; proteomics ; pyruvic acid ; quantitative trait loci ; roots ; tandem mass spectrometry
Sprache	Englisch
Erscheinungsverlauf	2018-02
Umfang	p. 147-175.
Erscheinungsort	Springer Netherlands
Dokumenttyp	Artikel
ZDB-ID	2377469-1
ISSN	1872-8847 ; 1872-8855
ISSN (online)	1872-8847
ISSN	1872-8855
DOI	10.1007/s11829-017-9562-0
Datenquelle	NAL Katalog (AGRICOLA)

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Artikel ; Online: Dynamic geospatial modeling of mycotoxin contamination of corn in Illinois: unveiling critical factors and predictive insights with machine learning

Castano-Duque, Lina / Winzeler, Edwin / Blackstock, Joshua M. / Liu, Cheng / Vergopolan, Noemi / Focker, Marlous / Barnett, Kristin / Owens, Phillip Ray / van der Fels-Klerx, H. J. / Vaughan, Martha M. / Rajasekaran, Kanniah

Frontiers in Microbiology. 2023 Nov. 01, v. 14

2023

Abstract: Mycotoxin contamination of corn is a pervasive problem that negatively impacts human and animal health and causes economic losses to the agricultural industry worldwide. Historical aflatoxin (AFL) and fumonisin (FUM) mycotoxin contamination data of corn, ...

Abstract	Mycotoxin contamination of corn is a pervasive problem that negatively impacts human and animal health and causes economic losses to the agricultural industry worldwide. Historical aflatoxin (AFL) and fumonisin (FUM) mycotoxin contamination data of corn, daily weather data, satellite data, dynamic geospatial soil properties, and land usage parameters were modeled to identify factors significantly contributing to the outbreaks of mycotoxin contamination of corn grown in Illinois (IL), AFL >20 ppb, and FUM >5 ppm. Two methods were used: a gradient boosting machine (GBM) and a neural network (NN). Both the GBM and NN models were dynamic at a state-county geospatial level because they used GPS coordinates of the counties linked to soil properties. GBM identified temperature and precipitation prior to sowing as significant influential factors contributing to high AFL and FUM contamination. AFL-GBM showed that a higher aflatoxin risk index (ARI) in January, March, July, and November led to higher AFL contamination in the southern regions of IL. Higher values of corn-specific normalized difference vegetation index (NDVI) in July led to lower AFL contamination in Central and Southern IL, while higher wheat-specific NDVI values in February led to higher AFL. FUM-GBM showed that temperature in July and October, precipitation in February, and NDVI values in March are positively correlated with high contamination throughout IL. Furthermore, the dynamic geospatial models showed that soil characteristics were correlated with AFL and FUM co
Schlagwörter	aflatoxins ; agricultural industry ; calcium carbonate ; corn ; fumonisins ; land use ; meteorological data ; microbiology ; normalized difference vegetation index ; remote sensing ; risk ; soil ; temperature ; Illinois
Sprache	Englisch
Erscheinungsverlauf	2023-1101
Erscheinungsort	Frontiers Media SA
Dokumenttyp	Artikel ; Online
Anmerkung	Resource is Open Access
ZDB-ID	2587354-4
ISSN	1664-302X
ISSN	1664-302X
DOI	10.3389/fmicb.2023.1283127
Datenquelle	NAL Katalog (AGRICOLA)

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Artikel: Dynamic geospatial modeling of mycotoxin contamination of corn in Illinois: unveiling critical factors and predictive insights with machine learning.

Castano-Duque, Lina / Winzeler, Edwin / Blackstock, Joshua M / Liu, Cheng / Vergopolan, Noemi / Focker, Marlous / Barnett, Kristin / Owens, Phillip Ray / van der Fels-Klerx, H J / Vaughan, Martha M / Rajasekaran, Kanniah

Frontiers in microbiology

2023 Band 14, Seite(n) 1283127

Abstract	Mycotoxin contamination of corn is a pervasive problem that negatively impacts human and animal health and causes economic losses to the agricultural industry worldwide. Historical aflatoxin (AFL) and fumonisin (FUM) mycotoxin contamination data of corn, daily weather data, satellite data, dynamic geospatial soil properties, and land usage parameters were modeled to identify factors significantly contributing to the outbreaks of mycotoxin contamination of corn grown in Illinois (IL), AFL >20 ppb, and FUM >5 ppm. Two methods were used: a gradient boosting machine (GBM) and a neural network (NN). Both the GBM and NN models were dynamic at a state-county geospatial level because they used GPS coordinates of the counties linked to soil properties. GBM identified temperature and precipitation prior to sowing as significant influential factors contributing to high AFL and FUM contamination. AFL-GBM showed that a higher aflatoxin risk index (ARI) in January, March, July, and November led to higher AFL contamination in the southern regions of IL. Higher values of corn-specific normalized difference vegetation index (NDVI) in July led to lower AFL contamination in Central and Southern IL, while higher wheat-specific NDVI values in February led to higher AFL. FUM-GBM showed that temperature in July and October, precipitation in February, and NDVI values in March are positively correlated with high contamination throughout IL. Furthermore, the dynamic geospatial models showed that soil characteristics were correlated with AFL and FUM contamination. Greater calcium carbonate content in soil was negatively correlated with AFL contamination, which was noticeable in Southern IL. Greater soil moisture and available water-holding capacity throughout Southern IL were positively correlated with high FUM contamination. The higher clay percentage in the northeastern areas of IL negatively correlated with FUM contamination. NN models showed high class-specific performance for 1-year predictive validation for AFL (73%) and FUM (85%), highlighting their accuracy for annual mycotoxin prediction. Our models revealed that soil, NDVI, year-specific weekly average precipitation, and temperature were the most important factors that correlated with mycotoxin contamination. These findings serve as reliable guidelines for future modeling efforts to identify novel data inputs for the prediction of AFL and FUM outbreaks and potential farm-level management practices.
Sprache	Englisch
Erscheinungsdatum	2023-11-01
Erscheinungsland	Switzerland
Dokumenttyp	Journal Article
ZDB-ID	2587354-4
ISSN	1664-302X
ISSN	1664-302X
DOI	10.3389/fmicb.2023.1283127
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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