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Article: Genetic mapping of host resistance to soybean sudden death syndrome

Collins, Paul Joseph / Tan, Ruijuan / Wen, Zixiang / Boyse, John F. / Chilvers, Martin I. / Wang, Dechun

Crop science. 2022 Mar., v. 62, no. 2

2022

Abstract: Soybean sudden death syndrome (SDS) is a disease caused by a soil‐borne fungus, Fusarium virguliforme. Many genetic studies have attempted to identify genes responsible for the quantitative host resistance to SDS. Three recombinant inbred line (RIL) ... ...

Abstract	Soybean sudden death syndrome (SDS) is a disease caused by a soil‐borne fungus, Fusarium virguliforme. Many genetic studies have attempted to identify genes responsible for the quantitative host resistance to SDS. Three recombinant inbred line (RIL) populations were evaluated for foliar SDS resistance at a naturally infested field site in Decatur, MI, during the 2014 and 2015 growing seasons. Lines were evaluated for disease severity (DS) on a 1–9 scale, disease incidence (DI) as an estimate of the percentage of plants with symptoms per plot, and disease index (DX) as a metric which integrates DS and DI. Phenotypic data was spatially adjusted to account for uneven pathogen distribution in the naturally infested field. A subset of RILs from each population were genotyped with the SoySNP6K Illumina Infinium BeadChip. Linkage maps unique to each population were constructed using JoinMap ver. 2. Composite interval mapping was performed using WinQTLCartographer ver. 2.5. Three quantitative trait loci (QTL) were identified across 2 yr and/or multiple populations. One QTL on Chromosome 10 appeared to be colocalized with the E2 maturity locus. Another QTL identified was on Chromosome 18, in a region which has been demonstrated to provide soybean cyst nematode (SCN) and SDS resistance in many studies (rhg1/Rfs2).
Keywords	Fusarium virguliforme ; Heterodera glycines ; disease incidence ; disease severity ; genotyping ; inbred lines ; loci ; pathogens ; phenotype ; quantitative traits ; soil fungi ; soybean sudden death syndrome
Language	English
Dates of publication	2022-03
Size	p. 713-727.
Publishing place	John Wiley & Sons, Ltd
Document type	Article
Note	JOURNAL ARTICLE
ZDB-ID	410209-5
ISSN	0011-183X
ISSN	0011-183X
DOI	10.1002/csc2.20689
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Article ; Online: Integrating Seeding Rates and Pesticide Programs for Managing Sclerotinia Stem Rot in Glycine max with Nitrogen Fertilizer Applications

Webster, Richard W. / Mueller, Brian D. / Chilvers, Martin I. / Byrne, Adam M. / Boyse, John F. / Widdicombe, William W. / Mueller, Daren S. / Wiggs, Stith / Kandel, Yuba / Telenko, Darcy E. P. / Ravellette, Jeffrey / Shim, Su / Smith, Damon L.

Plant Health Progress. 2023 Oct., v. 24, no. 3 p.320-325

2023

Abstract: Soybean production in the Upper Midwest region of the United States is consistently limited by the disease Sclerotinia stem rot (SSR). To control SSR, multiple management practices have been studied and implemented to reduce SSR development and preserve ... ...

Abstract	Soybean production in the Upper Midwest region of the United States is consistently limited by the disease Sclerotinia stem rot (SSR). To control SSR, multiple management practices have been studied and implemented to reduce SSR development and preserve yield. This study examined the effects of integrating soybean seeding rates and pesticide programs under nitrogen fertilizer applications in the form of urea (46-0-0) that may occur due to management of other crops, such as corn. From 10 site-years between 2020 and 2021, low seeding rates decreased SSR development while also decreasing yields and partial profits. The effect of pesticide applications on SSR development was influenced by both seeding rates and nitrogen applications. Consistently, applications of the fungicide Endura reduced SSR to the lowest levels while also maintaining the highest yields and partial profits. Soybeans grown with nitrogen applications experienced increased SSR development and decreased yields and partial profits. Overall, this work suggests that using low seeding rates and fungicides improves the management of SSR, and using nitrogen fertilizer applications can result in greater SSR development and decreased economic returns, especially in fields with a history of SSR.
Keywords	Glycine max ; Sclerotinia ; corn ; fungicides ; nitrogen ; nitrogen fertilizers ; soybeans ; stem rot ; urea ; Midwestern United States ; integrated pest management ; soybean ; white mold
Language	English
Dates of publication	2023-10
Size	p. 320-325.
Publishing place	The American Phytopathological Society
Document type	Article ; Online
ISSN	1535-1025
DOI	10.1094/PHP-10-22-0102-RS
Database	NAL-Catalogue (AGRICOLA)

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Article: Case Study of an Epidemiological Approach Dissecting Historical Soybean Sclerotinia Stem Rot Observations and Identifying Environmental Predictors of Epidemics and Yield Loss.

Fall, Mamadou L / Boyse, John F / Wang, Dechun / Willbur, Jaime F / Smith, Damon L / Chilvers, Martin I

Phytopathology

2018 Volume 108, Issue 4, Page(s) 469–478

Abstract: Sclerotinia sclerotiorum is a significant threat to soybean production worldwide. In this study, an epidemiological approach was used to examine 11 years of historical data from a soybean management performance trial in order to advance our understanding ...

Abstract	Sclerotinia sclerotiorum is a significant threat to soybean production worldwide. In this study, an epidemiological approach was used to examine 11 years of historical data from a soybean management performance trial in order to advance our understanding of Sclerotinia stem rot (SSR) development and to identify environmental predictors of SSR epidemics and associated yield losses. Recursive partitioning analysis suggested that average air temperature and total precipitation in July were the most significant variables associated with disease severity. High levels of SSR disease severity index were observed when the average temperature in July was below 19.5°C and total precipitation in July was moderate, between 20 and 108.5 mm. A biphasic sigmoidal curve accurately described the relationship between SSR disease severity index (DSI) and yield, with a DSI threshold of 22, below which minimal yield loss was observed. A 10% increase in the DSI, from 22.0 to 24.2, led to an 11% decrease in yield, from 3,308.14 to 2,951.29 kg/ha. Also, a yield threshold (3,353 kg/ha) that was higher than the annual U.S. average soybean yield (3,039.7 kg/ha) was suggested as an expected yield under low or no SSR pressure in the U.S. Midwest. These thresholds can allow soybean stakeholders to assess the value of disease control and establish an SSR baseline for cost-effective management to protect yields. Because S. sclerotiorum has more than 400 plant host species, and because having quantitative information concerning crop losses is crucial for decision making, this study shows the usefulness of historical data on SSR and, hence, can serve as a model in other SSR pathosystems (canola, dry bean, potato, pea, and so on).
MeSH term(s)	Ascomycota/physiology ; Logistic Models ; Models, Statistical ; Plant Diseases/microbiology ; Plant Diseases/statistics & numerical data ; Plant Stems/growth & development ; Plant Stems/microbiology ; Risk ; Glycine max/growth & development ; Glycine max/microbiology ; Weather
Language	English
Publishing date	2018-03-05
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	208889-7
ISSN	1943-7684 ; 0031-949X
ISSN (online)	1943-7684
ISSN	0031-949X
DOI	10.1094/PHYTO-12-16-0446-R
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Article: Genomic consequences of selection and genome-wide association mapping in soybean

Wen, Zixiang / Boyse, John F / Song, Qijian / Cregan, Perry B / Wang, Dechun

BMC genomics. 2015 Sept. 3, v. 16, no. 671

2015

Abstract: Crop improvement always involves selection of specific alleles at genes controlling traits of agronomic importance, likely resulting in detectable signatures of selection within the genome of modern soybean (Glycine max L. Merr.). The identification of ... ...

Abstract	Crop improvement always involves selection of specific alleles at genes controlling traits of agronomic importance, likely resulting in detectable signatures of selection within the genome of modern soybean (Glycine max L. Merr.). The identification of these signatures of selection is meaningful from the perspective of evolutionary biology and for uncovering the genetic architecture of agronomic traits. Two populations of soybean, consisting of 342 landraces and 1062 improved lines, were genotyped with the SoySNP50K Illumina BeadChip containing 52,041 single nucleotide polymorphisms (SNPs), and systematically phenotyped for 9 agronomic traits. A cross-population composite likelihood ratio (XP-CLR) method was used to screen the signals of selective sweeps. A total of 125 candidate selection regions were identified, many of which harbored genes potentially involved in crop improvement. To further investigate whether these candidate regions were in fact enriched for genes affected by selection, genome-wide association studies (GWAS) were conducted on 7 selection traits targeted in soybean breeding (grain yield, plant height, lodging, maturity date, seed coat color, seed protein and oil content) and 2 non-selection traits (pubescence and flower color). Major genomic regions associated with selection traits overlapped with candidate selection regions, whereas no overlap of this kind occurred for the non-selection traits, suggesting that the selection sweeps identified are associated with traits of agronomic importance. Multiple novel loci and refined map locations of known loci related to these traits were also identified. These findings illustrate that comparative genomic analyses, especially when combined with GWAS, are a promising approach to dissect the genetic architecture of complex traits.
Keywords	alleles ; landraces ; genome-wide association study ; genetic lines ; grain yield ; maturity groups ; selection methods ; Glycine max ; lodging ; chromosome mapping ; single nucleotide polymorphism ; lipid content ; proteins ; testa ; loci ; soybeans ; flowers ; color ; genomics ; population
Language	English
Dates of publication	2015-0903
Document type	Article
Note	2019-12-06
ISSN	1471-2164
DOI	10.1186/s12864-015-1872-y
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Genomic consequences of selection and genome-wide association mapping in soybean.

Wen, Zixiang / Boyse, John F / Song, Qijian / Cregan, Perry B / Wang, Dechun

BMC genomics

2015 Volume 16, Page(s) 671

Abstract: Background: Crop improvement always involves selection of specific alleles at genes controlling traits of agronomic importance, likely resulting in detectable signatures of selection within the genome of modern soybean (Glycine max L. Merr.). The ... ...

Abstract	Background: Crop improvement always involves selection of specific alleles at genes controlling traits of agronomic importance, likely resulting in detectable signatures of selection within the genome of modern soybean (Glycine max L. Merr.). The identification of these signatures of selection is meaningful from the perspective of evolutionary biology and for uncovering the genetic architecture of agronomic traits. Results: To this end, two populations of soybean, consisting of 342 landraces and 1062 improved lines, were genotyped with the SoySNP50K Illumina BeadChip containing 52,041 single nucleotide polymorphisms (SNPs), and systematically phenotyped for 9 agronomic traits. A cross-population composite likelihood ratio (XP-CLR) method was used to screen the signals of selective sweeps. A total of 125 candidate selection regions were identified, many of which harbored genes potentially involved in crop improvement. To further investigate whether these candidate regions were in fact enriched for genes affected by selection, genome-wide association studies (GWAS) were conducted on 7 selection traits targeted in soybean breeding (grain yield, plant height, lodging, maturity date, seed coat color, seed protein and oil content) and 2 non-selection traits (pubescence and flower color). Major genomic regions associated with selection traits overlapped with candidate selection regions, whereas no overlap of this kind occurred for the non-selection traits, suggesting that the selection sweeps identified are associated with traits of agronomic importance. Multiple novel loci and refined map locations of known loci related to these traits were also identified. Conclusions: These findings illustrate that comparative genomic analyses, especially when combined with GWAS, are a promising approach to dissect the genetic architecture of complex traits.
MeSH term(s)	Chromosome Mapping ; Genetic Loci ; Genetic Variation ; Genetics, Population ; Genome, Plant ; Genome-Wide Association Study ; Genomics ; Linkage Disequilibrium/genetics ; Phenotype ; Polymorphism, Single Nucleotide/genetics ; Principal Component Analysis ; Quantitative Trait, Heritable ; Reproducibility of Results ; Selection, Genetic ; Glycine max/genetics
Language	English
Publishing date	2015-09-03
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2041499-7
ISSN	1471-2164 ; 1471-2164
ISSN (online)	1471-2164
ISSN	1471-2164
DOI	10.1186/s12864-015-1872-y
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Article ; Online: QTL mapping and epistatic interaction analysis of field resistance to sudden death syndrome (Fusarium virguliforme) in soybean.

Tan, Ruijuan / Serven, Bradley / Collins, Paul J / Zhang, Zhongnan / Wen, Zixiang / Boyse, John F / Gu, Cuihua / Chilvers, Martin I / Diers, Brian W / Wang, Dechun

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik

2018 Volume 131, Issue 8, Page(s) 1729–1740

Abstract: Key message: Two interactive quantitative trait loci (QTLs) controlled the field resistance to sudden death syndrome (SDS) in soybean. The interaction between them was confirmed. Sudden death syndrome (SDS), caused by Fusarium virguliforme, is a major ... ...

Abstract	Key message: Two interactive quantitative trait loci (QTLs) controlled the field resistance to sudden death syndrome (SDS) in soybean. The interaction between them was confirmed. Sudden death syndrome (SDS), caused by Fusarium virguliforme, is a major disease of soybean [Glycine max (L.) Merr.] in the United States. Breeding for soybean resistance to SDS is the most cost-effective method to manage the disease. The objective of this study was to identify and characterize quantitative trait loci (QTLs) underlying field resistance to SDS in a recombinant inbred line population from the cross GD2422 × LD01-5907. This population was genotyped with 1786 polymorphic single nucleotide polymorphisms (SNPs) using SoySNP6 K iSelect BeadChip and evaluated for SDS resistance in a naturally infested field. Four SDS resistance QTLs were mapped on Chromosomes 4, 8, 12 and 18. The resistant parent, LD01-5907, contributed the resistance alleles for the QTLs on Chromosomes 8 and 18 (qSDS-8 and qSDS-18), while the other parent, GD2422, provided the resistance alleles for the QTLs on Chromosomes 4 and 12 (qSDS-4 and qSDS-12). The minor QTL on Chromosome 12 (qSDS-12) is novel. The QTL on Chromosomes 8 and 18 (qSDS-8 and qSDS-18) overlapped with two soybean cyst nematode resistance-related loci, Rhg4 and Rhg1, respectively. A significant interaction between qSDS-8 and qSDS-18 was detected by disease incidence. Individual effects together with the interaction effect explained around 70% of the phenotypic variance. The epistatic interaction of qSDS-8 and qSDS-18 was confirmed by the field performance across multiple years. Furthermore, the resistance alleles at qSDS-8 and qSDS-18 were demonstrated to be recessive. The SNP markers linked to these QTLs will be useful for marker-assisted breeding to enhance the SDS resistance.
MeSH term(s)	Alleles ; Chromosome Mapping ; Disease Resistance/genetics ; Epistasis, Genetic ; Fusarium/pathogenicity ; Genetic Linkage ; Genotype ; Plant Breeding ; Plant Diseases/genetics ; Plant Diseases/microbiology ; Polymorphism, Single Nucleotide ; Quantitative Trait Loci ; Glycine max/genetics ; Glycine max/microbiology
Language	English
Publishing date	2018-05-15
Publishing country	Germany
Document type	Journal Article
ZDB-ID	2170-2
ISSN	1432-2242 ; 0040-5752
ISSN (online)	1432-2242
ISSN	0040-5752
DOI	10.1007/s00122-018-3110-x
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Article ; Online: Different loci associated with root and foliar resistance to sudden death syndrome (Fusarium virguliforme) in soybean.

Tan, Ruijuan / Collins, Paul J / Wang, Jie / Wen, Zixiang / Boyse, John F / Laurenz, Randall G / Gu, Cuihua / Jacobs, Janette L / Song, Qijian / Chilvers, Martin I / Wang, Dechun

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik

2018 Volume 132, Issue 2, Page(s) 501–513

Abstract: Key message: Different loci associated with root resistance to F. virguliforme colonization and foliar resistance to phytotoxin damage in soybean. Use of resistant cultivars is the most efficacious approach to manage soybean sudden death syndrome (SDS), ...

Abstract	Key message: Different loci associated with root resistance to F. virguliforme colonization and foliar resistance to phytotoxin damage in soybean. Use of resistant cultivars is the most efficacious approach to manage soybean sudden death syndrome (SDS), caused by Fusarium virguliforme. The objectives of this study were to (1) map the loci associated with root and foliar resistance to F. virguliforme infection and (2) decipher the relationships between root infection, foliar damage, and plot yield. A mapping population consisting of 153 F
MeSH term(s)	Chromosome Mapping ; Disease Resistance/genetics ; Fusarium/pathogenicity ; Genetic Linkage ; Genotype ; Phenotype ; Plant Diseases/genetics ; Plant Diseases/microbiology ; Plant Leaves ; Plant Roots ; Quantitative Trait Loci ; Glycine max/genetics ; Glycine max/microbiology
Language	English
Publishing date	2018-11-16
Publishing country	Germany
Document type	Journal Article
ZDB-ID	2170-2
ISSN	1432-2242 ; 0040-5752
ISSN (online)	1432-2242
ISSN	0040-5752
DOI	10.1007/s00122-018-3237-9
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Article ; Online: Integrating GWAS and gene expression data for functional characterization of resistance to white mould in soya bean.

Wen, Zixiang / Tan, Ruijuan / Zhang, Shichen / Collins, Paul J / Yuan, Jiazheng / Du, Wenyan / Gu, Cuihua / Ou, Shujun / Song, Qijian / An, Yong-Qiang Charles / Boyse, John F / Chilvers, Martin I / Wang, Dechun

Plant biotechnology journal

2018 Volume 16, Issue 11, Page(s) 1825–1835

Abstract: White mould of soya bean, caused by Sclerotinia sclerotiorum (Lib.) de Bary, is a necrotrophic fungus capable of infecting a wide range of plants. To dissect the genetic architecture of resistance to white mould, a high-density customized single ... ...

Abstract	White mould of soya bean, caused by Sclerotinia sclerotiorum (Lib.) de Bary, is a necrotrophic fungus capable of infecting a wide range of plants. To dissect the genetic architecture of resistance to white mould, a high-density customized single nucleotide polymorphism (SNP) array (52 041 SNPs) was used to genotype two soya bean diversity panels. Combined with resistance variation data observed in the field and greenhouse environments, genome-wide association studies (GWASs) were conducted to identify quantitative trait loci (QTL) controlling resistance against white mould. Results showed that 16 and 11 loci were found significantly associated with resistance in field and greenhouse, respectively. Of these, eight loci localized to previously mapped QTL intervals and one locus had significant associations with resistance across both environments. The expression level changes in genes located in GWAS-identified loci were assessed between partially resistant and susceptible genotypes through a RNA-seq analysis of the stem tissue collected at various time points after inoculation. A set of genes with diverse biological functionalities were identified as strong candidates underlying white mould resistance. Moreover, we found that genomic prediction models outperformed predictions based on significant SNPs. Prediction accuracies ranged from 0.48 to 0.64 for disease index measured in field experiments. The integrative methods, including GWAS, RNA-seq and genomic selection (GS), applied in this study facilitated the identification of causal variants, enhanced our understanding of mechanisms of white mould resistance and provided valuable information regarding breeding for disease resistance through genomic selection in soya bean.
MeSH term(s)	Ascomycota ; Disease Resistance/genetics ; Gene Expression/genetics ; Genes, Plant/genetics ; Genetic Markers/genetics ; Genome-Wide Association Study ; Linkage Disequilibrium/genetics ; Plant Diseases/immunology ; Plant Diseases/microbiology ; Polymorphism, Single Nucleotide/genetics ; Quantitative Trait Loci/genetics ; Glycine max/genetics ; Glycine max/immunology ; Glycine max/microbiology
Chemical Substances	Genetic Markers
Language	English
Publishing date	2018-05-07
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2136367-5
ISSN	1467-7652 ; 1467-7652
ISSN (online)	1467-7652
ISSN	1467-7652
DOI	10.1111/pbi.12918
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Integrating GWAS and gene expression data for functional characterization of resistance to white mould in soya bean

Wen, Zixiang / Tan, Ruijuan / Zhang, Shichen / Collins, Paul J / Yuan, Jiazheng / Du, Wenyan / Gu, Cuihua / Ou, Shujun / Song, Qijian / An, Yong‐Qiang Charles / Boyse, John F / Chilvers, Martin I / Wang, Dechun

Plant biotechnology journal. 2018 Nov., v. 16, no. 11

2018

Abstract	White mould of soya bean, caused by Sclerotinia sclerotiorum (Lib.) de Bary, is a necrotrophic fungus capable of infecting a wide range of plants. To dissect the genetic architecture of resistance to white mould, a high‐density customized single nucleotide polymorphism (SNP) array (52 041 SNPs) was used to genotype two soya bean diversity panels. Combined with resistance variation data observed in the field and greenhouse environments, genome‐wide association studies (GWASs) were conducted to identify quantitative trait loci (QTL) controlling resistance against white mould. Results showed that 16 and 11 loci were found significantly associated with resistance in field and greenhouse, respectively. Of these, eight loci localized to previously mapped QTL intervals and one locus had significant associations with resistance across both environments. The expression level changes in genes located in GWAS‐identified loci were assessed between partially resistant and susceptible genotypes through a RNA‐seq analysis of the stem tissue collected at various time points after inoculation. A set of genes with diverse biological functionalities were identified as strong candidates underlying white mould resistance. Moreover, we found that genomic prediction models outperformed predictions based on significant SNPs. Prediction accuracies ranged from 0.48 to 0.64 for disease index measured in field experiments. The integrative methods, including GWAS, RNA‐seq and genomic selection (GS), applied in this study facilitated the identification of causal variants, enhanced our understanding of mechanisms of white mould resistance and provided valuable information regarding breeding for disease resistance through genomic selection in soya bean.
Keywords	Sclerotinia sclerotiorum ; biotechnology ; disease resistance ; fungi ; gene expression ; genomics ; genotype ; greenhouses ; loci ; marker-assisted selection ; prediction ; quantitative traits ; sequence analysis ; single nucleotide polymorphism ; soybeans
Language	English
Dates of publication	2018-11
Size	p. 1825-1835.
Publishing place	John Wiley & Sons, Ltd
Document type	Article
Note	JOURNAL ARTICLE
ZDB-ID	2136367-5
ISSN	1467-7652 ; 1467-7644
ISSN (online)	1467-7652
ISSN	1467-7644
DOI	10.1111/pbi.12918
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Article: Genomic consequences of selection and genome-wide association mapping in soybean

Wen, Zixiang / Boyse, John F. / Song, Qijian / Cregan, Perry B. / Wang, Dechun

BMC genomics

Volume v. 16,, Issue no. 6

Abstract	Crop improvement always involves selection of specific alleles at genes controlling traits of agronomic importance, likely resulting in detectable signatures of selection within the genome of modern soybean (Glycine max L. Merr.). The identification of these signatures of selection is meaningful from the perspective of evolutionary biology and for uncovering the genetic architecture of agronomic traits. Two populations of soybean, consisting of 342 landraces and 1062 improved lines, were genotyped with the SoySNP50K Illumina BeadChip containing 52,041 single nucleotide polymorphisms (SNPs), and systematically phenotyped for 9 agronomic traits. A cross-population composite likelihood ratio (XP-CLR) method was used to screen the signals of selective sweeps. A total of 125 candidate selection regions were identified, many of which harbored genes potentially involved in crop improvement. To further investigate whether these candidate regions were in fact enriched for genes affected by selection, genome-wide association studies (GWAS) were conducted on 7 selection traits targeted in soybean breeding (grain yield, plant height, lodging, maturity date, seed coat color, seed protein and oil content) and 2 non-selection traits (pubescence and flower color). Major genomic regions associated with selection traits overlapped with candidate selection regions, whereas no overlap of this kind occurred for the non-selection traits, suggesting that the selection sweeps identified are associated with traits of agronomic importance. Multiple novel loci and refined map locations of known loci related to these traits were also identified. These findings illustrate that comparative genomic analyses, especially when combined with GWAS, are a promising approach to dissect the genetic architecture of complex traits.
Keywords	selection methods ; genome-wide association study ; single nucleotide polymorphism ; alleles ; genetic lines ; loci ; Glycine max ; maturity groups ; color ; lipid content ; testa ; seeds ; chromosome mapping ; genomics ; flowers ; proteins ; grain yield ; soybeans ; landraces ; lodging ; population
Language	English
Document type	Article
ISSN	1471-2164
Database	AGRIS - International Information System for the Agricultural Sciences and Technology

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