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RESEARCH ARTICLE (Open Access)

The Australian digital Online Farm Trials database increases the quality of systematic reviews and meta-analyses in grains crop research

Judi R. Walters https://orcid.org/0000-0001-9772-6358 A B and Kate Light A
+ Author Affiliations
- Author Affiliations

A Centre for eResearch and Digital Innovation, Federation University Australia, Greenhill Enterprise Centre Ballarat Technology Park, Mount Helen, Vic. 3350, Australia.

B Corresponding author. Email: jr.walters@federation.edu.au

Crop and Pasture Science 72(10) 789-800 https://doi.org/10.1071/CP20534
Submitted: 7 January 2021  Accepted: 20 May 2021   Published: 20 August 2021

Journal Compilation © CSIRO 2021 Open Access CC BY

Abstract

Synthesis and analysis of past cropping research can provide valuable information to direct future decisions around crop management. Systematic reviews and meta-analyses are considered gold standards in the synthesis and analysis of scientific research because they distil large amounts of information about complex issues, provide a summary of knowledge to date, and identify knowledge gaps. However, several issues concerning the methodologies employed to conduct systematic reviews have been identified; among them is the risk of publication bias when a review relies too heavily on ‘white’ literature from published academic sources and in so doing fails identify relevant ‘grey’ literature. Grey literature is inherently difficult to identify and collect, but forms a large portion of information available in many fields including agricultural-based research within Australia. The Online Farm Trials (OFT) database is a digital database of crop research field trial data from across Australia that has the potential for use as a discipline-specific source of grey literature to inform systematic reviews and meta-analyses. Using a case study approach to investigate the amount of information available on time of sowing (sowing date) on crop yield across Australia, we demonstrate that the OFT database provides easy access to transparent and reproducible search results similar to other commonly used academic databases.

Keywords: agriculture, Australia, crop research, cropping, database, FAIR principles, findable, grains, literature review, meta-analysis, metadata, OFT, sowing date, systematic review, time of sowing.


References

Adams RJ, Hillier-Brown FC, Moore HJ, Lake AA, Araujo-Soares V, White M, Summerbell C (2016) Searching and synthesising ‘grey literature’ and ‘grey information’ in public health: critical reflections on three case studies. Systematic Reviews 5, 164
Searching and synthesising ‘grey literature’ and ‘grey information’ in public health: critical reflections on three case studies.Crossref | GoogleScholarGoogle Scholar |

AEGIC (Australian Export Grains Innovation Centre) (2019) Australia’s grain outlook 2030. Available at: https://www.aegic.org.au/wp-content/uploads/2019/11/AEGIC-Australias-Grain-Outlook-2030.pdf (accessed 14 August 2020).

Barbour V (2020) Science publishing has opened up during the coronavirus pandemic. It won’t be easy to keep it that way. Available at: https://theconversation.com/science-publishing-has-opened-up-during-the-coronavirus-pandemic-it-wont-be-easy-to-keep-it-that-way-142984 (accessed 23 April 2021).

Beckmann M, von Wehrden H (2012) Where you search is what you get: literature mining – Google Scholar versus Web of Science using a data set from a literature search in vegetation science. Journal of Vegetation Science 23, 1197–1199.
Where you search is what you get: literature mining – Google Scholar versus Web of Science using a data set from a literature search in vegetation science.Crossref | GoogleScholarGoogle Scholar |

Briscoe S (2015) Web searching for systematic reviews: a case study of reporting standards in the UK Health Technology Assessment programme. BMC Research Notes 8, 153
Web searching for systematic reviews: a case study of reporting standards in the UK Health Technology Assessment programme.Crossref | GoogleScholarGoogle Scholar | 25889619PubMed |

Briscoe S (2018) A review of the reporting of web searching to identify studies for Cochrane systematic reviews. Research Synthesis Methods 9, 89–99.
A review of the reporting of web searching to identify studies for Cochrane systematic reviews.Crossref | GoogleScholarGoogle Scholar | 29065246PubMed |

Briscoe S, Nunns M, Shaw L (2020) How do Chochrane authors conduct web searching to identify studies? Findings from a cross-sectional sample of Cochrane Reviews. Health Information and Libraries Journal 37, 293–318.
How do Chochrane authors conduct web searching to identify studies? Findings from a cross-sectional sample of Cochrane Reviews.Crossref | GoogleScholarGoogle Scholar | 32511888PubMed |

Cochrane Training (2021) Cochrane handbook for systematic reviews of interventions. Ver. 6.2, 2021. Available at: https://training.cochrane.org/handbook/current (accessed 22 April 2021).

Cooper C, Booth A, Britten N, Garsdale R (2017) A comparison of results of empirical studies of supplementary search techniques and recommendations in review methodology handbooks: a methodological review. Systematic Reviews 6, 234
A comparison of results of empirical studies of supplementary search techniques and recommendations in review methodology handbooks: a methodological review.Crossref | GoogleScholarGoogle Scholar | 29179733PubMed |

Cooper C, Lovell R, Husk K, Booth A, Garside R (2018) Supplementary search methods were more effective and offered better value than bibliographic database searching: a case study from public health and environmental enhancement. Research Synthesis Methods 9, 195–223.
Supplementary search methods were more effective and offered better value than bibliographic database searching: a case study from public health and environmental enhancement.Crossref | GoogleScholarGoogle Scholar | 29193834PubMed |

Cruz SMDd, Nascimento JAPd (2019) Towards integration of data-driven agronomic experiments with data provenance. Computers and Electronics in Agriculture 161, 14–28.
Towards integration of data-driven agronomic experiments with data provenance.Crossref | GoogleScholarGoogle Scholar |

Editorial (2019) The importance of no evidence. Nature Human Behaviour 3, 197
The importance of no evidence.Crossref | GoogleScholarGoogle Scholar | 30953022PubMed |

Enticott J, Buck K, Shawyer F (2018) Finding ‘hard to find’ literature on hard to find groups: technique to search grey literature on refugees and asylum seekers. International Journal of Methods in Psychiatric Research 27, e1580
Finding ‘hard to find’ literature on hard to find groups: technique to search grey literature on refugees and asylum seekers.Crossref | GoogleScholarGoogle Scholar | 28868640PubMed |

Falagas ME, Pitsouni EI, Malietzis GA, Pappas G (2008) Comparison of PubMed, Scopus, Web of Science, and Google Scholar: strengths and weaknesses. The FASEB Journal 22, 338–342.
Comparison of PubMed, Scopus, Web of Science, and Google Scholar: strengths and weaknesses.Crossref | GoogleScholarGoogle Scholar | 17884971PubMed |

Fanelli D (2012) Negative results are disappearing from most disciplines and countries. Scientometrics 90, 891–904.
Negative results are disappearing from most disciplines and countries.Crossref | GoogleScholarGoogle Scholar |

Fletcher A, Weeks C, Lawes R (2016) Why are WA farmers early sowing/dry sowing? GRDC Grains Research Update. Available at: https://grdc.com.au/resources-and-publications/grdc-update-papers/tab-content/grdc-update-papers/2016/03/why-are-wa-farmers-sowing-earlier-or-dry-sowing (accessed 19 October 2020).

Garousi V, Felderer M, Mantyla MV (2019) Guidelines for including grey literature and conducting multivocal literature reviews in software engineering. Information and Software Technology 106, 101–121.
Guidelines for including grey literature and conducting multivocal literature reviews in software engineering.Crossref | GoogleScholarGoogle Scholar |

Gibert A, Gray EF, Westoby M, Wright IJ, Falster S (2016) On the link between functional traits and growth rate: meta-analysis shows effects change with plant size, as predicted. Journal of Ecology 104, 1488–1503.
On the link between functional traits and growth rate: meta-analysis shows effects change with plant size, as predicted.Crossref | GoogleScholarGoogle Scholar |

Godin K, Stapleton J, Kirkpatrick SJ, Hanning RM, Leatherdale ST (2015) Applying systematic review search methods to the grey literature: a case study examining guidelines for school-based breakfast programs in Canada. Systematic Reviews 4, 138
Applying systematic review search methods to the grey literature: a case study examining guidelines for school-based breakfast programs in Canada.Crossref | GoogleScholarGoogle Scholar | 26494010PubMed |

GRDC (Grains Research and Development Corporation) (2011) Time of sowing. Available at: https://grdc.com.au/resources-and-publications/all-publications/factsheets/2011/03/time-of-sowing (accessed 13 May 2020).

Gusenbauer M, Haddaway NR (2020) Which academic search systems are suitable for systematic review or meta-analyses? Evaluating retrieval qualities of Google Scholar, PubMed, and 26 other resources. Research Synthesis Methods 11, 181–217.
Which academic search systems are suitable for systematic review or meta-analyses? Evaluating retrieval qualities of Google Scholar, PubMed, and 26 other resources.Crossref | GoogleScholarGoogle Scholar | 31614060PubMed |

Haidich AB (2010) Meta-analysis in medical research. Review article. Hippokratia 14, 29–37.

Higgins J, Thomas J (Eds) (2019) Cochrane Handbook for Systematic Reviews of Interventions. Available at: https://training.cochrane.org/handbook/current (accessed 3 September 2020).

Hopewell S, McDonald S, Clarke MJ, Egger M (2007) Grey literature in meta-analysis of randomized trials of health care interventions. Cochrane Database of Systematic Reviews Methodology Review 2, MR000010

Hyman G, Espinosa H, Camargo P, Abreu D, Devare M, Arnaud E, Porter C, Mwanzia L, Sonder K, Traore S (2017) Improving agricultural knowledge management: the AgTrials experience. F1000 Research 6, 317
Improving agricultural knowledge management: the AgTrials experience.Crossref | GoogleScholarGoogle Scholar | 28580127PubMed |

Koutsos TM, Menexes GC, Dordas CA (2019) An efficient framework for conducting systematic literature reviews in agricultural sciences. The Science of the Total Environment 682, 106–117.
An efficient framework for conducting systematic literature reviews in agricultural sciences.Crossref | GoogleScholarGoogle Scholar | 31108265PubMed |

Kukal MS, Irmak S (2018) US agro-climate in the 20th century: growing degree days, first and last frost, growing season length, and impacts on crop yields. Scientific Reports 8, 6977
US agro-climate in the 20th century: growing degree days, first and last frost, growing season length, and impacts on crop yields.Crossref | GoogleScholarGoogle Scholar | 29725053PubMed |

Manning BK, Adhikari KN, Trethowan R (2020) Impact of sowing time, genotype, environment and maturity on biomass and yield components in faba bean (Vicia faba). Crop & Pasture Science 71, 147–154.
Impact of sowing time, genotype, environment and maturity on biomass and yield components in faba bean (Vicia faba).Crossref | GoogleScholarGoogle Scholar |

McAuley L, Pham B, Tugwll P, Moher D (2000) Does the inclusion of grey literature influence estimates of intervention effectiveness reported in meta-analyses? Lancet 356, 1228–1231.
Does the inclusion of grey literature influence estimates of intervention effectiveness reported in meta-analyses?Crossref | GoogleScholarGoogle Scholar | 11072941PubMed |

Moher D, Liberati A, Tetzlaff J, Altman DG, The PRISMA Group (2009) Preferred reporting items for systematic reviews and meta-analyses: the PRIMSA statement. PLoS Medicine 6, e1000097
Preferred reporting items for systematic reviews and meta-analyses: the PRIMSA statement.Crossref | GoogleScholarGoogle Scholar | 19753108PubMed |

Murphy A, McKenna K, Milne R, Taylor M, Corbett J, Dahlhaus P, Thompson H (2015) Online Farm Trials (OFT) impact research: eResearch (first wave) extended timeframe research study. Centre for eResearch and Digital Innovation, Federation University Australia, Ballarat, Vic., Australia.

Ogundari K, Bolarinwa OD (2018) Impact of agricultural innovation adoption: a meta-analysis. The Australian Journal of Agricultural and Resource Economics 62, 217–236.
Impact of agricultural innovation adoption: a meta-analysis.Crossref | GoogleScholarGoogle Scholar |

Olson CM, Rennie D, Cook D, Dickersin K, Flanagin A, Hogan JW, Zhu Q, Reiling J, Pace B (2002) Publication bias in editorial decision making. Journal of the American Medical Association 287, 2825–2828.
Publication bias in editorial decision making.Crossref | GoogleScholarGoogle Scholar | 12038924PubMed |

Open Access (2020) Progress Report. Available at: https://oa2020.org/progress-report/ (accessed 23 April 2020).

Riveros C, Dechartres A, Perrodeau E, Haneef R, Boutron I, Ravaud P (2013) Timing and completeness of trial results posted at ClininicalTrials.gov and published in journals. PLoS Medicine 10, e1001566
Timing and completeness of trial results posted at ClininicalTrials.gov and published in journals.Crossref | GoogleScholarGoogle Scholar | 24311990PubMed |

Saleh AA, Ratajeski MA, Bertolet M (2014) Grey literature searching for health sciences systematic reviews: a prospective study of time spent and resources utilized. Available at: https://journals.library.ualberta.ca/eblip/index.php/EBLIP/article/view/20629/17128 (accessed 23 April 2021).

Setter TL, Munns R, Stefanova K, Shabala S (2020) What makes a plant science manuscript successful for publication? Functional Plant Biology 47, 1138–1146.
What makes a plant science manuscript successful for publication?Crossref | GoogleScholarGoogle Scholar | 32693907PubMed |

Stapleton J, Carter C, Bredahl L (2020) Developing systematic search methods for the library literature: methods and analysis. Journal of Academic Librarianship 46, 102190
Developing systematic search methods for the library literature: methods and analysis.Crossref | GoogleScholarGoogle Scholar |

Stephens DJ, Lyons TJ (1998) Variability and trends in sowing dates across the Australian wheatbelt. Australian Journal of Agricultural Research 49, 1111–1118.
Variability and trends in sowing dates across the Australian wheatbelt.Crossref | GoogleScholarGoogle Scholar |

Tillett S, Newbold E (2006) Grey literature at The British Library: revealing a hidden resource. Interlending & Document Supply 34, 70–73.
Grey literature at The British Library: revealing a hidden resource.Crossref | GoogleScholarGoogle Scholar |

Walters J, Milne R, Thompson H (2018) Online Farm Trials: a national web-based information source for Australian grains research, development and extension. Rural Extension & Innovation Systems Journal 14, 117–123.

Walters J, Light K, Robinson N (2020) Using agricultural metadata: a novel investigation of trends in sowing date in on-farm research trials using the Online Farm Trials database. F1000Research 9, 1305
Using agricultural metadata: a novel investigation of trends in sowing date in on-farm research trials using the Online Farm Trials database.Crossref | GoogleScholarGoogle Scholar | 34354820PubMed |

Wills B, Parker J, Thompson H, Taylor M, Feely P (2018) Online Farm Trials (OFT) External Data Audit Report. Centre for eResearch and Digital Innovation. Federation University Australia, Ballarat, Vic., Australia.

Wiréhn L (2018) Nordic agriculture under climate change: A systematic review of challenges, opportunities and adaptation strategies for crop production. Land Use Policy 77, 63–74.
Nordic agriculture under climate change: A systematic review of challenges, opportunities and adaptation strategies for crop production.Crossref | GoogleScholarGoogle Scholar |