Evidence map›Paper›PMID 38516168›Full record

ArticleGrass and forage science : the journal of the British Grassland Society2023

Translating and applying a simulation model to enhance understanding of grassland management.

Michail L Giannitsopoulos, Paul J Burgess, Matthew J Bell, Goetz M Richter, Cairistiona F E Topp, Julie Ingram, Taro Takahashi

Abstract read
In one paragraph

Article in Grass and forage science : the journal of the British Grassland Society, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Translating and applying a simulation model to enhance understanding of grassland management.Grass and forage science : the journal of the British Grassland Society · 2023
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Michail L GiannitsopoulosSchool of Water, Energy and Environment Cranfield University Cranfield Bedfordshire UK.ORCID https://orcid.org/0000-0001-8952-7244
Paul J BurgessSchool of Water, Energy and Environment Cranfield University Cranfield Bedfordshire UK.ORCID https://orcid.org/0000-0001-8210-3430
Matthew J BellDepartment of Agriculture Hartpury University HEC Gloucester Gloustershire UK.ORCID https://orcid.org/0000-0003-0675-4797
Goetz M RichterRothamsted Research Sustainable Soils and Crops Harpenden Hertfordshire UK.ORCID https://orcid.org/0000-0003-2180-9514
Cairistiona F E ToppScotland's Rural College Peter Wilson Building, King's Building Edinburgh UK.ORCID https://orcid.org/0000-0002-7064-638X
Julie IngramCountryside & Community Research Institute University of Gloucestershire Gloucestershire UK.ORCID https://orcid.org/0000-0003-0712-4789
Taro TakahashiRothamsted Research, Net Zero and Resilient Farming North Wyke Okehampton UK.ORCID https://orcid.org/0000-0002-3492-7299

Funding

Biotechnology and Biological Sciences Research Council BBS/E/C/000I0320Biotechnology and Biological Sciences Research Council BBS/E/C/000I0330
6 · The paper itself

Abstract

Each new generation of grassland managers could benefit from an improved understanding of how modification of nitrogen application and harvest dates in response to different weather and soil conditions will affect grass yields and quality. The purpose of this study was to develop a freely available grass yield simulation model, validated for England and Wales, and to examine its strengths and weaknesses as a teaching tool for improving grass management. The model, called LINGRA-N-Plus, was implemented in a Microsoft Excel spreadsheet and iteratively evaluated by students and practitioners (farmers, consultants, and researchers) in a series of workshops across the UK over 2 years. The iterative feedback led to the addition of new algorithms, an improved user interface, and the development of a teaching guide. The students and practitioners identified the ease of use and the capacity to understand, visualize and evaluate how decisions, such as variation of cutting intervals, affect grass yields as strengths of the model. We propose that an effective teaching tool must achieve an appropriate balance between being sufficiently detailed to demonstrate the major relationships (e.g., the effect of nitrogen on grass yields) whilst not becoming so complex that the relationships become incomprehensible. We observed that improving the user-interface allowed us to extend the scope of the model without reducing the level of comprehension. The students appeared to be interested in the explanatory nature of the model whilst the practitioners were more interested in the application of a validated model to enhance their decision making.

Indexed as

agronomydecision supporteducationgrassland managementLINGRA

Identifiers

PMID38516168
PMCPMC10952769

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.