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master_table_lit_search_analysis_basic_155_models_20230225.xlsx (89.91 kB)

master_table_lit_search_analysis_basic_155_models_20230225.xlsx

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posted on 2023-03-09, 05:35 authored by Robert ClarkRobert Clark

This spreadsheet was produced following a literature search conducted across the Scopus, EBSCOhost, and Web of Science (WoS) databases. The search targeted peer-reviewed papers, books, and book chapters published globally from January 2015 to December 2021. The search string 

"(estimat* OR predict*) AND (yield* OR product*) AND (wheat OR barley OR canola OR oilseed* OR rapeseed* OR cereal*) AND model* "

was applied across the three databases and a separate EndNote data base accumulated over the period 01/01/2020 – 31/12/2021 using ad hoc searches and publisher alerts.   

The Scopus data base was searched first, followed by searches across the EBSCOhost, WoS and EndNote databases in that order. After duplicate records were removed, search results were filtered using the following criteria:

  • The paper, book chapter or book was peer reviewed and written in English
  • The primary purpose of the paper, book chapter or book was the development and testing of a yield prediction model
  • The location, crop, yield units, input and prediction scale and extent were thoroughly documented
  • The models targeted either wheat, barley, or canola (or some combination of these crops) 
  • The model output resolution was at sub-paddock scale or higher (e.g. paddock regional, national), but excluded plot scale models
  • The model was applied across extensive areas (> 100km x 100km)
  • Input data (for running the model) was limited to accessible published data. Model development and calibration may use in situ data, but the model must not rely on in situ data to run. In this study, the data typically included publicly available, satellite-based, remotely sensed data and spatially continuous meteorological, soil moisture, landform, soil, and agronomic data as well as crop maps. Data collected by, UAV or other airborne sensors, paddock scale in situ measurements or private farmer records, were excluded. 

The search identified a total of 11,908 papers. After removing duplicate records and filtering based on title and the abstract, this was reduced to 388 papers. Another 46 papers were identified and added from the EndNote database. After a detailed scrutiny of the papers and strict application of the search criteria, 118 papers were identified that fitted the literature review criteria. Some of these papers described models for multiple crop types and a range of spatial resolution. This resulted in the review identifying 155 models. 


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