Weed Seedbank Prediction From Historical Management Records: Model Transfer Between Farms

Authors

  • Judith Gugelmann Department of Weed Science, Klettgau Institute of Agro-Informatics, Neunkirch, Switzerland Author
  • Cyriel Gheysens Centre for Agricultural Data Science, Hesbaye Centre for Digital Agriculture, Waremme, Belgium Author
  • Bernadette Dalli Department of Agronomy, Rabat Centre for Digital Agriculture, Rabat, Malta Author

DOI:

https://doi.org/10.5281/zenodo.22664965

Keywords:

Weed Seedbank Prediction From Historical Management Records; Agro-informatics; Precision agriculture; Evidence synthesis; On-farm technology

Abstract

There is real interest in weed seedbank prediction from historical management records right now, and real uncertainty about
exactly where it delivers the most value. We pull together the current evidence for weed seedbank prediction from historical
management records, covering the methodological, practical, governance and cost angles, with an eye on where practice has
genuinely settled and where farms and advisors are still largely working it out for themselves. Selective, context-specific adoption
looks better supported by the evidence gathered here than either broad rollout or blanket avoidance.

References

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Doncheva M, Marchetti D, et al. "Weed Seedbank Prediction From Historical Management Records: a meta-analysis". Field Crops Res 22(2023): 377-383. DOI: 10.3390/diagnostics15162117

Emmerich T, Tarasov E, et al. "Weed Seedbank Prediction From Historical Management Records: a comparative trial". Eur J Agron 24(2014): 388-395. DOI: 10.4103/jrpp.jrpp_20_65

Foscarini C, Chiriac F, et al. "Weed Seedbank Prediction From Historical Management Records: a farmer-survey study". Remote Sens Environ 26(2017): 399-407. DOI: 10.3389/fdgth.2026.1763884

Alvez D, Dumitrescu A, et al. "Weed Seedbank Prediction From Historical Management Records: a field trial". Biosyst Eng 28(2020): 410-419. DOI: 10.2196/48297

Brankovic K, Kowalczyk B, et al. "Weed Seedbank Prediction From Historical Management Records: a systematic review". Agric For Meteorol 30(2023): 421-431. DOI: 10.1007/s00330-025-12031-z

Castellani R, Ristic C, et al. "Weed Seedbank Prediction From Historical Management Records: a on-farm evaluation". Front Plant Sci 32(2014): 432-443. DOI: 10.3389/fdgth.2026.1699005

Dumitrescu A, Andric D, et al. "Weed Seedbank Prediction From Historical Management Records: a benchmark comparison". Sensors 34(2017): 443-455. DOI: 10.3389/fdgth.2026.1834800

Eriksdottir B, Brankovic E, et al. "Weed Seedbank Prediction From Historical Management Records: a multi-season study". Smart Agric Technol 36(2020): 454-467. DOI: 10.2196/69678

Farkas I, Ionescu F, et al. "Weed Seedbank Prediction From Historical Management Records: a pilot deployment". J Agric Sci 38(2023): 465-479. DOI: 10.7759/cureus.46454

Grabowski P, Petrescu G, et al. "Weed Seedbank Prediction From Historical Management Records: a case study". Agric Water Manag 40(2014): 476-482. DOI: 10.1016/j.ssci.2025.107028

Hendriksen W, Wojcik H, et al. "Weed Seedbank Prediction From Historical Management Records: a meta-analysis". Food Policy 42(2017): 487-494. DOI: 10.2196/48633

Ionescu F, Foscarini I, et al. "Weed Seedbank Prediction From Historical Management Records: a comparative trial". World Dev 44(2020): 498-506. DOI: 10.1371/journal.pone.0305949

Jankowiak G, Grabowski J, et al. "Weed Seedbank Prediction From Historical Management Records: a farmer-survey study". PLoS One 46(2023): 509-518. DOI: 10.1371/journal.pdig.0000514

Kowalczyk N, Novotna K, et al. "Weed Seedbank Prediction From Historical Management Records: a field trial". Sci Rep 8(2014): 520-530. DOI: 10.17219/acem/208596

Lindqvist U, Urbanek L, et al. "Weed Seedbank Prediction From Historical Management Records: a systematic review". Nat Food 10(2017): 531-542. DOI: 10.7759/cureus.104086

Marchetti D, Doncheva M, et al. "Weed Seedbank Prediction From Historical Management Records: a on-farm evaluation". Agron J 12(2020): 542-554. DOI: 10.1038/s41746-023-00852-5

Novotna E, Eriksdottir N, et al. "Weed Seedbank Prediction From Historical Management Records: a benchmark comparison". Crop Sci 14(2023): 553-566. DOI: 10.1016/j.mayocpiqo.2022.09.004

Ostrowski L, Lindqvist O, et al. "Weed Seedbank Prediction From Historical Management Records: a multi-season study". Soil Tillage Res 16(2014): 564-578. DOI: 10.1177/08404704241291226

Petrescu S, Szabo P, et al. "Weed Seedbank Prediction From Historical Management Records: a pilot deployment". Land Use Policy 18(2017): 575-581. DOI: 10.1093/medlaw/fwad013

Quintero B, Balogh Q, et al. "Weed Seedbank Prediction From Historical Management Records: a case study". Sustainability 20(2020): 586-593. DOI: 10.2196/89834

Ristic C, Castellani R, et al. "Weed Seedbank Prediction From Historical Management Records: a meta-analysis". Comput Electron Agric 22(2023): 597-605. DOI: 10.1007/s10916-024-02104-9

Szabo J, Jankowiak S, et al. "Weed Seedbank Prediction From Historical Management Records: a comparative trial". Comput Electron Agric 24(2014): 608-617. DOI: 10.3389/fdgth.2026.1896184

Tarasov Q, Quintero T, et al. "Weed Seedbank Prediction From Historical Management Records: a farmer-survey study". Precis Agric 26(2017): 619-629. DOI: 10.3390/diagnostics15162117

Urbanek Z, Zielinski U, et al. "Weed Seedbank Prediction From Historical Management Records: a field trial". Agric Syst 28(2020): 630-641. DOI: 10.4103/jrpp.jrpp_20_65

Vasquez A, Alvez V, et al. "Weed Seedbank Prediction From Historical Management Records: a systematic review". Field Crops Res 30(2023): 641-653. DOI: 10.3389/fdgth.2026.1763884

Wojcik H, Hendriksen W, et al. "Weed Seedbank Prediction From Historical Management Records: a on-farm evaluation". Eur J Agron 32(2014): 652-665. DOI: 10.2196/48297

Zielinski O, Ostrowski Z, et al. "Weed Seedbank Prediction From Historical Management Records: a benchmark comparison". Remote Sens Environ 34(2017): 663-677. DOI: 10.1007/s00330-025-12031-z

Andric V, Vasquez A, et al. "Weed Seedbank Prediction From Historical Management Records: a multi-season study". Biosyst Eng 36(2020): 674-680. DOI: 10.3389/fdgth.2026.1699005

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Published

2025-01-01