Model-based analysis of skill oriented labour management in a multi-operations and multiworker static cut rose cultivation system

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Worldwide competitive challenges urge growers to further improve operational performance. In this paper, the objective ‘model-based analysis and improvement of the operation of horticultural production systems’ was narrowed to ranking simulated labour management scenarios in a multi-operations and multi-worker static cut-rose cultivation system. Eight scenarios with worker skill as a central theme were simulated including a practical labour management scenario applied by a Dutch cut-rose grower. The GWorkS-model was prepared for simulation of disbudding and bending in addition to harvest, three crop operations representing over 90% of crop-bound labour time, as well as for full scale simulation of the greenhouse using all workers and equipment. The sub-models on disbudding and bending were verified using data acquired in practice. Both processes were reproduced accurately. The model study on work scenarios showed that labour organisation choices might yield up to 5 s per harvested rose difference in total labour time for harvest, bending and disbudding between the best and worst scenario, which is equivalent to 7.1 € m-2 labour costs difference per year. Scenarios pointed out that working with low skilled, low paid workers is not effective. Specialised workers were most time effective, -17.5% compared to the reference, but overall a permanent team of skilled generalists ranked best in a multi-factorial assessment. Reduced crop operation diversity per day improved labour organisational outputs but ranked almost the same as the reference. The reference scenario was outranked by 5 scenarios. Overall, the GWorkS-model provided clear answers to research questions using the full complexity of crop operations.
Original languageEnglish
Pages (from-to)87-102
JournalBiosystems Engineering
Issue numberJuly
Publication statusPublished - 2015


  • discrete-event simulation
  • harvest operations


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