TY - JOUR
T1 - Simulation of harvest operations in a static rose cultivation system
AU - van 't Ooster, A.
AU - Bontsema, J.
AU - van Henten, E.
AU - Hemming, S.
PY - 2014
Y1 - 2014
N2 - Labour is the most dominant cost factor in Dutch cut-rose production. To improve crop production systems and labour management, a generic process modelling approach was developed enabling the impact of different scenarios on labour productivity to be assessed. The crop production system with crop handling processes is defined as a stochastic discrete event system. This paper demonstrates the model flexibility and transferability by adapting an existing model developed for a mobile rose production system to a model for a static growing system for cut roses. The paper describes the adaptation process. The adapted model was validated for the harvest process at a 3.6 ha production site in the Netherlands. Work scenarios were simulated to examine effects of skill, equipment, and harvest management. The model reproduces the harvest process accurately. A seven workday validation for an average skilled harvester showed a relative root mean squared error (RRMSE) under 5% for both labour time and harvest rate. A validation over 96 days for various harvesters showed a higher RRMSE, 15.2% and 13.6% for labour time and harvest rate respectively, mainly caused by the absence of model parameters for individual harvesters. The model was successfully used in scenario studies and indicated that worker skill was an important cost factor, differences associated with harvest trolley type are small, and that an extra harvest cycle per day is only feasible when compensated by product price. Overall, the generic model concept performs well for a static growing system when extended with system specific properties and process elements. (C) 2013 IAgrE. Published by Elsevier Ltd. All rights reserved.
AB - Labour is the most dominant cost factor in Dutch cut-rose production. To improve crop production systems and labour management, a generic process modelling approach was developed enabling the impact of different scenarios on labour productivity to be assessed. The crop production system with crop handling processes is defined as a stochastic discrete event system. This paper demonstrates the model flexibility and transferability by adapting an existing model developed for a mobile rose production system to a model for a static growing system for cut roses. The paper describes the adaptation process. The adapted model was validated for the harvest process at a 3.6 ha production site in the Netherlands. Work scenarios were simulated to examine effects of skill, equipment, and harvest management. The model reproduces the harvest process accurately. A seven workday validation for an average skilled harvester showed a relative root mean squared error (RRMSE) under 5% for both labour time and harvest rate. A validation over 96 days for various harvesters showed a higher RRMSE, 15.2% and 13.6% for labour time and harvest rate respectively, mainly caused by the absence of model parameters for individual harvesters. The model was successfully used in scenario studies and indicated that worker skill was an important cost factor, differences associated with harvest trolley type are small, and that an extra harvest cycle per day is only feasible when compensated by product price. Overall, the generic model concept performs well for a static growing system when extended with system specific properties and process elements. (C) 2013 IAgrE. Published by Elsevier Ltd. All rights reserved.
U2 - 10.1016/j.biosystemseng.2013.04.005
DO - 10.1016/j.biosystemseng.2013.04.005
M3 - Article
SN - 1537-5110
VL - 120
SP - 34
EP - 46
JO - Biosystems Engineering
JF - Biosystems Engineering
ER -