کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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84736 | 158900 | 2010 | 7 صفحه PDF | دانلود رایگان |

Knowing the amount of herbage mass available on the farm (ideally measured weekly) is an important step in achieving high pasture utilization on pastoral dairy farms in New Zealand, but the information must be used in a timely manner to make efficient management decisions. However, most New Zealand dairy farmers do not measure their pastures regularly. This project aimed to develop a simple alternative, in the form of a prototype software tool (Pasture Growth Simulation Using Smalltalk, PGSUS) to predict herbage mass at an individual paddock level, which reduces (not eliminates) the requirement for physical data collection and provides more information from the measurements taken. The main data requirements are pasture herbage mass for each paddock and grazing or cutting events. A climate-driven pasture simulation model is used to predict herbage mass between intermittent pasture measurements. The pasture model contains certain empirical parameters that are fitted to the observed data for each paddock individually, using all the previous data to “train” the model. PGSUS requires daily weather data, including mean, minimum and maximum air temperature, solar radiation, rain and potential evapotranspiration. Data from the Virtual Climate Station Network (VCSN) from NIWA (National Institute of Water and Atmospheric Research Ltd., New Zealand) are used to drive the model. Preliminary testing was done on two commercial dairy farms, one in the Waikato (North Island) and the other in the Canterbury (South Island) regions of New Zealand. Up to 28 days without measurements, PGSUS estimated herbage mass with correlation of approximately 0.9 and with small bias.
Research highlights▶ A climate-driven pasture model is used to predict herbage mass on dairy farms. ▶ Four model parameters are fitted to the observed data for each paddock (learning). ▶ Climate data from the Virtual Climate Station Network are used to drive the model. ▶ Preliminary testing on two commercial dairy farms of New Zealand was satisfactory. ▶ The model estimated herbage mass with an R2 of 80% and small bias.
Journal: Computers and Electronics in Agriculture - Volume 74, Issue 1, October 2010, Pages 66–72