مدل‌سازی رشد و عملکرد گندم پاییزه در استان همدان

ﭼﻜﻴﺪه ﺑﻪ ﻣﻨﻈﻮر ﻣﺪل ﺳﺎزی ﻣﺮاﺣﻞ رﺷﺪ و ﻋﻤﻠﻜﺮد ﮔﻨﺪم ﺑﺮ اﺳﺎس آﻣﺎر ﻫﻮاﺷﻨﺎﺳﻲ اﺳﺘﺎن ﻫﻤﺪان (دﻣﺎی ﺣﺪاﻗﻞ، دﻣﺎی ﺣﺪاﻛﺜﺮ، ﻣﻘﺪار ﺗﺎﺑﺶ و ﻣﻴﺰان ﺑﺎرﻧﺪﮔﻲ) ﺑﺎ اﺳﺘﻔﺎده از زﻳﺮ ﻣﺪلﻫﺎی ﻣﺮﺑﻮط ﺑﻪ ﻓﻨﻮﻟﻮژی، ﺗﻮﻟﻴﺪ و ﺗﻮزﻳﻊ ﻣﺎده ﺧﺸﻚ، ﺗﻐﻴﻴﺮات ﺳﻄﺢ ﺑﺮگ در ﮔﻴﺎه ﮔﻨﺪم ﻣﻄﺎﻟﻌﻪ ای در داﻧﺸﻜﺪه ﻛﺸﺎورزی داﻧﺸﮕﺎه وﻟﻴﻌﺼﺮ (ﻋﺞ) رﻓﺴﻨﺠﺎن در ﺑﻬﺎر ﺳﺎل 1394 ﺻﻮرت ﮔﺮﻓﺖ ﭘﺎراﻣﺘﺮﻫﺎی زﻳﺮ ﻣﺪل ﻣﺬﻛﻮر ﺑﺎ اﺳﺘﻔﺎده از داده ﻫﺎی ﻣﺮﺑﻮط ﺑﻪ ﭘﮋوﻫﺶ ﻫﺎی ﺻﻮرت ﮔﺮﻓﺘﻪ در اﻳﺮان و ﺳﺎﻳﺮ ﻛﺸﻮرﻫﺎ ﺑﺮآورد ﮔﺮدﻳﺪ. ﺑﺎ اﺳﺘﻔﺎده از ﻣﺪل ﻣﺬﻛﻮر ﺗﻐﻴﻴﺮات روزاﻧﻪ ﻣﺮﺑﻮط ﺑﻪ ﻓﻨﻮﻟﻮژی،ﻣﺎده ﺧﺸﻚ ﻛﻠﻮ ﺷﺎﺧﺺ ﺑﺮداﺷﺖ ﻣﺤﺎﺳﺒﻪ ﺷﺪ ﺳﭙﺲ ﻋﻤﻠﻜﺮد در ﭘﺎﻳﺎن ﻓﺼﻞ رﺷﺪ ﭘﻴﺶ ﺑﻴﻨﻲ ﮔﺮدﻳﺪ. ﻳﻜﻲ از ﻣﻌﻴﺎرﻫﺎی ارزﻳﺎﺑﻲ ﻣﺪل، ﻣﻘﺎﻳﺴﻪ ضرایب رگرسیون خطی بین عملکرد مشاهده شده و پیش بینی شده ( b=0.90±0.67 و a=0.73±0.10) با ضرایب خط 1:1 که (0و1) ﻣﻲ ﺑﺎﺷﺪ. در ﺧﺼﻮص ﺿﺮﻳﺐ ﺗﻐﻴﻴﺮات ﻣﺮﺑﻮط ﺑﻪ ﻋﻤﻠﻜﺮد داﻧﻪ ﭘﻴﺶ ﺑﻴﻨﻲ ﺷﺪه و ﻣﺸﺎﻫﺪه ﺷﺪه (7/28=cv) دﻗﺖ ﻣﺪل ﺑﺴﻴﺎر ﺑﺎﻻ ﺑﻮده ﺑﻪ ﮔﻮﻧﻪ ای ﻛﻪ در آزﻣﺎﻳﺸﺎت ﻣﺰرﻋﻪ ای ﺣﺪ ﻣﺠﺎز ﺑﺮای ﺿﺮﻳﺐ ﺗﻐﻴﻴﺮات 20 ﺗﺎ 25 ﻣﻲ ﺑﺎﺷﺪ. ﻣﻘﺪار r2 ﺑﺮای ﻋﻤﻠﻜﺮد داﻧﻪ ﺑﺮاﺑﺮ ﺑﺎ0/81 ﺑﻮده ﻛﻪ اﻳﻦ اﻣﺮ ﺑﻴﺎﻧﮕﺮ اﻳﻦ اﺳﺖ ﻛﻪ ﺑﻪ اﺣﺘﻤﺎل 81 درﺻﺪ داده ﻫﺎی ﭘﻴﺶ ﺑﻴﻨﻲ ﺷﺪه ﺑﺎ داده ﻫﺎی ﻣﺸﺎﻫﺪه ﺷﺪه ﻫﻤﺨﻮاﻧﻲ دارﻧﺪ. از دﻳﮕﺮ آﻣﺎره ﻫﺎﻳﻲ ﻛﻪ ﺑﺮای ارزﻳﺎﺑﻲ دﻗﺖ ﻣﺪل اﺳﺘﻔﺎده ﻣﻲ ﮔﺮدد، ﺟﺬر ﻣﻴﺎﻧﮕﻴﻦ ﻣﺮﺑﻌﺎت ﺧﻄﺎ (rmse) ﻣﻲ ﺑﺎﺷﺪ ﻛﻪ در ﻣﻮرد ﻋﻤﻠﻜﺮد داﻧﻪ 0/43 ﺑﻮد ﻛﻪ ﻧﺸﺎن دﻫﻨﺪه دﻗﺖ ﺑﺎﻻی ﻣﺪل در ﭘﻴﺶ ﺑﻴﻨﻲ ﻋﻤﻠﻜﺮد اﺳﺖ. ﻧﺘﺎﻳﺞ ﻧﺸﺎن ﻣﻲ دﻫﺪ ﻛﻪ داﻣﻨﻪ ﺗﻐﻴﻴﺮات ﻋﻤﻠﻜﺮد داﻧﻪ ﮔﻨﺪم ﺑﺮای داده ﻫﺎی ﻣﺸﺎﻫﺪه ﺷﺪه ﺑﻴﻦ 4/08 ﺗﻦ ﺗﺎ 8/01 ﺗﻦ در ﻫﻜﺘﺎر و ﻣﻴﺎﻧﮕﻴﻦ داده ﻫﺎ 6/09 ﺗﻦ ﺑﻮد و ﺑﺮای داده ﻫﺎی ﭘﻴﺶ ﺑﻴﻨﻲ ﺷﺪه داﻣﻨﻪ ﺗﻐﻴﻴﺮات ﻋﻤﻠﻜﺮد ﺑﻴﻦ 4/08 ﺗﺎ 7/59 ﺗﻦ و ﻣﻴﺎﻧﮕﻴﻦ آﻧﻬﺎ 5/53 ﺗﻦ در ﻫﻜﺘﺎر ﺑﻮد.

Modeling growth and yield of winter wheat in Hamadan province

To prediction growth and yield of crops should be studied phonological sub models, production and distribution of dry matter and soil water balance. This study was conducted to predict the yield of wheat on weather conditions in Hamedan. model parameters for each sub model were estimated by using data from different sowing date in the years from 1982 to 2002 in Hamadan and data from other researchers in other parts. According to the province meteorological data (minimum temperature, maximum temperature, irradiance and rainfall) and by using the following sub models of phenology, production and distribution of dry matter was calculated changes of growth and yield. And yield of wheat crop yield was predicted at the end of the growing season. Variations of grain yield was observed between 4.08 to 8.01 ton per hectare and the average data was 6.09 tons and for prediction data Range of yield Variations was between 4.08 to 7.59 ton per hectare and that average was 5.53 ton per hectare that all of the them Simulated yield had a good correspond with the observed yield. Thus, according to the ability to appropriate the model to simulate phenological stages of wheat, Could be use it as a convenient tool for better management planning and wheat fields as well as a decision support system used in Hamedan.