پیش‌بینی مرحله‌های رشد و عملکرد ذرت در همدان

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری گروه زراعت، دانشکدۀ کشاورزی، دانشگاه ولی‌عصر(عج) رفسنجان

2 استادیار گروه زراعت، دانشگاه علوم کشاورزی و منابع طبیعی گرگان

چکیده

به‌منظور مدل‌سازی مراحل رشد و عملکرد ذرت بر پایۀ آمار هواشناسی استان همدان (دمای کمینه، دمای بیشینه، میزان تابش و میزان بارندگی) با استفاده از زیر مدل­های مربوط به پدیدشناسی (فنولوژی)، تولید و توزیع مادۀ خشک، تغییرپذیری‌های سطح برگ در گیاه ذرت  بررسی‎ در دانشکدۀ کشاورزی دانشگاه ولیعصر (عج) رفسنجان در سال بهار 1394 صورت گرفت. با استفاده از مدل یادشده تغییرپذیری روزانۀ مربوط به پدیدشناسی، مادۀ خشک کل، سطح برگ محاسبه و سپس عملکرد پیش‌بینی شد. یکی از معیارهای ارزیابی مدل، مقایسۀ ضریب رگرسیون خطی بین عملکرد مشاهده‌شده و پیش‌بینی‌شده (23/0±93/0=a و 11/2± 29/0=b) با ضریب‌های خط 1:1 که (0و1) است. در زمینۀ ضریب تغییرپذیری مربوط به عملکرد دانۀ پیش‌بینی‌شده و مشاهده‌شده (13/4=CV) دقت مدل بسیار بالا بوده به‌گونه‌ای که در آزمایش‌های مزرعه‌ای حد مجاز برای ضریب تغییرپذیری 20 تا 25 است. میزان R2 برای عملکرد دانه برابر با 69/0 بوده که این امر بیانگر این است که به‌احتمال 69 درصد داده‌های پیش‌بینی‌شده با داده‌های مشاهده‌شده همخوانی دارند. از دیگر آماره‌هایی که برای ارزیابی دقت مدل استفاده می‌شود، جذر میانگین مربعات خطا (RMSE) است که در مورد عملکرد دانه 36/0 بود که نشان‌دهندۀ دقت بالای مدل در پیش‌بینی میزان عملکرد است. نتایج این بررسی نشان می‌دهد که دامنۀ تغییرپذیری عملکرد دانۀ ذرت برای داده‌های مشاهده‌شده بین 54/8 تن تا 99/9 تن در هکتار و میانگین داده‌ها 09/9 تن بود و برای داده‌های پیش‌بینی‌شده دامنۀ تغییرپذیری عملکرد بین 02/8 تا 25/9 تن و میانگین آن‌ها 75/8 تن در هکتار بود.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Predict the growth and yield of corn in Hamedan

نویسندگان [English]

  • Amir Dadrasi 1
  • Benjamin Torabi 2
1 Ph.D. Student, Department of Agronomy, Agriculture College, Vali-e-Asr University of Rafsanjan, Iran
2 Assistant of Professor, Department of Agronomy, Gorgan University of Agricultural Sciences and Natural Resources, Iran
چکیده [English]

In order to modeling of growth stages and yield of corn according to Hamedan province meteorological data (minimum and maximum temperature, radiation and rainfall) By using the sub models of phenology, production and distribution of dry matter  and leaf area changes in maize studies was conducted at the Faculty of Agriculture, University of Vali-e-Asr Rafsanjan in spring 2015. Daily changes of phenology, total dry matter and leaf area was calculated using the model and the yield was predicted. One of the criteria to evaluation of a model is Comparison between coefficients of linear regression of observed and predicted yield (b=0.29±2.11 and a=0.93±0.23) and coefficients of line 1:1 (1, 0). Accuracy of the model related to coefficient of variations of predicted and observed seed yield (CV=4.13) was very high so that in field experiments coefficient of variations limit is 20 to 25. R2 quantity of seed yield was 0.69; showing that the probability for coordination of predicted and observed data is 69 percent. The Root mean square error is the other statistics which is used to evaluation of model accuracy. The Root mean square error of seed yield was 0.36, which is evidence of accuracy of model for yield prediction. domain variation for observed and predicted data were 8.54-9.99 tones and 8.02-9.25 tons per hectare respectively and the means were 9.09 and 8.75 tones per hectare respectively.

کلیدواژه‌ها [English]

  • Corn
  • Grain yield
  • modeling
  • Phenology
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