کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8880219 | 1624793 | 2018 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Modeling the seed yield of Ajowan (Trachyspermum ammi L.) using artificial neural network and multiple linear regression models
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
ANNRMSEMLRMLPNSBMSESDWplant height - ارتفاع گیاهAjowan - بلهMAE - بلهMultiple linear regressions - رگرسیون خطی چندگانهRoot mean square error - ریشه میانگین خطای مربعArtificial Neural Network - شبکه عصبی مصنوعیLeaf length - طول برگSeed yield - عملکرد دانهSelection criteria - معیارهای انتخابMean Absolute Error - میانگین خطا مطلقMean Square Error - میانگین مربع خطاartificial intelligence - هوش مصنوعیshoot dry weight - وزن خشک ساقهMulti-Layer Perceptron - چند لایه ی PerceptronMedicinal plant - گیاه دارویی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علوم کشاورزی و بیولوژیک
علوم زراعت و اصلاح نباتات
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Ajowan is a medicinal plant with useful pharmaceutical compounds in its seeds. Seed yield improvement in ajowan through a better understanding of the relationship between seed yield and its components is one of the most important goals of any breeding program. In the present study, artificial neural network (ANN) along with multiple regression model (MLR) were applied to predict the seed yield of ajowan through seed yield components. According to the simple correlation analysis, four characters (number of secondary branches, shoot dry weight, number of umbellets in an inflorescence, and biological yield) were selected as input variables in both artificial neural network and multiple linear regressions models. The network with SigmoidAxon transfer function, Levenberg-Marquart learning algorithm, one hidden layer with four neurons, 1000 training epochs and with a root mean square error (RMSE) of 0.147, a mean absolute error (MAE) of 0.127 and a determination coefficient (R2) of 0.932 was selected as the final ANN model. The performance of ANN was better than MLR with a RMSE of 0.210 and a r2 of 0.792. Biological yield and shoot dry weight were the most important yield components traits that affect the seed yield of ajowan and assigned as selection criteria using both ANN and MLR models.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Industrial Crops and Products - Volume 117, July 2018, Pages 224-234
Journal: Industrial Crops and Products - Volume 117, July 2018, Pages 224-234
نویسندگان
Mohsen Niazian, Seyed Ahmad Sadat-Noori, Moslem Abdipour,