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study of environmental factors affecting the growth and production of barley plant by using artificial neural network technology
العناوين الأخرى
دراسة العوامل البيئية المؤثرة علي نمو و إنتاج نبات الشعير المستنبت باستخدام تقنية الشبكات العصبية الاصطناعية
المؤلفون المشاركون
Barakah, Shayma Muhammad
al-Awadi, Muhammad Nabil
Buhayri, Zaynab Husayn
Junaydi, Muhammad Abd al-Majid
المصدر
Arab Universities Journal of Agricultural Sciences
العدد
المجلد 27، العدد 3 (31 يوليو/تموز 2019)، ص ص. 1843-1851، 9ص.
الناشر
تاريخ النشر
2019-07-31
دولة النشر
مصر
عدد الصفحات
9
التخصصات الرئيسية
الموضوعات
الملخص EN
The impact of climate on crop production has vital importance.
Climate variables affect the different crops during different stages of the growth and the development.
This research aims to study the environmental factors affecting the growth and production of barley (Hordeum Sp.
, Gramineae) in a hydroponic system, to provide information to farmers and decision makers by using Artificial Neural Network (ANN) Model for production prediction.
Multilayer feed-forward ANN (fully connected) was used in supervised manner and the training method was the back-propagation algorithm by using MATLAB program.
The inputs in the ANN model of barley were: seeds density (kg/m2), lighting duration (h/day), light intensity (Lux), temperature (cº), relative humidity (% ) and growing period (days).
The outputs were: plant length (cm), yield (kg/m2), protein (% ), dry matter (% ), and conversion factor.
Results revealed that the optimal configuration for the ANN model consisted of four layers (6-25-30-5).
The hidden layers had 25 and 30 nodes in the first and second hidden layers respectively for the ANN model.
Hyperbolic tangent transfer function was employed in hidden and output layers of the ANN model.
The learning rate and the momentum parameter were 0.005 and 0.9 respectively for the ANN model.
Iterations were 10000 epochs during training process for the ANN model.
The results showed that the variation between target and predicted outputs was small while the correlation coefficient (R) was 0.99.
Also, the results revealed that the major parameters affecting on all the outputs were seeds density and the duration of the lighting followed by the other factors i.
e.
temperature (cº), relative humidity (% ), growing period (days) and light intensity (Lux).
Seeds density has a higher percent relative importance, on yield, plant length, protein (% ), DM (% ) and conversion factor equal to 22.8% , 24% , 25% , 24% and 22.8% respectively.
The developed ANN model was beneficial tool for barley production prediction.
The barley yield prediction could be helpful for farmers, decision makers and planning to manage their crop better by providing a series of recommendations about crops planting and clarifying its impact on changes to these factors under the study in order to avoid losses and reach the best benefit (maximization of yield).
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Barakah, Shayma Muhammad& al-Awadi, Muhammad Nabil& Buhayri, Zaynab Husayn& Junaydi, Muhammad Abd al-Majid. 2019. study of environmental factors affecting the growth and production of barley plant by using artificial neural network technology. Arab Universities Journal of Agricultural Sciences،Vol. 27, no. 3, pp.1843-1851.
https://search.emarefa.net/detail/BIM-999992
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Barakah, Shayma Muhammad…[et al.]. study of environmental factors affecting the growth and production of barley plant by using artificial neural network technology. Arab Universities Journal of Agricultural Sciences Vol. 27, no. 3 (2019), pp.1843-1851.
https://search.emarefa.net/detail/BIM-999992
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Barakah, Shayma Muhammad& al-Awadi, Muhammad Nabil& Buhayri, Zaynab Husayn& Junaydi, Muhammad Abd al-Majid. study of environmental factors affecting the growth and production of barley plant by using artificial neural network technology. Arab Universities Journal of Agricultural Sciences. 2019. Vol. 27, no. 3, pp.1843-1851.
https://search.emarefa.net/detail/BIM-999992
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
-
رقم السجل
BIM-999992
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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