Projecting changes of maize yield based on regional weather parameters using Artificial Neural Network

Barka Aliyu Mivanyi 7 PAGES (2667 WORDS) Essay/Paper
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Maize is one of the largest food crop cultivated in Mubi region. It is produced annually and serves as the source of food and revenue. This work developed, an artificial neural network (ANN) model based on the data collected to forecast Maize yield in terms of weather parameters (Temperature and Rainfall). Predicted yield increased by 0.37 tons, 0.67 tons, 289.48tons and 0.17 tons in 2006, 2011, 2014 and 2015 and reduced by 0.52 tons, 0.32 tons, 5.53 tons, 15.44 tons, 0.45 tons and 0.25 tons in 2007, 2008, 2009, 2010, 2012 and 2013 respectively. It is also observed that, Maize yield is negatively correlated with temperature (r = - 0.6657) and positively correlated with rainfall (r = 0.0763). 

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APA

Barka, A (2019). Projecting changes of maize yield based on regional weather parameters using Artificial Neural Network. Afribary.com: Retrieved August 19, 2019, from https://afribary.com/works/projecting-changes-of-maize-yield-based-on-regional-weather-parameters-using-artificial-neural-network

MLA 8th

Aliyu Mivanyi, Barka. "Projecting changes of maize yield based on regional weather parameters using Artificial Neural Network" Afribary.com. Afribary.com, 01 Feb. 2019, https://afribary.com/works/projecting-changes-of-maize-yield-based-on-regional-weather-parameters-using-artificial-neural-network . Accessed 19 Aug. 2019.

MLA7

Aliyu Mivanyi, Barka. "Projecting changes of maize yield based on regional weather parameters using Artificial Neural Network". Afribary.com, Afribary.com, 01 Feb. 2019. Web. 19 Aug. 2019. < https://afribary.com/works/projecting-changes-of-maize-yield-based-on-regional-weather-parameters-using-artificial-neural-network >.

Chicago

Aliyu Mivanyi, Barka. "Projecting changes of maize yield based on regional weather parameters using Artificial Neural Network" Afribary.com (2019). Accessed August 19, 2019. https://afribary.com/works/projecting-changes-of-maize-yield-based-on-regional-weather-parameters-using-artificial-neural-network