- Gaziosmanpaşa Üniversitesi Ziraat Fakültesi Dergisi
- Cilt: 40 Sayı: 2
- Estimating Corn Yield Using Statistical, Machine Learning and Deep Learning Methods
Estimating Corn Yield Using Statistical, Machine Learning and Deep Learning Methods
Authors : Cevher ÖZDEN
Pages : 74-80
Doi:10.55507/gopzfd.1320542
View : 43 | Download : 46
Publication Date : 2023-09-17
Article Type : Research
Abstract :Yield estimation is an important field of study in agriculture. Forecasting yields provides producers, consumers, traders and policymakers with important preliminary information and time to take necessary action. Corn is an important product in terms of international trade and is widely used in human and animal nutrition throughout the world. Adana produces the highest amount of corn sown both as main and secondary product in Türkiye. Therefore, in this study, corn yield was tried to be estimated by using various meteorological parameters and plant fertilizer usage amounts. For this purpose, statistical (Auto-ARIMA), machine learning (Random Forest) and deep learning (CNN, LSTM) methods were used. The study findings showed that all models used predicted maize yield highly accurately. However, the highest accuracy LSTM model estimated the yield of first corn crop.Keywords : Verim tahmini, derin öğrenme, mısır