Sensitivity analysis of wheat yield based on growing degree days in different growth stages: Application of machine learning approach enhanced by grey systems theory

Author:

Zhou Jincheng,Wang Dan,Nezhad kheirollah Sayna,Maroufpoor SamanORCID,Band Shahab S.

Publisher

Elsevier BV

Subject

Horticulture,Computer Science Applications,Agronomy and Crop Science,Forestry

Reference77 articles.

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2. Allen, R.G., Pereira, L.S., Raes, D., Smith, M., 1998. FAO Irrigation and drainage paper No. 56. Rome: Food and Agriculture Organization of the United Nations 56, e156.

3. Predicting average regional yield and production of wheat in the Argentine Pampas by an artificial neural network approach;Alvarez;Eur. J. Agron.,2009

4. Wheat Yield Prediction based on Sentinel-2, Regression and Machine Learning Models in Hamedan, Iran;Ashourloo;Scientia Iranica.,2022

5. Artificial intelligence approach to estimating rice yield;Babaee;Irrig. Drain.,2021

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