Yield prediction in banana (Musa × paradisiaca) (cv Grand Naine) by ANN models
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Authors
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R VENUGOPALAN
Principal Scientist (Agricultural Statistics), Section of Economics and Statistics, Indian Institute of Horticultural Research, Hesseraghatta Lake PO, Bangalore, Karnataka 560 089
Keywords:
ANN, Banana, Biometrical factors, SASDownloads
References
Cheng B and Titterington D M. 1994. Neural networks: A review from a statistical perspective. Statistical Science 9: 42–54. DOI: https://doi.org/10.1214/ss/1177010638
Hochachka W M, Caruana, R, Fink D Munson, A Riedewald, M Sorokina D and Kelling S. 2007. Data-mining discovery of pattern and process in ecological systems. Journal of Wildlife Management 71: 2 427–37. DOI: https://doi.org/10.2193/2006-503
Singh R K and Prajneshu. 2008. Artificial neural network methodology for modelling and forecasting maize crop yield. Agricultural Economics Research Review 21: 5–10.
Venugopalan R. 2010. Application of statistical principles for evolving crop-logging models in banana (cv Ney Poovan). Tropical Agriculture 87(1): pp 29–32.
Warner B and Misra M. 1996. Understanding neural networks as statistical tools. American Statistician 50: 284–93. DOI: https://doi.org/10.1080/00031305.1996.10473554
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