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A Markov chain approach to crop yield forecasting

Author

Listed:
  • Matis, J. H.
  • Saito, T.
  • Grant, W. E.
  • Iwig, W. C.
  • Ritchie, J. T.

Abstract

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Suggested Citation

  • Matis, J. H. & Saito, T. & Grant, W. E. & Iwig, W. C. & Ritchie, J. T., 1985. "A Markov chain approach to crop yield forecasting," Agricultural Systems, Elsevier, vol. 18(3), pages 171-187.
    • Handle: RePEc:eee:agisys:v:18:y:1985:i:3:p:171-187
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    Cited by:

    1. Mikkel Bojesen & Hans Skov-Petersen & Morten Gylling, 2013. "Forecasting the potential of Danish biogas production: spatial representation of Markov chains," IFRO Working Paper 2013/16, University of Copenhagen, Department of Food and Resource Economics.
    2. Mkhabela, Thulasizwe S., 2004. "Estimates of the increase in milk production due to the introduction of maize silage to a dairy farm in KwaZulu-Natal: A time series approach," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 43(4), pages 1-8, December.
    3. Peace Bamurigire & Anthony Vodacek & Andras Valko & Said Rutabayiro Ngoga, 2020. "Simulation of Internet of Things Water Management for Efficient Rice Irrigation in Rwanda," Agriculture, MDPI, vol. 10(10), pages 1-12, September.
    4. GwanSeon Kim & Mehdi Nemati & Steven Buck & Nicholas Pates & Tyler Mark, 2020. "Recovering Forecast Distributions of Crop Composition: Method and Application to Kentucky Agriculture," Sustainability, MDPI, vol. 12(7), pages 1-17, April.

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