Delivering a simple maize [Zea mays] maturity and harvest date prediction model
2001
Laurenson, M. (National Agricultural Research Center, Tsukuba, Ibaraki (Japan)) | Ninomiya, S.
This paper describes an operational implementation of a simple model to assist with maize variety selection and harvest data prediction, using personal computer (PC) relational database software. The three-stage growing-degree model uses daily weather data and any current season field observations of silking and maturity to predict physiological maturity and harvest date. Thirty years of historical data are used to estimate the expected harvest date and its variation, and explore the risk of frosts prior to crop maturity. A grain procurement company used the software over several seasons to advise its clients, and the software was extensively revised over this period. Experience with this single crop, PC-based, monolingual system has led us to embark on the development of a new multi-crop, Internet-based, multilingual system. A number of elements of the new system have been completed or prototyped. Its key concepts include the use of a mediated architecture, centralised object-oriented databases, and Internet-based mapping software.
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