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This article in AJ

  1. Vol. 71 No. 2, p. 251-256
     
    Received: Feb 18, 1978
    Published: Mar, 1979


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doi:10.2134/agronj1979.00021962007100020009x

A Model for Predicting Soybean Yields from Climatic Data1

  1. R. W. Hill,
  2. D. R. Johnson and
  3. K. H. Ryan2

Abstract

Abstract

The single most important factor that influences soybean (Glycine max (L.) Merr.) yields from one location to another, or from one year to the next, is moisture availability. A better understanding of how water influences yields is essential for maximizing yields through water management practices. The objective of this study was to develop a model that determines soybean yield as a function of moisture availability during four periods of growth.

Data inputs include the amount of soil water in storage at the beginning of the season, available soil water storage capacity for the root zone, and daily values of rainfall, irrigation, maximum and minimum temperatures, and specific parameters for each cultivar that relate phenology to daylength and temperature.

The program predicts yield as a function of the relative transpiration during each of four growth periods: emergence to beginning flowering; beginning flowering to beginning podfill; beginning podfill to end of flowering; end of flowering to maturity.

When the program is used for scheduling irrigation, the required amount and tuning of irrigation water for any planting date is determined by simulating the effects of applying supplemental water in incremental amounts and times. The “best” resultant irrigation scheduling is indicated for any pre-selected yield level.

The program does not eliminate the need for field trials, but it can be used for identifying management practices that will maximize yields through water management or the avoidance of dry periods. Thus, field research can be concentrated on problem areas with resultant savings of time and money.

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