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Copper deficiencies have been observed in a number of crops grown on both organic and mineral soils in the Atlantic Coastal Plain. In order to recommend fertilization correctly, soil test calibrations are needed for the extractants used in the region. Soybeans (Glycine max), corn (Zea mays), and wheat (Triticum aestivum) were grown in the greenhouse on 15 soils fertilized with Cu at several rates. Percent maximum yield for the plant growth on each untreated soil was calculated from the dry matter produced. Four soil extractants were used: Double acid (DA); Mehlich‐Bowling (MB); Ammonium bicarbonate‐DTPA (AB); and Mehlich‐3 (M3). Percent maximum yield was expressed as a function of Cu released from the untreated soils by each extractant with a linear plateau model. The extractants performed similarly in explaining plant response, with each accounting for about 70% of the variation. The soil critical levels, determined by the junction of the response and the plateau portions of the surface, for DA, MB, AB, and M3 were similar among crops and averaged 0.26, 0.62, 0.53, and 0.37 mg L−1 Cu, respectively. Wheat and soybeans were also grown in the field on seven soils with two rates of Cu. Grain yields of the two crops were related to MB extractable Cu with the Cate‐Nelson method, which indicated a critical level of 0.70 mg L−1. Critical whole plant and leaf Cu concentrations were also determined. The critical whole plant Cu concentrations for soybeans, corn, and wheat, each grown 5 weeks in the greenhouse, were 3.8, 1.8, and 3.8 mg kg−1, respectively. Deficiency symptoms developed on corn and wheat at slightly lower values, 1.5 and 2.9 mg kg−1, respectively. In the field, the critical leaf concentrations at early flowering were 6 mg kg−1 for soybeans and 4 mg kg−1 for wheat.

<p>The prediction of national soybean yield and production could be improved its accuracy by integrating a simulation model and Geographic Information Systems (GIS). The objective of this research was to integrate a simulation model with a GIS, to predict the potential yield and production of soybean in the soybean production centers of East Java. This study was conducted from December 2013 till May 2014. The approach used in this study was a systems approach using a simulation model as solution to the problem. The model is SUCROS.SIM (Simple Universal Crops Growth Simulator), which was written using Powersim software and Spreadsheet in order to be fully integrated with GIS. The initial phase of the integration process between SUCROS.SIM and GIS are as follows (a) model validation, using input data of soybean plant assimilate partitioning, (b) climatic data (solar radiation, maximum and minimum temperatures) collected from the climatological station (BMKG) Karangploso Malang and (c) observation data of soybean yields of two varieties (Wilis and Argomulyo) at Muneng Experiment Station. It was found that the coefficients of determination of simulation model of soybean yield potential (R2) range from 0.945-0.992 and RMSE (Root Mean Square Error) values range from 0.11 to 0.25 t/ha. The average of soybean yield potential and production in 2012 at soybean production centers of East Java were 1.94 t/ha and 293,459 ton, respectively. The conclusion is SUCROS.SIM valid to be integrated with GIS.</p>