Spatial variability of soil properties, corn quality and yield in two Illinois, USA fields: Implications for precision corn management

Y. Miao, D. J. Mulla, P. C. Robert

Research output: Contribution to journalArticlepeer-review

36 Scopus citations

Abstract

Better understanding of within-field spatial variability of crop quality parameters and yield are needed for precision management of crops. This study was conducted to determine the magnitude of within-field variability in soil properties, corn (Zea mays L.) quality parameters and yield and to characterize their spatial structures. Another objective was to compare the effects of hybrid on corn quality, yield, and the spatial structure of grain quality. Four Pioneer hybrids were planted side-by-side, two in each of the two study fields in eastern Illinois, USA. Coefficients of variation (CV%) for soil properties varied from 6.3 (pH) to 56.8% (soil test P). All the soil properties (except pH at Site 2) displayed well-defined spatial structures, with either strong or moderate spatial dependence. Variability in corn quality and yield (CVs < 10%) was smaller than variability in soil properties. Most quality parameters examined at Site 1 exhibited either moderate or strong spatial dependence, except that corn oil (both hybrids), kernel roundness and weight (hybrid 33Y18) did not show any spatial correlation. Hybrid 33G26 had significantly higher yield and quality for most quality parameters than 33Y18 at Site 1. At Site 2, hybrid 34W67 was significantly lower in oil and protein content, length, roundness and vitreousness than 34K77, but higher in other quality parameters. Significant differences in spatial structures were also observed across hybrids for some corn quality parameters. We conclude that hybrid selection is an important strategy for precision management of corn for optimum yield and quality.

Original languageEnglish (US)
Pages (from-to)5-20
Number of pages16
JournalPrecision Agriculture
Volume7
Issue number1
DOIs
StatePublished - Mar 2006

Keywords

  • Corn quality
  • Geostatistical analysis
  • Hybrid difference
  • Precision crop management
  • Spatial variability

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