Soil-sampling issues for precision management of crop production

Glen C. Rains, Daniel L. Thomas, George Vellidis

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

A study to examine soil-sampling issues for adequate representation of soil property variation in precision agriculture was conducted on a 26-ha farm growing cotton under a center-pivot irrigation system. Proper sampling depth, appropriate representation of field variability and laboratory-to-laboratory variances were examined. Sampling depth significantly affected soil sample test results of phosphorous and pH when comparing sample depths of 7.5 and 15 cm, while potassium levels were not significantly affected. The field was divided into a grid of 31 points and seven management zones. Recommended application of phosphate, potash and lime were substantially different when comparing zone and grid, field delineation. When soil sample test results from two laboratories were compared, there was a significant difference in measured potassium, phosphorous, and pH levels. Each laboratory also used different criteria for developing recommended rates to meet yield goals. Consequently, laboratory choice, depth of soil sample, and field delineation all affected the resulting recommended application rates and could result in poor precision management decisions. Cotton yields were measured with a yield monitor and used to compare yield goals to application rates. There was not an evident correlation between additional fertilizer and increased yield. It was suggested that variable yield goals might also be an efficient way of utilizing the field strengths when making application recommendations.

Original languageEnglish
Pages (from-to)769-775
Number of pages7
JournalApplied Engineering in Agriculture
Volume17
Issue number6
Publication statusPublished - Nov 1 2001

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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  • Cite this

    Rains, G. C., Thomas, D. L., & Vellidis, G. (2001). Soil-sampling issues for precision management of crop production. Applied Engineering in Agriculture, 17(6), 769-775.