USE OF MULTIPLE REGRESSION ANALYSIS AND LINEAR EQUATIONS TO PREDICT SOIL PRODUCTIVITY.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A systematic method was developed, supported by actual yield measurements to rank soils based on their productivity. Soil productivity functions in the form of linear equations with coefficients generated from multiple regression analyses were developed from experimental research plot areas. Hay yields under a high level of management were collected along with climate data. The soils at each of the eight plot areas were mapped, described, sampled, characterized, classified, and interpreted. Five parameters were identified which account for 56% of the yield variation. In descending order of significance, these factors were: (1) rainfall-soil storage, (2) effective drainage class, (3) organic carbon, (4) temperature, and (5) sum of bases. For most soils in the study, soil erosion would result in a significant reduction in water storage capacity and in a lower organic carbon content which reduces hay yields and soil productivity. (Author abstract. )

Original languageEnglish (US)
Title of host publicationASAE Publication
PublisherASAE
Number of pages1
ISBN (Print)0916150690
StatePublished - Jan 1 1985

Publication series

NameASAE Publication

ASJC Scopus subject areas

  • Engineering(all)

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