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Improvement in regression of corn yield with plant height using relative data
Author(s) -
Yin Xinhua,
McClure M Angela,
Hayes Robert M
Publication year - 2011
Publication title -
journal of the science of food and agriculture
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.782
H-Index - 142
eISSN - 1097-0010
pISSN - 0022-5142
DOI - 10.1002/jsfa.4477
Subject(s) - yield (engineering) , linear regression , regression analysis , cropping , mathematics , approximation error , agronomy , zea mays , regression , agriculture , statistics , biology , ecology , materials science , metallurgy
BACKGROUND: The traditional approach of analyzing absolute variable data across multiple locations and/or years has drawbacks in precision agriculture. This study was conducted to evaluate the impacts of using relative yield and plant height data of corn ( Zea mays L.) on the regression of yield with plant height using linear and exponential models in a nitrogen (N) rate field trial under four cropping systems. RESULTS: The use of relative yield to replace absolute yield frequently increased the determination coefficient ( R 2 ) values in the regression of yield with plant height on datasets combined across cropping systems or/and years. Relative yield and relative plant height sometimes further enhanced the R 2 values compared with relative yield and absolute plant height. All these improvements mostly occurred when the fit of the model was not strong with absolute yield and absolute plant height or relative yield and absolute plant height. The advantages of using relative data of yield or/and plant height were similar for the two regression models. CONCLUSION: The use of relative yield or relative data of both yield and plant height may be effective in improving the regression of corn yield with plant height across multiple cropping systems/locations and years in precision agriculture. Copyright © 2011 Society of Chemical Industry