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Associations between field characteristics and soybean plant performance using canonical correlation analysis

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Abstract

The main objective of this study is to find associations between site characteristics (topographic, and soil physical and chemical properties) and soybean [Glycine max (L.) Merr.] plant performance (e.g. yield, canopy development) occurring at a field scale. The study took place in an Illinois production field in the 2000 and 2001 seasons. These associations were studied with canonical correlation analysis (CCA) followed by a spatial analysis of the resulting canonical variables with semivariography. The CCA discovered several significant associations between site characteristics. The first pair of canonical variables had a correlation coefficient of 0.76. The site characteristics most consistently correlated with the first pair of canonical variables were organic matter (OM) (r = 0.64 and 0.51 for the 2000 and 2001 seasons, respectively), pH (r = 0.39 and 0.51 for the 2000 and 2001 seasons, respectively), and deep electrical conductivity (ECD) (r = 0.53 and 0.49 for the 2000 and 2001 seasons, respectively). Site variables soil phosphorous (P) and soil potassium (K) were inconsistently correlated with the site characteristics canonical variable. These results indicate that site variables related to soil water retention are more consistently associated with soybean performance than site variables related to soil fertility. The plant performance characteristic most correlated with the soybean performance canonical variable were NDVIN (r = 0.76 and 0.72 for the 2000 and 2001 seasons, respectively), SPAD (r = 0.70 and 0.47 for the 2000 and 2001 seasons, respectively), and yield (r= 0.44 and 0.58 for the 2000 and 2001 seasons, respectively). The variables NDVIN, yield, ECD are obtained with sensors and thus they can be easily used at a production field scale. The common spatial structures in pairs of the canonical variables confirm the relationship between site properties and soybean performance, proving their potential in the demarcation of uniform areas within production fields. This approach can be used to explore soil plant relationships in other field studies.

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Abbreviations

Band825:

reflectance in the band between 824 and 826 nm

CCA:

canonical correlation analysis

GIS:

geographic information systems

GPS:

global positioning system

LDB:

leaf dry biomass

NIR727:

near infrared reflectance centered in 727 nm

nd R752:

Red reflectance centered in 752 nm

NIR795:

near infrared reflectance centered in 795 nm

R650:

red reflectance centered in 650 nm

NIR795:

near infrared reflectance centered in 795 nm

NIR757:

near infrared reflectance centered in 757 nm

PA:

precision agriculture

PC:

carbon concentration in plant

R650:

red reflectance in the portion of the spectrum between 630 and 680 nm

R732:

Red reflectance in the portion of the spectrum between 727 and 737 nm

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Authors and Affiliations

  1. Department of Crop Sciences, University of Illinois at Urbana-Champaign, Turner Hall 1102 S. Goodwin Ave.,, Urbana, IL, 61801, USA

    Nicolás F. Martín, Germán Bollero & Donald G. Bullock

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  1. Nicolás F. Martín
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  2. Germán Bollero
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  3. Donald G. Bullock
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Correspondence to Donald G. Bullock.

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Martín, N.F., Bollero, G. & Bullock, D.G. Associations between field characteristics and soybean plant performance using canonical correlation analysis. Plant Soil 273, 39–55 (2005). https://doi.org/10.1007/s11104-004-6639-1

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