Soil property predictors of soybean yield using yield contest sites. Issue 6 (2nd November 2017)
- Record Type:
- Journal Article
- Title:
- Soil property predictors of soybean yield using yield contest sites. Issue 6 (2nd November 2017)
- Main Title:
- Soil property predictors of soybean yield using yield contest sites
- Authors:
- Adams, Taylor C.
Brye, Kristofor R.
Purcell, Larry C.
Ross, Jeremy
Gbur, Edward E.
Savin, Mary C. - Abstract:
- ABSTRACT: State yield contests offer a unique opportunity to examine the high end of crop productivity. Yield-contest-entered and average-yielding areas on the same or a similar soil can provide large yield and soil property variations to better examine the relationships among various near-surface soil properties and soybean ( Glycine max L. [Merr.]) yield. The objective of this study was to evaluate the relationships among a suite of near-surface soil properties and soybean yield across average- and high-yield areas using state yield-contest sites. Multiple regression analyses were conducted to evaluate best-fit relationships among various soil physical, chemical, and biological properties and yield separately for average- and high-yielding areas and for data combined across yield areas. Soybean yield variation was most explained for the high-yield-area dataset ( R 2 = 73%) and less explained for the average-yield-area ( R 2 = 51%) and the combined ( R 2 = 50%) datasets. Extractable soil Ca and S explained the largest proportion of yield variation (37% and 31% of total sum of squares) in the high-yield setting and both were inversely related to yield. A better understanding of the soil environment may be a key component of more frequent attainment of the 6270 kg ha −1 (100 bu acre −1 ) soybean yield mark. Additional soil properties, beyond those evaluated in this study, may need to be included for a more complete understanding of the soil environment that is associatedABSTRACT: State yield contests offer a unique opportunity to examine the high end of crop productivity. Yield-contest-entered and average-yielding areas on the same or a similar soil can provide large yield and soil property variations to better examine the relationships among various near-surface soil properties and soybean ( Glycine max L. [Merr.]) yield. The objective of this study was to evaluate the relationships among a suite of near-surface soil properties and soybean yield across average- and high-yield areas using state yield-contest sites. Multiple regression analyses were conducted to evaluate best-fit relationships among various soil physical, chemical, and biological properties and yield separately for average- and high-yielding areas and for data combined across yield areas. Soybean yield variation was most explained for the high-yield-area dataset ( R 2 = 73%) and less explained for the average-yield-area ( R 2 = 51%) and the combined ( R 2 = 50%) datasets. Extractable soil Ca and S explained the largest proportion of yield variation (37% and 31% of total sum of squares) in the high-yield setting and both were inversely related to yield. A better understanding of the soil environment may be a key component of more frequent attainment of the 6270 kg ha −1 (100 bu acre −1 ) soybean yield mark. Additional soil properties, beyond those evaluated in this study, may need to be included for a more complete understanding of the soil environment that is associated with high-yield soybean production. … (more)
- Is Part Of:
- Journal of crop improvement. Volume 31:Issue 6(2017)
- Journal:
- Journal of crop improvement
- Issue:
- Volume 31:Issue 6(2017)
- Issue Display:
- Volume 31, Issue 6 (2017)
- Year:
- 2017
- Volume:
- 31
- Issue:
- 6
- Issue Sort Value:
- 2017-0031-0006-0000
- Page Start:
- 816
- Page End:
- 829
- Publication Date:
- 2017-11-02
- Subjects:
- Arkansas -- multiple regressions -- soil fertility -- soybean production -- ultra-high yields
Crop science -- Periodicals
631.5 - Journal URLs:
- http://www.informaworld.com/smpp/title~db=all~content=t792303981~tab=issueslist ↗
http://www.tandfonline.com/loi/wcim20 ↗
http://www.haworthpress.com/web/JCRIP ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/15427528.2017.1372326 ↗
- Languages:
- English
- ISSNs:
- 1542-7528
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4965.652000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 5445.xml