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Carbon‐13 Discrimination Can be Used to Evaluate Soybean Yield Variability
Author(s) -
Clay D. E.,
Clay S. A.,
Jackson J.,
Dalsted K.,
Reese C.,
Liu Z.,
Malo D. D.,
Carlson C. G.
Publication year - 2003
Publication title -
agronomy journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.752
H-Index - 131
eISSN - 1435-0645
pISSN - 0002-1962
DOI - 10.2134/agronj2003.4300
Subject(s) - yield (engineering) , summit , agronomy , environmental science , water stress , mathematics , biology , geography , physical geography , materials science , metallurgy
Diagnostic tools for assessing the cause of soybean [ Glycine max (L.) Merr.] yield variability in whole fields are needed. The objective of this study was to determine if 13 C discrimination (Δ) can be used to assess the factors responsible for soybean yield variability. Research was conducted in five eastern South Dakota fields between 1999 and 2001. Yields in the summit–shoulder areas of Brookings, Moody, South Dakota State University (SDSU), and Lovjoy were 20 to 60% less than the rest of the field. Adding water to plants growing in the summit–shoulder areas in Moody and SDSU increased yield and Δ. However, in the foot‐slope position, adding water did not impact yield or Δ. Based on the spatial relationships among protein content, yields, chlorophyll meter readings, and Δ at Moody and SDSU, (i) the reduced yields in the summit–shoulder areas most likely resulted from reduced plant vigor resulting from water stress; (ii) lower protein concentrations in summit–shoulder areas in Moody had a limited impact on Δ; and (iii) interactions among water availability, protein content, and yield can occur. In a combined analysis in the four fields where grain samples were collected at harvest (Moody, SDSU, Lovjoy, and TE80), Δ explained 62% of the total yield variability. Results from this experiment suggest that Δ can be used to help assess water stress, provided that N stress is absent. By understanding the causes of yield variability, producers will be able to make better management decisions.