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Intensive field phenotyping of maize (Zea mays L.) root crowns identifies phenes and phene integration associated with plant growth and nitrogen acquisition.

York LM, Lynch JP - J. Exp. Bot. (2015)

Bottom Line: Root phenes from both older and younger whorls of nodal roots contributed to variation in shoot mass and N uptake.The additive integration of root phenes accounted for 70% of the variation observed in shoot mass in low N soil.These results demonstrate the utility of intensive phenotyping of mature root systems, as well as the importance of phene integration in soil resource acquisition.

View Article: PubMed Central - PubMed

Affiliation: Department of Plant Science, The Pennsylvania State University, University Park, PA 16802, USA Ecology Graduate Program, The Pennsylvania State University, University Park, PA 16802, USA.

No MeSH data available.


Related in: MedlinePlus

Multiple panels show the effect of the most significant and explanatory phenes from all whorls on total shoot mass in low nitrogen plots after stepwise multiple linear regression. (A–F) The relationship of the following phenes to total shoot mass: LRBD.1, NRGA,3, NRGA.4, DTB.4, NRGA.5, and NO.5. Abbreviations are as given in Table 1, and the appended number identifies the whorl in which the phene was measured. (G) Fitted values are calculated from the linear combinations of the above phenes using the coefficients determined by multiple linear regression. (This figure is available in colour at JXB online.)
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Figure 5: Multiple panels show the effect of the most significant and explanatory phenes from all whorls on total shoot mass in low nitrogen plots after stepwise multiple linear regression. (A–F) The relationship of the following phenes to total shoot mass: LRBD.1, NRGA,3, NRGA.4, DTB.4, NRGA.5, and NO.5. Abbreviations are as given in Table 1, and the appended number identifies the whorl in which the phene was measured. (G) Fitted values are calculated from the linear combinations of the above phenes using the coefficients determined by multiple linear regression. (This figure is available in colour at JXB online.)

Mentions: In LN, linear regression of all root phenes from all whorls against shoot mass identified 24 phenes with significant relationships. Stepwise regression of the most significant root phenes of different whorls in LN, and not including stem widths, revealed a model containing +LRBD.1, +NRGA.3, +NRGA.4, +DTB.4, +NRGA.5, and +NO.5 (numerical suffix denotes the node position, + and – indicating positive and negative relationships, respectively) as the most parsimonious model which accounted for 69% of the variation in shoot mass (Fig. 5). In HN, linear regression of all root phenes from all whorls against shoot mass identified 22 phenes with regression P-values <0.1. Stepwise regression of the most significant root phenes of different whorls in HN, and not including stem widths, revealed a model containing +LRD.1, –NRGA.2, +LRL.4, and +LRL.5 as the most parsimonious model which accounted for 49% of the variation in shoot mass (Fig. 6). In LN, a multiple regression model including the nodal occupancies of all whorls explained 34% of shoot mass variation, while a regression model with total nodal root number explained 22%. In HN, neither the multiple regression model of all whorl occupancies nor the regression model with NRN were significant. Percentage reduction in shoot mass was calculated for every genotype and block combination, then all root phenes were regressed, which identified 12 root phenes with regression P-values <0.1. Stepwise regression of these root phenes identified –NRGA.4, –NRD.5, and –NRN as the most parsimonious model, explaining 33% of the variation in percentage reduction in shoot mass (P<0.01).


Intensive field phenotyping of maize (Zea mays L.) root crowns identifies phenes and phene integration associated with plant growth and nitrogen acquisition.

York LM, Lynch JP - J. Exp. Bot. (2015)

Multiple panels show the effect of the most significant and explanatory phenes from all whorls on total shoot mass in low nitrogen plots after stepwise multiple linear regression. (A–F) The relationship of the following phenes to total shoot mass: LRBD.1, NRGA,3, NRGA.4, DTB.4, NRGA.5, and NO.5. Abbreviations are as given in Table 1, and the appended number identifies the whorl in which the phene was measured. (G) Fitted values are calculated from the linear combinations of the above phenes using the coefficients determined by multiple linear regression. (This figure is available in colour at JXB online.)
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4585417&req=5

Figure 5: Multiple panels show the effect of the most significant and explanatory phenes from all whorls on total shoot mass in low nitrogen plots after stepwise multiple linear regression. (A–F) The relationship of the following phenes to total shoot mass: LRBD.1, NRGA,3, NRGA.4, DTB.4, NRGA.5, and NO.5. Abbreviations are as given in Table 1, and the appended number identifies the whorl in which the phene was measured. (G) Fitted values are calculated from the linear combinations of the above phenes using the coefficients determined by multiple linear regression. (This figure is available in colour at JXB online.)
Mentions: In LN, linear regression of all root phenes from all whorls against shoot mass identified 24 phenes with significant relationships. Stepwise regression of the most significant root phenes of different whorls in LN, and not including stem widths, revealed a model containing +LRBD.1, +NRGA.3, +NRGA.4, +DTB.4, +NRGA.5, and +NO.5 (numerical suffix denotes the node position, + and – indicating positive and negative relationships, respectively) as the most parsimonious model which accounted for 69% of the variation in shoot mass (Fig. 5). In HN, linear regression of all root phenes from all whorls against shoot mass identified 22 phenes with regression P-values <0.1. Stepwise regression of the most significant root phenes of different whorls in HN, and not including stem widths, revealed a model containing +LRD.1, –NRGA.2, +LRL.4, and +LRL.5 as the most parsimonious model which accounted for 49% of the variation in shoot mass (Fig. 6). In LN, a multiple regression model including the nodal occupancies of all whorls explained 34% of shoot mass variation, while a regression model with total nodal root number explained 22%. In HN, neither the multiple regression model of all whorl occupancies nor the regression model with NRN were significant. Percentage reduction in shoot mass was calculated for every genotype and block combination, then all root phenes were regressed, which identified 12 root phenes with regression P-values <0.1. Stepwise regression of these root phenes identified –NRGA.4, –NRD.5, and –NRN as the most parsimonious model, explaining 33% of the variation in percentage reduction in shoot mass (P<0.01).

Bottom Line: Root phenes from both older and younger whorls of nodal roots contributed to variation in shoot mass and N uptake.The additive integration of root phenes accounted for 70% of the variation observed in shoot mass in low N soil.These results demonstrate the utility of intensive phenotyping of mature root systems, as well as the importance of phene integration in soil resource acquisition.

View Article: PubMed Central - PubMed

Affiliation: Department of Plant Science, The Pennsylvania State University, University Park, PA 16802, USA Ecology Graduate Program, The Pennsylvania State University, University Park, PA 16802, USA.

No MeSH data available.


Related in: MedlinePlus