The first publication in which NAM was used to identify QTLs was authored by the Buckler lab on the genetic architecture of maize flowering time, and published in the summer of 2009 . In this groundbreaking study, the authors scored days to silking, days to anthesis, and the silking-anthesis interval for nearly one million plants, then performed single and joint stepwise regression and inclusive composite interval mapping ( ICIM ) to identify 39 QTLs explaining 89 % of the variance in days to silking and days to anthesis and 29 QTLs explaining 64 % of the variance in the silking-anthesis interval.
12.
The first publication in which NAM was used to identify QTLs was authored by the Buckler lab on the genetic architecture of maize flowering time, and published in the summer of 2009 . In this groundbreaking study, the authors scored days to silking, days to anthesis, and the silking-anthesis interval for nearly one million plants, then performed single and joint stepwise regression and inclusive composite interval mapping ( ICIM ) to identify 39 QTLs explaining 89 % of the variance in days to silking and days to anthesis and 29 QTLs explaining 64 % of the variance in the silking-anthesis interval.
13.
The first publication in which NAM was used to identify QTLs was authored by the Buckler lab on the genetic architecture of maize flowering time, and published in the summer of 2009 . In this groundbreaking study, the authors scored days to silking, days to anthesis, and the silking-anthesis interval for nearly one million plants, then performed single and joint stepwise regression and inclusive composite interval mapping ( ICIM ) to identify 39 QTLs explaining 89 % of the variance in days to silking and days to anthesis and 29 QTLs explaining 64 % of the variance in the silking-anthesis interval.
14.
The first publication in which NAM was used to identify QTLs was authored by the Buckler lab on the genetic architecture of maize flowering time, and published in the summer of 2009 . In this groundbreaking study, the authors scored days to silking, days to anthesis, and the silking-anthesis interval for nearly one million plants, then performed single and joint stepwise regression and inclusive composite interval mapping ( ICIM ) to identify 39 QTLs explaining 89 % of the variance in days to silking and days to anthesis and 29 QTLs explaining 64 % of the variance in the silking-anthesis interval.
