1 Citation 180 Views 11 Downloads
Studies characterizing the effect of a century of plant breeding on
physiological traits are highly needed to identify candidate traits for
future improvement in maize (Zea mays L.). A global evaluation of kernel
weight progress over time requires the assembly of large and reliable data
documenting genetic improvements in this trait across commercial breeding
programs in different regions. We compiled a global dataset of yield and
yield components from 34 published and unpublished studies comparing two
or more maize cultivars from different decades of commercial release under
field conditions. The dataset includes 750 entries of kernel weight data
(requirement to be included in the systematic review), of which 642 and
666 include data entries of grain yield and kernel number, respectively.
We also extracted the metadata describing experimental site information,
agronomic management practices, and genotypic information. This dataset
can be useful to identify trends of yield improvement across management
conditions, with proper consideration of the trade-off between kernel
number and kernel weight in maize.
180 views reported since publication in 2021.