The first paradigm of plant breeding involves direct selection-based phenotypic observation,
followed by predictive breeding using statistical models for quantitative traits constructed …

Harnessing cutting-edge technologies to enhance crop productivity is a pivotal goal in
modern plant breeding. Artificial intelligence (AI) is renowned for its prowess in big data …

Food systems face new climatic and socioecological challenges and farmers need a
diversity of new plant varieties to respond to these. While plant breeding is important …

Map** of environmental variables often relies on map accuracy assessment through cross-
validation with the data used for calibrating the underlying map** model. When the data …

This perspective describes the opportunities and challenges of data-driven approaches for
crop diversity management (genebanks and breeding) in the context of agricultural research …

Matching crop varieties to their target use context and user preferences is a challenge faced
by many plant breeding programs serving smallholder agriculture. Numerous participatory …

In the smallholder, low-input farming systems widespread in sub-Saharan Africa, farmers
select and propagate crop varieties based on their traditional knowledge and experience. A …

Where CGIAR breeding programs rely on the private sector for the multiplication and
distribution of improved cultivars, persistent challenges have dampened their impact on …

Societal Impact Statement Agricultural sustainability depends on the adaptation of crops to
their local environment. Smallholder farmers who save seed provide an essential …

With the prioritization of social inclusion in agricultural development, donors and research
centers have shown growing interest in gender-intentional varietal development and …