Reviewing the essential roles of remote phenotyping, GWAS and explainable AI in practical marker-assisted selection for drought-tolerant winter wheat breeding.

Marker-assisted selection (MAS) plays a crucial role in crop breeding improving the speed and precision of conventional breeding programmes by quickly and reliably identifying and selecting plants with desired traits. However, the efficacy of MAS depends on several prerequisites, with precise phenotyping being a key aspect of any plant breeding programme. Recent advancements in high-throughput remote phenotyping, facilitated by unmanned aerial vehicles coupled to machine learning, offer a non-destructive and efficient alternative to traditional, time-consuming, and labour-intensive methods. Furthermore, MAS relies on knowledge of marker-trait associations, commonly obtained through genome-wide association studies (GWAS), to understand complex traits such as drought tolerance, including yield components and phenology. However, GWAS has limitations that artificial intelligence (AI) has been shown to partially overcome. Additionally, AI and its explainable variants, which ensure transparency and interpretability, are increasingly being used as recognised problem-solving tools throughout the breeding process. Given these rapid technological advancements, this review provides an overview of state-of-the-art methods and processes underlying each MAS, from phenotyping, genotyping and association analyses to the integration of explainable AI along the entire workflow. In this context, we specifically address the challenges and importance of breeding winter wheat for greater drought tolerance with stable yields, as regional droughts during critical developmental stages pose a threat to winter wheat production. Finally, we explore the transition from scientific progress to practical implementation and discuss ways to bridge the gap between cutting-edge developments and breeders, expediting MAS-based winter wheat breeding for drought tolerance.

Effect of Two Seeding Rates on Nitrogen Yield and Nitrogen Fixation of Winter and Spring Faba Bean.

Faba bean (Vicia faba L. minor) is an important grain legume and is widely used as food and feed. It is traditionally used as a spring crop in Central European cropping systems. There is increasing interest in winter faba bean due to a higher yield potential, but limited knowledge of nitrogen (N) yields and nitrogen fixation (NFIX) exists. Therefore, the purpose of this study was to compare N concentrations, N yield of plant fractions, soil mineral N (SMN) and SMN sparing in the soil after harvest, NFIX and N balance of two winter faba bean varieties (Diva and Hiverna) to those of a spring faba bean (Alexia) using two seeding rates (25 versus 50 germinable seeds m-2) in a two-year field experiment under Pannonian climate conditions in eastern Austria. The winter faba bean varieties had higher N yields and NFIX, not only due to higher biomass yields, but also due to higher N concentrations and a higher percentage of N derived from atmosphere in the biomass. Conversely, the soil mineral N after harvest was lower compared to the spring faba bean. All treatments had a negative N balance due to higher grain N yield than NFIX. Winter faba beans left higher amounts of biologically-fixed N in residues for the subsequent crop, whereas spring faba bean left more SMN. Winter faba bean varieties obtained good results with both seeding rates, whereas the grain yield and the grain N yield of Alexia tended to higher with the higher seeding rate.