Using phenomic selection to predict hybrid values with NIR spectra measured on the parental lines: proof of concept on maize.

Phenomic selection based on parental spectra can be used to predict GCA and SCA in a sparse factorial design. Prediction approaches such as genomic selection can be game changers in hybrid breeding. They allow predicting the genetic values of hybrids without the need for their physical production.

Improvement in genomic prediction of maize with prior gene ontology information depends on traits and environmental conditions.

Classical genomic prediction approaches rely on statistical associations between traits and markers rather than their biological significance. Biologically informed selection of genomic regions can help prioritize polymorphisms by considering underlying biological processes, making prediction models robust and accurate. Gene ontology (GO) terms can be used for this purpose, and the information can be integrated into genomic prediction models through marker categorization.

High-Temperature Oxidation of NbTi-Bearing Refractory Medium- and High-Entropy Alloys.

The oxidation of six NbTi-i refractory medium- and high-entropy alloys (NbTi + Ta, NbTi + CrTa, NbTi + AlTa, NbTi + AlMo, NbTi + AlMoTa and NbTi + AlCrMo) were investigated at 1000 °C for 20 h. According to our observation, increased Cr content promoted the formation of protective CrNbO and CrO oxides in NbTi + CrTa and NbTi + AlCrMo, enhancing oxidation resistance. The addition of Al resulted in the formation of AlTi-rich oxide in NbTi + AlTa.