Image?based high?throughput phenotyping for the estimation of persistence of perennial ryegrass ( <i>Lolium perenne</i> L.)—A review

Perennial ryegrass (Lolium perenne L.) is considered the most important pasture species in temperate agriculture, with over six million hectares of sown area Australia alone. However, perennial has poor persistence some environments because low tolerance to a range both abiotic and biotic stresses. To breed ryegrass, cultivars greater productivity may require evaluation genotypes number years. Persistence assessment breeding depends on manual ground cover estimation or counting surviving plants tillers known area. These methods are subjective labour intensive, which limit data collection large-scale programs. With rapid development sensors image processing algorithms, image-based high-throughput phenotyping (HTP) becoming commonplace major food crops. Image-based HTP approaches consist deployment wide ground-based airborne platforms analysed through pipelines. shows high potential for use programs be able reduce timeframes releasing new cultivars. Moreover, existing could further developed include precise tools traits such as senescence, botanical composition, pathogen pest resistance. In this study, we reviewed precision agriculture discussed their feasibility breeding. Although paper focuses application principles equally apply other forage species.