Recent technology advances in genomics, high-throughput genotyping, trait phenotyping, quantitative genetics and modelling methodologies have enabled implementation of molecular-enhanced plant breeding strategies. The commercial sector has adopted these technologies and it is iteratively refining and optimising their application to increase the scale and efficiency of plant breeding programs for a range of crops. We review examples from commercial maize breeding and discuss further advances we expect to see developed and adopted in the near future.

Field experiments tested above- and below-ground effects of anhydrous ammonia and urea fertilisers injected in bands mid-way between rows of wheat in a one-pass sowing operation. Banding led to high concentrations of ammonium that persisted in the bands, causing complex but recoverable changes to soil microorganisms, and providing a slow-release source of nitrogen for the crop. Mid-row banding is a promising method of supplying fertiliser nitrogen where continuous cropping is depleting soil reserves and where alternative application methods are inefficient or risky.

Soil salinity is on the rise, with one quarter of the global cultivated land already salinized, and the nutritionally-rich foxtail millet offers as an ideal crop for such degraded soils. In search of the best tolerant source, the salinity response of the foxtail millet core collection was assessed and the top ten grain yielding accessions under salinity were identified. These selected accessions can help in breeding for climate-smart, salinity-tolerant varieties of foxtail millet ensuring nutritional security in future.

Selenium is an essential micronutrient in human nutrition, but about 1000 million people worldwide may present Se deficiencies due to low concentrations of Se in foodstuffs. Se fertilisation of crops has demonstrated to be a suitable way to increase Se in foodstuffs, however little information is available about its effect on the quality parameters of bread-making wheat under semi-arid conditions. Se application resulted in significant increments of Se concentration in grain and flour, being grain yield and quality parameters not affected or slightly favored by Se fertilisation.

White clover competes poorly against pasture grasses for soil phosphate, which can limit its growth or require higher applications of phosphate fertilisers. Some plants created by crossing white clover with a closely related, wild species called Trifolium uniflorum were larger than white clover when grown with low phosphate supply. This indicates that hybridisation between white clover and T. uniflorum may provide a means of overcoming the existing phosphate limitations of this major pasture legume, resulting in environmental and economic benefits from reduced fertiliser use and increased clover production.

Previous studies in sand culture indicated that hybrids between white clover and Trifolium uniflorum were more tolerant of low external phosphate supply than white clover. Similar results were observed in soil, at low to intermediate phosphate levels, and there was variation among the hybrids for responses to changing soil phosphate, and root traits relevant to phosphate acquisition. This confirms that hybridisation with T. uniflorum may result in improved phosphate efficiency in white clover, potentially contributing to reduced environmental and economic costs of fertiliser use, and increased production on marginal land.”

Knowing the time of flowering in annual clovers is important because it determines farm management decision in relation to grazing, seed harvest, species selection and seed set for regeneration. In all species, autumn sown crops took longer time to flower compared to those sown in spring. The differences in flowering time suggests the suitability of gland clover for areas that dry out quickly in late spring, balansa clover for areas of wet winter and dry summer, and arrowleaf and Persian clovers for areas that receive higher spring rainfall.

A pasture growth rate (PGR) model, when used in conjunction with in-situ sensor measurements estimated the growth rate of a tall fescue pasture with an accuracy of ~2 kg DM/ha.day. The empirical light use efficiency (LUE) model was evaluated at sub-paddock scale using in-situ sensor data and replicated plots. The use of local temperature, plant canopy reflectance and relative soil moisture sensor measurements as inputs into the model means accurate pasture growth monitoring can be applied to large scale sensor networks.