Fertiliser nitrogen use in Australia has increased from 35 Gg N in 1961 to 972 Gg N in 2002, and most of the nitrogen is used for growing cereals. However, the nitrogen is not used efficiently, and wheat plants, for example, assimilated only 41% of the nitrogen applied. This review confirms that the efficiency of fertiliser nitrogen can be improved through management practices which increase the crop’s ability to compete with loss processes. However, the results of the review suggest that management practices alone will not prevent all losses (e.g. by denitrification), and it may be necessary to use enhanced efficiency fertilisers, such as controlled release products, and urease and nitrification inhibitors, to obtain a marked improvement in efficiency. Some of these products (e.g. nitrification inhibitors) when used in Australian agriculture have increased yield or reduced nitrogen loss in irrigated wheat, maize and cotton, and flooded rice, but most of the information concerning the use of enhanced efficiency fertilisers to reduce nitrogen loss to the environment has come from other countries. The potential role of enhanced efficiency fertilisers to increase yield in the various agricultural industries and prevent contamination of the environment in Australia is discussed.
Using NIR and NMR predictions of quality traits overcomes a major barrier for the application of genomic selection to accelerate improvement in grain end-use quality traits of wheat. Grain end-use quality traits are among the most important in wheat breeding. These traits are difficult to breed for, as their assays require flour quantities only obtainable late in the breeding cycle, and are expensive. These traits are therefore an ideal target for genomic selection. However, large reference populations are required for accurate genomic predictions, which are challenging to assemble for these traits for the same reasons they are challenging to breed for. Here, we use predictions of end-use quality derived from near infrared (NIR) or nuclear magnetic resonance (NMR), that require very small amounts of flour, as well as end-use quality measured by industry standard assay in a subset of accessions, in a multi-trait approach for genomic prediction. The NIR and NMR predictions were derived for 19 end-use quality traits in 398 accessions, and were then assayed in 2420 diverse wheat accessions. The accessions were grown out in multiple locations and multiple years, and were genotyped for 51208 SNP. Incorporating NIR and NMR phenotypes in the multi-trait approach increased the accuracy of genomic prediction for most quality traits. The accuracy ranged from 0 to 0.47 before the addition of the NIR/NMR data, while after these data were added, it ranged from 0 to 0.69. Genomic predictions were reasonably robust across locations and years for most traits. Using NIR and NMR predictions of quality traits overcomes a major barrier for the application of genomic selection for grain end-use quality traits in wheat breeding.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.