How do we define NUE?

The most common definition of nutrient use efficiency (NUE) is the yield of a given crop per unit available nutrient (N and P). This can be used to assess the efficiency of nutrient use of a given cropping system or farm, on an annual or multi-year basis.   
For calculation of NUE in this project, partners focussed on annual NUE.  Available N in some cases included the soil mineral N (SMN) to a depth of 90 cm in the spring of the cropping year, as well as the added fertilizer N.  In other cases, only added fertilizer N was included in the calculation.  Therefore, the formula used was either:
NUE = kg dry matter yield/kg (SMN+fertilizer N) OR NUE = kg dry matter yield/kg fertilizer N

How does plant genotype influence NUE?

Plant genotype can influence NUE due to differences in nutrient uptake (e.g. root characteristics) or nutrient utilization (e.g. maturation type; translocation efficiency). Reducing fertilizer input and breeding plants with increased NUE is currently one of the key goals of research on plant nutrition.

How does farming practice influence NUE?

There is also potential to improve NUE through agronomic innovation and best practice.  Precision farming can be used to improve the timing and rate of N application so that it coincides more closely with crop demand.  NUE of the whole crop rotation can be improved through optimizing the sequence of deep- and shallow-rooted crops, with deep rooting crops following those with shallow roots so that they can “mop up” excess nutrients that may have moved down through the soil profile below the rooting zone.  Similarly, “catch crops” following the main crop in a rotation can capture excess nutrients and retain them in an organic form for the subsequent crop.  Including legumes in crop rotations can improve the fertilizer NUE since inputs of fertilizer can be replaced with biologically fixed N. 

How does the environment influence NUE?

The environment is the third factor which influences NUE.  Environment (including soil type and local weather conditions) impacts on the potential of the crop for optimal growth, and is particularly relevant in environments where water can be limiting.  The local environment can also impact on the expression of genes, so that genotypes that display particular characteristics in one location may not perform similarly in another place.   This is often demonstrated by differences in the ranking of crop varieties when they are arranged in yield order, depending on where they are grown.

What is meant by the GxExM interaction?

A GxExM (genotype x environment x management) interaction occurs when the response of one genotype to a particular management system depends on the environment where it is grown.  To put this in simpler terms, it means that a genotype that may be the highest yielding in one location (environment) under one particular management system, may not be the highest yielding in another location or under another management system.  This interaction makes it very difficult to make broad recommendations about best practice across a range of locations and cropping systems.  Understanding the genotype by management by environment (or GxExM) interactions that affect NUE is essential if we are to develop the higher yielding, more nutrient efficient cropping systems of the future.

What are molecular markers and how can they be used to develop NUE varieties?

A molecular marker is a string or sequence of nucleic acid which makes up a segment of DNA located near the DNA sequence of a desired gene.  Molecular markers are used by plant breeders to speed up varietal development through marker-assisted selection (MAS).  This allows breeders to analyze only a tiny bit of plant tissue from a seedling to find out if that seedling contains the desired gene. If it doesn’t, the breeders can quickly move on and concentrate on analysis of another seedling, eventually working only with the plants which contain a specific trait (see www.isaaa.org for more information on these approaches).   In the NUE-CROPS project various approaches were used to identify molecular markers including classical quantitative trait loci (QTL) methods, association genetics, genetic bridging (between species) and gene expression profiling (reverse genetics).  Studies were conducted in a range of management systems and environments to capture the effects of GxExM on NUE.