## 1 Introduction
### Cereal Breeding
#### 1.2.1 Protein  
Malting barley is purchased from farmers and traded based on protein content and the most common way to rapidly measure content is using NIR. Until the last few years, when a farmer delivered a sample to a grain handling depot, that was the first time barley passed through an NIR. However, recent developments have seen NIR installed on grain harvesters for real time predictions of protein and moisture, coupled with yield data [4; 5]. This allows farmers on broad-acre farms to have an understanding of the protein content within and between each paddock and potentially allow the farmer to exclude high protein grain accordingly. In addition, grain data can be related to nitrogen fertilizer inputs and the amount nitrogen extracted and stored in the grain. Grain trading companies have networks of instruments across national programs to accumulate sufficient volumes for domestic and/or export markets. However, long before varieties are released, breeding programs use NIR to select for breeding lines within a protein range [6; 7; 8; 9]. New barley varieties have been through years of testing in a breeding program. Intense selection is required to ensure potential new varieties can meet expectations of the farmers and the malting and brewing industries. Structured breeding trials grown over numerous locations and years provide grain for detailed quality testing where protein content is the first screen [10]. Its importance means that protein calibrations have been reported in numerous reports (see reviews: [11; 12]). There are several Nitrogen-Hydrogen (NH) absorbance regions and the use of spectra alone can be used for selection [8; 13]. It has been shown that spectra can differ between growing regions and to a less extent underlying genetics [11; 14]. Thus with a NIR spectrophotometer with a full spectra region it could be possible to do selections for protein and other traits without needing the support of any chemistry to develop calibrations. Spectral data was used to identify genetic traits in a breeding population where important genetic regions were identified [8; 15]. Further, the use of NIR in assessing protein content in breeding, understanding the heritability of an important trait such as protein is important and it has been shown exactly that, i.e., heritability can be calculated for protein content using predicted protein data [16]. To fully understand the potential quality of breeding lines, and where protein is the key industry trait, other barley grain and malt quality traits have been correlated to protein content [6; 7; 17; 18]. The success of any infrared studies is based on precise and accurate calibrations, where most research would expect an R\({}^{2}\) of \(>\)0.95 and Root Mean Standard Error Prediction \(<\) 0.5% for protein. The early instruments had a limited number of wavelengths and calibrations were built using multiple linear regression [19], but the latest instruments have 1000 s of wavelengths using PLS, ANN and other machine learning techniques [20]. Typical analysis of barley protein content is on bulk samples with 1000 s of grains in the sample tested. However, several studies have shown NIR has the capacity to scan and predict single grains and from that data show the distribution of protein content in a sample [21; 22; 23]. These studies showed variation between single kernels within a spike of barley as well as variation in other quality parameters based on grains sorted into sub-groups of protein content. The ideal protein level for malting barley is 10% to 11% (db) but current commercial crops vary in protein content within a paddock thus the variation is delivered in bulk for processing. For optimal malting barley, high through-put predictive single-kernel sorting would deliver this ideal protein range but limitations in speed of prediction, physical sorting and extra storage negate this at the commercial scale. Protein content has been and will remain the first and key trait in any malting barley quality [24; 25; 26; 27].