Low-cost automated biochemical phenotyping for optimised nutrient quality components in ryegrass breeding

Abstract

Quantification of forage quality is essential for the identification of elite genotypes in forage grass breeding. Perennial ryegrass is the most important temperate species for global pastoral agriculture. However, the protein content of ryegrass generally exceeds the requirements of a grazing animal, and the ratio of water soluble carbohydrate (WSC) to protein is too low for efficient protein utilisation. This results in poor nitrogen use efficiency (NUE) in the farming system by livestock, and hence limits optimal animal production. New ryegrass cultivars with optimised WSC and protein content are desirable for farming efficiencies. Several methods are available for quantification of WSC and plant protein (such as near-infrared spectroscopy [NIRS] and high performance liquid chromatography [HPLC]). However, such methods are labour-intensive, low-throughput and cost-prohibitive for commercial breeding programs, which typically need to assess thousands of samples annually. An accurate high-throughput micro-plate-based protocol has been developed and validated, with the ability to simultaneously process and quantify WSC and plant protein with a high level of automation, and an increase in sample processing of ~10-fold compared with commonly-used methods, along with a 3-fold cost reduction. As WSC and protein are extracted simultaneously and quantified within micro-plates, consumable costs are minimised with optimal reagent use efficiency, resulting in a low per sample cost that is suitable for commercial pasture breeding companies. This is the first demonstration of a forage quality phenotyping protocol suitable for broad-scale application, and will allow breeders to select elite genotypes based not only on visual assessment but also on WSC : protein ratios for improved ruminant nutrition.