Any arable farmer or commercial crop grower wants to know their efforts will be worthwhile. Success is measured in various ways, but profitablility and sustainability are key indicators of the success of a farming enterprise. For crop growers, profitability is linked to maximising yield for fixed costs. A key aim is to produce high yields but use less costly and potentially damaging inputs such as herbicides and pesticides. Choice of variety plays a pivotal role in the profitability of the farming enterprise as it offers farmers the ability to produce high yields with possibily lower inputs. However by its very nature, the choice of the “correct” variety is open to many unknowns, such as weather variability which will not only affect the actual growth and development of the plant, but in turn the prevalence of crop diseases and other abiotic stresses. Therefore growers need as much predictability to the manner in which varieties respond to these uncertainties as they can get.
In Australia the Grains Research and Development Corporation, in conjunction with the Australian Crop Accreditation System have set up the National Variety Trials (NVT) program. A program designed to provide information on newly released crop varieties to aid with crop variety selection decisions, based upon their individual growing conditions. Driven by the increasing commercial focus of plant breeding programs in Australia the NVT program conducts around 600 trials on the full range of commercially significant field crops including wheat, barley, triticale, oat, canola, lupin, lentil, field pea, faba bean and chickpea in over 250 geographic distinct locations. This national program of comparative crop variety testing provides standardised trial management, data generation, collection and dissemination and is managed through an internet accessed database, that ensures a common approach and uniformity across the system.
The NVT program allows for single national analysis for each crop rather than state- based ones, and the results of the analysis are presented in terms of an estimated yielding ability for a specific environment. So whilst the data collected is nationally, providing more data and information and allowing for greater predictability, the results are now provided for individual areas and environmental conditions.
The large number of trials and consequently huge amounts of data (for example 210,000 records for wheat alone) collected needs a data analysis system that can manage large datasets; and given that the results are used in choosing grain varieties, which will have an economic impact, such a tool must be highly accurate and trusted. The biometricians who run the analysis use ASReml.
The analysis model which is used is unique to ASReml as it involves the use of a two-stage linear mixed model in which the data from each trial is weighted according to its statistical and biological reliability. The linear mixed model includes terms which aim to model the variety by environment interactions in a plausible and interpretable manner.
”ASReml is the package that helps farmers, breeders and crop variety evaluators obtain the most reliable predictions of genetic value for a range of crops grown in different environments; farmers can get the best information available about performance of varieties in their own location and make an informed decision,” says Professor Brian Cullis, Research Leader for DPI Biometrics and leader of the SAGI (Statistics for the Australian Grains Industry) project, the project which run the analyses for the NVT program. “ASReml is the only package we trust to run this type of analysis because of its proven accuracy, speed and flexibility for these types of complex two-stage models.”
ASReml is a vital tool in the NVT program; it has allowed for the analysis of huge amounts of data on the performance of different crops under different conditions. Without reliable analysis tools the reports would not have the credibility they have, and therefore Australian growers would not have the access to such useful reports to aid them in crop selection.