Gary D. Gillespie

Selecting the correct variety of a cereal crop is a vital first step, influencing all subsequent crop husbandry decisions and determining the potential successfulness of a crop in both economic and agronomic terms. Growers make this decision by considering farm location, local trial results and knowledge, and their priorities. Balancing these factors, information sources, and priorities is challenging for growers. Complex multi‐factor analyses are required in the decision‐making process; while computer‐based decision support systems (DSSs) have been created to support this process, the localized nature and poor user‐friendliness of the DSSs have resulted in limited grower adoption. This study aims to design a user‐centric DSS to assist growers in selecting an optimal cereal variety for their priorities in each field. The system integrates local factors with independent cereal variety evaluation data, such as national “recommended lists.” It can be applied globally where such listings are available. Two use cases are described with Ireland's Department of Agriculture, Food, and the Marine and New Zealand's Foundation for Arable Research wheat ( Triticum aestivum L.) recommended lists. Characteristic evaluation scores for each variety were normalized and weighted based on user priorities and field location using the simple additive weighting method. Growers’ local yield history of each variety, if available, can be included to create a site‐specific DSS. The outcome is an overall ranking of the varieties present on the recommended list, enabling the user to make an informed decision on their chosen variety while accommodating market demands, seed availability, and their own preference.

In the last century, breeding programs have traditionally favoured yield-related traits, grown under high-input conditions, resulting in a loss of genetic diversity and an increased susceptibility to stresses in crops. Thus, exploiting understudied genetic resources, that potentially harbour tolerance genes, is vital for sustainable agriculture. Northern European barley germplasm has been relatively understudied despite its key role within the malting industry. The European Heritage Barley collection (ExHIBiT) was assembled to explore the genetic diversity in European barley focusing on Northern European accessions and further address environmental pressures. ExHIBiT consists of 363 spring-barley accessions, focusing on two-row type. The collection consists of landraces (~14%), old cultivars (~18%), elite cultivars (~67%) and accessions with unknown breeding history (~1%), with 70% of the collection from Northern Europe. The population structure of the ExHIBiT collection was subdivided into three main clusters primarily based on the accession’s year of release using 26,585 informative SNPs based on 50k iSelect single nucleotide polymorphism (SNP) array data. Power analysis established a representative core collection of 230 genotypically and phenotypically diverse accessions. The effectiveness of this core collection for conducting statistical and association analysis was explored by undertaking genome-wide association studies (GWAS) using 24,876 SNPs for nine phenotypic traits, four of which were associated with SNPs. Genomic regions overlapping with previously characterised flowering genes (HvZTLb) were identified, demonstrating the utility of the ExHIBiT core collection for locating genetic regions that determine important traits. Overall, the ExHIBiT core collection represents the high level of untapped diversity within Northern European barley, providing a powerful resource for researchers and breeders to address future climate scenarios.

Development of novel methods to inhibit ammonia (NH ₃ ) volatilization losses has become a strong research focus to reduce the environmental impact of agriculture and as a potential area for growth in the fertilizer industry. European Union legislation on the regulation of NH ₃ emission from mineral fertilizers after 2030, will only allow urea fertilizers with reduced NH ₃ emissions by at least 30% to remain in use. The recent increase in fertilizer prices has also created a renewed impetus to curb these losses. This paper details the results of an experiment comparing the rates of volatilization from granular urea treated with NutriSphere‐N®, untreated urea and an unfertilized control as well as placing the results in context by conducting a review of similar studies featuring NutriSphere‐N®. The study was conducted in a light and temperature‐controlled growth chamber using the chamber built in air flow which collected any NH ₃ volatilized from a flask containing fresh soil with applied treatment and transported the NH ₃ to an acid trap where the volatilized NH ₃ was captured and exhaust air was removed. The experiment ran for 3 weeks and resulting samples were analysed colorimetrically and adjusted for differences in airflow. The temporal results show that urea dominated the flux profile but the pattern of fluxes from the two fertilizer N treatments were similar. When analysed cumulatively over the duration of the experiment, the fluxes from the NutriSphere‐N® treated urea were significantly ( p = .018) (86%) lower than untreated urea and were not significantly different from the untreated control ( p = .959).

Suppressed wool prices in Ireland over the last number of years has led to situations where the cost of shearing animals is greater than the wools’ value, leading to net losses per animal for farmers. Populations of sheep in Ireland and nutrient values of wool from literature sources were used to determine the quantity of nutrients that could be produced on an annual basis using hydrolysis techniques. Results of this study suggest that up to 15.8% of the nitrogen required to produce Ireland’s cereal crops can be met annually using hydrolysed sheep wool in an economically feasible manner along with considerable amounts of sulphur, zinc, and copper. Most of the cost associated with the process is the purchasing of wool from farmers at an economically favourable level for farmers. Based on the spatial distribution of these animals, the town of Athlone is the most suitable location for a processing facility.