IJAFR, vol. 63, 2024
Articles published in 2024
Recent Submissions
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The effect of nitrogen and phosphorus fertiliser application rate and strategy on herbage production and nitrogen response in springMaximising herbage yield while reducing nitrogen (N) fertiliser input, particularly in spring, is essential to ensure environmental and economic sustainability on grassland farms. A plot experiment was conducted over 2 yr, comparing three different spring N application rates of 30 (30N), 60 (60N) and 90 (90N) kg N/ha using three different spring application strategies: 0:100 (S1), 50:50 (S2) or a 33:66 (S3) split across February and March, respectively. Half of the plots also received phosphorus (P) fertiliser with the first application of N at a rate of 13 kg P/ha. Nitrogen fertiliser application for the remainder of the year (April–September) was the same for all plots (23 kg N/ha/application). Both spring and cumulative herbage yields were significantly affected (P < 0.05) by N application rate; 90N had the greatest spring and cumulative herbage yield compared to 30N and 60N (10,925, 9,834 and 10,499 kg DM/ha, respectively); however, N response reduced as N application rate increased. Nitrogen application strategy had a significant effect (P < 0.05) on spring herbage yield, with S1 significantly lower than S2 and S3. Applying 13 kg P/ha in spring increased herbage yield at defoliations 2 (23 April) and 3 (15 May) (+133 and 56 kg DM/ha, respectively), relative to no application of P fertiliser, as well as increasing cumulative herbage yield (+241 kg DM/ha). The results of the current study indicate that N should be applied in early February and the strategic application of N and P during spring can increase spring and cumulative herbage yield.
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Estimating conservation value and natural capital value of land cover classes in the Irish National Land Cover Map and application to a case study areaConservation science and planning, by measuring proxies of biodiversity and ecosystem services provision, aim to identify priority areas for nature conservation and ecosystem services. In Ireland, fine-scale data on ecosystems functioning and biodiversity are limited, making it challenging to map conservation value (CV) and natural capital value (NCV) accurately. We elicited expert knowledge to rank habitat classes mapped in the recently published National Land Cover Map (NLCM) (EPA and Tailte Éireann, 2023). A scoring system from 0 to 10 was used to score habitats based on their estimated provision of biodiversity (CV) and ecosystem services (NCV). As a case study, we applied this scoring system to a catchment in the south-east of Ireland (>2,000 km2) with land cover information available from the draft NLCM. The expert elicitation showed little overall difference between the scores assigned by the team and the experts invited to validate the CV and NCV scores. However, some scores were revised based on experts’ contributions. Results of the mapping exercise indicated a high correlation between monads with high CV and high NCV scores. Future work should focus on differentiating the weighting assigned to each ecosystem service associated with each land cover class. This could result in changes in the overall NCV scores assigned to each habitat (and monads). Nevertheless, the approach developed here has the potential to identify areas in the landscape that should be targeted for conservation. For reproducibility, we provide the R code for analysis at polygon scale.
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Exploring the presence of genotype-by-environment interactions between dairy cow herds milking once-a-day or twice-a-day for the entire lactationThe objective was to explore if the regression of phenotypic performance for six milk production traits on the respective estimate of genetic merit for that trait differed by herd milking frequency; variance components for each trait in the two milking frequency environments were also estimated as well as the genetic correlation between the same trait in both environments. The data used included 12,581 lactations from 5,456 cows in 32 spring-calving once-a-day (OAD) milking herds. Each OAD herd was matched with three contemporary twice-a-day (TAD)-milking herds; 35,823 lactations from 15,188 cows in 96 TAD herds were used. Mean yield was 20% (fat yield) to 31% (milk yield) lower in OAD herds. Milk protein concentration was 11% higher in OAD herds, while milk fat concentration was 16% higher in OAD herds. The mean back-transformed somatic cell score (SCS) was 100,390 cells/mL in OAD herds and 72,493 cells/mL in TAD herds. The association between each milk production trait and its respective estimate of genetic merit differed by herd milking frequency; the estimated regression coefficients were larger in TAD for just milk yield and SCS. The genetic correlation between the same trait in OAD versus TAD was all ≥0.73 with the exception of SCS (genetic correlation of 0.48) which suggests some re-ranking of sires between environments. In conclusion, differences in the scale of the genetic variance were evident for both milking frequencies and possible re-ranking was evident for SCS.
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The first survey using high-throughput sequencing of cereal and barley yellow dwarf viruses in Irish spring and winter barley cropsYellow dwarf viruses (YDVs) are the most economically important plant viruses impacting cereal production worldwide and include viruses from the genus Luteovirus (e.g., barely yellow dwarf virus (BYDV)-PAV, BYDV-PAS, BYDV-MAV, BYDV-kerII, BYDV-kerIII) and Polerovirus (e.g., cereal yellow dwarf virus (CYDV)-RPV, CYDV-RPS). Until now, much of our knowledge on YDVs infecting Irish barley crops (Hordeum vulgare L.) has come from serological assays; however, due to cross-reactivity it can be difficult to discriminate between viruses of different species. In this study, we have carried out a high-throughput sequencing survey of symptomatic crops, positive with serological assays, to identify YDVs infecting Irish spring and winter barley crops and establish reference genomes to support further development of molecular surveillance tools. In total, RNA was extracted from 45 symptomatic crop samples that were collected across Ireland over 2 yr and sequenced following rRNA depletion. Three samples of barley plants from BYDV-infected aphid colonies were also included. BYDV-MAV was identified in all field samples sequenced. This confirms previous evidence based on serological assays that BYDV-MAV is the dominant YDV in Irish barley crops. We have also identified BYDV-PAS in 29% of symptomatic field samples, the first report of this species in Ireland. In addition, BYDV-PAV was also found, and crop samples with mixed infections were common; although in mixed infections the greatest proportion of YDV reads originated from BYDV-MAV. Finally, CYDV-RPS, the more severe variant of CYDV-RPV belonging to the genus Polerovirus, was identified in a single sample. The complete genomes, assembled from this first sequence-based survey, will enable the development of molecular surveillance tools with greater virus specificity, to further support the Irish aphid and YDV monitoring network.