Effects of row deep tillage for the growth base formed by piling up soil in damp lowlands behind coastal sand dunes to construct coastal disaster prevention forest belts on the Kujukuri coastline,Japan

ABSTRACT

To successfully afforest coastal forest belts ensuring high disaster prevention, growth bases for them have been constructed by piling up soil in the low wetlands along the Kujukuri coastline. Ground surfaces in such bases are often covered with water because of soil compaction, leaving them susceptible to stagnant water. Water stagnation in soil is problematic, potentially interfering with afforesting coastal forests. Therefore, row deep tillage was conducted for parts of growth bases to combat the poor physical properties of the existing soil. Here, we surveyed soil profiles and measured vertical soil hardness distribution in two forest stands with piling up soil to evaluate the effectiveness of tillage for man-made soil. Soil hardness measurements indicated that the vertical areas with ‘soft’ and ‘hard/consolidated’ soil alternately appeared in growth base profiles. Generally, soil of the dense and very hard layers was apt to be formed by strong compaction of the filled-up soil because of heavy machinery usage during growth base preparation. Such dense and hard soils in the untilled areas of the profiles were also observed in this study. By contrast, it was confirmed that row deep tillage drastically improved soil physical properties, i.e., decreased hardness and increased water permeability, because the sequential hardened subsoil layers were well-broken-up. Moreover, it was observed many thick and large roots penetrated deeper layers with deep tillage areas. These results suggest that row deep tillage of hardened soil is quite effective at securing the areas and providing the physical conditions for deeply penetrated roots into deeper soils, which increases healthy root development. They show the effects of soil hardness reduction and water permeability improvement have been maintained for two decades, at least, after construction. These findings will be useful for alleviating some problems of soil compaction, water stagnation, and tree-growth hindrance that have been encountered on afforestation sites with man-made soil.     

Genomic evaluation using SNP‐ and haplotype‐based genomic relationship matrices in a closed line of Duroc pigs

A simulation analysis and real phenotype analysis were performed to evaluate the impact of three different relationship matrices on heritability estimation and prediction accuracy in a closed‐line breeding of Duroc pigs. The numerator relationship matrix (NRM), single nucleotide polymorphism (SNP)‐based genomic relationship matrix (GRM) (G_S), and haplotype‐based GRM (G_H) were applied in this study. We used PorcineSNP60 genotype array data (38 114 SNPs) of 831 Duroc pigs with four selection traits. In both heritability estimation and prediction accuracy, the accuracy depended on the number of animals with records. For heritability estimation, a large difference in the results among three relationship matrices was not shown, but the trend of the estimated heritabilities between GRMs, that is G_S < G_H, was shown in this population. For the accuracy of prediction values in test animals, the accuracies of prediction values obtained by two GRMs were higher than that by the NRM in this population. The accuracies obtained by GRMs using animals with no records were lower than that by the NRM using animals with their performance records, but were close to that by the NRM using animals with full‐sib testing records.