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Genetic diversity and population structure of Iranian oak (Quercus spp.) accessions based on ISSR and CBDP markers
The Response of the Mycobiome to the Biofumigation of Replanted Soil in a Fruit Tree Nursery
In a long-term monoculture with fruit trees and tree nurseries, it is necessary to regenerate the soil due to the risk of apple replant disease (ARD). The occurrence of ARD is manifested in the structure of the mycobiome. The assumption of our experiment was that the use of oil radish (Raphanus sativus var. oleifera), white mustard (Sinapis alba), and marigold (Tagetes patula L.) as phytosanitary plants for biofumigation would provide crops with nutrients, improve soil physicochemical properties, and influence the diversity of microbiota, including fungal networks, towards a beneficial mycobiome. Metagenomic analysis of fungal populations based on the hypervariable ITS1 region was used for assessing changes in the soil mycobiome. It showed that biofumigation, mainly with a forecrop of marigold (Tagetes patula L.) (R3), caused an improvement in soil physicochemical properties (bulk density and humus) and the highest increase in the abundance of operational taxonomic units (OTUs) of the Fungi kingdom, which was similar to that of agriculturally undegraded soils, and amounted to 54.37%. In this variant of the experiment, the most OTUs were identified at the phylum level, for Ascomycota (39.82%) and Mortierellomycota beneficial fungi (7.73%). There were no such dependencies in the soils replanted with forecrops of oilseed radish (Raphanus sativus var. oleifera) and white mustard (Sinapis alba). Biofumigation with marigold and oil radish contributed to a reduction in the genus Fusarium, which contains several significant plant-pathogenic species. The percentages of operational taxonomic units (OTUs) of Fusarium spp. decreased from 1.57% to 0.17% and 0.47%, respectively.
Diversity of Bacterial Communities in Horse Bean Plantations Soils with Various Cultivation Technologies
Modern agriculture should limit its degrading impact on the soils, the natural environment, and the climate. No-tillage soil cultivation technologies, which have been in use for many years and are constantly being improved, are a good example of these actions; although, in-depth studies on their impact on the soil microbial community are currently scarce. The aim of our study was to evaluate the effect of cultivation technology on the soil bacterial community to assess differences that can be reflected in the environmental and agricultural functionality, identifying possible bacterial species with ecological properties. In this context, the composition of bacterial communities (at the phyla, order, class, and species levels) was evaluated under different conditions, such as conventional tillage (CT) (plophing), reduced tillage (RT) (stubble cultivator), strip tillage (ST), and no-tillage (direct sowing on stubble and fallow buffer zone of the experimental field), in a horse bean plantation. Metagenomic methods (next generation sequencing technology, NGS) were used to determine the percentage of individual operational taxonomic units (OTUs). Our study showed that no-tillage cultivation technologies, mainly strip and no-tillage methods, had a positive effect on microbiological communities. In fact, key species related to soil fertility and crop yield, such as Gemmatimonas aurantiaca (a microorganism that reduce nitrous oxide, N2O in soil) and Aeromicrobium ponti (a beneficial species for the soil environment, essential for the proper functioning of the crop agroecosystem), increased in reduced cultivation technologies. These species can determine soil fertility and crop yields, and therefore, they are very important for sustainable and even regenerative agriculture. Further studies of soil samples collected from other crop plantations under different cropping systems may indicate beneficial microbial species that are important for soil fertility.
Agro-morphological characterization and machine learning-based prediction of genetic diversity in six-row barley genotypes from Türkiye
Abstract The restricted genetic diversity observed in modern barley represents a significant obstacle to enhancing productivity. This study addresses this issue by characterising 445 six-row barley genotypes from the Osman Tosun Gene Bank in Türkiye. A comprehensive analysis of 22 agro-morphological traits, comprising 11 qualitative and 11 quantitative traits, was conducted to explore morphological, growth and phenological diversity. Principal component analysis identified four principal components, which collectively explained 72.86% of the total variance. Of these, the first two components accounted for 52.45%. Based on agro-morphological similarities, the genotypes were grouped into seven clusters. Clusters 5, 6, and 7 contained genotypes with high-yield traits, including early maturity, increased grain per spike, and higher thousand grain weight. The findings contribute directly to the expansion of the barley gene pool. Moreover, this study provides a comprehensive characterisation of the hitherto overlooked six-row barley germplasm present in Türkiye. This offers invaluable genetic resources for future breeding and molecular studies. Furthermore, the study compares the performance of three machine learning models (XGBoost, MARS, and Gaussian Processes) in predicting the harvest index from various traits. The XGBoost model demonstrated superior predictive ability, with the lowest RMSE (0.137), MAPE (0.222), and MAD (0.101) values, and was able to explain 99.8% of the barley variation. This research highlights the potential of machine learning algorithms in enhancing barley breeding by accurately predicting beneficial traits for yield improvement.