Grapevine (Vitis vinifera L.) is an economically important fruit crop whose productivity and fruit quality are adversely affected by abiotic stresses such as drought and salinity. Late Embryogenesis Abundant (LEA) proteins contribute to plant stress tolerance, whereas WUSCHEL-related homeobox (WOX) transcription factors are primarily involved in plant development. Here, we performed a genome-wide identification and bioinformatics characterization of the LEA2 and WOX gene families in grapevine to investigate their potential roles in abiotic stress responses. A total of 36 VvLEA2 and 29 VvWOX genes were identified. Phylogenetic analysis classified VvLEA2 genes into two major clades and a distinct singleton lineage, while VvWOX genes formed three major clades, with phylogenetic relationships broadly supported by gene structure and conserved motif patterns. Most VvLEA2 genes were intronless, whereas VvWOX genes exhibited greater exon–intron diversity. Subcellular localization prediction indicated diverse cellular distributions of VvLEA2 proteins, with a predominance at the plasma membrane, while VvWOX proteins were predominantly predicted to be nuclear-localized. miRNA analysis identified 195 miRNAs potentially targeting 35 VvLEA2 genes and 270 miRNAs targeting all 29 VvWOX genes. Promoter analysis revealed numerous stress-, hormone-, and development-related cis-regulatory elements. Overall, these in silico findings suggest potential roles for VvLEA2 and VvWOX genes in grapevine stress responses and developmental regulation, while experimental validation is required to confirm these predicted functions and regulatory relationships. The findings provide a foundation for future functional studies and stress-tolerance-oriented grapevine breeding.
Protists represent the largest proportion of eukaryotic diversity acting as a part of the soil microbiome. They play a significant role in mediating carbon and nitrogen cycles, influencing nutrient availability and overall soil health. However, their diversity is shaped by many factors, including plant species, bacterial microbiome, precipitation and organic matter. Here, we investigated protist diversity in date palm rhizosphere soils without and with different combinations of organic, bio-organic and chemical fertilizer treatments. Results showed that soil conductivity, salinity and total dissolved solids (TDS) correlated with the protist diversity. The highest protist diversity was found in the treatment using bio-organic fertilizers mixed with 30 % chemical fertilizer. Higher chemical fertilizer content on the other hand tended to decrease the protist diversity. The highest abundance of protist genera belonged to supergroups of Archaeaplastida, Alveolata, Rhizaria, Amoebozoa and Stramenopiles. The most abundant classes of protist were Filosa-Sarcomonadea, Colpodea, Variosea, Tubulinea and Chlorophyceae. Overall, our results suggest that balanced fertilization with organic matter inputs can enhance protist diversity, improve soil health, and contribute to sustainable crop productivity.
The digital transformation of the agri-food sector offers significant opportunities for sustainable growth, yet measuring this transition remains a persistent challenge for official statistical systems. Focusing on Armenia as a representative emerging economy, this paper investigates the evidence gaps in official agricultural statistics regarding digital agriculture. Employing a qualitative, evidence-based review of national statistical instruments and the Digital Agriculture Measurement Framework (DAMF), a tripartite analytical lens linking agri-food sector development, digitalization, and official statistics, the study evaluates the capacity of current official statistics to capture digital adoption. The findings reveal a fundamental instrumentation gap: existing frameworks are structurally oriented toward physical production and traditional assets, failing to operationalize key digital variables such as connectivity, ICT skills, and precision technology use. Furthermore, the study demonstrates that digitalization cannot be reliably inferred from traditional proxies, such as general machinery ownership. To bridge this gap and align with international standards set by the FAO and Eurostat, the paper proposes a gap matrix and recommends the integration of specific digital indicators alongside high-frequency mobile reporting tools. Addressing these methodological limitations is essential to enable advanced empirical research and support data-driven policymaking for agricultural modernization.
Soil Moisture Regimes (SMR) serve as diagnostic criteria in Soil Taxonomy (ST), linking soil processes with climate and functioning as essential indicators for soil classification, agricultural planning, and land-use management. Determining SMR in tropical regions is challenging due to high spatial variability, limited observational data, and pronounced climatic fluctuations, which complicate the application of frameworks developed for temperate zones. This review synthesizes the historical and conceptual evolution of SMR, assesses empirical and physically based estimation methods, and evaluates their applicability in tropical America, with a focus on Colombia. It is proposed that SMR should be conceptualized as dynamic, scale-dependent indicators of soil-climate interactions, rather than static taxonomic attributes predicated on climatic stability. The main findings are as follows: (i) traditional climatic proxies, such as the Newhall model, frequently oversimplify soil hydrology and may misclassify SMR in soils with distinctive hydrophysical properties; (ii) the notion of a climatically stationary “normal year” is increasingly untenable under rapid climate change, particularly in regions influenced by the El Niño–Southern Oscillation (ENSO) and the Intertropical Convergence Zone (ITCZ); (iii) physically based models and hydropedological approaches yield more robust and spatially explicit SMR estimates by integrating soil hydraulic properties, landscape processes, and subsurface-atmosphere interactions; and (iv) in Colombia, SMR estimation predominantly relies on climatic zonation rather than direct soil moisture monitoring, resulting in considerable uncertainties in soil classification and land-use planning. Advancing SMR science in tropical regions requires strengthening empirical baselines through long-term root-zone monitoring, integrating soil physical properties and landscape processes into estimation methods, and developing dynamic SMR indicators that capture intra-annual and interannual variability. This review will contribute to reconceptualizing SMR as critical indicators of soil-climate interactions, thereby supporting more informed and sustainable decision-making in the context of increasing climatic uncertainty.
This study characterized the goat populations of north and central Gondar zones in Ethiopia using morphological characteristics and structural indices. A representative sample of 792 (106 males and 686 females, including kids) goats from the lowland, midland, and highland agroecologies were assessed for nine qualitative traits, whereas 583 mature (>1 PPI) animals were used for assessing 10 quantitative linear body measurement characteristics. Moreover, 12 structural indices were calculated from the quantitative traits measured. Descriptive statistics and GLM procedures of SPSS version 20 were used for data analysis based on the data type. The results revealed a diversity of qualitative characteristics among the agroecological zones, which can be attributed to adaptation mechanisms in the respective areas. Traits such as lateral ear orientation, presence of wattles, and polled horns were strongly associated with highland agroecology, whereas plain coat color pattern, short and smooth hair, droopy ears, and a straight head profile were closely linked to lowland environments. Similarly, quantitative morphological characteristics and derived structural indices showed significant variation within populations and between agroecologies. Both age and sex of the goats have exerted significant effects on almost all the traits considered. In general, goats from the lowland, older and male goats, exhibited higher values for most of the morphological and weight indices, whereas highland goats, females, and younger goats tended to present smaller morphological and index values. Accordingly, the goats in the study area could be classified as dairy-type and medigline animals based on their compactness and body indices. Overall, the findings highlighted clear morphological variation among agroecological zones, reflecting adaptive responses to environmental conditions, management practices, and potential genetic influences. The observed within-population variability further suggests opportunities for selective breeding to enhance productivity while maintaining environmental adaptability.
