Application of date palm waste compost is quite beneficial in improving soil properties and crop growth. However, the effect of its application on soil microbial communities is less understood. High-throughput sequencing and quantitative real-time PCR (qPCR) were used to evaluate the effect of compost application on the soil microbial composition in a barley field during the tillering, booting and ripening stages. The results showed that compost treatment had the highest bacterial and fungal abundance, and its application significantly altered the richness (Chao1 index) and α-diversity (Shannon index) of fungal and bacterial communities. The dominant bacterial phyla found in the samples were Proteobacteria and Actinobacteria while the dominant fungal orders were Ascomycota and Mortierellomycota. Interestingly, compost enriched the relative abundance of beneficial microorganisms such as Chaetomium, Actinobacteriota, Talaromyces and Mortierella and reduced those of harmful microorganisms such as Alternaria, Aspergillus and Neocosmospora. Functional prediction based on Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) showed that amplicon sequence variant (ASV) sequences related to energy metabolism, amino acid metabolism and carbohydrate metabolism were associated with compost-treated soil. Based on Fungi Functional Guild (FUNGuild), identified fungi community metabolic functions such as wood saprotroph, pathotroph, symbiotroph and endophyte were associated with compost-treated soil. Overall, compost addition could be considered as a sustainable practice for establishing a healthy soil microbiome and subsequently improving the soil quality and barley crop production.

Soil is a vital component of the ecosystem that drives the holistic homeostasis of the environment. Directly, soil quality and health by means of sufficient levels of soil nutrients are required for sustainable agricultural practices for ideal crop yield. Among these groups of nutrients, soil carbon is a factor which has a dominating effect on greenhouse carbon phenomena and thereby the climate change rate and its influence on the planet. It influences the fertility of soil and other conditions like enriched nutrient cycling and water retention that forms the basis for modern ‘regenerative agriculture’. Implementation of soil sensors would be fundamentally beneficial to characterize the soil parameters in a local as well as global environmental impact standpoint, and electrochemistry as a transduction mode is very apt due to its feasibility and ease of applicability. Organic Matter present in soil (SOM) changes the electroanalytical behavior of moieties present that are carbon-derived. Hence, an electrochemical-based ‘bottom-up’ approach is evaluated in this study to track soil organic carbon (SOC). As part of this setup, soil as a solid-phase electrolyte as in a standard electrochemical cell and electrode probes functionalized with correlated ionic species on top of the metalized electrodes are utilized. The surficial interface is biased using a square pulsed charge, thereby studying the effect of the polar current as a function of the SOC profile. The sensor formulation composite used is such that materials have higher capacity to interact with organic carbon pools in soil. The proposed sensor platform is then compared against the standard combustion method for SOC analysis and its merit is evaluated as a potential in situ, on-demand electrochemical soil analysis platform.

Open-source legacy data available for training soil organic carbon (SOC) models are limited and not uniformly distributed in space or time. While some process-based models predict SOC changes, most of the large-scale data-driven SOC modeling efforts overlook temporal shifts. Accounting for the expected temporal drift allows us to increase the accuracy of dataset available for machine learning models. Here we present an approach for creating proximity-based distance matrices using the legacy data available in contiguous US (CONUS) and generating spatially resolved temporal shift projections that adjust observations to the target date. The approach was evaluated by comparing SOC observations projected to two reference years, SOC₁₉₈₀ and SOC₂₀₂₀ and without temporal adjustment (SOC_no−adj). Stocks of SOC projections showed significant differences between SOC_no−adj and SOC₂₀₂₀. Baseline estimate of SOC stocks in CONUS croplands (top 1 m) were higher based on SOC_no−adj (14.49 Pg C) compared to SOC₂₀₂₀ (13.29 Pg C), for pasture lands 15.49 Pg (SOC_no−adj) and 14.22 Pg C (SOC₂₀₂₀), for forest lands at 39.52 Pg C (SOC_no−adj) and 40.83 Pg C (SOC₂₀₂₀). The study results confirmed the validity of our methodology, and its capability to enhance SOC stock projections effectively with temporal adjustments. Potential users of this study’s outcomes include many stakeholders involved in carbon incentive programs, including farmers, scientists, policy makers, and industry partners.

Proteomic analysis was performed to investigate the differentially abundant proteins (DAPs) in barley roots during the tillering stage. Bioinformatic tools were used to interpret the biological function, the pathway analysis and the visualisation of the network amongst the identified proteins. A total of 72 DAPs (33 upregulated and 39 downregulated) among a total of 2580 proteins were identified in response to compost treatment, suggesting multiple pathways of primary and secondary metabolism, such as carbohydrates and energy metabolism, phenylpropanoid pathway, glycolysis pathway, protein synthesis and degradation, redox homeostasis, RNA processing, stress response, cytoskeleton organisation, and phytohormone metabolic pathways. The expression of DAPs was further validated by qRT-PCR. The effects on barley plant development, such as the promotion of root growth and biomass increase, were associated with a change in energy metabolism and protein synthesis. The activation of enzymes involved in redox homeostasis and the regulation of stress response proteins suggest a protective effect of compost, consequently improving barley growth and stress acclimation through the reduction of the environmental impact of productive agriculture. Overall, these results may facilitate a better understanding of the molecular mechanism of compost-promoted plant growth and provide valuable information for the identification of critical genes/proteins in barley as potential targets of compost.