Journal Paper Digests 2026 #26
- Beyond taxonomic richness: Network topology and functional gene abundance reveal tillage and nitrogen as physiological and topological filters across heterogeneous corn agroecosystems
- MIR/FTIR spectroscopy for precision winemaking in smart wineries: state of the art, challenges, and prospects
- Interpretable Additive Modeling of Soil Organic Carbon and Its Fractions From Mid-Infrared Spectra Using MCR-ALS
- Duration Is Not Age: A Thermodynamic Framework for Pedogenetic Time
Duration Is Not Age: A Thermodynamic Framework for Pedogenetic Time
The concept of time in pedology has been operationalized almost exclusively as chronological or radiometric age, following Jenny’s (1941) state factor formalism, which treats the soil as a passive recorder of elapsed time rather than as an active archive of energetic history. I argue that this conflates two different quantities: elapsed time and the capacity of that interval to drive pedogenic processes. I propose that pedogenetic time (Tped) is more rigorously defined as the integral of effective energy coupled to edaphic processes, ∫ Eex(τ) dτ, where coupling efficiency η(τ) ∈ [0,1] captures the fraction of gross energy input directed toward pedogenic reactions rather than dissipated. Tped constitutes a formal mechanism of soil memory: current pedogenic state depends not on calendar age alone but on the entire path by which effective energy has accumulated, a fundamentally hysteretic relationship in which identical present conditions can sustain different trajectories depending on prior energetic history. This path-dependency introduces property-specific thermodynamic thresholds (ΘP) governing the emergence of soil properties, and defines energetic retrogression, the collapse of η(τ) under degradation or climate stress, as pedogenetic memory loss. Two contrasting cases anchor the argument: arid chronosequences exhibiting chronic pedogenic youth despite large calendar age, and technogenic soils showing premature pedogenic ageing through managed high-efficiency inputs. Independent convergence with biological ageing theory, JMAK phase-transition kinetics, geomorphological energy balance, and non-equilibrium thermodynamics supports the framework, which aligns with recent global evidence that energy limitation, not carbon availability, governs soil microbial activity. Chronological age measures the duration of pedogenesis; Tped measures its depth, with direct consequences for chronosequence interpretation, climate-change modelling and Critical Zone restoration.
Interpretable Additive Modeling of Soil Organic Carbon and Its Fractions From Mid-Infrared Spectra Using MCR-ALS
Modeling soil organic carbon (OC) contents from mid-infrared (MIR) spectra remains challenging, and conventional multivariate spectroscopic models often lack chemical interpretability. The objective of this study was to examine whether an additive model based on non-negative multivariate curve resolution—alternating least squares (MCR-ALS) could reproduce variations in OC contents of whole soils and size-separated fractions while providing a chemically interpretable description of that variation. The approach was implemented on MIR spectra of forest and woodland soils in Israel, including fine (< 50 μm) and coarse (> 50 μm) fractions representing mineral-associated organic matter (MAOM) and particulate organic matter (POM), respectively. The OC content was represented as a sum of contributions from nonnegative MCR-ALS spectral components, and the effects of soil fractionation and spectral range selection (4000–400 cm−1 versus optimized subranges) were evaluated. Using the full MIR spectral range, the additive model reproduced OC contents more effectively for the POM-associated fraction than for the whole soils, explaining 71.7% and 38.2% of the observed variance, respectively, whereas no improvement was obtained for the MAOM-associated fraction (16.1%). Optimization of the spectral range increased the explained variance to 69.1% for the whole soils and 56.1% for the MAOM-associated fraction. Leave-one-out cross-validation indicated the predictive capability of the optimized models (Q2 = 0.625, 0.526 and 0.512 for the POM-associated fraction, whole soils and the MAOM-associated fraction, respectively), while bootstrap analysis supported the stability of several optimized parameter estimates. These results demonstrate the potential of spectral range optimization for effective OC modeling using nonnegative MCR-ALS. Analysis of model performance versus the number of MCR components revealed transition-like behavior, supporting the identification of chemically meaningful components. Overall, this study establishes a physically grounded and interpretable framework for MCR-ALS-based modeling of soil OC from MIR spectra, highlighting the roles of soil fractionation, optimization of continuous spectral windows, and interpretability of spectral components.
MIR/FTIR spectroscopy for precision winemaking in smart wineries: state of the art, challenges, and prospects
Mid-infrared (MIR) spectroscopy, particularly through Fourier-transform (FT) instrumentation, has reached a high level of analytical maturity in oenology as a rapid and nondestructive tool for grape must and wine analysis, quality control, and authenticity assessment. Despite nearly three decades of intensive research demonstrating its strong potential to extract biochemically meaningful information, the translation of MIR spectroscopy into real-time or near-real-time process monitoring tools for decision support in wineries remains limited. To date, only a few applications employ portable or at-line FTIR configurations, while true in-line or on-line sensing at critical winemaking stages is largely restricted to pilot-scale implementations and laboratory prototypes. This review critically examines the reasons behind this gap. Evidence from related scientific and technological disciplines (food science and technology, photonics and sensor engineering, informatics and intelligent computing) is discussed from a system-level perspective. The main idea is to describe the state-of-the-art beyond analytical performance metrics, to identify opportunities for improving technology readiness and enabling integration into winery processes. The review contributes to the ongoing discussion on the strong potential of Mid-infrared (MIR/FTIR) spectroscopy across the wine production chain and outlines pathways for integrating spectroscopy, data analytics and oenological domain knowledge in the next generation of precision winemaking systems.
Beyond taxonomic richness: Network topology and functional gene abundance reveal tillage and nitrogen as physiological and topological filters across heterogeneous corn agroecosystems
Soil microbial communities underpin key ecosystem functions, yet their responses to agricultural intensification remain difficult to predict across heterogeneous landscapes. This study evaluated the impact of nitrogen (N) fertilization rates (0–200 kg N/ha) and tillage intensity (conventional ploughing, reduced tillage, direct drilling) on bacterial diversity, functional potential, and co-occurrence networks across 84 corn fields in southern Québec, Canada. Using 16S rRNA gene sequencing and qPCR of N-cycling genes (nifH, amoA, nirK), we reveal a hierarchy of drivers. Soil texture and pH dominated bacterial composition, explaining ∼46% of the variance and overriding the effects of management on alpha- and beta-diversity. Texture also constrained topology, with fine soils favoring dense, centralized networks while coarse soils promoted decentralized, modular architectures. However, this taxonomic homeostasis concealed a reorganization of function and structure. Nitrogen fertilization induced a functional reallocation, significantly increasing amoA and suppressing nifH gene abundance. Tillage intensity reshaped microbial network topology, with direct drilling promoting modular and niche-partitioned networks, while reduced tillage exhibited low connectivity and high centralization, hypothesized to reflect structural vulnerability in transitional systems. These patterns indicate that agricultural management operates primarily as a physiological and topological filter rather than a taxonomic driver, consistent with concepts of functional redundancy and network-mediated stability in microbial ecosystems. Thus, soil health assessments should move beyond taxonomic richness to include indicators of network topology and functional gene abundance, which offer more sensitive metrics of ecosystem resilience. Consequently, sustainable management strategies must prioritize preserving these microbial co-occurrence architectures and functional redundancy to ensure long-term soil fertility.