Moisture insensitive prediction of soil properties from VNIR reflectance spectra based on external parameter orthogonalization

Moisture is the single most important factor that affects soil reflectance spectra, particularly for field applications. Interest in using soil VNIR spectral libraries, which are commonly based on dry ground soils, to predict soils in the intact field-moist condition (in situ VNIR) is growing. External parameter orthogonalization (EPO) has been proposed as a useful method that links dry ground VNIR models to field moist scans. The goal of this study is to test EPO on a wider set of soil properties and four different modeling techniques, namely, Partial Least Squares Regression (PLS), Artificial Neural Network (ANN), Random Forest (RF), and Support Vector Machine (SVM). We selected and scanned 352 archived soil samples fromNebraska, USA, among which 185 samples were used to develop dry groundmodels and the remaining 167 sampleswere rewetted to eight differentmoisture levels for EPO development and testing. Two methods to determine optimum number of EPO components, model-coupled cross validation (Model-Coupled-CV) and Wilk\u27s Λ were also compared. The results showed that EPO minimized the variability of soil spectra induced by moisture. Results suggest a preference for the Wilk\u27s Λ method over Model-Coupled-CV for determining the number of EPO components g, as it produced smoother transformed spectra and more parsimonious models. Among the eight soil properties tested, EPO caused significant improvements for soil Organic Carbon (OC), Inorganic Carbon (IC), and Total Carbon (TC) prediction, marginal improvement for sand and clay, and no improvement for pH, Mehlich-3 Phosphorus, and Cation Exchange Capacity. The failed EPO for the latter three properties is attributable to the poor initial dry-ground models that EPO was built upon. For OC, IC, and TC, EPO coupled effectively with all four modeling methods, with ANN and SVM outperforming the other two slightly. This adds flexibility to the implementation of EPO in predicting field moist soils. As there are increasing demands of spatially-explicit soil data in many disciplines, EPO would be an important essential part for the future in situ VNIR based proximal soil sensing technology

Carbon-sensitive pedotransfer functions for plant available water

Currently accepted pedotransfer functions show negligible effect of management-induced changes to soil organic carbon (SOC) on plant available water holding capacity (θAWHC), while some studies show the ability to substantially increase θAWHC through management. The Soil Health Institute\u27s North America Project to Evaluate Soil Health Measurements measured water content at field capacity using intact soil cores across 124 long-term research sites that contained increases in SOC as a result of management treatments such as reduced tillage and cover cropping. Pedotransfer functions were created for volumetric water content at field capacity (θFC) and permanent wilting point (θPWP). New pedotransfer functions had predictions of θAWHC that were similarly accurate compared with Saxton and Rawls when tested on samples from the National Soil Characterization database. Further, the new pedotransfer functions showed substantial effects of soil calcareousness and SOC on θAWHC. For an increase in SOC of 10 g kg–1 (1%) in noncalcareous soils, an average increase in θAWHC of 3.0 mm 100 mm–1 soil (0.03 m3 m–3) on average across all soil texture classes was found. This SOC related increase in θAWHC is about double previous estimates. Calcareous soils had an increase in θAWHC of 1.2 mm 100 mm–1 soil associated with a 10 g kg–1 increase in SOC, across all soil texture classes. New equations can aid in quantifying benefits of soil management practices that increase SOC and can be used to model the effect of changes in management on drought resilience

Linking soil microbial community structure to potential carbon mineralization: A continental scale assessment of reduced tillage

Potential carbon mineralization (Cmin) is a commonly used indicator of soil health, with greater Cmin values interpreted as healthier soil. While Cmin values are typically greater in agricultural soils managed with minimal physical disturbance, the mechanisms driving the increases remain poorly understood. This study assessed bacterial and archaeal community structure and potential microbial drivers of Cmin in soils maintained under various degrees of physical disturbance. Potential carbon mineralization, 16S rRNA sequences, and soil characterization data were collected as part of the North American Project to Evaluate Soil Health Measurements (NAPESHM). Results showed that type of cropping system, intensity of physical disturbance, and soil pH influenced microbial sensitivity to physical disturbance. Furthermore, 28% of amplicon sequence variants (ASVs), which were important in modeling Cmin, were enriched under soils managed with minimal physical disturbance. Sequences identified as enriched under minimal disturbance and important for modeling Cmin, were linked to organisms which could produce extracellular polymeric substances and contained metabolic strategies suited for tolerating environmental stressors. Understanding how physical disturbance shapes microbial communities across climates and inherent soil properties and drives changes in Cmin provides the context necessary to evaluate management impacts on standardized measures of soil microbial activity

Synthesis : Goals to Achieve Soil Security

To work towards achieving soil security in the next two decades, participants identified goals to secure soil so that it can contribute to solving other global issues. Specific goals for each dimension were designed to achieve the overall objective of soil security, catalyse research and practice and contribute to soil policy. Agreed goals included: 1. Fifty percent of soil is used according to its capability by 2030. 2. Soil condition is optimally managed according to the inherent capability in 50 % of managed soil systems by 2030. 3. Increase annual capital value of soil ecosystem services by 5 % per annum by 2030 and commercial land values based on full economic value of soil capability and condition, by 2020. 4. Ninety percent awareness and understanding of soil security amongst the general public by 2030. 5. Fifty percent of national governments recognise soil security in their laws and regulations by 2025. It was agreed that we should work towards making soil security a recognised sustainable development goal in its own right

A minimum suite of soil health indicators for North American agriculture

The concept of soil health is appropriately receiving increased attention from governments, producers, corporations, and other stakeholders because of the many functions of soil that support ecosystem services and farm profitability. With this interest, there is growing need to verify and monitor changes in soil health that result from how agricultural soil is managed. There are many indicators of soil health and, although this benefits the scientific community, it complicates interpretation across studies. The North American Project to Evaluate Soil Health Measurements (NAPESHM) assessed over 30 available measurements on 124 long-term agricultural research sites with replicated soil health treatments and created new pedotransfer functions. This analysis draws on findings from NAPESHM to identify a minimum suite of effective indicators of soil health for the North American Continent. The criteria for a minimum suite of effective indicators are that they (1) primarily reflect soil health rather than inherent soil properties or fertility, (2) are responsive to agricultural management practices that exemplify soil health principles, (3) are conducive to measuring soil health at scale in terms of cost and availability, and (4) are not redundant with regard to linking different soil functions to ecosystem services. Many indicators were determined effective for use in soil health studies and based on this analysis, soil organic C concentration, aggregate stability, and 24 h C mineralization potential were selected for the minimum suite of indicators. Using this minimum suite, as few as three laboratory measurements can be made to assess and track improvement in soil functioning as a result of soil management changes. These indicators may be supplemented with new pedotransfer functions to also estimate changes in available water holding capacity. This minimal suite of soil health measurements is recommended for scaling up soil health assessments across North America, and possibly beyond

Effect of Air- and Water-Filled Voids on Neutron Moisture Meter Measurements of Clay Soil

Air- and water-filled voids around neutron moisture meter (NMM) access tubes have been cited as sources of volumetric water content (θ) measurement error in cracking clay soils. The objectives of this study were to experimentally quantify this potential error stemming from (i) uncertainty in bulk density (ρ) sampling and (ii) the impact of air- and water-filled voids. Air- and water-filled voids were simulated using ∼0.6-cm (small) and ∼1.9-cm (large) annuli around access tubes. After NMM measurements were taken in a tightly installed access tube, either a small or large annulus was installed in the same borehole. Additional NMM measurements were taken with the annulus filled with air, and then water and ρ and θ were measured. The RMSE of the NMM calibration using all 11 installations was 0.02 m m. However, if two cores were used for calibration, the ratio of NMM-measured θ to in situ θ was significantly different ( < 0.05) from measured θ half the time (RMSE, 0.012–0.05 m m). Small air-filled voids created drier estimates of θ (bias, −0.039 m m; < 0.001), wherease small water-filled voids were not significantly different from the calibration. Air- and water-filled voids from larger annuli were significantly lower and higher ( < 0.001) than core-measured θ, with biases of −0.068 and 0.080 m m, respectively. Although this work does not correct NMM-predicted θ to matrix θ, it does bound NMM error under field conditions in a cracking clay soil

Diffuse reflectance mid-infrared spectroscopy is viable without fine milling

While diffuse reflectance Fourier transform mid-infrared spectroscopy (mid-DRIFTS) has been established as a viable low-cost surrogate for traditional soil analyses, the assumed need for fine milling of soil samples prior to analysis is constraining the commercial appeal of this technology. Here, we reevaluate this assumption using a set of 2380 soil samples collected across North American agricultural soils. Cross-validation indicated that the best preprocessing (standard normal variate) and model form (memory-based learning) resulted in very good and nearly identical predictions for the <2 mm preparation and fine-milled preparation of these soils for total organic carbon (TOC), clay, sand, pH and bulk density (BD). Application of larger models built from the USDA NRCS mid-DRIFTS library also resulted in minimal performance differences between the two sample preps. Lower predictive performance of the existing library was attributed to less-than-perfect spectral representativeness of the library. Regardless of model form, there was very little variability between replicates of the <2 mm prep, suggesting that the lack of fine milling did not lead to more heterogeneous subsamples. Additionally, there was no relationship between residual error and soil texture, implying these results should be robust across most soil types. Overall, in agreement with other recent findings, these results suggest that routine scanning of standard <2 mm preparation does not degrade predictive performance of mid-DRIFTS-based inference systems. With good standard operating procedures including quality control and traditional analysis on a small percent of samples, mid-DRIFTS can become a routine tool in commercial soil laboratories

Impressions of digital soil maps: The good, the not so good, and making them ever better

Since the turn of the millennium, digital soil mapping (DSM) has revolutionized the production of fine resolution gridded soil data with associated uncertainty. However, the link to conventional soil maps has not been sufficiently explained nor are the approaches complementary and synergistic. Further training on the digital soil mapping approaches, and associated strengths and weaknesses is required. The user community requires training in, and experience with, the new digital soil map products, especially about the use of uncertainties for risk modelling and policy development. Standards are required for public and private sector digital soil map products to prevent the production of poor-quality information which will become misleading and counter-productive. Machine-learning methods are to be used with caution with respect to their interpretability and parsimony. The use of DSM products for improved pedological understanding and soil survey interpretations requires urgent investigation.</p

Case_Study_3_soil_plant_interaction_NIR

Raw NIR images with gps log and ground truth data for case study 3 soil and plants interaction. The RGB and NIR images were split as two files due to the file size limit

Case_Study_3_soil_plant_interaction_RGB

Raw RGB images with gps log and ground truth data for case study 3 soil and plants interaction. The RGB and NIR images were split as two files due to the file size limit