Objective
1. Spectroscopic characterization of soil organic carbon (SOC) stability using FT-NIR and Mid-IR on SK soils (legacy soil samples)
2. Develop machine learning predictive models for carbon and integrate spectral information with existing soil libraries.
3. Understand linkages between soil physicochemical properties and the quality and stability of SOC (synchrotron data vs wet chemistry data).
4. Method development for collecting and processing soil spectra in the field from intact field moist core samples.
5. Assess and compare high and a low-cost near infrared device for SOC stock and bulk density estimation at the field-scale.
6. Perform cost-benefit of the different spectroscopic strategies with traditional SOC stock estimates.
Project Description
Soil organic carbon (SOC) is perhaps the most important single contributor to both soil health and agricultural productivity in Saskatchewan. Quantification of SOC typically relies upon on wet chemistry or dry combustion methods, which are time-, labor-, and energy-intensive, which raises analysis costs and limits the number of measurements. Consequently, there is a need for innovative solutions that can help laboratories rapidly characterize soils, implement internal quality controls, and reduce costs and ecosystem impacts, ensuring timely and reliable results for growers and the industry. Soil spectroscopy has emerged as an alternative to wet chemistry and dry combustion methods for the rapid measurement of SOC. However, this technology is not yet widely adopted in soil laboratories, primarily due to a lack of standards and protocols, spectral libraries, capacity in spectral methods, and expertise in chemometrics. Soil spectral libraries integrate soil spectra with conventionally measured soil information, creating a vital resource for researchers and practitioners. The Canadian Prairie Soil Spectral Library (CPSSL) is being developed through a collaborative effort involving a multidisciplinary team to address these critical gaps in soil information. One aspect of spectroscopy that is seldom explored by soil researchers is that spectra can be used not only for quantification (SOC stocks) but also contain information about the quality of soil C (e.g. the relative abundance of aliphatic, aromatic, carboxylic, carbohydrate groups). We propose a detailed spectroscopic study of legacy soil samples that builds on the Prairie Soil Carbon Balance (PSCB) and Carbon Sequestration Under Pasture and Forage Resources (CSUPFR) projects. The PSCB project provided an estimate of SOC stock change over time in commercial fields in Saskatchewan. However, measuring the SOC stocks only at the relatively coarse sampling resolution did not enable us to fully explain why some fields did not exhibit continued SOC gains despite long-term conservation tillage practices. Past research clearly demonstrates that management practices, such as no-till, have led to an increase in SOC stocks in the Canadian Prairies. However, a recent study indicates that SOC stocks are sensitive to climate cycles and may not remain stable under future climate variability. Meanwhile, the CSUPFR project initially focused on the perennial forage cover spanning over 8 million hectares in Saskatchewan to address the gaps in insufficient data regarding SOC stocks and the effects of forage management on SOC storage. Nonetheless, questions remain about the stability of SOC under those management practices and land uses. Sustainably meeting the increasing food demand in a changing climate and sequestering SOC to enhance soil health requires detailed understanding of management practices. Agriculture is rapidly transitioning to a data-driven approach, enhancing decision-making and improving productivity, sustainability, and profitability. Saskatchewan contains 50% of Canada’s arable land and plays a crucial role in this effort, making effective soil management in this region significant for the entire nation. However, due to cost constraints, a major barrier to progress is the lack of critical soil information available at precise temporal and spatial scales. This research will provide rapid and cost-effective spectroscopic quantification of SOC and reliable spectral data through the CPSSL, assisting in implementation and producer/landowner decision-making. Furthermore, a comprehensive understanding of SOC stability will support efforts to develop future SOC stocks and help producers maintain and enhance SOC reserves and crop and forage yields, while also potentially capitalizing on C markets and building climate resilience against future climate vulnerabilities in the prairies. Effective SOC improvement interventions through soil C sequestration require robust methodologies to measure, report, and verify changes in SOC stocks. Additionally, SOC must be monitored to ensure that the net balance of sequestered C is stable. Spectroscopic methods can evaluate SOC stability across various land use practices and offer potential benefits for future C sequestration in the prairie region. Therefore, achieving a better understanding of SOC stability and changes in SOC stocks under various types of soil management across different land uses is essential. An important research gap that needs to be directly addressed is whether the wavelengths used to predict SOC are the same for different soil zones and management practices, or if the changes in SOC qualities result in models choosing different features. We will employ spectral feature analysis on existing SK spectral libraries, expand the libraries with mid-IR and synchrotron XAS spectra to improve SOC predictions with existing lab-based models and samples, and then choose the best wavelengths (to minimize overlap with other soil properties and effect of sampling location). This also will be extremely valuable for model calibration and estimations using in-field soil spectroscopy. Accurate estimation of SOC stocks is particularly challenging, as traditional methods requires measurement of both SOC concentration and soil bulk density (BD). This is labor-intensive, time-consuming and expensive, and hence limits routine testing of these parameters at the field scale. While several studies have demonstrated the ability to predict SOC concentrations and other soil properties using soil spectroscopy, most prior studies were conducted using laboratory-based measurements on dried and ground soil samples. Eliminating this step and providing in-situ or in-field estimates of SOC stocks would reduce cost and provide more rapid measurement and monitoring of SOC stocks in the Canadian prairies. There is now a great opportunity to do so with the recent advances in handheld and field-portable spectrometers. It is well-known that soil moisture, vegetation and soil surface roughness have a major impact on spectral features and hence can significantly reduce prediction accuracy of soil properties when using fresh soil samples or in situ spectral measurements, which has limited its application at the field scale. Fortunately, methods have been developed to minimize the effects of moisture on the soil spectra and improve predictions. Truck-mounted systems have been used for in-situ measurement of SOC concentrations but not SOC stocks and are also costly and not readily available to producers. Studies in the Canadian prairies and elsewhere have evaluated low-cost, portable and/or miniaturized spectrometers for prediction SOC concentrations and stocks but under laboratory conditions. To our knowledge, there has been no studies conducted in the Canadian prairies for direct estimates of SOC stock at the field-scale using field measurements with low-cost and/or field-portable spectrometers. Predictions of various soil properties from in-situ measurements in other parts of the world have been conducted with low-cost handheld and/or field-portable spectrometers, but with varying degrees of accuracy especially after accounting for the effects of moisture. We propose to develop strategies for in-field collection soil spectra and predict SOC stocks at the field scale.
