Developing portable VNIR spectroscopy for soil organic carbon quantification

Soil systems provision many essential ecosystem services including food resources, water filtration and climate regulation. The accumulation and storage of soil organic carbon (SOC) is central to soil health and delivers a climate mitigation service of global significance. However, widespread monitoring of SOC is constrained by the costs, expertise and labour demands associated with traditional quantification methodologies, such as wet oxidation and dry combustion techniques. Diffuse reflectance spectroscopy (DRS) within the visible-near infrared (VNIR) range (400-1100 nm) offers a rapid and low cost means of SOC quantification. Specifically, recent developments to portable/ handheld VNIR spectrophotometer instruments are successfully facilitating cost-effective and accurate in-situ measurements, expanding global access to SOC quantification tools.

This research investigates the use of portable VNIR spectrophotometers for predicting SOC content in soils across parkland and links-style golf courses. Our aim is to develop novel machine learning-based pedometric SOC prediction models based on VNIR spectra and SOC reference values, and to integrate models into an open access software for non-specialists to easily quantify SOC at their own golf courses. To determine the optimal spectrum acquisition strategy, spectrophotometer scans were conducted in-situ using sub-sections of fresh soils cores (to 15cm depth) and ex-situ using processed samples. Processed samples underwent drying and milling to increase homogenisation and reduce the impacts of spectrum disturbing factors, such as water content and surface roughness. Furthermore, in-situ scans of surface vegetation were conducted to understand the link between the VNIR spectra of vegetation and SOC content. Following preliminary investigations, we will compare the accuracy of SOC quantification by three VNIR spectrophotometers, which vary in wavelength range and cost. Overall, this research aims to support greenskeepers to monitor SOC sequestration and storage, and in-turn soil health and quality, across courses. In doing so, this research will empower greenskeepers to use evidence-based soil management practices. Additionally, understanding the carbon sequestration and storage abilities of golf course soil systems will ameliorate the accuracy and transparency of the golfing industry’s net climate impact.  

Our findings will contribute to the development of in-situ VNIR spectroscopy as a scalable, cost-effective and environmentally friendly analytical tool for SOC quantification by expanding its applications to turfgrass systems. Overall, this research will advance machine learning-based pedometric approaches, their application in practical land management and the global accessibility of SOC quantification tools.