In agriculture, soil quality is integral to facilitating good farming practices and maximizing crop yield. A new study examines how visible-near-infrared (vis-NIR) spectroscopy is being used to evaluate soil quality.
For agriculture as an industry to thrive, farmers need to ensure that the soil for their crops is of high quality. Because soil quality is essential for the flourishing of the agriculture industry, farmers and scientists are continually to explore new ways to assess soil quality.
According to a new review article published in the European Journal of Soil Science, in-field soil spectroscopy, also known as visible–near-infrared (vis-NIR) spectroscopy, can overcome some of the limitations that farmers and scientists experience with traditional, preexisting methods.
Numerous studies have explored using vis-NIR spectroscopy and other spectroscopic techniques such as mid-IR and NIR spectroscopy (2–4). These studies looked at predictive models and hyperspectral data in their research to develop effective prediction models for soil particle content (4). In their review article, the research team, led by Frank Leibisch and his team at Agroscope in Zurich, Switzerland, touched upon these topics while discussing vis-NIR’s application through proximal sensing.
The primary objective of this study was to examine the current state of knowledge, identify existing gaps, and propose future directions for research (1). Leibisch and his team scoured the archives and compiled literature on the subject, evaluating various aspects of in-field soil spectroscopy, such as sensor range, carrier platforms, sensor types, measurement methodologies, and the soil properties most analyzed (1).
The researchers were able to determine several key aspects as to why in-field soil spectroscopy improves on traditional methods. The most important advantage is that the technique can analyze several key soil properties simultaneously (1). Among the most frequently measured properties are soil carbon content (including soil organic carbon, soil organic matter, and total carbon), texture (comprising clay, silt, and sand), total nitrogen, pH levels, and cation exchange capacity (1). These properties are crucial indicators of soil health and fertility, making them invaluable for precision agriculture.
The research team also was able to use the literature to forecast the challenges of widely implementing in-field soil spectroscopy. They noted that currently, there is a lack of standardization in measurement protocols (1). The diversity in tools, methods, and cropping systems used across different studies has led to a wide variation in results, making it difficult to compare data and draw reliable conclusions (1). This lack of consistency hinders the broader adoption of the technology in practical farming applications (1).
Once the team identified the major challenges in implementing this technology, Liebisch and his team focused their paper on proposing a solution. They argued for the development of a widely accepted best practice protocol for in-field soil spectroscopy (1). Standardizing the methods and data analysis techniques would not only improve the reliability of soil property measurements but also facilitate the cross-calibration with soil spectral libraries derived from laboratory spectroscopy (1). This protocol would be a significant step towards harmonizing the use of this technology in various agricultural settings, ensuring that it can be applied effectively and consistently across different regions and farming systems (1).
The review also noted that there needs to be an expansion of databases to include data from a wider range of instruments and cropping systems. By integrating existing knowledge from laboratory spectroscopy with in-field methods, researchers can refine the calibration techniques used in soil spectroscopy, enhancing the accuracy of soil property predictions (1).
With the ability to rapidly assess soil conditions on-site, farmers can make more informed decisions about crop management, irrigation, and fertilizer application. This real-time data could lead to more efficient use of resources, reduced environmental impact, and ultimately, more sustainable and profitable farming operations.
Unlike traditional soil testing methods that require time-consuming and labor-intensive laboratory analysis, in-field soil spectroscopy allows for the rapid prediction of multiple soil properties from a single spectral reading. As the research team explains in their study, with a few modifications and adjustments, this technique could revolutionize agricultural practices by providing farmers with real-time data on soil conditions, enabling more informed decision-making and ultimately leading to increased crop yields and sustainable farming practices.
(1) Piccini, C.; Metzger, K.; Debaene, G.; et al. In-Field Soil Spectroscopy in Vis-NIR Range for Fast and Reliable Soil Analysis: A Review. Eur. J. Soil Sci. 2024, 75 (2), e13481. DOI:
(2) Wetzel, W. Analyzing Soil Acidification Using Mid-Infrared Spectroscopy. Spectroscopy. Available at:
(3)Wetzel, W. Monitoring Soil Quality Using MIR and NIR Spectral Models: An Interview with Felipe Bachion de Santana. Spectroscopy. Available at:
(4) Xia, K.; Cheng, Q.; Xia, S.; et al. Optimization of a Soil Particle Content Prediction Model Based on a Combined Spectral Index and Successive Projections Algorithm Using Vis-NIR Spectroscopy. Spectroscopy 2020, 35 (12), 24–34.
