A recent review article highlights the promise of near-infrared (NIR) spectroscopy for on-farm analysis of liquid organic manure.
Sustainable farming practices are important in preserving the Earth and its natural resources. These practices are designed to support long-term food security and promote the economic and social well-being of farming communities. Because these practices are becoming more popular, more research is being conducted to try and improve them even further.
A recent review article published in Agriculture discusses the need for improved calibration and regulatory oversight of near-infrared (NIR) spectroscopy sensors used on farms to analyze the nutrient content of liquid organic manures (LOMs) (1). This study was led by Charlotte Hopker of Georg-August-Universität Göttingen and the University of Applied Sciences. With her team, they demonstrated in their article that while NIR spectroscopy has yielded some benefits in practical agriculture settings, there are still limitations that need to be addressed (1).
Tractor cultivating field at spring | Image Credit: © ValentinValkov - stock.adobe.com
LOMs provide plants with the necessary nutrients required for them to thrive (2). These products are used as fertilizers in sustainable farming, and they are generally considered to be more eco-friendly and cost-effective alternatives to traditional fertilizers (2). LOMs can vary significantly in their nutrient composition; as a result, it is important that farmers have a good way to analyze the nutrient content in LOMs to prevent over- or under-fertilizing their crops. Both over- and under-fertilizing crops can result in environmental degradation and reduced crop productivity (1).
In their review article, Hopker and her team focus on NIR spectroscopy, which is already used in laboratory environments to assess agricultural products, but its on-farm application remains technically and logistically challenging (1). They preface their article by describing the advantages of NIR spectroscopy. This technique, the authors explain, offers speed, ease of use, and the ability to collect data continuously (1).
The review article emphasizes that environmental factors such as temperature fluctuations, vibrations, and sensor placement can significantly influence the accuracy of on-farm NIR spectroscopy readings. In controlled laboratory settings, these variables can be minimized, but in real-world farming conditions, they present a substantial challenge (1).
To improve trust in NIR spectroscopy as a tool for managing LOM fertilization, Hopker and her team point to the role of the German Agricultural Society (DLG), which currently verifies the reliability of NIRS systems. Through rigorous testing, DLG evaluates the degree to which NIR spectroscopy data aligns with traditional laboratory analysis across various manure types and compositions.
However, the review emphasizes that much more needs to be done. One consideration is where NIR sensors are on machinery. Because sensor position can influence accuracy, the research team mentioned that evaluating sensor positioning should receive increased focus in future studies (1).
Another consideration is periodic sampling. The researchers mention that during manure application periods, the samples should be tested in laboratories to provide benchmark values (1). Doing so would allow scientists to adjust NIR spectroscopy sensor readings as needed to minimize differences between real-time and laboratory-based nutrient values.
However, the biggest challenge currently, according to the researchers, is regulatory inconsistency. Citing their home country of Germany as an example, states such as Bavaria and North Rhine-Westphalia allow farmers to use NIR spectroscopy readings for compliance documentation, whereas others like Lower Saxony do not (1). Because different areas of Germany have different regulations, these rules prevent the widespread adoption of NIR technology in agriculture.
To remedy this, the research team argues that a formal quality assurance program for NIR spectroscopy sensors should be created. The authors state that this could be comparable to the mandatory technical inspections for crop protection sprayers already in place in Germany (1). Regular maintenance and certification by an independent body would give farmers confidence in their equipment and foster broader usage of NIR spectroscopy in sustainable fertilization practices (1).
In the long term, developing a quality assurance program could be the key to smarter, more sustainable nutrient management in agriculture, the authors conclude (1).
Evaluating Microplastic Detection with Fluorescence Microscopy and Raman Spectroscopy
July 2nd 2025A recent study presented a dual-method approach combining confocal micro-Raman spectroscopy and Nile Red-assisted fluorescence microscopy to enhance the accuracy and throughput of microplastics detection in environmental samples.
Toward a Generalizable Model of Diffuse Reflectance in Particulate Systems
June 30th 2025This tutorial examines the modeling of diffuse reflectance (DR) in complex particulate samples, such as powders and granular solids. Traditional theoretical frameworks like empirical absorbance, Kubelka-Munk, radiative transfer theory (RTT), and the Hapke model are presented in standard and matrix notation where applicable. Their advantages and limitations are highlighted, particularly for heterogeneous particle size distributions and real-world variations in the optical properties of particulate samples. Hybrid and emerging computational strategies, including Monte Carlo methods, full-wave numerical solvers, and machine learning (ML) models, are evaluated for their potential to produce more generalizable prediction models.
Combining AI and NIR Spectroscopy to Predict Resistant Starch (RS) Content in Rice
June 24th 2025A new study published in the journal Food Chemistry by lead authors Qian Zhao and Jun Huang from Zhejiang University of Science and Technology unveil a new data-driven framework for predicting resistant starch content in rice