Tackling the Heat: Overcoming Matrix Challenges in Pesticide Residue Analysis of Chili Powder Using LC–MS/MS

Chili powder’s complex matrix—rich in pigments, oils, and capsinoids—poses major challenges for pesticide residue analysis. In this interview, Raviraj Chandrakant Shinde, senior application scientist at PerkinElmer, discusses his team’s development of a high-throughput liquid chromatography tandem mass spectrometry (LC–MS/MS) method for quantifying 135 pesticides with improved accuracy and robustness. He describes how optimized extraction and dispersive solid-phase extraction (d-SPE) cleanup protocols minimized matrix effects, ensuring reproducible results across diverse chili powder samples.

You have recently published a paper on the analysis of pesticide residues in chili powder using liquid chromatography tandem mass spectrometry (LC–MS/MS) (1). How did this research come about?

Chili powder is a widely consumed spice with significant culinary and economic importance globally. However, chili crops are often treated with multiple classes of pesticides to manage pests and diseases, raising concerns about pesticide residues in the final powder form consumed by the public. Monitoring these residues is essential to ensure food safety and to comply with domestic and international regulatory standards. Accurate pesticide quantification in this chili powder creates analytical challenges because of the matrix's complexity, including high pigment content, capsinoids, essential oils, and other interfering compounds. These components of the chili powder matrix can affect extraction efficiency, cause matrix interferences, and complicate detection and quantification for certain pesticides.

Traditional analytical approaches may suffer because of poor recoveries, elevated limits of detection and quantification (LOD/LOQ), or labor-intensive and time-consuming sample preparation steps.

Given these challenges, we aimed to develop and optimize a high-throughput analytical method suitable for routine monitoring laboratories specifically to achieve reliable quantification across a wide range of pesticide residues, while maintaining acceptable sensitivity, precision, and accuracy. We focused on improving each stage from sample extraction and cleanup to LC–MS/MS detection and conducted a thorough validation, including both intra-day and inter-day performance assessments.

What were the main challenges encountered when optimizing the extraction and cleanup procedures for chili powder, and how did you overcome them?

Chili powder represents a highly complex matrix because of its rich composition of strongly pigmented compounds (such as carotenoids and red pigments), capsinoids, oils, lipids, and other organic materials. These co-extractive components can interfere significantly with pesticide analysis. They may contribute to matrix effects in LC–MS/MS detection—notably ion suppression or enhancement—thereby compromising the accuracy, sensitivity, and reproducibility in the results. Furthermore, such co-extractives can contaminate the chromatographic system, leading to increased background noise, clogging, and reduced column lifespan, ultimately affecting instrument performance and maintenance frequency.

To address these challenges, we optimized an extraction protocol using acetonitrile as the primary solvent, selected for its effective miscibility with a broad range of pesticides and its relatively low co-extraction of non-polar matrix components. Further, many other essential parameters were considered during method development, including sample size, solvent volume, solvent composition, and cleanup strategy.

A critical step in the workflow was the use of dispersive solid-phase extraction (d-SPE) for matrix cleanup. Various sorbents—primary secondary amine (PSA), C18, and graphitized carbon black (GCB)—were evaluated individually and in combination. These sorbents target different classes of matrix interferences: PSA removes organic acids and some sugars, C18 targets non-polar compounds like lipids, and GCB is effective in removing pigments.

The optimization of d-SPE involved systematically varying the type and number of sorbents, as well as the volume of extract subjected to cleanup. Over-cleaning was a particular concern, as excessive sorbent use—especially GCB—can reduce recoveries of certain planar pesticide molecules. After careful evaluation, we identified a combination of sorbents and conditions that provided effective cleanup while maintaining acceptable recoveries and minimizing matrix effects. The final optimized method demonstrated reduced matrix interference and improved analytical performance for the targeted pesticide residues.

Can you elaborate on how the matrix effects specific to chili powder, such as pigmentation and capsinoids, influenced the analytical performance?

The presence of pigments and other coloured compounds, particularly carotenoids and related mid-polar to non-polar organic molecules, introduces substantial analytical challenges during LC–MS/MS-based pesticide residue analysis. These matrix components may co-extract with pesticides because of their similar physicochemical properties and can coelute during chromatographic separation. Such compounds can cause background signal fluctuations and deposit in the mass spectrometer ion source, leading to ion suppression and reduced instrument sensitivity.

In some cases, these interfering compounds may also participate in adduct formation or affect the ionization efficiency of target analytes, further compromising method sensitivity, reproducibility, and peak symmetry. These matrix effects not only pose hardware-related issues, such as contamination and shortened component lifespans, but also create methodological difficulties, including poor peak shape, compromised LODs, and inconsistent quantification.

To mitigate these effects, our optimized method incorporates a carefully tailored extraction and d-SPE cleanup protocol that significantly reduces the presence of matrix-derived interferences. By selecting appropriate sorbents and optimizing their amounts and combinations, we effectively minimized ion suppression/enhancement effects. As a result, the final method demonstrated robust matrix tolerance, with repeatable and reproducible quantification of the target pesticide residues across multiple sample batches and analytical runs.

How did you ensure the method's robustness and reproducibility across different batches of chili powder?

Chili powder presents significant analytical challenges because of its complex matrix, necessitating meticulous attention to every step—from sample preparation through analysis. Multiple factors influence the recovery of pesticides, including the choice of extraction solvent, sample size, cleanup sorbents, calibration strategy, and validation procedures. In this study, acetonitrile was selected as the extraction solvent for its effectiveness in recovering a broad spectrum of pesticides. Sample size was carefully optimized, balancing precision and ruggedness; smaller sample sizes tend to precision above the acceptable limits as per SANTE guidelines, while larger samples increase matrix effects, compromising method robustness. Given the challenging nature of chili powder, a d-SPE cleanup strategy effectively minimized matrix interferences, leading to improved repeatability of results.

To verify robustness and reproducibility, multiple batches of chili powder representing various origins, colors, and spice preparations were used for method applicability on market sample analysis and validation. This ensured the method’s applicability across diverse sample types with varying pigment and oil content. In addition, intra-day and inter-day precision were assessed by analyzing spiked samples repeatedly over three days, involving different analysts. Relative standard deviations (RSDs) below 15% were consistently achieved, demonstrating method precision. Measurement uncertainty was monitored to ensure performance remained within acceptable limits.

Given the complex matrix, what strategies would you recommend for routine monitoring laboratories to implement your method effectively?

Given the complexity of chili powder as a matrix, the following strategies are recommended for routine monitoring laboratories to ensure reliable and accurate pesticide residue analysis:

1. Optimized Cleanup Procedures: Implement and regularly verify cleanup protocols (for example, dispersive SPE using PSA, GCB, C18) to effectively reduce matrix interferences while minimizing analyte loss. Regular assessment of cleanup efficiency is essential to maintain sensitivity and accuracy.
2. Use of Matrix-Matched Calibration and Internal Standards: Employ matrix-matched calibration standards to compensate for matrix effects consistently. Where possible, incorporate isotopically labeled internal standards, especially for key or problematic pesticides. If isotopic standards are unavailable for all analytes, focus on those most affected by matrix effects to improve quantification accuracy.
3. Comprehensive Quality Control (QC) Measures: Incorporate regular QC samples such as method blanks, spiked controls, and replicate samples within each analytical batch. Monitor recovery rates and relative standard deviations (RSDs) to ensure method precision and accuracy. Include inter-batch comparisons to detect any drift or inconsistencies over time.
4. Continuous Monitoring and Management of Matrix Effects: Routinely evaluate matrix effects for each pesticide or pesticide class within chili powder samples. Adjust sample dilution, cleanup procedures, or calibration approaches as needed to mitigate these effects and maintain data integrity.
5. Robust Standard Operating Procedures (SOPs): Develop detailed SOPs with clear acceptance criteria for parameters such as recoveries, precision (RSD), and LOQs. Ensure all analysts are trained to follow these SOPs consistently to achieve reproducible results across different operators and time points.

How did you select the 135 pesticides included in your analysis, and are there plans to expand this list in future studies?

In this study, we targeted 135 pesticides representing a multi-class group including insecticides, fungicides, and herbicides relevant to chili cultivation and trade. The selection criteria included:

• Local Usage: Pesticides recommended or commonly used in India, as per guidelines from the Central Insecticides Board & Registration Committee, India.
• Regulatory Requirements: Pesticides regulated by the Food Safety and Standards Authority of India (FSSAI) and those with maximum residue limits (MRLs) set by both Indian and EU regulations.
• Historical Data: Pesticides frequently detected in prior studies and surveillance programs.
• Availability of Standards: Ready availability of analytical standards for reliable quantification.
• Chemical Diversity: Ensuring coverage of diverse chemical classes to make the method broadly applicable.

The method achieved a LOQ of 0.005 mg/kg for all 135 pesticides.

What are your plans for future expansion of the method?

We plan to expand the pesticide scope in future studies to keep pace with evolving agricultural practices and regulatory changes. As pesticide use patterns shift—new chemistries emerge, older pesticides get banned, and metabolites or degradation products gain relevance—the method will be periodically re-evaluated and updated accordingly.

In addition to expanding the scope of our method, we are developing a simplified approach for the analysis of multi-class pesticides in complex matrices such as spices. Various novel technologies have been introduced to address these challenges, with automated sample preparation and cleanup being prime examples. In this approach, the sample is placed into an automated cleanup instrument, which delivers a clean extract ready for analysis by LC–MS/MS or gas chromatography (GC)–MS/MS. However, careful selection of the appropriate cleanup cartridge is critical to ensure optimal results. While dispersive and automated cleanup methods have provided excellent outcomes, we are currently working on a new research project aimed at minimizing sample preparation altogether. This method is expected to be published soon on scientific platforms and promises to overcome many challenges faced by analytical scientists working with difficult samples like spices.

Reference

(1) Shinde, R. C.; Suraliwala, M.; Kumar, D.; Atugade, S.; Shiragave, P. High-Throughput Quantification of Pesticide Residues in Complex Matrix (Chili Powder) Using Liquid Chromatography Tandem Mass Spectrometry: Inter-and Intra-Day Validation. J. AOAC Int. 2025, qsaf079. DOI: 10.1093/jaoacint/qsaf079

Raviraj Chandrakant Shinde is a scientist specializing in food safety and analytical chemistry. Over the past decade, Shinde has focused on method development and validation for complex food matrices, including spices, grains, and processed products. His primary research interests lie in enhancing sensitivity, throughput, and robustness for challenging-to-analyze polar/ionic compounds and single-residue methods in routine monitoring laboratories.

Shinde earned his PhD in analytical chemistry, with a dissertation centered on developing novel analytical methods. He has published extensively in high-impact, peer-reviewed journals and is an active member of several national and international scientific communities and associations.

Recognized with numerous awards (such as AOAC INTERNATIONAL Eurofins Foundation “Testing for Life” Award in 2021 in Boston, USA; Emerging Scientist Award, National Biotech Youth Award, Young Scientist Award) for his contributions to research and innovation in advancing food science, pharmaceutical analysis, and environmental monitoring. He has been invited to deliver talks at prestigious institutions and is known for his excellence in research. His dedication to the field is reflected in his active participation in scientific discussions, research publications, and commitment to fostering advancements in analytical chemistry and food safety.