Reduction of pesticide residues in quinoa through Lean Six Sigma and good agricultural practices: A process capability-based approach
Keywords:
Lean Six Sigma, Good Agricultural Practices, Process capability, Pesticide residues, Chlorpyrifos, Agroexport supply chain, Statistical process control, DMAIC methodology, Food safety, Variability reductionAbstract
Pesticide residue variability is a persistent challenge in high-value agroexport supply chains, where upstream agricultural heterogeneity limits the effectiveness of industrial controls. This study develops an integrated Lean Six Sigma (LSS) and Good Agricultural Practices (GAP) framework to reduce chemical risk in quinoa production using a process capability–based approach. A dataset of 312 quinoa lots processed by AGRIPROCESS S.A.C. between July 2024 and July 2025 was analyzed following the DMAIC methodology. Chlorpyrifos was identified as the critical-to-quality parameter, accounting for most non-conformities relative to international maximum residue limits. Statistical analysis revealed significant process instability (Cp = 0.597; Cpk = 0.560), indicating an incapable and off-centered process. Upstream variability was strongly associated with low GAP compliance among specific suppliers, who contributed disproportionately to overall dispersion. Based on these findings, a comprehensive improvement model is proposed, integrating standardized agricultural practices, supplier segmentation, enhanced traceability, and real-time statistical process control. The proposed framework provides a replicable and data-driven strategy for reducing chemical variability, strengthening food safety, and improving regulatory compliance across agroexport supply chains in emerging economies.
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Copyright (c) 2025 Julio César Carrasco Bocangel, Fiorella del Carmen Valdivia Rosas, José Cardenas Medina

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