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Review reveals critical knowledge gaps regarding phomopsin persistence during processing of lupin crops, indicating a need for validated analytical controls and safety standards.
Lupin is an increasingly important protein crop, but evidence linking its nutritional and technological potential with fungal contamination, processing safety, and analytical control remains fragmented. This review integrates these areas within a field-to-product assessment of lupin-based food and feed systems, explicitly distinguishing among evidence obtained directly from lupin, findings generated in other legume matrices, and mechanistic inferences. Diaporthe toxica can colonize lupin tissues and seeds, providing a pathway for phomopsins to enter food and feed chains; however, occurrence data are scarce, geographically limited, and focused mainly on phomopsin A (PHO-A). Toxicological evidence is derived predominantly from animal studies, and no health-based guidance values have been established for phomopsins. Processing can reduce quinolizidine alkaloids and other antinutritional constituents, but direct evidence that soaking, heating, fermentation, or germination eliminates phomopsins from lupin is lacking. PHO-A persistence has been demonstrated in artificially contaminated pea-based products. These findings indicate that conventional heating cannot be assumed to detoxify contaminated lupin, but they do not provide quantitative retention data for lupin matrices. LC-MS/MS is currently the most suitable analytical approach, although heterogeneous contamination, insufficiently described sampling, matrix effects, variable sample preparation, and the limited availability of analytical standards and reference materials constrain data comparability. Research priorities include representative occurrence monitoring, validated methods covering relevant lupin matrices, mass-balance processing studies using contaminated lupin, characterization of transformation products, and exposure assessment. This integrated framework distinguishes established evidence from model-derived findings and unresolved knowledge gaps, thereby supporting risk-based control from crop production to final products.
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Padewska et al. (2026) studied this question.
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