Hard-to-Cook Phenomenon in Pulses: Mechanistic Insights, Influencing Factors, and Detection Perspectives

The hard-to-cook (HTC) defect remains a major postharvest quality constraint in pulses, reducing cooking efficiency, textural quality, consumer acceptance, and processing performance. Although many mechanisms and analytical methods have been proposed, the literature remains fragmented, with limited integration among mechanistic evidence, measurable markers, and practical detection approaches. This review critically evaluates HTC development in pulses using an evidence-weighted mechanism–marker–method framework. Current evidence indicates that HTC development is primarily governed by cotyledon cell-wall reinforcement, involving pectin redistribution, reduced pectin extractability, and Ca²⁺/Mg²⁺-mediated middle-lamella strengthening. In contrast, hydration restriction, membrane deterioration, seed coat effects, starch–protein matrix resistance, and phenolic- or lignin-mediated wall reinforcement appear to act as conditional contributors. HTC susceptibility is further influenced by intrinsic factors such as cultivar background, pectin–mineral status, seed coat properties, and cotyledon matrix characteristics, whereas elevated storage temperature, relative humidity, prolonged storage, and hydration conditions act as the major extrinsic triggers of HTC expression. Conventional methods, including cooking-time assessment, Mattson bean cooker analysis, texture testing, sensory evaluation, hydration measurements, and biochemical assays, remain essential for defining HTC severity and validating mechanisms, although they are generally destructive, labour-intensive, time-consuming, or low-throughput. Emerging approaches, including Vis/NIRS, hyperspectral imaging, FTIR, digital imaging, and NMR/MRI, provide complementary predictive, molecular, spatial, and hydration-related information at different readiness levels. This framework supports more reliable HTC detection and assessment for research, breeding, storage monitoring, processing optimization, and industrial quality control.