Near-infrared (NIR), mid-infrared (MIR), Raman spectroscopy and hyperspectral imaging (HSI) were comprehensively compared for their capacity to evaluate the composition and texture characteristics of apple purees issued from a large variability (cultivar, fruit thinning, post-harvest mealy texture and processing). NIR, MIR and HSI techniques had a good ability to estimate puree composition such as soluble solids (RPD >2.5), titratable acidity (RPD >2.4) and dry matter (RPD >2.3). Raman spectroscopy was less accurate to determine puree biochemical (RPD <1.8) and textural parameters (RPD <1.4) than the other techniques. MIR was the best tool to identify aforementioned factors (>91.7% of correct classification) and satisfactory predict the puree average particle size (RPD = 2.9), viscosity (RPD ≥2.1) and viscoelasticity (RPD >2.3). Consequently, NIR, MIR and HSI should be prioritized as process analytical technologies to detect apple puree variability, and assess their texture and taste.