Near infrared spectroscopy determination of chemical and sensory properties in tomato

Fast and massive characterization of quality attributes in tomatoes is a necessary step toward its improvement; for sensory this process time-consuming very expensive, which causes absence routine phenotpying. We aimed to assess the feasibility near infrared (NIR) spectroscopy as fast economical tool predict both chemical properties tomatoes. built partial least squares models from spectra recorded tomato puree juice 53 genetically diverse varieties grown two environments. Samples were divided calibration (210 samples traits, 45 traits) validation sets (60 10, respectively) using Kennard Stone algorithm. Models gave r 2 values higher than 0.97 fructose, glucose, soluble solids content, dry matter (relative standard error prediction, RSEP% ranged 3.5–5.8), while lower (ranging 0.702–0.917 taste-related traits (RSEP%: 9.1–20.0), 0.009–0.849 texture related 3.6–72.1)). For such explosiveness, juiciness, sweetness, acidity, taste intensity, aroma mealiness, NIR potentially useful scanning large collections identify likely candidates select quality.