Reflectance based non-destructive determination of colour and ripeness of tomato fruits.

The preference and quality of tomato fruit are primarily determined by its apparent colour and appearance. Non-destructive and rapid methods for assessment of tomato colour and ripeness are therefore of immense significance. This study was conducted to identify reflectance-based indices and to develop models for the non-destructive determination of colour and ripeness (maturity) of tomato fruits. Tomato fruits of two varieties and two hybrids, representing different ripening stages were investigated. Fruits were either harvested directly from the plants or they were picked up from the lots stored at 25 °C. Reflectance from individual fruit was recorded in a spectrum ranging from 350 to 2500 nm. These fruits at different ripening stages were ranked on a relative ripening score (0.0-8.5). Obtained data (reflectance and ripening score) were subjected to chemometric analysis. In total, six models were developed. The first-best model was based on the index R521 (reflectance at wavelength 521 nm) i.e., y (colour/ripeness) =  - 2.456 ln (x) - 1.093 where x is R521. This model had a root mean standard error of prediction (RMSEP) ≥ 0.86 and biasness =  - 0.09. The second-best model y = 2.582 ln (x) - 0.805 was based on the index R546 (x) and had RMSEP ≥ 0.89 and biasness = 0.10. Models could bifurcate tomatoes into basic ripening stages and also red and beyond red tomato fruits from other stages across the varieties/hybrids and ripening conditions [for plant harvested (fresh) and stored (aged) fruits]. Findings will prove useful in developing simple and thereby cost-effective tools for rapid screening/sorting of tomato fruits based on their colour or ripeness not only for basic research (phenotyping) but also for the purpose of processing, value-addition, and pharmaceutical usages. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12298-022-01126-2. © Prof. H.S. Srivastava Foundation for Science and Society 2022.