Prediction Models for Assessing Lycopene in Open-Field Cultivated Tomatoes by Means of a Portable Reflectance Sensor: Cultivar and Growing-Season Effects

J Agric Food Chem. 2018 May 9;66(18):4748-4757. doi: 10.1021/acs.jafc.8b01570. Epub 2018 Apr 27.

Abstract

Reflectance spectroscopy represents a useful tool for the nondestructive assessment of tomato lycopene, even in the field. For this reason, a compact, low-cost, light emitting diode-based sensor has been developed to measure reflectance in the 400-750 nm spectral range. It was calibrated against wet chemistry and evaluated by partial least squares (PLS) regression analyses. The lycopene prediction models were defined for two open-field cultivated red-tomato varieties: the processing oblong tomatoes of the cv. Calista (average weight: 76 g) and the fresh-consumption round tomatoes of the cv. Volna (average weight: 130 g), over a period of two consecutive years. The lycopene prediction models were dependent on both cultivar and season. The lycopene root mean square error of prediction produced by the 2014 single-cultivar calibrations validated on the 2015 samples was large (33 mg kg-1) in the Calista tomatoes and acceptable (9.5 mg kg-1) in the Volna tomatoes. A more general bicultivar and biyear model could still explain almost 80% of the predicted lycopene variance, with a relative error in red tomatoes of less than 20%. In 2016, the in-field applications of the multiseasonal prediction models, built with the 2014 and 2015 data, showed significant ( P < 0.001) differences in the average lycopene estimated in the crop on two sampling dates that were 20 days apart: on August 19 and September 7, 2016, the lycopene was 98.9 ± 9.3 and 92.2 ± 10.8 mg kg-1 FW for cv. Calista and 54.6 ± 13.2 and 60.8 ± 6.8 mg kg-1 FW for cv. Volna. The sensor was also able to monitor the temporal evolution of lycopene accumulation on the very same fruits attached to the plants. These results indicated that a simple, compact reflectance device and PLS analysis could provide adequately precise and robust (through-seasons) models for the nondestructive assessment of lycopene in whole tomatoes. This technique could guarantee tomatoes with the highest nutraceutical value from the production, during storage and distribution, and finally to consumers.

Keywords: Lycopersicon esculentum; lycopene; optical sensor; partial least squares regression; reflectance; tomato.

MeSH terms

  • Antioxidants / analysis
  • Antioxidants / metabolism
  • Carotenoids / analysis*
  • Carotenoids / metabolism
  • Fruit / chemistry*
  • Fruit / growth & development
  • Fruit / metabolism
  • Lycopene
  • Seasons
  • Solanum lycopersicum / chemistry
  • Solanum lycopersicum / growth & development*
  • Solanum lycopersicum / metabolism

Substances

  • Antioxidants
  • Carotenoids
  • Lycopene